Although modern agriculture needs to be based on accurate real-time data on soil, plant, and environmental conditions, affordable, sufficiently sensitive, and robust monitoring devices for this purpose are currently missing. According to scientists, low-cost sensors based on new smart materials and printing technologies offer a suitable solution. The results of multidisciplinary research thus far and proposals for the development of these devices have been presented by researchers from Czechia, Great Britain, Spain, and the USA in a review article in the prestigious journal <a target="_blank" rel="noopener noreferrer" href="https://www.nature.com/articles/s41467-026-68778-6#Abs1">Nature Communications</a>.“Sensor technologies for monitoring plant health are still in their infancy. Only simple sensors capable of monitoring basic parameters such as pH, soil moisture, or temperature are commonly available on the market. However, if farmers are to face current challenges, including climate change, and ensure sufficient food for humanity, they need much more effective tools that will enable them to monitor, for example, various pathogens, including bacteria and fungi. In our opinion, a suitable solution is a combination of new smart materials and printing for the production of inexpensive, durable, and scalable materials,” said the article’s first author, David Panáček from CATRIN, who worked on the study during his internship at Imperial College London.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/CATRIN_Soucasne_senzory_nestaci_Vedci_navrhuji_novou_cestu_ke_sledovani_zdravi_rostlin_b4014952a3.jpg" alt="CATRIN: David Panáček" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_CATRIN_Soucasne_senzory_nestaci_Vedci_navrhuji_novou_cestu_ke_sledovani_zdravi_rostlin_b4014952a3.jpg 208w," sizes="100vw" width="1536" height="1152">Sensors for monitoring plant health, for example, lag behind similar devices used in human medicine. According to the authors, advances in materials science, which will enable the development of scalable sensor technologies, play a key role in this potential shift. “Printing techniques, including inkjet printing, screen printing, aerosol printing, 3D printing, and direct laser writing, offer flexible ways to produce flexible sensors, large-area sensors, and sensors integrated directly into plants. The review article summarizes recent advances in printable low-dimensional materials for agricultural sensors, analyzes their physico-chemical properties in relation to sensor performance, and discusses key challenges and future opportunities requiring interdisciplinary integration,” said one of the corresponding authors, Michal Otyepka.The research brought together materials scientists, chemists, biologists, sensing experts, and printing technology specialists. Materials research and the use of graphene-based smart materials were led by scientists from CATRIN at Palacký University and VŠB-Technical University of Ostrava. Plant biologists from CATRIN contributed their knowledge of plant development, their responses to stress conditions, and the monitoring of their properties. Researchers from Imperial College London took care of the electronics, while representatives from<a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/companies/36"> CEITEC – VUT</a> focused on printing technologies. The team also included leading experts in sensing from the Catalan Institute of Nanoscience and Nanotechnology in Barcelona, and Joseph Wang of the University of California San Diego, the “father of sensing and electrochemistry,” also contributed his extensive knowledge.“This is a groundbreaking study on this topic, which has managed to attract some truly big names in their respective fields. Last but not least, the study demonstrates that interdisciplinarity at CATRIN gives rise to completely new and promising research topics, such as plant sensing and its use for studying plant-environment interactions and smart agriculture,” added another corresponding author, Nuria De Diego.

Current sensors are not good enough. Scientists propose a new way to monitor plant health

In the week from February 16, the following webinars await you in the field of atomic and molecular spectroscopy and spectrometry<blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinars">👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</a></h4>👉 Search and filter in the largest global database with over 5 000 GC, LC, MS and spectroscopy webinars.</blockquote><h5>1. Thermo Fisher Scientific: The Perfect Pair for GMP Compliance – IonicX and TruScan for Raw Material Identification and Verification</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>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.<h5>2. Milestone: Reliable Mercury Analysis in Environmental Samples – Tools, Techniques, and Best Practices</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>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.<h5>3. Agilent Technologies: Learn How to Confirm Your Data on ICP-OES – Are You Getting the Right Result?</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>This webinar discusses accuracy and precision in ICP-OES analysis and practical strategies to ensure reliable and defensible results.

