This study systematically compares four widely used lysosome enrichment strategies, including density gradient separation, magnetic bead isolation, filter-based enrichment, and subcellular fractionation. Using the THP-1 monocytic cell line, the methods were evaluated for lysosome yield, purity, membrane integrity, reproducibility, scalability, and contamination through complementary analytical techniques and proteomics.The results showed that gradient- and bead-based methods achieved the highest lysosomal purity, while subcellular fractionation yielded larger numbers of lysosomes but with greater contamination and variability. Filter-based enrichment enabled rapid processing but recovered mainly nonintact lysosomes. The findings provide practical guidance for selecting lysosome isolation methods in both research and clinical applications.<blockquote><h4>The original article</h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05792">Benchmarking Lysosome Enrichment Methods: A Guide for Research and Clinical Translation</a></h4>Anniek L. de Jager, Sara Kassem, Louis Alesha, Brigitta A.E. Naber, Inge F. de Laat, Bas de Mooij, Kyra van der Pan, Erik Bos, Roman I. Koning, Jacques J.M. van Dongen*, Cristina Teodosio*, and Paula Díez*Anal. Chem. 2026, 98, 6, 4585–4600<a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acs.analchem.5c05792">https://doi.org/10.1021/acs.analchem.5c05792</a><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a></h6></blockquote>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.<div>Since their discovery by De Duve et al. <a href="javascript:void(0);">(1)</a> in 1955, lysosomes have emerged as dynamic organelles critical to cellular homeostasis, regulating processes from nutrient sensing to plasma membrane repair. <a href="javascript:void(0);">(2−5)</a> These acidic, enzyme-packed vesicles <a href="javascript:void(0);">(6,7)</a> are now acknowledged as central players in pathologies far beyond their classical association with lysosomal storage disorders (LSDs). Dysfunctional lysosomes are involved in neurodegenerative diseases (e.g., Alzheimer’s, Parkinson’s), <a href="javascript:void(0);">(8−10)</a> cancer metastasis, <a href="javascript:void(0);">(11−13)</a> and cardiovascular disorders. <a href="javascript:void(0);">(14,15)</a> At the same time, lysosomal proteins like GBA1 and LAMP2 serve as biomarkers and therapeutic targets. <a href="javascript:void(0);">(16−19)</a> Despite their clinical significance, a major challenge in lysosomal research persists since lysosomes constitute less than 5% of cellular volume, <a href="javascript:void(0);">(20,21)</a> requiring precise enrichment for accurate analysis in diagnostic and therapeutic development. <a href="javascript:void(0);">(22,23)</a>Current lysosome isolation methods, including density gradient-based separation, <a href="javascript:void(0);">(24−28)</a> filter-based size exclusion approaches, <a href="javascript:void(0);">(29)</a> magnetic particle phagocytosis, <a href="javascript:void(0);">(30−33)</a> subcellular fractionation (SCF), <a href="javascript:void(0);">(34)</a> and immunoprecipitation strategies, <a href="javascript:void(0);">(35,36)</a> vary widely in yield, purity, structural integrity, and practicality. For instance, density gradient-based methods, which often use Percoll <a href="javascript:void(0);">(37)</a> or sucrose, <a href="javascript:void(0);">(38)</a> while well-established, user-friendly, and cost-effective, coisolate organelles with similar densities, such as endosomes, peroxisomes, and mitochondria, <a href="javascript:void(0);">(39,40)</a> and can be time-consuming, potentially affecting lysosomal protein integrity. Conversely, filter-based size exclusion methods isolate lysosomes based on their size, <a href="javascript:void(0);">(29)</a> offering shorter processing times and straightforward protocols. Nevertheless, these approaches may result in cross-contamination, as various cellular vesicles share similar sizes. <a href="javascript:void(0);">(20,21)</a> Magnetic bead-based methods (e.g., superparamagnetic iron oxide nanoparticles, SPION) involve