<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezICPMS Library in the week of 2nd February 2026? Check out new documents from the field of spectroscopy/spectrometry and related techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT SPECTROSCOPY/SPECTROMETRY RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><strong>LabRulezGCMS</strong></a> libraries.</p></blockquote><p>This week we bring you application notes by <strong>Agilent Technologies</strong>, <strong>Metrohm,</strong> <strong>Shimadzu </strong>and<strong> Thermo Fisher Scientific!</strong></p><h3><strong>1. Agilent Technologies: High Precision Analysis of Major Components in Precious Metals by ICP-OES</strong></h3><p><strong>Determination of major components in jewelry alloys by ICP-OES and standard bracketing per ISO methods</strong></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_precious_metals_standard_bracketing_5800_icp_oes_5994_8849en_agilent_5260c9c8be.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Accurate quantification of major components in precious metal alloys can be challenging due to high precision and accuracy requirements, often to stringent industry-specific standards. This challenge is particularly relevant for the precious metals industry, where the stoichiometric composition and purity of metal alloys define both product quality and commercial value. A technique for high-precision measurements developed specifically for the precious metals industry is standard bracketing. As described in ISO methods 11494 and 11495 for ICP-OES analysis,<sup>1,2</sup> this technique employs standard–sample–standard sequencing, which improves control over instrumental fluctuations and matrix effects, ensuring high levels of accuracy and precision.</p><p>Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES) is a powerful technique that is often used to analyze trace impurities in a broad range of samples. Both the Agilent 5800 and 5900 ICP-OES instruments are inherently precise, as discussed elsewhere.<sup>3</sup> However, precision is further improved when the instruments are operated with the ISO-compliant standard bracketing feature within the Agilent ICP Expert Pro software version 7.8 onwards. The software provides additional useful features for jewelry assaying, catalyst refining, and material recycling. These functions include built-in automated result summarization, reporting in fineness (‰), karat (k), or concentration units, and processing tools specifically for determining major components and purity analysis. Standard bracketing is also applicable to other demanding applications, such as semiconductors, fertilizers, and the emerging battery materials sector.&nbsp;</p><p>In this study, the Agilent 5800 Vertical Dual View (VDV) ICP-OES with Agilent SPS 4 autosampler and ICP Expert 7.8 Pro software4 was used to determine the purity of gold (Au), palladium (Pd), and platinum (Pt) in three precious metal alloys. The analytical procedure was in accordance with ISO methods 11494 and 11495.</p><h4><strong>Experimental&nbsp;</strong></h4><h5><strong>Instrumentation&nbsp;</strong></h5><p>The <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=5800+VDV+ICP-OES"><strong>Agilent 5800 VDV ICP-OES</strong></a> was configured with the <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=SPS+4+autosampler"><strong>Agilent SPS 4 autosampler</strong></a>, which provided automated sample delivery to the instrument (Figure 1). The 5800 ICP-OES was equipped with a SeaSpray nebulizer, double-pass cyclonic spray chamber, and Agilent one-piece VDV torch with a 1.8 mm internal diameter (id) injector. All components were controlled by Agilent ICP Expert Pro* 7.8 software. Instrument operating parameters are listed in Table 1.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>This application demonstrates the effectiveness of highprecision standard bracketing calibration for the quantification of major components in gold, palladium, and platinum alloys using the Agilent 5800 VDV ICP-OES.&nbsp;</p><p>By employing gravimetrically prepared standards and integrating internal standard correction, the method improves analytical precision (RSD) more than threefold compared to conventional external calibration. It also reduces sample-tosample fluctuations, resulting in a 400× improvement in RPD values between duplicate measurements.&nbsp;</p><p>The high precision and reproducibility of the standard bracketing method enable accurate assaying of precious‑metal samples, making it ideal for quality control of high‑value materials where composition control is often required within ±0.1%.&nbsp;</p><p>The latest version of <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=+ICP+Expert+Pro+software"><strong>Agilent ICP Expert Pro software</strong></a> facilitates the standard bracketing method and includes tools for in-worksheet calculations and custom result displays. This approach simplifies metal-alloy purity testing, enables direct interpretation of sample purity in industry-standard terms, and provides confident, traceable quantification in accordance with ISO methods.&nbsp;</p><p>The method is useful in other applications that require tight composition control, such as battery materials, catalysts, semiconductors, and fertilizers.</p><h3><strong>2. Metrohm: Biodiesel content in diesel with nearinfrared spectroscopy</strong></h3><p><strong>Monitor the fuel blending process within seconds</strong></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_nir_126_download_800056c376.pdf"><strong>Full PDF for download</strong></a></li></ul><p>The properties of biodiesel fuel, which is produced from vegetable oils or animal fat, are very similar to petroleum-derived diesel, but biodiesel pollutes less. In most countries the common biodiesel blend is B20, which ranges from 6% to 20% biodiesel content. Measuring the biodiesel content in diesel is important, as higher levels can cause deposits in older diesel engines, clogging the fuel filters and pumps. Fuels with high levels of biodiesel also tend to absorb more moisture compared to petroleum-derived fuels. With near-infrared spectroscopy (NIRS), the biodiesel content is determined in seconds without any sample preparation. Compared to other test methods like those used in ASTM D7467, biodiesel content analysis with NIR spectroscopy saves time and enables the implementation of online process monitoring with fiber optics.</p><h4><strong>EXPERIMENTAL EQUIPMENT&nbsp;</strong></h4><p>Twenty-one diesel samples with varying biodiesel content from 0% to 20% were measured on the <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=220&amp;search=OMNIS+NIR"><strong>OMNIS NIR Analyzer</strong></a> Liquid (Figure 1) in transmission mode (1000–2250 nm) using 8 mm disposable vials. The vial temperature was set and monitored at 30 °C with the built-in vial sensor to ensure consistent measurement performance. OMNIS Software was used for all data acquisition and prediction model development.</p><h4><strong>CONCLUSION</strong></h4><p>This Application Note shows the results of a biodiesel content analysis test without the need for any sample preparation, using near-infrared spectroscopy in place of other more time-intensive analytical techniques. This ultimately leads to a reduction in workload and the related costs. Alongside the biodiesel content test, additional fuel quality parameters like cetane number, moisture, or flash point can be determined with NIRS.</p><h3><strong>3. Shimadzu: Quantitative Analysis of Lead (Pb) and Arsenic (As) in Cosmetic Raw Material Powders</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_01_00965_en_dc464e4caa.pdf"><strong>Full PDF for download</strong></a></li></ul><h4><strong>User Benefits</strong></h4><ul><li>&nbsp;With simple sample preparation, lead and arsenic in cosmetic raw material powder can be quantified simultaneously.</li><li>Increased X-ray tube output and optimized optical design have improved sensitivity for heavy elements.</li><li>Continuous analysis of up to 48 samples is possible, improving analysis throughput.</li></ul><p>The management of lead and arsenic contained in cosmetics raw materials is important for protecting people's health. Although colorimetric methods have been used for these analyses, there is a growing need for trace control due to tighter regulations in recent years, leading to a consideration of a shift to instrumental methods that enable quantification. Candidates for instrumental methods include ICP optical emission spectrometry/mass spectrometry and X-ray fluorescence spectrometry. While the former method is highly sensitive, powder and solid samples need to be dissolved in an acid such as nitric acid or hydrochloric acid. In contrast, X-ray fluorescence analysis is convenient because it can be analyzed without dissolving the sample.&nbsp;</p><p>This application news introduces the analysis of two inorganic oxide powders (talc and titanium oxide) using the energydispersive <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=1&amp;search=ALTRACE"><strong>X-ray fluorescence Spectrometer ALTRACE</strong></a> (Fig. 1).</p><h4><strong>Conclusion&nbsp;</strong></h4><p>This application news reports on the quantitative analysis of lead (Pb) and arsenic (As) in two types of inorganic oxide powders: talc and titanium oxide. The analysis was performed using the energy-dispersive X-ray fluorescence spectrometer ALTRACE, which allows for the analysis of powders without dissolving them. ALTRACE enables simultaneous analysis of Pb and As, unlike traditional colorimetric methods that test them separately. Additionally, ALTRACE can analyze 48 samples continuously, significantly improving the efficiency of the testing process.</p><h3><strong>4. Thermo Fisher Scientific: Advantages of coincident XPS-Raman in the analysis of mineral oxide species</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/advantages_xps_raman_analysis_mineral_oxide_an52950_d492664cb5.pdf"><strong>Full PDF for download</strong></a></li></ul><p>XPS is an extremely versatile technique that has found widespread use in a myriad of application areas, from contact lenses to aerospace materials. XPS is unique in that it can quantify the elemental and chemical composition of a material’s surface with extreme selectivity, since the typical information depth of XPS being less than 10 nanometers.&nbsp;</p><p>Raman spectroscopy is utilized in many similar application areas as it requires little sample preparation, is nondestructive, provides information on molecular structure, and enables users to identify materials quickly, thanks to extensive spectral libraries.&nbsp;</p><p>The implementation of XPS and Raman with other analysis techniques is well established; XPS has a long history of complementary use with related ultra-high vacuum (UHV) analysis techniques, such as UV photoelectron spectroscopy, Auger electron spectroscopy, and ion scattering spectroscopy. In these cases, additional equipment is added to the spectrometer to give coincident, complementary information.</p><p>To overcome these problems, the <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=3&amp;search=ARXPS"><strong>Thermo Scientific™ Theta Probe Angle-Resolved X-ray Photoelectron Spectrometer (ARXPS) System</strong></a> has been integrated with the <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/products/2238"><strong>Thermo Scientific iXR™ DXR3 Flex Raman Spectrometer</strong></a> to provide a multimodal analysis platform. The system aligns the XPS analysis position exactly with the Raman analysis position, ensuring that the data is collected from the same position.&nbsp;</p><p>The coincident XPS-Raman removes any requirement to transfer the sample from one instrument to the next between analyses, minimizing additional sample handling and exposure to different conditions that can lead to sample contamination or degradation.</p><h4><strong>Summary&nbsp;</strong></h4><p>In conclusion, XPS is used for quantitative determination of both elemental and chemical composition for any solid material compatible with UHV analysis, whereas Raman spectroscopy is used for identification of referenced compounds by careful spectral matching that searches algorithms and spectral databases. The combination of XPS and Raman spectroscopy on the DXR3 Flex Raman Spectrometer integrated with the Theta Probe ARXPS System, allows more powerful analysis of a material than either technique in isolation, with the cleanliness, purity and stoichiometry of a sample determined using XPS, and identification and quantification of molecular structures determined using Raman spectroscopy. As both techniques are aligned to the same position within the vacuum system, all the time-consuming aspects of locating the same analysis point when transferring between instruments is removed, giving absolutely certainty that all the information acquired has come from the same region of sample, which is particularly useful when studying nonuniform samples.</p>

News from LabRulezICPMS Library - Week 06, 2026

<p><strong>In the week from February 9, the following webinars await you in the field of atomic and molecular spectroscopy and spectrometry</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 000 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. Thermo Fisher Scientific: Process Raman – A Reliable and Versatile Tool for Downstream Process Monitoring and Control for mAb Production</strong></h5><ul><li>Tu, 10.2.2026 16:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5808">Registration</a></li></ul><p>The presentation highlights how process Raman spectroscopy offers several advantages over traditional in-line UV-Vis analysis for process monitoring and metabolite production control.</p><h5><strong>2. Bruker: Meet Compact-Q DEER Spectrometer – Your Gateway to Quantum Innovation</strong></h5><ul><li>Tu, 10.2.2026 17:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5757">Registration</a></li></ul><p>Discover how the Compact-Q DEER spectrometer enables high-fidelity qubit characterization and control, combining advanced microwave architecture, AWGs, and cryogen-free operation.</p><h5><strong>3. Agilent Technologies: Novel Advancements in Trace Level Determination and Long-Term Stability of Metals in TMAH and UPW Matrices</strong></h5><ul><li>Tu, 10.2.2026 21:30 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/3733">Registration</a></li></ul><p>Explore novel approaches for trace-level metal determination and long-term stability assessment in TMAH and ultrapure water matrices.</p><h5><strong>4. AZoM: From First to Best – Introducing the Litesizer DIF Series</strong></h5><ul><li>We, 11.2.2026 15:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5765">Registration</a></li></ul><p>Join this live webinar introducing the new Litesizer DIF series of laser diffraction particle size analyzers.</p><h5><strong>5. Anton Paar: Polymer Rheology – Rotational and Transient Measurements on a Polymer Melt</strong></h5><ul><li>We, 11.2.2026 18:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5786">Registration</a></li></ul><p>Learn how rotational and transient viscosity measurements on rotational rheometers reveal polymer melt flow behavior, from method setup and accessories to data interpretation.</p><h5><strong>6. Milestone: Practical Guidance to Improve the Journey from Sample to Heavy Metals Analysis for Environmental Labs</strong></h5><ul><li>Th, 12.2.2026 16:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5803">Registration</a></li></ul><p>Improve heavy metals analysis in environmental laboratories with practical tips on reagents, filtration, cleaning, and workflow optimization to enhance data quality and efficiency.</p><h5><strong>7. Agilent Technologies: Moving from R&amp;D and Limited QC on a UV-Vis-NIR Instrument to Large-Scale QC Using an Autosampler</strong></h5><ul><li>Th, 12.2.2026 20:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/2104">Registration</a></li></ul><p>This presentation covers key aspects of adding and using an autosampler to maximize UV-Vis-NIR QC workflows when scaling from R&amp;D to routine quality control.</p>