the endocytic uptake of magnetic beads, <a href="javascript:void(0);">(35,41)</a> offering specificity but altering lysosomal physiology through forced phagocytosis, which hampers functional assays, such as in cancer drug screening. <a href="javascript:void(0);">(42,43)</a> Finally, SCF, which employs sequential lysis steps to enrich specific organelles, including lysosomes, <a href="javascript:void(0);">(34,44)</a> is a rapid, easy-to-use, and cost-effective method; however, significant cross-contamination is linked to this method. <a href="javascript:void(0);">(34,44)</a> Such trade-offs are rarely addressed in single-modality studies, leaving clinicians and researchers without clear guidance for protocol selection. This gap is particularly critical in translational contexts, where diagnostic laboratories that prioritize high-purity lysosomes for biomarker discovery require protocols different from those of therapeutic teams that need lysosomes for drug efficacy testing.Previous comparative studies, such as the proteomic analysis by Singh et al., <a href="javascript:void(0);">(35)</a> have provided valuable insights but primarily focused on yield and purity assessments via proteomic markers, overlooking several key parameters with potentially relevant impacts in translational and clinical applications. Critically, these studies often omit functional and practical metrics: for instance, they typically do not evaluate lysosomal membrane integrity, which is vital for enzyme activity and therapeutic testing, nor do they consider the scalability and feasibility of protocols for contexts where only limited patient samples are available or the potential presence of isolation artifacts. This omission of practical, multimodal assessment represents a critical gap that prevents researchers from selecting a protocol optimized for specific clinical goals.Our study seeks to address these limitations by employing a multimodal framework that evaluates four widely used lysosome isolation methods across several metrics that are critical for clinical applications. We systematically assessed the yield and reproducibility of each method, factors that are essential for biobanking and high-throughput diagnostic workflows. We also examined organelle purity, crucial for avoiding false positives in proteomic biomarker screenings, together with lysosomal membrane integrity, an important consideration for functional studies and drug testing. Finally, we considered the scalability of each method, ensuring that our findings are relevant for studies involving rare or precious patient-derived cells together with the cost and processing time of each technique. Thus, by integrating nanoparticle tracking analysis (NTA), spectral flow cytometry, transmission electron microscopy (TEM), and mass spectrometry (MS)-based proteomics, our study revealed distinct advantages for each method depending on the intended application. With this comprehensive benchmark, we bridged a critical gap between fundamental lysosome biology and clinical implementation, guiding researchers and clinicians in the selection of the most appropriate isolation strategies tailored to their diagnostic or therapeutic goals.<h3>Experimental Section</h3><h4>Liquid Chromatography–Tandem Mass Spectrometry Analysis (LC–MS/MS)</h4>For liquid chromatography–tandem mass spectrometry (LC–MS/MS) studies, a total of 15 μg of proteins were reduced with 10 mM DTT at 45 °C for 30 min, followed by alkylation with 40 mM 2-iodoacetamide (IAA, Sigma-Aldrich) at RT for 30 min. This last reaction was quenched with 20 mM DTT, and protein digestion and peptide recovery were performed using hydrophilic and hydrophobic beads (Sera-Mag Carboxylate-Modified Magnetic Particles, Cytiva, Marlborough, MA/USA) according to the Single-Pot Solid-Phase-enhanced Sample Preparation (SP3) method. <a href="javascript:void(0);">(46,47)</a> In short, samples were incubated twice with beads (1:10 (w/w) protein:bead ratio) in 70% acetonitrile (ACN) for 18 min at RT. After incubation, bead-bound proteins were retained by using a DynaMag-PCR Magnet (Thermo Fisher), and contaminants were washed away three times with 80% ethanol (Sigma-Aldrich). Proteins were digested using a Trypsin/LysC mix (1:25 (w/w) enzyme:protein ratio, Promega, Madison, WI/USA) in 50 mM ammonium bicarbonate at RT overnight. Beads were then washed twice with ACN, after which peptides were eluted in 2% (v/v) dimethyl sulfoxide (DMSO, Thermo Fisher), lyophilized in a freeze-dryer, and stored at −20 °C. Samples were then tagged using the tandem mass tag (TMT) labeling kit (TMTpro 16plex tags, Thermo Fisher) by resuspending the lyophilized peptides in 40 mM HEPES pH 8.4 and labeling with the TMT tags at a 1:5 (w/w) sample:tag ratio for 1 h at RT. The labeling reaction was quenched with 5% hydroxylamine. TMT-labeled lysosome samples were pooled, lyophilized in a freeze-dryer, and stored at −20 °C until LC–MS/MS analysis.<h4>Mass Spectrometry Data Acquisition and Analysis</h4>MT-labeled peptides were dissolved in solvent A (water/formic acid (FA), 100/0.1 (v/v)) and analyzed by online C18 nano-HPLC MS/MS, coupling an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=3&amp;search=UltiMate+3000">UltiMate 3000 gradient HPLC system</a> (Thermo Fisher) and an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/401">Orbitrap Exploris 480 mass spectrometer</a> (Thermo Fisher). A total of 12 fractions were injected onto a precolumn (300 μm × 5 mm; PepMap100 C18 5 μm, Thermo Fisher) equilibrated with solvent A and eluted via a homemade analytical nano-HPLC column (50 cm × 75 μm; ReproSil-Pur C18-AQ 1.9 μm) using solvent B (80/20/0.1 (v/v/v) ACN/water/FA) in a gradient from 5 to 30% in 160 min. The nano-HPLC column was drawn to a tip of ∼5 μm and functioned as an electrospray needle. A Sonation PRSO-V2 column oven was used to maintain the analytical column temperature at 50 °C. The MS1 spectra were recorded in the Orbitrap at a mass-to-charge ratio (m/z) range of 350–1,600, a resolution of 120,000, a maximum injection time of 50 ms, and automatic gain control (AGC) at standard. Dynamic exclusion was applied after n = 1 with an exclusion duration of 45 s and a mass tolerance of 10 ppm. Charge states 2–5 were included. Precursors for MS2 were selected using a TopSpeed method of 3 s at a resolution of 45,000 and fragmented by high-energy collision-induced dissociation (HCD) at a normalized collision energy (NCE) of 36%, with an AGC at 200 and the maximum injection time set to auto. The isolation window for MS/MS was 1.2 Da.Raw data files were converted to the peak list by using <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1782">Proteome Discoverer v2.4</a> (Thermo Fisher), followed by protein identification employing the UniProtKB database (Homo sapiens, 20,596 entries) using Mascot v2.2.07 (Matrix Science Inc., Boston, MA/USA) with the following parameters: precursor and fragment mass tolerances of 10 ppm and 0.02 Da, respectively; TMT16plex on N-term and Lys as fixed modifications; oxidation on Met and acetylation of N-term as variable modifications; and full tryptic digestion (no P rule) with up to 2 missed cleavages. A false discovery rate (FDR) of 1% was set for peptide spectrum matches (PSMs), peptides, and proteins.The MS data have been deposited via the PRIDE partner repository to the ProteomeXchange Consortium with the identifier PXD040003.<h3>Results</h3><h4>Quantification and Size Distribution of Isolated Vesicle Fractions</h4>To assess the yield and size distribution of vesicles isolated by different methods, nanoparticle tracking analysis (NTA) was employed. The SCF procedure yielded the highest median number of vesicles per cell (2,356.3 ± 7,461.7; median ± range), followed by gradient-based (1,630.2 ± 1632.3), filter-based (228.2 ± 265.6), and bead-based isolation (27.8 ± 35.2). Both filter- and bead-based approaches resulted in significantly lower yields compared to SCF (p-value = 0.002 and p-value &lt;0.0001, respectively), and the gradient-based method yielded significantly more vesicles than the bead-based approach (p-value = 0.002; <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05792#fig1">Figure 1</a>A).