Webinars LabRulezICPMS Week 07/2026

<p><strong>LA-ICP-MS imaging, particularly in TOF mode, provides rapid, high-resolution elemental maps of complex geological materials, but quantitative accuracy is often limited by heterogeneous mineralogy. This study introduces a workflow using UMAP for unsupervised dimensionality reduction combined with k-means clustering to segment mineral phases directly from per-pixel elemental data.</strong></p><p>Cluster compositions are matched to known minerals based on stoichiometry, allowing phase-specific normalization and reducing quantification errors by up to 60%. Validated on dawsonite-bearing sandstones, the approach enables consistent phase-resolved geochemical comparisons across depth profiles and establishes UMAP as a practical tool for accurate, interpretable multielement imaging.</p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05398"><strong>Mineral Phase-Resolved Quantification in LA-ICP-MS Imaging</strong></a></h4><p>Barbara Umfahrer, Jakub Buday, Pavel Pořízka, Jozef Kaiser, Paolo S. Garofalo*, and Detlef Günther*</p><p>Anal. Chem. 2026, 98, 1, 581–589</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acs.analchem.5c05398">https://doi.org/10.1021/acs.analchem.5c05398</a></p><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6></blockquote><p><strong>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.</strong></p><p>Since its introduction in 1985, <a href="javascript:void(0);">(1)</a> Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS) has matured into a routine technique for both qualitative and quantitative elemental analysis, finding use in diverse fields such as geology, <a href="javascript:void(0);">(2−4)</a> biology, <a href="javascript:void(0);">(5,6)</a> materials science, <a href="javascript:void(0);">(7)</a> and cultural heritage. <a href="javascript:void(0);">(8,9)</a> Especially in comparison to liquid analysis techniques, the method excels through minimal sample preparation, negligible sample destruction, and low limits of detection, which enable trace element analysis. However, besides the availability of standard reference materials, a longstanding challenge of quantitative LA-ICP-MS is the need for a suitable internal standard to account for variations in ablation rate and transport efficiency, as well as instrumental drift. <a href="javascript:void(0);">(10)</a> Developed for applications in geological matrices, this requirement was elegantly circumvented by Liu et al. <a href="javascript:void(0);">(11)</a> through 100 wt % normalization, which assumes that all detected elements form oxides summing up to 100 wt %. This approach was conceptually inspired by the summed-spectrum normalization calibration procedure introduced by Leach and Hieftje in 2000, which emphasized the use of total signal intensities for robust internal standardization. <a href="javascript:void(0);">(12)</a> The 100 wt % normalization strategy was subsequently extended to the bulk analysis of carbonates. <a href="javascript:void(0);">(13)</a></p><p>Concurrently, the advent of time-of-flight (TOF) mass analyzers and the development of fast-washout laser ablation cells <a href="javascript:void(0);">(14−16)</a> have transformed LA-ICP-MS into a powerful imaging tool, capable of generating spatial maps across a variety of sample matrices at high data acquisition rates. <a href="javascript:void(0);">(17−19)</a> Furthermore, in comparison to, e.g., X-ray fluorescence spectroscopy (XRF) or Scanning Electron Microscopy with Energy-Dispersive X-ray Spectroscopy (SEM-EDS), LA-ICP-MS offers a high depth resolution of approximately 0.2 μm on glass, enabling precise measurement of fine-scale structures not only laterally but also in depth. <a href="javascript:void(0);">(18)</a> However, as the volume and complexity of these elemental images have grown according to the progressive advancement of the method itself, now consisting of gigabytes of data produced within minutes, manual data interpretation has become increasingly impractical. To uncover meaningful details and patterns, researchers have applied multivariate methods such as Principal Component Analysis (PCA) and k-means clustering to reduce dimensionality and delineate distinct regions within the images. <a href="javascript:void(0);">(20−23)</a> The nonlinear dimensionality reduction technique Uniform Manifold Approximation and Projection (UMAP), <a href="javascript:void(0);">(24)</a> which supports data interpretation with its capability to capture and separate subtle local structures, has first been employed to LA-ICP-MS bulk analysis data in 2024, where it was used to classify pyrite samples and discriminate between Pb and Zn deposit types. <a href="javascript:void(0);">(25,26)</a> In combination with elemental imaging, UMAP has recently been applied to biological tissue data sets as an exploratory analysis tool, <a href="javascript:void(0);">(27)</a> further enhancing the ability to visualize and interpret complex elemental distributions.</p><p>Despite these advances, no existing approach combines the unsupervised segmentation of mineral phases by UMAP with phase-specific normalization. In this study, we introduce a UMAP-driven workflow that (1) automatically segments distinct mineralogical phases within fine-grained geological matrices and (2) applies phase-specific 100 wt % normalization (e.g., oxide <a href="javascript:void(0);">(11)</a> or carbonate <a href="javascript:void(0);">(13)</a>), thereby improving quantification accuracy and enabling phase-specific quantitative interpretation of mineral distributions in complex matrices.</p><h4><strong>Materials and Methods</strong></h4><h5><strong>LA-ICP-TOFMS Imaging</strong></h5><p>LA-ICP-TOFMS analyses were performed using a 193 nm ArF excimer laser (GeoLas C, Lambda Physik, Göttingen, Germany) coupled to an ICP-TOFMS instrument (icpTOF 2R, TOFWERK AG, Thun, Switzerland). Ablation was conducted in the modified parallel flow ablation cell (MPFAC) <a href="javascript:void(0);">(16,34)</a> under a He atmosphere (99.999%, Linde Gas Schweiz AG, Dagmersellen, Switzerland) with Ar (99.996%, Linde Gas Schweiz AG) used as the carrier gas. A piezoelectrically driven xyz translational stage (1 nm resolution, SmarAct GmbH, Oldenburg, Germany) enabled precise sample positioning. Laser, stage movement, and ICP-TOFMS data acquisition were synchronized using a custom-built imaging control system. <a href="javascript:void(0);">(19)</a> The system was optimized each day based on maximum sensitivity while ensuring a <sup>238</sup>U<sup>+</sup>/<sup>232</sup>Th<sup>+</sup> intensity ratio of 1.0 to 1.1 on NIST SRM 610 and a <sup>232</sup>Th<sup>16</sup>O<sup>+</sup>/<sup>232</sup>Th<sup>+</sup> rate of below 0.5%.</p><h5><strong>LIBS Imaging</strong></h5><p>The LIBS analyses were performed on a Firefly system (Lightigo, Czech Republic). The laser (1064 nm, 5 mJ, pulse duration ∼10 ns, diameter 6 mm, operating at 50 Hz) was focused on the sample with a singlet lens (focal length 50 mm) to a 30 μm spot. The spatial resolution of the acquired elemental maps, with a size of about 16 mm × 26 mm, was 20 μm. Plasma radiation is collected by a multifiber configuration with a collimator and an optical fiber (400 μm core diameter), which delivered the light to several Czerny–Turner spectrometers (resolution 0.25–0.4 nm). The spectral range of the spectrometers is 180–850 nm. The radiation is collected 1.5 μs after ablation, with a gate width of 15 μs.</p><p>Data processing was done with Python 3.11.8 in the Spyder environment and included background correction and per-pixel z-score normalization.</p><h4><strong>Results and Discussion</strong></h4><h5><strong>LIBS and XRD Measurements</strong></h5><p>To assess whether carbonate-based normalization <a href="javascript:void(0);">(13)</a> is warranted, first, large-scale LIBS elemental intensity maps of the samples across about a third of the thin sections were acquired. <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05398#fig1">Figure 1</a> reveals the results for “Layer 2” of the Poggio del Gatto sandstone for selected elements. A complete mapping of all four thin sections can be found in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acs.analchem.5c05398/suppl_file/ac5c05398_si_001.pdf">Figures S3 and S6</a> in the Supporting Information. The maps reveal that C is strongly enriched in fracture veins as well as in finer-grained domains within the matrix and correlates with Ca, indicating carbonate minerals rather than oxides. Bulk XRD analysis identifies calcite alongside quartz, plagioclase, white mica, and kaolinite. These complementary observations confirm calcite as a major phase and thus justify the need for performing the 100 wt % normalization on a carbonate basis for pixels representing calcite.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2026_98_1_581_589_Figure_1_LIBS_elemental_intensity_maps_of_the_data_set_from_Layer_2_of_the_Poggio_del_Gatto_sandstone_mounted_on_a_microscope_slide_73ada1b7b8.jpg" alt="Anal. Chem. 2026, 98, 1, 581–589: Figure 1. LIBS elemental intensity maps of the data set from “Layer 2” of the Poggio del Gatto sandstone mounted on a microscope slide, depicting calcite veins and fine-grained structures within the matrix, underlining the need for carbonate-based normalization for specific pixels. Emission lines for evaluation are shown in the corresponding subfigure title. The epoxy used to fix the thin section on the slide is visible along the margin." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2026_98_1_581_589_Figure_1_LIBS_elemental_intensity_maps_of_the_data_set_from_Layer_2_of_the_Poggio_del_Gatto_sandstone_mounted_on_a_microscope_slide_73ada1b7b8.jpg 245w," sizes="100vw" width="2088" height="414"></p><h5><strong>Renormalization Based on Carbonates</strong></h5><p>Applying an oxide-based normalization to carbonate samples will introduce composition-dependent biases that cannot immediately be generalized as a singular numerical value. The difference between the molecular masses of carbonate CO<sub>3</sub><sup>2–</sup> and its oxide equivalent O<sup>2–</sup> yields an intrinsic bias on the order of a factor of about two, depending on the stoichiometry. Once this data is renormalized to a total of 100 wt %, the magnitude of the error becomes highly dependent on the specific elemental composition of the sample. An exemplary calculation illustrating this effect for a representative calcite pixel is provided in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acs.analchem.5c05398/suppl_file/ac5c05398_si_001.pdf">Table S2</a>, yielding a relative error of 79%. In practice, this error varies across the image according to the local phase composition. <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05398#fig6">Figure 6</a> illustrates the impact of normalization approaches for layer 2 of the samples as well as the spatial distribution of the resulting relative error. The figure presents Ca and Si elemental maps in two rows, while the first three columns compare different normalization strategies: normalization based on all oxides, normalization based on all carbonates, and a pixel-wise normalization guided by mineral phase identification, as outlined in the workflow proposed in this study. The final column displays the relative error between the bulk oxide- or carbonate-based normalization and the pixel-wise, phase-informed normalization.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2026_98_1_581_589_Figure_6_Comparison_of_normalization_strategies_for_Ca_and_Si_LA_ICP_TOFMS_elemental_maps_in_Layer_2_ce3a0c1a5c.jpg" alt="Anal. Chem. 2026, 98, 1, 581–589: Figure 6. Comparison of normalization strategies for Ca and Si LA-ICP-TOFMS elemental maps in “Layer 2” of the Poggio del Gatto sandstone. Rows show Ca (top) and Si (bottom); columns compare (1) oxide-based normalization, (2) carbonate-based normalization, (3) pixel-wise, phase-informed normalization (this study), and (4) relative error between the first two and the phase-informed approach." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2026_98_1_581_589_Figure_6_Comparison_of_normalization_strategies_for_Ca_and_Si_LA_ICP_TOFMS_elemental_maps_in_Layer_2_ce3a0c1a5c.jpg 202w," sizes="100vw" width="2088" height="1622"></p><p>For Ca (in this matrix primarily associated with calcite, a dominant carbonate phase in our samples), the relative error depicted quantifies the effect of applying oxide-based normalization across the entire image. This results in a systematic overestimation of the Ca concentration by approximately 60%. Conversely, for Si─in this matrix found mainly in quartz and various plagioclase phases─the error is shown for applying carbonate-based normalization across an oxidic matrix. In such cases, the Si concentrations are underestimated by roughly 10% to 40%, depending on the mineral phase.</p><p>These findings highlight that using a single normalization scheme across heterogeneous samples introduces substantial quantification errors. To mitigate this, the pixel-wise phase segmentation enabled by the proposed UMAP-based workflow offers a significant advantage, especially in fine-grained matrices. In short, phase-aware, pixel-wise normalization combines the strengths of both normalization approaches and proves to be highly beneficial.</p><h4><strong>Conclusion</strong></h4><p>This study demonstrates that phase-specific normalization, guided by unsupervised phase segmentation of LA-ICP-MS images, can substantially improve the accuracy of elemental quantification in fine-grained geological matrices. Rather than relying on a single global assumption (e.g., all oxides or all carbonates), the workflow adapts normalization to the actual mineralogy, minimizing systematic errors and enabling phase-resolved geochemical interpretation.</p><p>The segmentation step, based on UMAP embedding and <i>k</i>-means clustering, is fully unsupervised. However, the subsequent matching of clusters to specific minerals still relies on a limited set of preidentified stoichiometries and is therefore not yet fully unsupervised. Expansion to larger stoichiometric databases could help overcome this limitation and move toward automated mineral classification. A key challenge remains the similarity of cation ratios in certain mineral groups, which may still require complementary data to ensure robust assignments.</p><p>Overall, beyond the specific case of the Poggio del Gatto sandstone presented in this study, this work provides a framework for quantitative elemental imaging of complex geological samples and is readily transferable to other contexts that require spatially resolved composition-aware normalization. This contribution adds a practical implementation to a growing literature that already uses multivariate statistics to unlock the immense information depth of LA-ICP-TOFMS.</p>