<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2026_98_6_4585_4600_Figure_1_Quantification_and_size_analyses_of_isolated_vesicles_2d5c120f05.jpeg" alt="Anal. Chem. 2026, 98, 6, 4585–4600: Figure 1. Quantification and size analyses of isolated vesicles. A) Quantification of isolated vesicles per cell, shown as median with range. Circles represent technical replicates. B) Size distribution of isolated vesicles (in nm), displaying average D10 (red), D50 (blue), and D90 (gray), depicted as median with range. Circles represent technical replicates. C–F) Particle distribution plots showing mean concentration at specific sizes; each line represents a technical replicate. For each method, six technical replicates are shown, except for SCF, which includes 12 replicates. SCF, subcellular fractionation. Statistical significance: p &lt; 0.05 and FDR 5%. For statistical analysis, the nonparametric Kruskal–Wallis test was used and corrected for multiple comparisons using the method of Benjamini and Hochberg." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2026_98_6_4585_4600_Figure_1_Quantification_and_size_analyses_of_isolated_vesicles_2d5c120f05.jpeg 126w," sizes="100vw" width="1383" height="1708">Median vesicle size (D50) was comparable across all methods: 159.5 ± 17.2 nm (gradient-based), 169.9 ± 82.7 nm (filter-based), 168.9 ± 42.4 nm (bead-based), and 150.0 ± 55.6 nm (SCF). Similarly, decile 10 (D10) values were consistent, ranging from 87.1 ± 87.3 nm (SCF) to 108.2 ± 3.1 nm (gradient-based). However, filter-based isolation led to higher size heterogeneity of the isolated particles, capturing significantly larger vesicles at the upper end (D90:308.5 ± 110.7 nm) compared to SCF (244.9 ± 112.6 nm, p-value = 0.005), while gradient- and bead-based methods showed intermediate D90 values (250.8 ± 31.7 nm and 273.0 ± 45.9 nm, respectively; <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05792#fig1">Figure 1</a>B). Notably, greater intra-assay variation in concentration and size distribution was observed with filter-based and SCF methods compared to the other approaches (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05792#fig1">Figure 1</a>C–F).<h4>Morphology of the Isolated Fractions</h4>Transmission electron microscopy (TEM) of the isolated fractions confirmed the presence of heterogeneously sized vesicles, in line with the size distributions obtained by NTA. Notably, only the gradient-based method yielded relatively pure vesicle preparations. In contrast, filter-based and SCF methods displayed contamination with cellular debris or protein aggregates, while the bead-based approach was associated with the presence of lipid structures (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.analchem.5c05792#fig2">Figure 2</a>).<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2026_98_6_4585_4600_Figure_2_Transmission_electron_microscopy_TEM_of_isolated_fractions_f14ddbe180.jpeg" alt="Anal. Chem. 2026, 98, 6, 4585–4600: Figure 2. Transmission electron microscopy (TEM) of isolated fractions. Panels A–D show TEM images of the four isolated fractions. Insets display magnified views of the regions outlined in black squares. Black arrows indicate identified representative isolated vesicles, and white arrows denote areas of contamination." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2026_98_6_4585_4600_Figure_2_Transmission_electron_microscopy_TEM_of_isolated_fractions_f14ddbe180.jpeg 145w," sizes="100vw" width="1263" height="1361"><h3>Conclusion</h3>This study provides a systematic benchmarking of four lysosome isolation strategies, revealing inherent trade-offs among yield, integrity, purity, and reproducibility driven by their underlying separation principles. No single method is universally optimal; instead, the method selection must be guided by the intended downstream application. By integrating complementary analytical approaches in a clinically relevant and challenging monocytic model, our work offers a practical framework to support the informed selection of lysosome enrichment strategies, facilitating reliable lysosomal analyses in both research and translational settings.</div>