Mineral Phase-Resolved Quantification in LA-ICP-MS Imaging

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezICPMS Library in the week of 9th February 2026? Check out new documents from the field of spectroscopy/spectrometry and related techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT SPECTROSCOPY/SPECTROMETRY RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><strong>LabRulezGCMS</strong></a> libraries.</p></blockquote><p>This week we bring you application notes by <strong>Agilent Technologies</strong>, <strong>Metrohm,</strong> <strong>Shimadzu </strong>and<strong> Thermo Fisher Scientific!</strong></p><h3><strong>1. Agilent Technologies: Black Pepper Origin Differentiation Using Large ICP-MS Datasets and Chemometric Tools</strong></h3><p><strong>Elemental profiling using an </strong><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=1&amp;search=7850+ICP-MS"><strong>Agilent 7850 ICP-MS</strong></a><strong> and Agilent </strong><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=1&amp;search=Mass+Profiler+Professional+software"><strong>Mass Profiler Professional (MPP) software</strong></a></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_black_pepper_origin_7850_icp_ms_5994_8741en_agilent_7c190968ef.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Black pepper’s high value and global demand are drivers for economically motivated adulteration, a fraudulent practice that can pose public health risks. Because black pepper is most often sold in ground, crushed, or mixed forms, its supply chain is difficult to monitor and manage. Also, consumer campaigns against deforestation and the European Union Regulation on Deforestation-free (EUDR) products have increased calls for greater sourcing transparency. Products with a known geographical indication can demand a higher price. Companies do not want to become implicated in false claims about the sourcing of products, and many are keen to have full visibility of their products’ origin. To address this need, the European Commission has established the Protected Geographical Indication (PGI) system to protect regional specific products, thereby promoting their unique characteristics based on geographical origin and traditional competence of production. The PGI scheme has increased the demand for detailed information regarding the geographical source of food products, a trend that is likely to continue as EUDR is implemented across the EU and associated markets. Verifying the geographical origin of black pepper using elemental fingerprints is highly relevant to protecting value chain stakeholders, ensuring both quality and traceability while upholding the principles of food integrity.&nbsp;</p><p>Several analytical methods can be used for profiling certain elements in foods. However, inductively coupled plasma mass spectrometry (ICP-MS) is unique because of its rapid throughput, multi-element capability, ultratrace sensitivity, isotopic analysis, versatility across sample types, low sample volume requirements, compliance with regulatory requirements, and low cost.<sup>3</sup>&nbsp;</p><p>The Agilent 7850 ICP-MS is equipped with an Octopole Reaction System (ORS4 ), a collision/reaction cell (CRC) that uses helium (He) gas and Kinetic Energy Discrimination (KED) to remove polyatomic interferences on key analytes.<sup>4</sup> If left unchecked, these interferences can affect data accuracy in complex food products. The integration of the 7850 with Agilent ICP-MS MassHunter software streamlines data analysis. When integrated with chemometric analysis, ICP-MS demonstrates high precision in multi-elemental profiling of diverse food matrices, effectively distinguishing their geographical origin.<sup>5</sup>&nbsp;</p><p>In this study, 150 black pepper samples from five countries (Brazil, Cambodia, India, Indonesia, Vietnam) were analyzed using the 7850 ICP-MS to obtain elemental fingerprints of the samples. Agilent Mass Profiler Professional (MPP) software was used to process the ICP-MS elemental data and to construct chemometric models for distinguishing the geographical origin of the samples, as adapted from Chilaka et al.<sup>5</sup></p><h4><strong>Experimental&nbsp;</strong></h4><h5><strong>Instrumentation&nbsp;</strong></h5><p>An <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=1&amp;search=7850+ICP-MS"><strong>Agilent 7850 single-quadrupole ICP-MS</strong></a> was used for the analysis of 38 elements in the black pepper samples. Sample introduction was performed via a peristaltic pump connected to an Agilent MicroMist nebulizer and an Agilent SPS 4 autosampler. All elements were measured using helium collision (He KED) mode, except for boron (B), which was analyzed in no gas mode. Instrument control was performed using <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=1&amp;search=MassHunter"><strong>Agilent ICP-MS MassHunter 5.1 software</strong></a>, and data processing was conducted using <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=1&amp;search=Mass+Profiler+Professional+software"><strong>Agilent MPP software</strong></a>, version 15.1. Instrument operating conditions as shown in Table 1.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>This study investigated the potential of ICP-MS elemental profiling coupled with chemometric analysis for geographical origin discrimination of black pepper samples from five countries, including Brazil, Cambodia, India, Indonesia, and Vietnam. A total of 38 elements was measured in 150 black pepper samples using the Agilent 7850 ICP-MS. Chemometric analysis was performed on the ICP-MS elemental data using Agilent Mass Profiler Professional (MPP) software. The PCA analysis exhibited satisfactory reliability and classification rates and demonstrated potential for the authentication of the geographical origin of black pepper. However, the separation of the Cambodian and Vietnamese samples was less distinct than the other groups, revealing potential similarities in elemental profiling between the bordering countries, which share similar climatic, geological, and agricultural conditions. Using LDA and RF classification models on the black pepper test set, we achieved a high overall accuracy in determining the geographical origin of the samples. These findings provide empirical support for the combined use of elementomics and chemometric techniques in black pepper authentication, contributing to fraud prevention. The study also demonstrates the potential of the method for application to other food types.</p><h3><strong>2. Metrohm: Milk powder analysis by near-infrared spectroscopy</strong></h3><p><strong>Determination of moisture, fat, lactose, and protein content</strong></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_nir_128_download_867321cfb0.pdf"><strong>Full PDF for download</strong></a></li></ul><p>For milk powder producers, final product control is essential to meet strict regulatory standards, guarantee comprehensive quality assurance, ensure consistent nutritional quality, and extend shelf life. These are all especially important for infant formula and dairy ingredients used in sensitive applications. Near-infrared spectroscopy (NIRS) is a fast, reagentfree method for measuring key quality parameters such as moisture, protein, lactose, and fat content directly in milk powder. The NIRS solution requires no sample preparation, enabling real-time monitoring either in the lab or directly on the production line. This allows producers to react quickly to process variations, minimize waste, and maintain product integrity batch after batch.</p><h4><strong>EXPERIMENTAL EQUIPMENT&nbsp;</strong></h4><p>More than 600 samples of powdered milk from different suppliers were analyzed on an <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=56&amp;search=OMNIS+NIR"><strong>OMNIS NIR Analyzer</strong></a> (Figure 1). The different milk powders were placed into an OMNIS sample cup and analyzed in diffuse reflection mode. To include sample variety, the sample rotated during measurement to collect spectra from different locations. The automatically averaged spectra were used for model development. Reference values were obtained by official methods, e.g., AOAC 927.05 (moisture), AOAC 939.02 (protein), and AOAC 932.06 (fat). For the lactose content determination, a phenol-sulfuric acid method was used.</p><h4><strong>CONCLUSION</strong></h4><p>This Application Note presented the analysis of milk powder using NIR spectroscopy. Models for several quality parameters (fat, protein, lactose, and moisture content) were created. Independent validation samples confirmed the robustness and reliability of the models, with high correlation coefficients and low prediction errors achieved across all parameters. Notably, the dataset included samples from diverse global origins, capturing a broad range of product variability. This study shows that NIRS can be successfully integrated into the quality control workflow for dairy powder analysis.</p><h3><strong>3. Shimadzu: Analysis of Electrolyte and Electrode in LIB Degraded by Overcharge and High Temperature</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_01_01064_en_b4f9f4330a.pdf"><strong>Full PDF for download</strong></a></li></ul><h4><strong>User Benefits</strong></h4><ul><li>ICP-AES enables accurate quantification of cathode material dissolved in electrolytes.</li><li>GC-MS assesses degradation from components in electrolytes with unknown usage.</li><li>EDXRF easily evaluates transition metals, phosphorus, fluorine, and other elements deposited on electrodes</li></ul><p>When lithium-ion batteries are used in EVs or ESS applications, numerous cells are connected in series and parallel to form modules, and multiple modules are further connected to construct a pack. In such configurations—where many cells are connected in series—the state of charge of individual cells varies, as shown in Figure 1. Moreover, because the cells are densely packed to reduce volume, the ambient temperature experienced by each cell also varies. In this application, we conducted cycle tests under overcharged or high-temperature conditions, disassembled the degraded pouch cells, and analyzed both the electrolytes and the electrodes.</p><h4><strong>Analysis of electrolyte and electrode</strong></h4><p>Electrolytes and electrodes were extracted from the batteries degraded through the cycle tests (hereafter referred to as “degraded cells”) and analyzed using the instruments shown in Figures 3–5. It is known that electrolytesin degraded cells contain transition metals (Ni, Co, Mn) dissolved from the cathode active material1). In addition, electrolyte solvents are known to generate characteristic degradation products as deterioration progresses2). By analyzing these degradation-related elements and compounds, the degradation state of the battery can be assessed. In this article, we propose a multifaceted evaluation of electrolytes using <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=3&amp;search=ICPE-9820"><strong>ICP-AES</strong></a> and GC-MS. On both the cathode and anode, insulating layers known as CEI/SEI form on the electrode surfaces. Under improper charging conditions, excessive formation of these layers can lead to capacity loss. Furthermore, the dissolved metals from the cathode deposit and precipitate on the anode. These deposits can cause internal short circuits, posing risks such as fire hazards. While such electrode conditions are typically evaluated by ICP-AES or XPS to examine elemental content or surface chemical states, this article introduces a simpler evaluation method using <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=3&amp;search=EDX-8100"><strong>EDXRF</strong></a>.</p><h4><strong>Summary</strong></h4><p>Analysis of the electrolytesfrom degraded batteries using ICP-AES and GC-MS revealed dissolution of transition metals as well as the formation of degradation products. Furthermore, EDXRF analysis of the electrodes enabled straightforward detection of changesin elemental composition, including transition metals, fluorine, and phosphorus. These analytical techniques allow for a multifaceted evaluation of battery degradation. In real-world battery operation, fluctuations in charging conditions and ambient temperature introduce variability in degradation states. By assessing degradation mechanisms individually, as demonstrated in thisreport, it is possible to obtain insights that contribute not only to improving intrinsic battery performance but also to optimizing implementation methods and control conditions.</p><h3><strong>4. Thermo Fisher Scientific: Analyzing Spinel refractory MgO-Al2O3 premix using </strong><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=2&amp;search=ARL%E2%84%A2+X%E2%80%99TRA+Companion"><strong>ARL X’TRA Companion XRD</strong></a></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/spinel_refractory_xrd_an41525_en_75f2527e78.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Spinel refractories—primarily magnesia–alumina (MgAl₂O₄)— are the workhorses of high-temperature linings in steel ladles, cement rotary kilns, glass tanks, and non-ferrous smelters. Their appeal lies in a combination of shock resistance, chemical stability against basic slags, and an expansion behavior that mitigates cracking. Depending on the duty, they are used as bricks, castables, or gunned repairs, sometimes with engineered microstructures that blend spinel with periclase, corundum, or zirconia to tune creep, corrosion, and spalling performance.&nbsp;</p><p>X-ray diffraction (XRD) underpins manufacturing control from raw mix to fired product. During synthesis, XRD tracks the solid-state reaction of MgO and Al₂O₃ into spinel, verifying the disappearance of periclase and alumina and quantifying the spinel fraction by Rietveld analysis. Lattice parameters reveal cation stoichiometry and solid-solution effects; peak breadth trends indicate crystallite growth and microstrain, proxies for sintering progress. In finished components, XRD detects secondary phases such as calcium aluminates introduced by binders, slags, impurities, and it provides fingerprinting for batch-to-batch consistency after thermal exposure. Embedded into routine QA/QC, XRD shortens feedback loops, stabilizes recipes, and links processing conditions to the microstructure that governs refractory life.</p><h4><strong>Instrument &amp; software&nbsp;</strong></h4><p>The <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=2&amp;search=ARL%E2%84%A2+X%E2%80%99TRA+Companion"><strong>Thermo Scientific™ ARL™ X’TRA Companion</strong></a> X-Ray Diffractometer (c.f. Figure 1) is a simple, easy-to-use benchtop instrument for routine phase analysis as well as more advanced applications. The ARL X’TRA Companion uses a θ/θ goniometer (160 mm radius) in Bragg-Brentano geometry coupled with a 600 W X-ray source (Cu or Co). The radial and axial collimation of the beam is controlled by divergence and Soller slits, while air scattering is reduced by a variable beam knife. An integrated water chiller is available as an option. Thanks to the state-of-the art solid state pixel detector (55x55 μm pitch), the ARL X’TRA Companion provides very fast data collection and comes with single-click Rietveld quantification capabilities and automated result transmission to a LIMS (Laboratory Information Management System) seamless integrated into Thermo Scientific™ SolstiX™ Pronto instrument control software.</p><h4><strong>Your benefits&nbsp;</strong></h4><p>The ARL X’TRA Companion XRD workflow delivers answers in minutes, quantifying MgO, α-Al₂O₃, and MgAl₂O₄ while resolving Ca–Si silicates and trace Fe-spinels. Subtle differences between corundum and spinel are cleanly separated, and LOI drivers—carbonates, brucite, and Mg-sulfates—are identified and trended. These insights let you compute spinel potential, anticipate pore-closing expansion, and set the right pre-dry / prefire schedule to avoid spalling. You can clearly distinguish mid-grade, ore-derived feeds from premium low-silica materials, tighten incoming QA, and optimize formulations for cement/lime kilns, tundish linings, and other carbon-free basic applications.</p>

News from LabRulezICPMS Library - Week 07, 2026

<p><strong>In the week from February 16, the following webinars await you in the field of atomic and molecular spectroscopy and spectrometry</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 000 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. Thermo Fisher Scientific: The Perfect Pair for GMP Compliance – IonicX and TruScan for Raw Material Identification and Verification</strong></h5><ul><li>Tu, 17.2.2026 20:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5835">Registration</a></li></ul><p>Learn how the IonicX™ Portable XRF Analyzer enables rapid, at-line identification of ionic salts in GMP manufacturing, delivering real-time PASS/FAIL results and streamlined raw material verification.</p><h5><strong>2. Milestone: Reliable Mercury Analysis in Environmental Samples – Tools, Techniques, and Best Practices</strong></h5><ul><li>Th, 19.2.2026 16:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5804">Registration</a></li></ul><p>Episode 3 focuses on reliable mercury analysis in environmental samples, demonstrating how direct analysis simplifies workflows, reduces contamination risks, and delivers accurate results without digestion.</p><h5><strong>3. Agilent Technologies: Learn How to Confirm Your Data on ICP-OES – Are You Getting the Right Result?</strong></h5><ul><li>Th, 19.2.2026 20:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/2785">Registration</a></li></ul><p>This webinar discusses accuracy and precision in ICP-OES analysis and practical strategies to ensure reliable and defensible results.</p>

Webinars LabRulezICPMS Week 08/2026

<p><strong>Metalloproteins play essential roles in marine phytoplankton, yet their metalloproteomes remain poorly characterized. This study combines protein modeling, quantitative proteomics, and ICP-MS measurements to assess metal requirements across several phytoplankton species, including chlorophytes, a haptophyte, and a cyanobacterium.</strong></p><p>Results show strong agreement between proteome-inferred metal demands and measured cellular metal quotas, while providing deeper insight into biological functions. Mg-containing proteins were most abundant overall, with Zn, Fe, and Mn as dominant trace cofactors. Distinct differences between prokaryotic and eukaryotic phytoplankton were observed, and strain-level analysis demonstrated how metalloproteomes reflect environmental adaptation and metal limitation strategies.</p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.est.5c11233"><strong>Unlocking Phytoplankton Metallomes with Comparative Analysis of Metal Quotas, Quantitative Proteomics, and Inferred Metalloproteomes</strong></a></h4><p>Qiong Zhang*, Jiayou Ge, Fengjie Liu, Shabaz Mohammed, Kedong Yin, and Rosalind E. M. Rickaby</p><p>Environ. Sci. Technol. 2025, 59, 50, 27367–27377</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acs.est.5c11233">https://doi.org/10.1021/acs.est.5c11233</a></p><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6></blockquote><p><strong>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.</strong></p><p>Many important biological processes of phytoplankton, including photosynthesis, carbon fixation, and nitrogen reduction, rely on enzymes that have metals as cofactors. <a href="javascript:void(0);">(1)</a> It has been estimated that half of all enzymes must be associated with a particular metal to function. <a href="javascript:void(0);">(2)</a> The availability of metals in the environment has changed over geological time and, given imperfections in the selectivity of metal transport systems, proteins have evolved to make the best use of metals that are more available. <a href="javascript:void(0);">(3−5)</a> Depending on their evolutionary histories, different groups of marine phytoplankton may have differences in their metalloprotein compositions and metal transport strategies. The evolving trace metal availability in the environment, thus, may provide a selective pressure to promote the proliferation of different phytoplankton groups in the oceanic environment, affecting the phytoplankton community structure with knock-on effects on the marine food web and carbon sequestration. <a href="javascript:void(0);">(5)</a> It is crucial to understand the utilization of trace metals by different groups of marine phytoplankton that inhabit contrasting niches in the modern ocean, not only by assessing the accumulation of trace metals in cells but also examining the functions of trace metals in different biological pathways.</p><p>In previous studies, the utilization or requirements of trace metals by marine phytoplankton were mostly determined by measuring the elemental stoichiometry in cells (metallome or quota of trace metals). <a href="javascript:void(0);">(6−8)</a> In the field, attempts have also been made to investigate the elements in phytoplankton <a href="javascript:void(0);">(9,10)</a> which have then been compared with profiles in the abiotic environment to understand their relationships. <a href="javascript:void(0);">(11)</a> The discovery of various metal storage proteins and the plasticity in elemental quotas under different environmental conditions raise the question of whether intracellular trace metal quotas reflect true differences in trace metal usage by phytoplankton. <a href="javascript:void(0);">(12,13)</a> In the past few decades, more and more studies have focused on metal–protein partnerships, using approaches such as genome-wide analysis to identify homologues of known metalloproteins and other deduced metal-binding motifs encoded within sequenced genomes. <a href="javascript:void(0);">(5,14)</a> However, this approach has limitations in estimating metal abundance in cells because not all genes predicted in the genome would be translated and expressed as proteins under all environments, and a single gene for a metalloprotein could be highly expressed, such that a translation from genetic presence to a required concentration is not linear and could be environment-dependent. To obtain <i>in situ</i> metal abundance in metalloproteins in cells, native separation of proteins by HPLC or PAGE followed by the detection of metals using ICP-MS <a href="javascript:void(0);">(15,16)</a> has been used. This approach also has limitations in that, without bioinformatics, it cannot identify the function of proteins within which the metals are found, and it may also depend on the composition of the media to which the organism has been exposed and in which it has been growing. An ideal way to solve the problem would be to separate and purify each of the proteins and then identify both the associated metal (<i>e.g.,</i> by ICP-MS) and the protein sequence (<i>e.g.,</i> by mass spectrometry). However, this approach is constrained by the resolution of chromatographic or electrophoretic techniques, making it challenging to establish the metal–protein associations unambiguously; many proteins often co-occur in metal-containing fractions. Additionally, this method requires huge volumes of biomass and is both time-consuming and complex, complicating the reconstruction of the expressed metalloproteome in cells. The techniques and challenges for metalloproteomics have been discussed in detail in previously published review articles (and the references therein). <a href="javascript:void(0);">(17)</a></p><p>In this study, we determined the trace metal utilization (the metallome) of different phytoplankton from their expressed proteome via a protein modeling and homologue identification approach, and then compared the resulting metallome with the metal quota data measured by the traditional inductively coupled plasma mass spectrometry (ICP-MS). This approach allows the building of a link between the truly used trace elements and their biological functions in phytoplankton. We aim to fill the gap between an estimation of metals encoded in the genome and metal analysis by ICP-MS in phytoplankton, which may be more broadly applicable to infer cellular metallomes.</p><h3><strong>Materials and Methods</strong></h3><h4><strong>ICP-MS Analysis</strong></h4><p>All preparation of samples for ICP-MS measurement was undertaken using trace metal clean methods. All plasticware used in this study, including culture flasks, pipette tips, and centrifuge tubes, was precleaned in 10% quartz-distilled HCl and thoroughly rinsed with 18 MΩ cm water in a clean laboratory. Trace elements in the filtered lysates of <i>G. huxleyi</i> (OA1, OA4, OA8, OA15, OA16, OA23, and RCC 1242) and <i>Synechocystis</i> (FACHB898) strains were measured using an ICP-MS. The detailed ICP-MS method and instrumental settings are described in Zhang et al. (2018). <a href="javascript:void(0);">(31)</a></p><h4><strong>Protein Mass Spectrometry</strong></h4><p>The peptides were resuspended in 5% formic acid and 5% DMSO prior to mass spectrometry. They were separated on an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=3&amp;search=Ultimate+3000+UHPLC"><strong>Ultimate 3000 UHPLC </strong></a>system (Thermo Fisher Scientific) and electrosprayed directly into a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/559"><strong>Q-Exactive Mass Spectrometer</strong></a> (Thermo Fisher Scientific) through an EASY-Spray nanoelectrospray ion source (Thermo Fisher Scientific). The peptides were trapped on a C18 PepMap100 precolumn (300 μm i.d. × 5 mm, 100 Å, Thermo Fisher Scientific) using solvent A (0.1% formic acid in water) at a pressure of 500 bar. The peptides were separated on an in-house packed analytical column (75 μm i.d. × 50 cm packed with ReproSil-Pur 120 C18-AQ, 1.9 μm, 120 Å, Dr. Maisch GmbH) using a linear gradient (length: 65 min, 15% to 35% solvent B [0.1% formic acid in acetonitrile], flow rate: 200 nL/min). The raw data were acquired on the mass spectrometer in a data-dependent mode (DDA). Full scan MS spectra were acquired in the Orbitrap (scan range 350–1500 <i>m</i>/<i>z</i>, resolution 70000, AGC target 3e6, maximum injection time 50 ms). After the MS scans, the 10 most intense peaks were selected for HCD fragmentation at 30% of normalized collision energy. HCD spectra were also acquired in the Orbitrap (resolution 17500, AGC target 5e4, maximum injection time 120 ms, isolation window 1.5 <i>m</i>/<i>z</i>) with the first fixed mass at 180 <i>m</i>/<i>z</i>. Charge exclusion was selected for unassigned and 1+ ions. The dynamic exclusion was set to 20 s.