Benchmarking Lysosome Enrichment Methods: A Guide for Research and Clinical Translation

A Method for the Detection of Tire Wear Microplastics in Zebrafish Guts by Laterally Resolved LA-ICP-MS-Based Elemental Fingerprinting and Chemometrics

This leaflet is intended to help participants in quantitative proficiency testing (PT) schemes to better understand the performance assessment made by the PT provider [1-4].<h3>Performance assessment parameters&nbsp;</h3><h4>Assigned value&nbsp;</h4>In order to assess individual performances, the results reported by participants are compared to the value assigned by the PT provider (xpt). ISO 13528 [1] suggests five different ways to obtain xpt (Figure 1). In this context, the design of the PT scheme must reflect the objectives of the scheme, comparing results either to a predetermined xpt (independent from the participant results), or to a value derived from the reported results. The PT provider is responsible for defining xpt , taking into account the advantages and disadvantages of the various possibilities when establishing metrological traceability or estimating the uncertainty of the assigned value, u(xpt).<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Figure_1_e5ef5d1f9c.jpg" alt="Eurachem - Figure 1 Options for obtaining the assigned value, Xpt" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Figure_1_e5ef5d1f9c.jpg 245w," sizes="100vw" width="640" height="382"><h4>Uncertainty of the assigned value&nbsp;</h4>The uncertainty of the assigned value u(xpt) can be estimated in at least five different ways [1], each corresponding to the value assignment strategy illustrated in Figure 1. The different uncertainty evaluation methods are listed in Figure 2. This uncertainty can be reported as a standard uncertainty (u (xpt)), or as an expanded uncertainty U (xpt) with a coverage factor k, where U (xpt) = k . u (xpt). The choice of k will impact the level of confidence (e.g. approximately 95 % for k = 2).<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Figure_2_f41ebc0c61.jpg" alt="Eurachem: Figure 2 Options for obtaining the uncertainity of the assigned value, u(Xpt)" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Figure_2_f41ebc0c61.jpg 245w," sizes="100vw" width="727" height="378"><h4>Standard deviation for proficiency assessment&nbsp;</h4>Five possibilities are suggested by ISO 13528 to set the standard deviation for proficiency assessment spt (Figure 3). The chosen approach must comply with the objectives of the PT scheme.&nbsp;<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Figure_3_f09cb3969e.jpg" alt="Eurachem: Figure 3 Options for obtaining the standard deviation for proficiency assesment" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Figure_3_f09cb3969e.jpg 245w," sizes="100vw" width="638" height="355">Two approaches for performance assessments use spt as shown in Table 1.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Table_1_Scoring_for_performance_assessment_3dd03aa3fb.jpg" alt="Eurachem: Table 1 - Scoring for performance assessment." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Table_1_Scoring_for_performance_assessment_3dd03aa3fb.jpg 245w," sizes="100vw" width="1390" height="571"><h3>Performance assessment&nbsp;</h3>All performance assessments are based on the difference between the participant’s results (xi) and the assigned value (xpt) divided by a normalisation factor (Table 1).&nbsp;<ul><li>The percent difference D% is the normalised difference expressed as a percentage of xpt , for which a prescribed maximum relative permissible error (dE% = dE / xpt) is defined by the PT provider.&nbsp;</li><li>The z score (unitless) compares the participant’s deviation from the assigned value with the standard deviation for proficiency assessment (spt). When the uncertainty of the assigned value is significant (u(xpt) &gt; 0.3 spt), the z’ score should be used instead, to include the contribution of u(xpt) in the denominator.&nbsp;</li><li>The zeta (ζ) score (unitless) states whether the laboratory’s result agrees with the assigned value within the respective uncertainty. The denominator is the combined (standard) uncertainty of the assigned value u(xpt) and the (standard) measurement uncertainty reported by the laboratory u(xi). An unsatisfactory zeta score can either be caused by an inappropriate estimation of the measured quantity value (e.g. concentration, content), or of its measurement uncertainty, or both.&nbsp;</li><li>The En score (unitless), unlike the zeta score, uses a combination of expanded uncertainties as the normalisation factor. This combination corresponds to a confidence interval of approximately 95 %. En scores are often used in metrology comparisons among calibration laboratories.</li></ul><h3>Interpretation of performance scores&nbsp;</h3>According to ISO 13528:2022 clause 9.4.2, the conventional interpretation of the z, z’ and ζ scores is as follows:&nbsp;<ul><li>A result that gives |score| ≤ 2.0 is considered to be acceptable, indicating satisfactory performance.&nbsp;</li><li>A result that gives 2.0 &lt; |score| &lt; 3.0 is considered to give a warning signal, indicating questionable performance.&nbsp;</li><li>A result that gives |score| ≥ 3.0 is considered to be unacceptable (or action signal), indicating unsatisfactory performance.&nbsp;</li></ul>Similarly, |En| &lt; 1 and |D%| &lt; dE% indicate successful (acceptable) performance.