</p><h3><strong>Results and Discussion</strong></h3><h4><strong>Trace Elements Determined from the Expressed Proteomes of Different Phytoplankton</strong></h4><p>Based on the expressed proteome sequences, we predicted metal-binding proteins and compared their distribution among various phytoplankton species (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.est.5c11233#fig2">Figure 2</a>). The inference revealed 28 different metals in <i>G. huxleyi</i>, 31 different metals in <i>C. reinhardtii</i>, and 30 different metals in <i>Synechocystis</i>. Although only 6 different metals were identified in <i>O. tauri</i> proteins, it has to be noted that the analysis for <i>O. tauri</i> was only based on the 40 most abundant proteins reported in this organism <a href="javascript:void(0);">(21)</a> and, hence, the listed elements, including Mg, Fe, Mn, Ca, Zn, and Cu, may represent the most essential metals for the species.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Environ_Sci_Technol_2025_59_50_27367_27377_Figure_2_The_number_of_metal_binding_proteins_identified_in_the_expressed_proteome_of_the_haptophyte_G_9b8ac0f004.jpeg" alt="Environ. Sci. Technol. 2025, 59, 50, 27367–27377: Figure 2. The number of metal-binding proteins identified in the expressed proteome of the haptophyte G. huxleyi (a), the chlorophyte C. reinhardtii (b) and O. tauri(c), and the cyanobacteria Synechocystis (d). Pie charts show the percentages of metalloproteins containing specific metals. Original proteome data for G. huxleyi are from Mckew et al. (2013) (24) for C. reinhardtii are from Hsieh et al. (2013) (77) for O.tauriare from Martin et al. (2012) (21) for Synechocystisare from Chen et al. (2018). (22) *Noted that for O. tauri, only the 40 most abundant proteins were included in this analysis. ND: no metal binding was found in the proteins." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Environ_Sci_Technol_2025_59_50_27367_27377_Figure_2_The_number_of_metal_binding_proteins_identified_in_the_expressed_proteome_of_the_haptophyte_G_9b8ac0f004.jpeg 123w," sizes="100vw" width="934" height="1181"></p><p>The number of proteins that bind with different metals varies dramatically in phytoplankton. For metalloproteins, there are variations in the binding affinities of different metals to organic molecules. For example, the affinities of divalent metals to proteins have a tendency to follow a universal order of preference, namely the Irving-Williams series (Mg<sup>2+</sup> and Ca<sup>2+</sup> [weakest binding] &lt; Mn<sup>2+</sup> &lt; Fe<sup>2+</sup> &lt; Co<sup>2+</sup> &lt; Ni<sup>2+</sup> &lt; Cu<sup>2+</sup> &gt; Zn<sup>2+</sup>). <a href="javascript:void(0);">(43)</a> Cells can simultaneously contain proteins having high-affinity-binding metals, such as Cu and Zn, and others that require uncompetitive metals, such as Mg and Ca. One of the least competitive metals for binding with biological chelators, Mg, is even found to be the most widely distributed metal in the metalloproteomes of various phytoplankton species in this study, supporting the observations of high concentrations in the protein fraction of cells (at millimolar concentrations <a href="javascript:void(0);">(31)</a>).</p><p>In all phytoplankton species in our analysis, the Mg-containing proteins are found to have the highest proportion in all metalloproteins identified. About 30% of the metalloproteins in different strains of phytoplankton are found to contain Mg or depend on it for function (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.est.5c11233#fig2">Figure 2</a>), suggesting the important role of Mg in phytoplankton cells. It is generally coordinated in protein complexes by ATP or ADP and has also been found to be largely distributed in the chloroplasts or thylakoids in <i>G. huxleyi</i> and <i>Synechocystis</i>. <a href="javascript:void(0);">(22,24)</a> The essential roles of Mg in plants have been reported in various studies. Mg<sup>2+</sup> is known to be the central atom of the chlorophyll molecule, and its levels in the chloroplast regulate the activity of key photosynthetic enzymes. <a href="javascript:void(0);">(44)</a> It was reported that approximately 15–35% of total Mg is in the chloroplasts of a plant, <a href="javascript:void(0);">(45)</a> and it also serves as an osmotically active ion in the regulation of cells <a href="javascript:void(0);">(46)</a></p><h4><strong>Comparison Between Metallome Measured Directly and Reconstructed from Proteins</strong></h4><p>A large proportion of metals, such as Fe, Mn, and Cu, are found in membrane proteins,and may contribute significantly to total cellular quotas. <a href="javascript:void(0);">(54,55)</a> However, for method development purpose, we endeavored to remove the cell membranes from our samples to focus mostly on the analysis of intracellular metal quotas and metalloproteins in the cytosol fraction in this study. We note that our analysis includes some membrane-bound proteins likely derived from organelles or surface membranes disrupted during sonication.</p><p>The derivation of cellular metal composition, as determined by two different methods, is compared in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.est.5c11233#fig3">Figure 3</a>. The abundance of metal in the proteins is determined as the relative abundance of the protein multiplied by the number of metal ions needed for the specific protein. The abundance of the proteins was normalized to ensure that the total intensities from each replicate measurement for the same species were similar. Since the proteomic data used here were generated from different studies using different instruments, we cannot quantify or compare the absolute biomass of proteins used for each species. Therefore, we cannot compare the absolute trace metal abundance between species solely from metal inferences of expressed proteomes. Nevertheless, we can estimate the relative abundance of different metals in the same species. For the elements that are both measured by the ICP-MS and identified in the proteome, there are generally good correlations (<i>r</i><sup>2</sup> = 0.81 in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.est.5c11233#fig3">Figure 3</a>a and <i>r</i><sup>2</sup> = 0.74 in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.est.5c11233#fig3">Figure 3</a>b) between the two approaches. This indicates that the metal compositions determined from the protein modeling may be reliable and, therefore, can reflect the metal usage in different phytoplankton. This would provide a level of assurance to further investigate the metal binding associated with various proteins, thereby deepening our understanding of the roles that different metals play in phytoplankton.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Environ_Sci_Technol_2025_59_50_27367_27377_Figure_3_Relationship_between_the_abundance_of_metals_determined_by_ICP_MS_analysis_e7b259e376.jpeg" alt="Environ. Sci. Technol. 2025, 59, 50, 27367–27377: Figure 3. Relationship between the abundance of metals determined by ICP-MS analysis (normalized to C, mmol/mol C) and metal abundance determined from the metalloproteome analysis (the unit is arbitrary). To account for strain variations, the ICP-MS data for the cellular metal content of G. huxleyi are average values from 7 G. huxleyi strains isolated from different areas of the ocean, and the proteome-derived metal composition data are average values calculated from 2 of those G. huxleyi strains (OA1 and OA16) isolated previously, and data from Mckew et al., 2013. (24) The ICP-MS data for Synechocystis are from Synechocystis sp. FACHB898 measured in this study, and the proteome data are calculated from Chen et al., 2018. (22) Noted that the abundance of metals from each proteome was calculated by using the metal stoichiometry multiplied by the relative abundance of proteins, which provides only a relative relationship of different trace metals, not absolute abundance. The symbols represent the mean values, and the error bars indicate standard deviations." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Environ_Sci_Technol_2025_59_50_27367_27377_Figure_3_Relationship_between_the_abundance_of_metals_determined_by_ICP_MS_analysis_e7b259e376.jpeg 245w," sizes="100vw" width="1384" height="641"></p><p>Compared to the other metals investigated in this study, Ca and Mg appear to have a much higher relative abundance in the ICP-MS analysis than in the proteomic analysis of <i>G. huxleyi</i> and <i>Synechocystis</i> (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.est.5c11233#fig3">Figure 3</a>). These two elements are essential macronutrients for phytoplankton and plants. Ca is the most prominent secondary messenger that plays a crucial role in response to extracellular stimuli in all eukaryotes. Ca<sup>2+</sup> fluxes are transported via Ca channels and transporters, such as Ca-ATPase, regulating a series of important biological functions, including mineral uptake and utilization, K<sup>+</sup> homeostasis adjustment, and regulatory network activity in response to P or N deficiency. <a href="javascript:void(0);">(56)</a> Ca is not always incorporated into protein structures. The Ca abundance determined from the proteins in this study, therefore, is much lower than the actual Ca needed intracellularly. Similarly, the intracellular Mg<sup>2+</sup> and K<sup>+</sup> abundances should also be higher than those determined from the protein structures. Free Mg<sup>2+</sup> and K<sup>+</sup> are known to regulate cation–anion balance and serve as osmotically active ions in the regulation of cells <a href="javascript:void(0);">(46)</a> but free metal ion concentrations cannot be determined through the approach used in this study. Thus, it is not surprising to see much higher relative abundances of Ca and Mg in ICP-MS analysis than in proteomic analysis (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.est.5c11233#fig3">Figure 3</a>).</p>

Unlocking Phytoplankton Metallomes with Comparative Analysis of Metal Quotas, Quantitative Proteomics, and Inferred Metalloproteomes

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezICPMS Library in the week of 16th February 2026? Check out new documents from the field of spectroscopy/spectrometry and related techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT SPECTROSCOPY/SPECTROMETRY RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><strong>LabRulezGCMS</strong></a> libraries.</p></blockquote><p>This week we bring you application notes by <strong>Agilent Technologies</strong>, <strong>Metrohm,</strong> <strong>Shimadzu </strong>and<strong> Thermo Fisher Scientific!</strong></p><h3><strong>1. Agilent Technologies: Quality Assessment of Saffron by UV‑Vis Spectroscopy in Accordance with ISO 3632</strong></h3><p><strong>Integrated quantitative analysis using an </strong><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=Cary+3500+UV-Vis"><strong>Agilent Cary 3500 UV-Vis</strong></a><strong> and </strong><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=Cary+UV+Workstation"><strong>Cary UV Workstation</strong></a></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_saffron_uv_vis_cary_5994_8611en_agilent_92d74b2cbd.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Saffron is the world's most expensive spice, with its price per gram dependent on quality, origin, and purity. It is renowned for its vibrant color and distinctive flavor—attributes that contribute significantly to its culinary appeal. However, saffron's high market value and limited production make it vulnerable to adulteration, quality degradation, and mislabeling, all of which pose a risk to consumer health, safety, and trust.&nbsp;</p><p>Ultraviolet-Visible (UV-Vis) spectroscopy is a rapid, reliable analytical technique suitable for assessing spice quality by quantifying bioactive molecular markers. In saffron, crocin is the carotenoid compound responsible for color intensity, picrocrocin is the primary bittering agent, and safranal is the key contributor to aroma.&nbsp;</p><p>In this application note, we used an Agilent Cary 3500 UV-Vis spectrophotometer and Agilent Cary UV Workstation software to analyze a commercial saffron sample. The aim of the study was to grade the quality of the sample in accordance with ISO 3632-1:2025 and ISO 3632-2:2010 Spices — Saffron (Crocus&nbsp;sativus L.).<sup>1,2</sup> These well-established industry standards provide specifications and test methods for the analysis of dried saffron, including filaments, cut filaments, and powder. The standardized test methods outlined in ISO&nbsp;3632-2 support the classification and quality evaluation of saffron. The methods relate to the determination of moisture and volatile matter content (clause 7), crushing and sieving of samples for tests (clause 10), and the determination of the main characteristics using a UV-Vis spectrometric method (clause 14). Based on these evaluations and the quality criteria defined in ISO 3632-1:2025, saffron samples can be categorized into four commercial grades: Extra Class (EC), I, II, and III, with EC indicating the highest quality. &nbsp;</p><h4><strong>Experimental</strong></h4><h5><strong>Instrumentation&nbsp;</strong></h5><p>The blank cuvette and aqueous extract of sample cuvette were loaded in the <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=Cary+3500+UV-Vis"><strong>Agilent Cary 3500 Multicell UV-Vis</strong></a> (Figure&nbsp;1), which was operated using the parameters listed in Table 1. The instrument is powered by a xenon flash lamp that requires no warmup time and enables a full spectrum scan to be collected in under a second. The lamp includes a 10-year replacement warranty, minimizing the frequency and cost of replacement. The Cary 3500's modular design approach enables the spectrophotometer series to be configured towards varying sampling flexibility and scalability needs. For single sample applications and laboratories with reduced bench-space, the Cary 3500 Compact UV-Vis allows a user to measure a single sample and reference in ambient or temperature-controlled configuration. This application can also be conducted on the Cary 3500 Flexible UV-Vis, which has a larger-sized compartment for liquid and solid sample measurements, and for use with accessories.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>The Agilent Cary 3500 Multicell UV-Vis spectrophotometer combined with <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=Cary+UV+Workstation"><strong>Agilent Cary UV Workstation software</strong></a> provided precise quantification of color, taste, and aroma through the measurement of crocin, picrocrocin, and safranal compounds, respectively. The method supports the quality assessment of saffron in accordance with the ISO 3632 industry standard, enabling reliable grading of commercial samples while also flagging potential cases of adulteration, degradation, or mislabeling.&nbsp;</p><p>The Cary 3500 UV-Vis uses a reliable, long-lasting xenon flash lamp that requires no warmup time, allowing immediate operation and acquisition of full spectral scans for blank and saffron samples in under a second. These capabilities support high-throughput analysis of spices through the precise measurement of compound-specific absorbance&nbsp;peaks.&nbsp;</p><p>Using built-in spectral tools, automated calculations, and clear reporting features, the Cary UV Workstation significantly simplified the sampling-to-reporting workflow for saffron analysis. Customized calculations defined in ISO 3632 accelerate data processing and reduce calculation errors. The software also delivers results via a user-friendly interface, ideal for traceability.&nbsp;</p><p>Together, the Cary 3500 UV-Vis and Cary UV Workstation delivered significant time-savings by minimizing time spent analyzing data and allowing more time for quality assurance of samples. The Cary 3500 system provides an efficient solution for the determination of the main characteristics saffron in accordance with clause 14 of ISO 3632-2:2010.</p><h3><strong>2. Metrohm: Feed analysis with near-infrared spectroscopy (NIRS)</strong></h3><p><strong>Simple, fast multiparameter determination of animal feed</strong></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_nir_127_download_b6b6969944.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Livestock production is a complex process involving many independent and integrated operations. According to the World Health Organization (WHO), the foundations for successful livestock production are the availability of animal feed and efficient feeding. Quality control (QC) of feed and feed ingredients is crucial to ensure the production of safe and nutrient-rich animal feed. Typical QC parameters measured during the production of feed are fat, moisture, protein, fiber, ash, and starch. However, analyzing these parameters is usually done with wet chemistry, requiring different time-consuming procedures, complex analysis methods, and costly chemical reagents. Near-infrared spectroscopy (NIRS) offers rapid and reliable prediction of fat, moisture, protein, fiber, ash, and starch content of different feed types in a few seconds without any sample preparation.</p><h4><strong>EXPERIMENTAL EQUIPMENT</strong></h4><p>Around 500 samples of feed (e.g., for poultry, swine, cattle, goats, and sheep) were analyzed on a <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=56&amp;search=OMNIS+NIR"><strong>Metrohm NIR Analyzer</strong></a>. All measurements were performed in reflection mode using the large cup. The samples were measured in rotation to collect spectral data from several areas. Spectral averaging of signals from various spots helped to reduce influences from sample inhomogeneity. Metrohm software was used for all data acquisition and prediction model development.</p><h4><strong>CONCLUSION</strong></h4><p>This Application Note demonstrates the feasibility to determine multiple key quality parameters of feed with NIRS analysis. Several analytical methods are usually required to measure starch, ash, fiber, protein, moisture, and fat in animal feed (Table 4). NIR feed analysis offers an easier alternative with high accuracy and real-time results.</p><h3><strong>3. Shimadzu: Online TOC Measurement for Ultra-pure Water in Semiconductor Industries</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_01_01068_en_169a321574.pdf"><strong>Full PDF for download</strong></a></li></ul><h4><strong>User Benefits</strong></h4><ul><li>Enables stable measurement of ultra-pure water with TOC concentrations below 1 μg/L.</li><li>The large color touch panel and compact body make operation easy.</li><li>The Active-Path structure, which integrates the lamp and sample flow path, enables high oxidation performance.</li></ul><p>The semiconductor manufacturing process involves various stages such as wafer production, film formation, photolithography, etching, and resist stripping, each of which involves cleaning steps. Even minimal contamination on the semiconductor surface can impact product quality and yield, making it crucial to effectively remove dirt and impurities during cleaning. For this reason, the purity of the cleaning water used in these cleaning processesis extremely important. The recent trend towards ever-smaller, higher-capacity semiconductors means that ultra-pure cleaning water, thoroughly free of organic and other impurities, has become essential.</p><p>Typically, ultra-pure water is produced by first purifying tap or groundwater to produce pure water, and then further refining it into ultra-pure water. Impurities in water include organic and inorganic substances, particles, as well as microorganisms. Various methods, such as activated carbon filters, reverse osmosis (RO) membranes, ultraviolet lamps, and ion exchange resins, are used in combination to purify water into ultra-pure water.&nbsp;</p><p>Maintaining the quality of ultra-pure water used for semiconductor cleaning is critical. The online TOC analyzer for ultra-pure water, TOC-1000e S (Fig. 1), enables highly sensitive TOC measurement with a detection limit of 0.02 μg/L using UV oxidation and conductivity measurement methods. This application presents the features and functions of the <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=1&amp;search=TOC1000e+S"><strong>TOC1000e S</strong></a>, along with examples of online measurements of ultrapure water.</p><h4><strong>Features of </strong><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=1&amp;search=TOC1000e+S"><strong>TOC-1000e S&nbsp;</strong></a></h4><p>The TOC-1000e S is an ultra-compact device that can be installed on a tabletop, wall, or pole mount. The front panel features a large color touch panel that is highly visible even in dark environments, enabling easy operation. An excimer lamp (mercury-free) that emits high-energy ultraviolet light with a wavelength of 172 nm is used as the light source for the oxidation section. To ensure the oxidation of organic compounds, TOC-1000e S uses a unique structure called Active-Path, which integrates the excimer lamp and the sample flow channel. In a typical ultraviolet irradiation section, an air gap between the lamp and the sample flow channel results in inefficient ultraviolet light transmission and the generation of ozone within the device. However, in Active-Path, a sample flow path within the light-emitting part enables efficient irradiation of the sample with ultraviolet light while preventing ozone generation (Fig. 2).</p><h4><strong>Conclusion&nbsp;</strong></h4><p>TOC-1000e S enables the monitoring of TOC of ultra-pure water used in semiconductor manufacturing. The compact body and user-friendly interface assist usersin their routine operations.</p><h3><strong>4. Thermo Fisher Scientific: Analyzing SiC/Co materials for radar absorption and EMI shielding using ARL X’TRA Companion XRD</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/sicco_materials_an41524_en_8ad5cc0d6f.pdf"><strong>Full PDF for download</strong></a></li></ul><p>SiC–Co composites represent a new class of engineered materials designed to combine dielectric and magnetic loss mechanisms for effective absorption of electromagnetic radiation. By dispersing cobalt or cobalt ferrite phases within a silicon carbide or SiOC matrix, these composites achieve tunable permittivity and permeability, enabling efficient impedance matching across radar and microwave frequencies. For defense and aerospace applications, where low radar cross section and stable electromagnetic shielding are critical, such composites are attractive because they also retain thermal and mechanical stability beyond the capabilities of polymer-based absorbers.&nbsp;</p><p>X-ray diffraction (XRD) plays a central role in the development and quality control of these materials. It allows unambiguous identification of SiC polytypes that influence dielectric behavior, while simultaneously detecting cobalt, cobalt oxide, or ferrite phases that govern magnetic response. XRD quantification provides insight into crystalline-to-amorphous ratios, crystallite size, and micro strain directly linked to electromagnetic performance and high-temperature durability. By correlating phase composition with measured S-parameters, researchers can optimize absorber formulations and processing conditions to achieve reliable, broadband EMI shielding.</p><h4><strong>Instrument &amp; software&nbsp;</strong></h4><p>The <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=3&amp;search=ARL%E2%84%A2+X%E2%80%99TRA+Companion"><strong>Thermo Scientific™ ARL™ X’TRA Companion X-Ray Diffractometer</strong></a> (c.f. Figure 1) is a simple, easy-to-use benchtop instrument for routine phase analysis as well as more advanced applications. The ARL X’TRA Companion XRD uses a θ/θ goniometer (160 mm radius) in Bragg-Brentano geometry coupled with a 600 W X-ray source (Cu or Co). The radial and axial collimation of the beam is controlled by divergence and Soller slits, while air scattering is reduced by a variable beam knife. An integrated water chiller is available as an option. Thanks to the state-of-the art solid state pixel detector (55x55 μm pitch), the ARL X’TRA Companion XRD provides very fast data collection and comes with single-click Rietveld quantification capabilities and automated result transmission to a LIMS (Laboratory Information Management System) seamless integrated into Thermo Scientific™ SolstiX™ Pronto instrument control software.</p><h4><strong>Your benefits&nbsp;</strong></h4><p>The ARL X’TRA Companion XRD system delivers high-quality data in 10 minutes, enabling phase quantification, reliable identification of SiC polytypes, and advanced interpretation of anisotropic micro strain in Co. With the PONKCS method, the amorphous fraction can be quantified accurately. These structural insights directly link to physical properties such as dielectric–magnetic balance, EMI shielding efficiency, and radar absorption performance, providing a basis for fine-tuning materials to application needs.</p>

News from LabRulezICPMS Library - Week 08, 2026

<p><strong>In the week from February 23, the following webinars await you in the field of atomic and molecular spectroscopy and spectrometry</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 500 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. Thermo Fisher Scientific: Lunch and Learn Tips and Tricks Series – Qtegra Part 1</strong></h5><ul><li>Tu, 24.2.2026 13:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5795">Registration</a></li></ul><p>Explore practical Qtegra ISDS workflows to boost trace elemental analysis quality and laboratory productivity, and learn how integrated tools help you get more from your instrumentation.</p><h5><strong>2. LECO: Total Sulfur and Carbon Determination in Cement and Raw Materials</strong></h5><ul><li>Tu, 24.2.2026 16:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5938">Registration</a></li></ul><p>Join Lloyd Allen for a practical webinar on total sulfur and carbon analysis in cement materials using the LECO SC832, including ASTM C150 compliance and furnace configuration insights.</p><h5><strong>3. Technology Networks: Real-Time In-Line Insight for Therapeutic Protein Production</strong></h5><ul><li>Tu, 24.2.2026 16:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5796">Registration</a></li></ul><p>Discover how real-time, in-line Raman monitoring improves control and consistency in therapeutic protein manufacturing by delivering actionable insights across downstream operations.</p><h5><strong>4. SelectScience: Cruise Through Genomics Quantification and QC with Lunatic</strong></h5><ul><li>Tu, 24.2.2026 17:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5837">Registration</a></li></ul><p>Learn how Lunatic enables fast, dye-free DNA and RNA quantification for NGS and biobanking, delivering accurate concentration and purity data from 96 samples in under 10 minutes.</p><h5><strong>5. Bruker: Accelerating Soil Health Assessment – High-Throughput Analysis with IR and EPR Spectroscopy</strong></h5><ul><li>Tu, 24.2.2026 17:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5758">Registration</a></li></ul><p>Discover how IR and EPR spectroscopy enable rapid, high-throughput soil analysis—from carbon, clay, and pH to free radicals and metals—supporting scalable soil health and contamination monitoring.</p><h5><strong>6. Agilent Technologies: Microplastics in Wastewater – A Population Based Approach to Identifying Potential Sources</strong></h5><ul><li>Tu, 24.2.2026 21:30 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/2531">Registration</a></li></ul><p>Using LDIR within a closed wastewater treatment system, this webinar explores quantification of microplastics at different stages to identify potential contamination sources.</p><h5><strong>7. Mettler-Toledo: Dynamic Mechanical Analysis (DMA)</strong></h5><ul><li>Th, 26.2.2026 16:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5734">Registration</a></li></ul><p>Join this webinar to understand DMA principles, viscoelastic behavior, and practical applications for material testing across industries.</p><h5><strong>8. Bruker: Enhanced Data Capture for 3D Optical Profilers</strong></h5><ul><li>Th, 26.2.2026 17:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5911">Registration</a></li></ul><p>Discover Enhanced Data Capture metrology and learn how it delivers richer, more reliable measurements on steep, rough, and complex surfaces, including live demonstrations and real-world applications.</p>