Understanding PT performance assessment

Article

Academy

Scientific article

Science and research

Eurachem is a European network promoting international traceability of chemical measurements and good analytical practice. It provides expert guidance, supports method validation, uncertainty evaluation, proficiency testing, and facilitates discussion on technical and policy issues in analytical quality.

Eurachem

Everything from the world of analytical chemistry in one place. We connect people in solving their problems. At Labrulez you will find all the necessary information easily, quickly and clearly. Stop searching and start finding.

LabRulez

New Food magazine

Separation Science

Milestone

Have you fully exploited the potential of your analytical techniques in edible oil analysis? Our experts will reveal what you can achieve with CNSX-analysis, ICP-OES, AAS and UV/Vis in regulated standard analysis and beyond.
Price fluctuations, supply bottlenecks and export stops have highlighted in recent years how volatile and complex the supply chains of edible oils are. Exporters, importers and processors of edible oils face the challenges of rapid supplier qualification while achieving regulatory compliant, seamless, and efficient quality monitoring of their crude oil, intermediates and final products.
As agricultural products, edible oils are subject to natural quality fluctuations, while cultivation methods and long transport routes pose risks of contamination and oxidation. In addition, they go through a temperature- and additive-intensive process with the refinery, during which undesirable by-products can arise under certain circumstances.
Our webinar is aimed at industry, regulatory and contract laboratories involved in the analysis of edible oils. With combustion elemental analysis, ICP-OES, AAS and UV/Vis molecular spectroscopy, our experts will introduce four techniques which enable precise, efficient, and standard-compliant quality and process analysis of edible oils. They will also show you tips and tricks on how to exploit the additional potential for optimising your analytical workflows regarding the targeted and economic use of elaborate specific techniques.
Learn how to use these techniques for a variety of oils at different steps in the value and processing chain, and how to achieve optimal results and increase sample throughput.
Key learning points:
<ul>
<li>Explore how to carry out the comprehensive analysis of toxic elements, process inhibitors, catalyst poisons as well as the macro-mineral content with ICP-OES.
</li>
<li>Learn what combustion analysis can achieve in quality control and process monitoring, especially regarding the formation of unwanted compounds during refining.
</li>
<li>Discover how to streamline analytical workflows with quick screens for organic and inorganic Sulfur and Nitrogen as sum parameters with combustion analysis.
</li>
<li>Find out how to assess oxidation in oils via DOBI index, and how to monitor the efficiency of bleaching in refinery using UV/Vis spectrometry.
</li>
<li>Discover what AAS can do as an alternative spectrometric element technique in the analysis of edible oils.
</li>
<li>Meet our experts and discuss with us in the Q&amp;A.
</li>
</ul>
<blockquote>
Presenter: Dr. Angela Gröbel (Senior Product Manager / Expert Supervisor Chemical Analysis)
</blockquote>
<blockquote>
Angela is a Senior Product Manager and Expert Supervisor for the combustion elemental analysis and related sample preparation portfolio. She holds a PhD in analytical chemistry. Angela developed Analytik Jena’s first trace elemental analysis product line for organic matter, later she became an expert in determination of Sulfur, Nitrogen, and Chlorine across a broad range of industry segments, including oil and gas, food and agriculture and environmental protection. Since 2013 Angela has been Product Manager, responsible for the entire combustion elemental analysis and related sample preparation portfolio.
</blockquote>
<blockquote>
Presenter: Dr. Holger Sievers (Application Specialist Chemical Analysis)
</blockquote>
<blockquote>
Holger Sievers is an Application Specialist at Analytik Jena. He holds a PhD from the Technical University of Munich in the field of ultra-trace analysis of noble metals which he obtained after his Master’s focusing on inorganic and analytical chemistry. Holger joined Analytik Jena in 2018 after seven years of teaching at the University and is currently engaged in chemical analysis. His primary focus lies in atomic absorption spectrometry and element analysis in general.
</blockquote>
<blockquote>
Presenter: Sandra Wunsch (Application Specialist Chemical Analysis)
</blockquote>
<blockquote>
Sandra Wunsch has been an Application Specialist for molecular spectrometry at Analytik Jena since 2016. She has intense in-depth knowledge in scientific and industrial application of molecular spectrometry, and extensive experience in the market and application fields, especially in the areas of environment and food &amp; agriculture. As a graduated Nutritionist, she is an expert in the use of chemical analysis and especially the determination of molecular compounds in the food industry and related fields.
</blockquote>

New Food: Edible oil processing: How to monitor elements and compounds

Edible oil processing: How to monitor elements and compounds

How to use these techniques for a variety of oils at different steps in the value and processing chain, and how to achieve optimal results.

Join us for an insightful webinar in which we'll focus exclusively on the advancements and applications of ICP-OES. Gain in-depth knowledge of how this technique can enhance the workflow efficiency of the analysis of advanced materials samples (including plastic and solid electrolyte) in your laboratory. Don't miss this opportunity to stay ahead in the restriction of hazardous substances (RoHS) compliance and electrolyte testing with the latest innovations.In the first presentation, we will explore the European Union's &nbsp;RoHS directive limits on specific hazardous materials in electrical and electronic equipment (EEE). Compliance with RoHS regulations, especially in testing complex materials, such as plastics, poses challenges for manufacturers, importers, and distributors. ICP-OES provides a robust solution for RoHS compliance testing in terms of measurement of Cd, Cr, Pb, and Hg. The presentation highlights the detailed sample preparation and precise element analysis by ICP-OES, featuring Intelligent Rinse technology.In the second presentation, we will go on to explore solid-state batteries as an emerging battery technology that uses a solid superionic electrolyte material instead of traditional liquid-phase electrolytes. Learn more about this emerging technology as well as how ICP-OES can provide a simple way to accurately determine contaminants and ensure the quality of the final battery.<h5>By attending this presentation, you will learn:</h5><ul><li>Gain a comprehensive understanding of how inductively coupled plasma optical emission spectrometry (ICP-OES) can perform accurate analysis of hazardous substances in EEE for RoHS compliance testing and in electronic waste (e-waste) for monitoring and research purposes, while improving your laboratory’s efficiency and productivity.</li><li>Gain an understanding of solid-state battery technology and discover how to overcome hurdles while analyzing solid electrolyte using ICP-OES.</li></ul><h5>Who should attend:</h5><ul><li>Analytical chemists working in elemental analysis, materials scientists and engineers working with solid-state electrolytes or batteries, environmental scientists interested in RoHS compliance testing, quality assurance, and regulatory compliance, personnel involved in ensuring products meet RoHS or other regulatory standards, researchers in academia, and laboratory technicians and managers.&nbsp;</li></ul><blockquote>Presenter: Aimei Zou, Ph.D (Solution Scientist, Agilent Technologies, Singapore)Aimei joined Agilent in 2018 as a solution scientist based in Singapore. She received her Ph.D in Analytical Chemistry in 2008. Aimei has over 17 years of experience in method development, covering dynamic technologies from atomic spectroscopy, including ICP-MS, ICP-OES, and AAS, to LC and GC mass spectrometry. In her current role with the Global Solution Development Center, Aimei focuses on developing integrated workflow solutions for food, environmental, and emerging markets.Presenter:&nbsp;Ruby Bradford (Application Chemist, Agilent Technologies, Melbourne, Australia)Ruby is an application chemist at Agilent Technologies, having worked in the Atomic Spectroscopy Division since 2020. She works frequently on the analysis of fine chemicals using techniques such as ICP-OES and is experienced in method development and sample preparation techniques in the advanced materials sector. She has a particular passion for the booming lithium-ion battery market and promoting a sustainable future through electrification.</blockquote>