Webinars LabRulezICPMS Week 09/2026

<p><strong>Matrix effects significantly limit accurate nanoparticle sizing in single-particle ICP-MS, often causing signal attenuation and size underestimation. This study systematically evaluates matrix-induced biases and reports up to 10 nm underestimation of Ag nanoparticle sizes due to 30–50% signal loss.</strong></p><p>To overcome these challenges, a novel online internal standard calibration strategy was developed using multielement detection and nonanalyte elements (Pd, Au) as internal standards. Simultaneous measurement of analyte and standards enabled correction of signal response and nebulization efficiency within a single run. The optimized approach provided accurate particle size determination in simulated and real matrices, extending SP-ICP-MS applicability to complex environmental and biological samples.</p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c06975"><strong>A Simple Online Internal Standard Calibration Strategy for Single-Particle Inductively Coupled Plasma Mass Spectrometry Based on Multielement Analysis</strong></a></h4><p>Xiangwei Tian, Ying Wang, Peijie Yang, Dingyi Wang, Yanwei Liu, Yingying Guo, Yuning Hu*, Xiaoyan Zhang*, Ligang Hu, Yongguang Yin*, Yong Cai, and Guibin Jiang</p><p>Anal. Chem. 2025, 97, 51, 28139–28147</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acs.analchem.5c06975">https://doi.org/10.1021/acs.analchem.5c06975</a></p><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6></blockquote><p><strong>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.</strong></p><div><p>Nanoparticles (NPs) are ubiquitous in environmental and biological systems. <a href="javascript:void(0);">(1)</a> In the environment, billions of tons of natural NPs are formed annually through biogeochemical processes. <a href="javascript:void(0);">(1)</a> Engineered NPs are widely utilized in industrial, medical, and consumer products and inevitably released into the environment. <a href="javascript:void(0);">(2)</a> In biological systems, NPs can be endogenously formed <a href="javascript:void(0);">(3)</a> or acquired from environmental exposure. <a href="javascript:void(0);">(4)</a> Functional NPs can also be intentionally delivered into biological systems as probes or drugs. <a href="javascript:void(0);">(5−7)</a> Variations in physicochemical properties of NPs, such as size and elemental composition, can influence their distribution patterns and effects within environmental and biological systems. <a href="javascript:void(0);">(8,9)</a> Therefore, it is of great significance to resolve particle heterogeneity at the single-particle level. Single particle inductively coupled plasma mass spectrometry (SP-ICP-MS), with its high-throughput and sensitive capabilities for elemental and isotopic analysis, plays a key role in single-particle analysis. <a href="javascript:void(0);">(10,11)</a></p><p>Environmental particles always exist in complex or unknown matrices, such as ice cores, <a href="javascript:void(0);">(12)</a> wastewater, <a href="javascript:void(0);">(13)</a> and seawater. <a href="javascript:void(0);">(14)</a> Biological matrices are even more intricate, typically containing high concentrations of inorganic salts and organic matter. Matrix effects pose significant challenges for SP-ICP-MS analysis of environmental and biological samples. <a href="javascript:void(0);">(15)</a> Matrix effects on ICP-MS are generally categorized into spectral and nonspectral interferences. <a href="javascript:void(0);">(15)</a> Spectral interferences arise from isobaric overlaps or polyatomic ions (e.g., ArCl<sup>+</sup> from Cl<sup>–</sup> interfering with <sup>75</sup>As detection), which can often be eliminated using collision/reaction cell technique. <a href="javascript:void(0);">(16)</a> Nonspectral interferences refer to matrix-induced changes in signal intensity. <a href="javascript:void(0);">(17)</a> For instance, NaCl can suppress signal intensity, whereas low concentrations of methanol may lead to signal enhancement. Changes in signal intensity further contribute to errors in mass/size measurement. It was reported that a 4.5 g L<sup>–1</sup> NaCl matrix caused underestimation of As(0) NP and Ag NP sizes by 28% and 41%, respectively, while a 2% methanol matrix resulted in overestimations of approximately 6% and 20%. <a href="javascript:void(0);">(17)</a> Common strategies to address nonspectral interferences include sample dilution and matrix matching. <a href="javascript:void(0);">(15)</a> However, dilution pretreatments would greatly reduce the analytical throughput, and changes in matrix concentration may affect the properties or state of the analyte. In real-world samples, the matrices are always complex, making it difficult to prepare solutions with exactly the same composition for matrix matching. Isotope dilution analysis (IDA), which involves enriched isotopes of the analyte element for signal response correction, is another established approach. <a href="javascript:void(0);">(18−20)</a> Nevertheless, due to strict requirements on matrix types, isotope properties, and analyte concentrations, IDA has limited applicability to real-world sample measurements. Furthermore, among the previously reported methods, the potential influence of the matrix on particle nebulization efficiency has not been fully considered, <a href="javascript:void(0);">(18,21,22)</a> leaving quantitative uncertainties. <a href="javascript:void(0);">(17)</a> The online droplet calibration method based on the microdroplet generator and ICP-time-of-flight (TOF)-MS considers matrix effects on both signal response and nebulization efficiency; <a href="javascript:void(0);">(15,23)</a> however, the technical barriers and high cost largely limit its broader adoption. Till now, due to the lack of practical calibration methods, the characterization of NPs in real matrices typically involves laborious extraction procedures. <a href="javascript:void(0);">(24,25)</a> A need exists to develop a simple and reliable calibration strategy suitable for the measurement in the original matrix.</p><p>In this study, we first systematically investigated the specific matrix effects on SP-ICP-MS and the underlying mechanisms based on the fundamentals of ICP-MS. The influence of time resolution on multielement detection was explored from multiple analytical perspectives. To address limitations of previous methods, we proposed a simple and reliable online internal standard calibration method, which largely eliminates matrix effects on size/mass determination by SP-ICP-MS. By utilizing the multielement detection mode, the signals of the analyte element(s) and internal standard elements can be monitored within the same analytical run, allowing for simultaneous correction of the response factor, nebulization efficiency, and time-dependent signal fluctuations. Notably, the novel calibration strategy involving the use a nonanalyte element as the internal standard for signal response calibration was developed and validated. The proposed method demonstrated high feasibility and reliability when applied to simulated real-world samples. It is also applicable to single-particle analysis using other types of ICP-MS (e.g., ICP-TOF-MS) and shows promise for application in single-cell ICP-MS analysis.</p><h4><strong>Experimental Section</strong></h4><h5><strong>SP-ICP-MS Analysis</strong></h5><p><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=7900+ICP-MS"><strong>Agilent 7900 ICP-MS</strong></a> (Agilent Technologies; Santa Clara, CA, USA) equipped with a quadrupole mass analyzer was used for SP-ICP-MS analysis. Instrument parameters are given in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acs.analchem.5c06975/suppl_file/ac5c06975_si_001.pdf">Table S2</a>. The sample introduction system was composed of syringe pumps (Leifu Fluid; Baoding, China), a Mira Mist nebulizer (Burgener; Mississauga, Ontario, Canada), and a quartz dual-channel spray chamber (Agilent Technologies; Santa Clara, CA, USA) (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c06975#fig1">Figure 1</a>). The total sample flow rates were 300 μL min<sup>–1</sup> for all the experiments. Additionally, a more accessible introduction approach using the instrument’s integrated peristaltic pump was also tested (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acs.analchem.5c06975/suppl_file/ac5c06975_si_001.pdf">Figure S2</a>). Matrix effects on SP-ICP-MS analysis was investigated under the conventional single-element mode. The dwell time was 5 ms, with no stabilization time. The final inlet concentrations of Ag NPs and Au NPs were 50 ng L<sup>–1</sup> (∼4.2 × 10<sup>4</sup> particles mL<sup>–1</sup>) and 25 ng L<sup>–1</sup> (∼4 × 10<sup>4</sup> particles mL<sup>–1</sup>), respectively.</p><h4><strong>Results and Discussion</strong></h4><h5><strong>Matrix Effects on SP-ICP-MS and the Underlying Mechanisms</strong></h5><p>In the UPW matrix, the particle sizes determined by SP-ICP-MS (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c06975#fig2">Figure 2</a>A) were consistent with those measured by TEM (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acs.analchem.5c06975/suppl_file/ac5c06975_si_001.pdf">Figure S1A</a>). The most direct impact of matrix effects was observed as changes in the analyte signal intensity. Both the typical environmental and biological matrices we selected resulted in signal attenuation for the target elements. More pronounced signal attenuation was observed in the salt matrices with increasing concentration. Compared to measurements in UPW, the signal intensity of Ag NPs decreased by approximately 32% and 46% in DSW and PBS, respectively. Correspondingly, without matrix-matching correction, the particle sizes of Ag NPs were underestimated by approximately 12% and 19% in DSW and PBS, respectively (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c06975#fig2">Figure 2</a>A).</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2025_97_51_28139_28147_Figure_2_A_Particle_size_distribution_of_Ag_N_Ps_in_different_matrices_without_matrix_matching_f97e96e68c.jpeg" alt="Anal. Chem. 2025, 97, 51, 28139–28147: Figure 2. (A) Particle size distribution of Ag NPs in different matrices without matrix matching. The gray line and band denote the mean and standard deviation of the particle size determined by TEM. (B) Nebulization efficiency of Au NPs in different matrices. The letters on columns indicate the statistical difference obtained from one-way ANOVA test (p &lt; 0.05). (C) Signal intensity of standard Au NPs and AuCl4– solution in different matrices." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2025_97_51_28139_28147_Figure_2_A_Particle_size_distribution_of_Ag_N_Ps_in_different_matrices_without_matrix_matching_f97e96e68c.jpeg 245w," sizes="100vw" width="2100" height="537"></p><p>Matrix-induced attenuation/enhancement of signal intensity fundamentally arise from changes in the transport efficiency of the analyte. Transport efficiency is defined as a combination of several components (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c06975#fig1">Figure 1</a>): (i) the aerosol introduction efficiency (or nebulization efficiency) from the sample introduction system (typically comprising a nebulizer and spray chamber) to the ICP torch, as calculated using <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c06975#eq1">Equation 1</a>) or <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c06975#eq2">2</a>); (ii) the ionization efficiency of the analyte within the ICP torch; and (iii) the subsequent extraction and transport efficiency of ions from the sampling cone to the detector.</p><h5><strong>Validation of Online Internal Standard Calibration</strong></h5><p><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c06975#fig4">Figure 4</a>A displays the Ag NP size distribution determined when the three inlet streams (Ag NP suspension, Au NP suspension, and Pd solution) were mixed at equal flow rates (3 × 100 μL min<sup>–1</sup>). For all the matrices, the measured particle sizes showed good agreement with the actual sizes determined by TEM. Note that since both the Au NP suspension and Pd solution were prepared using UPW, the matrix containing analyte Ag NPs would be diluted upon online mixing. For real-world samples, excessive dilution could potentially change sample properties and reduce measurement throughput. To prevent excessive dilution, the calibration results were further assessed under conditions of reduced internal standard flow rates (Ag NP flow rate: 260 μL min<sup>–1</sup>; internal standard flow rates: both 20 μL min<sup>–1</sup>) (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c06975#fig4">Figure 4</a>B). Furthermore, an offline spiking approach was also tested by adding both the internal standards directly into the sample suspension (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acs.analchem.5c06975/suppl_file/ac5c06975_si_001.pdf">Figure S7A</a>). The measured sizes also agreed well with the true values. For easier access and use, online mixing using a peristaltic pump was also tested and demonstrated to accurately determine the particle sizes (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acs.analchem.5c06975/suppl_file/ac5c06975_si_001.pdf">Figure S7B</a>). The results demonstrate that neither the introduction approach and the mixing ratio affected the calibration performance, suggesting the high reliability and flexibility of the internal standard calibration method.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2025_97_51_28139_28147_Figure_4_A_B_Particle_size_distribution_of_Ag_N_Ps_in_different_matrices_measured_by_the_internal_standard_calibration_method_4ca8d3833d.jpeg" alt="Anal. Chem. 2025, 97, 51, 28139–28147: Figure 4. (A, B) Particle size distribution of Ag NPs in different matrices measured by the internal standard calibration method. (A) Flow rates of the analyte and internal standards were all 100 μL min–1. (B) Flow rates of the analyte and internal standards were 260 and 20 μL min–1, respectively. (C, D) Particle size distribution of Ag NPs in natural seawater (C) and human urine (D) matrices measured by external standard calibration or online internal standard calibration method. the flow rates of the analyte and internal standards were 260 and 20 μL min–1, respectively. The gray lines and bands denote the mean and standard deviation of the particle size determined by TEM." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2025_97_51_28139_28147_Figure_4_A_B_Particle_size_distribution_of_Ag_N_Ps_in_different_matrices_measured_by_the_internal_standard_calibration_method_4ca8d3833d.jpeg 189w," sizes="100vw" width="1433" height="1184"></p><p>Further, we evaluated the performance of the proposed method in handling real biological (human urine) and environmental (natural seawater) matrices (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c06975#fig4">Figure 4</a>C and D). In addition to high salt concentrations, both matrices contain abundant organic matter, which pose challenges to accurate SP-ICP-MS analysis. Without matrix matching, the sizes of Ag NPs in both matrices were significantly underestimated. Particularly in seawater, the size was underestimated by nearly 20 nm. Using the online internal standard calibration, the median sizes of Ag NPs in diluted seawater and urine matrices were 58.9 and 58.5 nm, respectively, in close agreement with those determined by TEM. Notably, the sizes of Ag NPs in undiluted real matrices can also be accurately determined, facilitating the measurement of environmental particles in the original matrix.</p><h4><strong>Conclusions</strong></h4><p>In this study, we addressed the significant challenge of matrix effects in SP-ICP-MS for accurate mass/size determination in complex environmental and biological samples. We elucidated the specific matrix effects on nebulization efficiency, ionization efficiency, and ion transport. It was demonstrated that Ag NP signal intensity decreased by approximately 32% and 46% in DSW and PBS, respectively, leading to underestimated particle sizes (12% and 19%, respectively). To address these issues, we developed and validated an online internal standard calibration strategy employing multielement detection with nonanalyte elements as internal standards. By simultaneously monitoring analyte (Ag) and internal standard elements (Au for nebulization efficiency, Pd for response factor) within a single analytical run via the peak-hopping mode, we achieved real-time correction for matrix-induced variations. Optimized time-resolution conditions, particularly a 5 ms dwell time, ensured a high probability of complete event acquisition (81.8%) while minimizing particle overlapping. The measured sizes of Ag NPs in simulated (DSW and PBS) and real (natural seawater and human urine) matrices that showed good agreement with true values. The proposed method demonstrated high reliability and flexibility, regardless of the internal standard mixing ratio (e.g., 100:100:100 or 260:20:20 μL min<sup>–1</sup>), introduction approach, and sample dilution levels. In contrast to enriched isotope internal standards, which proved ineffective in anion-rich matrices due to chemical reactions, the presented nonanalyte internal standards offer enhanced adaptability across various matrices.</p><p>This reliable and flexible method significantly extends the applicability of SP-ICP-MS to direct analysis of complex samples without laborious pretreatments. The potential for the measurement in the original matrix is particularly meaningful for single-cell analysis, allowing direct analysis of living cells in biological matrices. Note that the theory and method validated with Ag NPs are also applicable to the quantification of other elements in particles or cells. As a simplified alternative to the established online microdroplet calibration, <a href="javascript:void(0);">(23)</a> the proposed strategy shows great promise in the integration of advanced ICP-TOF-MS platforms for simultaneous calibration of multiple analyte elements.</p></div>

A Simple Online Internal Standard Calibration Strategy for Single-Particle Inductively Coupled Plasma Mass Spectrometry Based on Multielement Analysis