SeparationScience: Advanced ICP-OES Applications: From RoHS Compliance to Solid Electrolyte Analysis

Advanced ICP-OES Applications: From RoHS Compliance to Solid Electrolyte Analysis

Gain insights into how ICP-OES can optimize workflows for the analysis of complex materials.

ICP-OES Applications: Solid Electrolyte Analysis

Many laboratories face complex challenges when dealing with mercury analysis. What is the most reliable and effective technique that offers compelling cost benefits for your lab? The choice is among staying with traditional dedicated mercury techniques such as CV-AAS/AFS or perhaps move some of the samples over to the ICP mass spectrometer (ICP-MS), or investing in the direct mercury analyzer that is able to eliminate any sample pre-treatment and dissolution.This webinar offers a closer look at the comparison in running costs between Direct Mercury Analysis technique and CV-AAS/AFS, and also how it stacks up against ICP-MS, to understand which investment can be the best one for your laboratory. We will make a practical cost comparison using similar sample types that require some type of sample pretreatment or preparation (e.g., solids or liquids that require digestion).<h4>What you will learn:</h4><ul><li>Breakdown of the mercury analysis costs</li><li>Costs comparison and productivity for different techniques</li><li>Cost comparison for mercury determination with ICP-MS</li><li>Practical guidance to lower analysis costs</li></ul><blockquote>Speaker: Roberto Boschini (Product Manager at Milestone)</blockquote>

Milestone: The cost benefits of direct mercury analysis: Do you know the bottom line

The cost benefits of direct mercury analysis: Do you know the bottom line?

Webinar offers closer look at comparison in running costs between Direct Mercury Analysis technique and CV-AAS/AFS, and also how it stacks up against ICP-MS

The cost benefits of direct mercury analysis

Mercury has been banned in cosmetics by regulatory agencies, but it persists in some formulations of cosmetic products. Despite the serious health risks associated with its use, mercury is still an attractive ingredient of cosmetic products claiming to lighten skin and remove blemishes. Fraudulent creams and cosmetic products take advantage of mercury's cost-effectiveness and ability to extend shelf life. Because of these properties, mercury in its toxic form, methylmercury, can also be added later to products that have already been manufactured.<h4>The Need for Regulation and Analytical Methods</h4>The identification of such substance is central to the various regulatory frameworks. ISO has addressed this issue by introducing ISO 23674:2022, which emphasizes the use of direct mercury analysis and the ISO 23821:2022 which involves sample preparation and CV-AAS.Together with our guest speaker Dr. Maximilian Orlandi, Chemistry Lab Manager at Complife Group who has deep knowledge of the analysis of cosmetics and the ISO procedures and Iacopo Avolio, Product Specialists at Milestone, we will review the benefits of these methods.This webinar aims to highlight procedure of quantification of mercury traces in cosmetic products that consumers can be exposed to in their usage. These methods describe the determination of mercury traces in cosmetics by using direct solid analysis with no need of digestion or by CV-AAS that requires acid digestion.<blockquote>Speaker: Iacopo Avolio (Product Specialists at Milestone)Speaker: Maximilian Orlandi (Chemistry Lab Manager at Complife Group)</blockquote>

Milestone: Mercury Analysis in Cosmetics: A deep dive into the latest ISO analytical methods for trace metal determination

Mercury Analysis in Cosmetics: A deep dive into the latest ISO analytical methods for trace metal determination

Webinar aims to highlight procedure of quantification of mercury traces in cosmetic products that consumers can be exposed to in their usage.

ICPMS webinars focusing on Elemental Analysis - page 1