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezICPMS Library in the week of 23rd February 2026? Check out new documents from the field of spectroscopy/spectrometry and related techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT SPECTROSCOPY/SPECTROMETRY RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><strong>LabRulezGCMS</strong></a> libraries.</p></blockquote><p>This week we bring you application notes by <strong>Agilent Technologies</strong>, <strong>Metrohm,</strong> <strong>Shimadzu </strong>and<strong> Thermo Fisher Scientific!</strong></p><h3><strong>1. Agilent Technologies: UV-Vis Spectroscopy for Quality Assessment of Paprika as per ASTA Method 20.1</strong></h3><p><strong>From sample prep to analysis using the </strong><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=Cary+3500"><strong>Agilent Cary 3500 Multicell UV-Vis</strong></a></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_paprika_uv_vis_cary_5994_8612en_agilent_d903914b39.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Paprika is a widely used spice valued for its deep red color and characteristic flavor, contributing to its prominence in both culinary and commercial applications. As a high‑demand commodity produced from dried capsicum pods, paprika is subject to quality variation and adulteration, which can compromise product authenticity, consumer trust, and regulatory compliance. UV-Visible (UV-Vis) spectroscopy is a rapid, reproducible analytical technique for evaluating paprika quality by quantifying pigment concentration. In paprika, color intensity primarily arises from carotenoid compounds, and is commonly assessed using the ASTA Method 20.11 – a well-established industry standard that commercially grades paprika samples as a numerical ASTA color value.</p><p>In this application note, we used an <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=Cary+3500"><strong>Agilent Cary 3500 Multicell UV-Vis spectrophotometer</strong></a> and <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=UV+Workstation+software"><strong>Agilent Cary UV Workstation software</strong></a> to determine the ASTA color value of two commercial paprika samples. The measurements were performed in accordance with ASTA Method 20.1 for the determination of extractable color in capsicums and their&nbsp;oleoresins.</p><h4><strong>Results and discussion</strong></h4><h5><strong>Paprika samples' analysis&nbsp;</strong></h5><p>ASTA Method 20.1 measures the color intensity of paprika by extracting pigments with acetone and recording absorbance at 460 nm. The absorbance reading, along with sample weight is then used to calculate the ASTA color value. The ASTA color value is a crucial quality parameter for paprika and other spices, as it indicates the intensity and vibrancy of the red color, which is a key characteristic for consumers and food manufacturers. In this study, the two extracted paprika samples were each measured three times to produce triplicate results (Table 4). Sample 1 had a corrected ASTA color value of approximately 103, and sample 2 had a corrected ASTA color value of approximately 61, indicating a lower color intensity. The corrected ASTA color value was automatically generated in an easy-to-read table of values, and a scan report was automatically exported into a user-defined location.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>The Agilent Cary 3500 Multicell UV-Vis spectrophotometer with Agilent Cary UV Workstation software enabled fast, reliable, and standardized quality assessment of paprika samples. Using the well-established industry method, ASTA 20.1, the Cary 3500 system provided precise quantification of carotenoid pigments, supporting grading categorization. The high-throughput multicell design of the Cary 3500 Multicell UV-Vis spectrophotometer allows simultaneous measurement of up to seven samples and a reference, improving efficiency and minimizing variability. The Cary UV Workstation software simplifies data acquisition and analysis with intuitive spectral features such as the End of sequence analysis tool, which can be applied automatically to any scan method, and spectra comparisons through the Load spectrum tool. From sample absorbance measurement to final reporting, the Cary 3500 system eliminated the need for manual data processing or external tools, minimizing complexity and facilitating confidence.</p><h3><strong>2. Metrohm: NIRS analysis of forages</strong></h3><p><strong>Multiparameter determination in a few seconds</strong></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_nir_131_download_2f897ff7f5.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Forages are plants or parts of plants eaten by both livestock and wildlife. Forages provide bulk, help with weight maintenance, and combat several issues [1]. Alfalfa forage is high in protein—well-suited to promote muscle mass in beef cattle or to increase the production of dairy cows [2]. Alfalfa is also commonly used for horse feed. These animals require forages with good palatability along with high digestibility, intake potential, and protein levels, thus increasing the demand for alfalfa and other high-quality feeds. Farmers have responded by producing even higherquality alfalfa in recent years. Since forage quality depends on chemical, biological, and dynamic properties, both measured and calculated methods must be used. Standard alfalfa assays measure neutral detergent fiber (NDF), acid detergent fiber (ADF), crude protein (CP), ash, moisture, and protein. For alfalfa pellets, the mean particle size is also important. Near-infrared spectroscopy (NIRS) offers rapid and reliable prediction of fat, moisture, crude protein, fiber, ash and starch in a few seconds and without sample preparation.</p><h4><strong>EXPERIMENTAL EQUIPMENT</strong></h4><p>Samples of alfalfa (including fresh alfalfa, alfalfa pellets, and alfalfa cubes) were analyzed on a <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=220&amp;search=NIR+Analyzer"><strong>Metrohm NIR Analyzer</strong></a>. All measurements were performed in reflection mode using the large cup. The samples were measured in rotation to collect spectral data from several areas. Spectral averaging of signals from several spots helped to reduce sample inhomogeneity. The reference values were measured according to ISO norms described at the end of this Application Note. Metrohm software was used for all data acquisition and prediction model development.</p><h4><strong>CONCLUSION&nbsp;</strong></h4><p>This Application Note demonstrates the feasibility to determine multiple key parameters of alfalfa forage with NIR spectroscopy. Several analytical methods are usually required to measure key quality parameters for forage (Table 4). NIRS forage analysis enables a highly accurate, cost-effective, and fast alternative.</p><h3><strong>3. Shimadzu: Analysis of Heavy Metals in Baby Food Using ICP-MS</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_01_01039_en_c563bb1b82.pdf"><strong>Full PDF for download</strong></a></li></ul><h4><strong>User Benefits</strong></h4><ul><li>Heavy metals in various baby foods can be analyzed simultaneously with sufficient sensitivity.</li><li>Stable analysis can be performed even for baby foods with high matrix content.</li><li>Using the standard LabSolutions ICPMS rinse function, the time to clean the sample introduction system is minimized, which prevents carryover.</li></ul><p>Infants’ metabolic pathways are still developing, and because of their lower body weight, they are known to be more susceptible to the effects of harmful substances. In the United States, the Baby Food Safety Act 2021<sup>1)</sup>, and in the EU, Commission Regulation (EU) 2023/915<sup>2)</sup> and Commission Regulation (EU) 2024/1987<sup>3)</sup> require the control of toxic metals contained in baby foods. ICP-MS is suitable for the analysis of trace amounts of toxic metal elements because it can perform multi-element simultaneous analysis with high sensitivity.</p><p>However, baby foods vary in matrix composition, which raises concerns about non-spectral interferences and long-term stability during ICP-MS analysis. This Application News describes the analysis of five baby foods with different matrices using the <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=1&amp;search=ICPMS-2040%2F2050"><strong>ICPMS-2040/2050</strong></a> (Fig. 1). Additionally, spike recovery tests and long-term stability were assessed based on the Food and Drug Administration (FDA) Elemental Analysis Manual (EAM) Section 4.7<sup>4)</sup>.</p><h4><strong>Equipment Configuration and Analysis Conditions&nbsp;</strong></h4><p>The equipment configuration is shown in Table 2. To reduce running costs, a mini-torch with lower argon gas consumption compared to conventional torches was used for analysis. Additionally, to streamline sample preparation, an Online Internal Standard Kit was utilized for online addition.&nbsp;</p><p>The analysis conditions are detailed in Table 3. After analyzing high-concentration samples, the sample introduction system can influence the analysis values of subsequent samples (carryover). If carryover occurs, re-measurement is necessary, which consumes additional time and samples. With LabSolutions ICPMS, rinse solutions can be set for each sample, enabling effective cleaning in minimal time. Normal cleaning was performed using pure water (Rinse solution 1), and an additional acid rinse solution (Rinse solution 2) was introduced only after high-concentration samples.</p><p>For example, Table 4 shows the difference in carryover concentration when measuring a blank sample after introducing a sample with a CCV concentration, comparing the case where rinse solution 2 is added for an additional 240 seconds to the case where it is not. Among the elements measured this time, Se and Hg tend to have a higher risk of carryover, but by introducing rinse solution 2, carryover was reduced to below the detection limit. Moreover, even if unexpectedly high-concentration samples are introduced, the Extended Rinsing function allows for automatic additional rinsing (Fig. 3). This eliminates the need to repeatedly check analysis values or to set a uniform cleaning time uniformly, thus reducing the verification effort, the amount of rinse solution required, and the analysis time while preventing carryover.&nbsp;</p><p>Furthermore, to minimize time spent cleaning the sample introduction system, ProActive Rinsing was used (Fig. 4). When measuring multiple samples, starting the rinse in advance during measurement reduces the measurement time for subsequentsamples.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>In this Application News, elemental analysis of baby food was conducted using the ICPMS-2040/2050. We achieved detection limits that met stringent standards. The spike recovery tests yielded good results for all samples with different matrices, confirming the validity of the analysis. Additionally, we analyzed 50 samples of infant formula with a high matrix over approximately six hours and confirmed good stability. The ICPMS-2040/2050 offers high sensitivity, accurate analysis, and good stability. Its Extended Rinsing and ProActive Rinsing functions effectively clean the sample introduction system, preventing carryover. Therefore, the ICPMS-2040/2050 is a suitable instrument for elemental analysis in baby food.</p><h3><strong>4. Thermo Fisher Scientific: Food protection methods assessed by Surface Enhanced Raman Spectroscopy</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/food_protection_methods_surface_enhanced_raman_spectroscopy_an54670_en_5c5e701389.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Lipid oxidation is a major issue for the meat industry as it can not only affect&nbsp;sensory quality in terms of flavor and odor but can also lead to the formation of toxic compounds such as malondialdehyde (MDA) and cholesterol oxidation products, as well as the accumulation of carbonyls, alcohols and volatile acids. The degree of oxidation depends on various factors such as the type of meat, the fat content, the storage temperature, the availability of oxygen and the type of packaging<sup>1, 2</sup>. To prevent oxidation, synthetic antioxidants are commonly added to meat products, but consumers are now demanding more natural products<sup>3</sup>. Several studies have been carried out to evaluate the antioxidant activity of many essential oils or extracts from plants or spices such as rosemary, cinnamon or oregano, and the new trend is to develop innovative packaging by adding these natural antioxidants directly to the packaging materials<sup>4–6</sup>. These materials, often films, are known as “active packaging” because they enable the controlled release of active agents either on the surface or in the internal atmosphere of the product, or by trapping the radicals responsible for harmful effects on food quality. However, the antioxidant performance of these films must be accurately determined to enable the selection of the right packaging for each foodstuff.&nbsp;</p><p>Among all the techniques available, Raman spectroscopy is a promising candidate for detecting most molecular species with high specificity and sensitivity, particularly in the presence of Surface-Enhanced Raman Scattering (SERS). Indeed, SERS is a physical phenomenon that occurs in the presence of a rough nano-structured metallic surface that causes the intensification of Raman signals from molecules adsorbed to the surface thanks to the combination of a chemical effect and an electromagnetic effect<sup>7</sup> . The metals used are generally gold or silver, which can be prepared by electrochemical roughening, metallic coating, or deposition of nanoparticles (often in a colloidal form). Commercial solutions are available, but many researchers prefer to create their own SERS substrates. The scope of this work is to investigate the potential of a home-made SERS substrate to compare the lipid oxidation over time in ground pork preserved either in a low-density polyethylene (LDPE) conventional packaging or in an active packaging containing oregano extract.</p><h4><strong>Material and method&nbsp;</strong></h4><p>Fresh ground pork meat was purchased in bulk from a local supermarket and 22 g samples of meat were placed in 5-cm diameter polystyrene Petri dishes. Each sample was covered with an active film and packed in an LDPE bag under a normal atmosphere. Reference samples were also prepared using conventional LDPE films. All samples were stored in a refrigerator at 5 °C and their lipid extracts were analyzed after 0, 7, 9, 11, 14 and 16 days using a home-made SERS substrate based on silver nanoparticles deposited on a glass Petri dish. A special home-made cooling system was used to perform the analyses at low temperature and SERS spectra were measured at -2 °C on a <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/products/2239"><strong>Thermo Scientific™ DXR3 Raman Microscope</strong></a> (Waltham, MA, USA) with a 532 nm laser source, a 900 lines/mm grating covering the 50-3500 cm-1 spectral range and an x10 objective (NA 0.40). The laser power was set at 5&nbsp;mW, and 20 exposures of 30 s each were selected to acquire all data. Thermo Scientific™ OMNIC™ v. 9.2 software was used for data collection and analysis. All the measurements were performed in triplicate. As the decrease in the peak at 1655&nbsp;cm-1 (stretching of C=C bonds from unsaturation) can be attributed to lipid peroxidation, and the 1439 cm-1 (scissoring deformation of CH<sub>2</sub>) is not affected by it, the area ratio between 1655 cm-1 and 1439 cm-1 bands was calculated to follow the lipid oxidation.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>The effectiveness of a home-made SERS substrate coupled with a home-made cooling system was demonstrated for monitoring lipid oxidation in packaged ground pork meat over time. The advantages of this technique are its speed and the minimal sample handling requirements. An improvement factor of the order of 107 over conventional Raman was observed. This study also confirmed the greater efficacy of active packaging containing oregano extracts against lipid oxidation in ground pork, compared to conventional LDPE packaging.</p>

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