Webinars LabRulezICPMS Week 08/2026

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.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.<blockquote><h4>The original article</h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acs.est.5c11233">Unlocking Phytoplankton Metallomes with Comparative Analysis of Metal Quotas, Quantitative Proteomics, and Inferred Metalloproteomes</a></h4>Qiong Zhang*, Jiayou Ge, Fengjie Liu, Shabaz Mohammed, Kedong Yin, and Rosalind E. M. RickabyEnviron. Sci. Technol. 2025, 59, 50, 27367–27377<a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acs.est.5c11233">https://doi.org/10.1021/acs.est.5c11233</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.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.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 in situ 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 (e.g., by ICP-MS) and the protein sequence (e.g., 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>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.<h3>Materials and Methods</h3><h4>ICP-MS Analysis</h4>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 G. huxleyi (OA1, OA4, OA8, OA15, OA16, OA23, and RCC 1242) and Synechocystis (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><h4>Protein Mass Spectrometry</h4>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">Ultimate 3000 UHPLC </a>system (Thermo Fisher Scientific) and electrosprayed directly into a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/559">Q-Exactive Mass Spectrometer</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 m/z, 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 m/z) with the first fixed mass at 180 m/z. Charge exclusion was selected for unassigned and 1+ ions. The dynamic exclusion was set to 20 s.<h3>Results and Discussion</h3><h4>Trace Elements Determined from the Expressed Proteomes of Different Phytoplankton</h4>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 G. huxleyi, 31 different metals in C. reinhardtii, and 30 different metals in Synechocystis. Although only 6 different metals were identified in O. tauri proteins, it has to be noted that the analysis for O. tauri 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.<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">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 (Mg2+ and Ca2+ [weakest binding] &lt; Mn2+ &lt; Fe2+ &lt; Co2+ &lt; Ni2+ &lt; Cu2+ &gt; Zn2+). <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>).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 G. huxleyi and Synechocystis. <a href="javascript:void(0);">(22,24)</a> The essential roles of Mg in plants have been reported in various studies. Mg2+ 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><h4>Comparison Between Metallome Measured Directly and Reconstructed from Proteins</h4>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.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 (r2 = 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 r2 = 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.<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">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 G. huxleyi and Synechocystis (<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. Ca2+ 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+ 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 Mg2+ and K+ abundances should also be higher than those determined from the protein structures. Free Mg2+ and K+ 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>).

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

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The Czech Advanced Technology and Research Institute (CATRIN) at Palacký University is a cutting-edge scientific hub dedicated to advancing research in the fields of nanotechnology, biotechnology, and biomedicine. At its core, CATRIN boasts outstanding scientific teams, featuring international researchers. We emphasize interdisciplinarity, foster global collaborations, and work to translate our research findings into practical applications.

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The Need for Half-Mass Measurement is real when running a single quad ICP-MS and with doubly charged interferences.ORS is very capable at the removal of polyatomic interferences under Helium Collision Mode; however, some samples contain high and variable levels of Rare Earth Elements (REE’s). REE’s that have relatively low second ionization potentials meaning they can form ions with a 2+ charge. Even at only 1% formation, if concentrations are high, the interferences can be significant enough. Let me show you how to set the half-mass measurement up in your software.<blockquote>Presenter: Jenny Nelson, PhD (Application Scientist, Agilent Technologies, Inc).Dr. Jenny Nelson is an Applications Scientist with Agilent Technologies specializing in Inductively Coupled Plasma Mass Spectroscopy (ICP-MS), Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES), Microwave Plasma Atomic Emission Spectroscopy (MP-AES). Her broad knowledge of atomic spectroscopy has been applied to both AOAC and ASTM through her serving on expert review panels, chairing committees, and volunteering to develop new methods needed by the industry.Presenter: L. Craig Jones (ICP-MS Application Scientist, Agilent Technologies, Inc.)Craig has been with Agilent for over 15 years as an ICP-MS applications scientist. He has been involved with multiple type of applications for ICP-MS, including environmental, pharmaceutical, semiconductor, geologic, and clinical analyses, to name a few. Previous to Agilent he worked in an environmental lab performing analysis and supervising both the inorganic and organic sections of the laboratory. In his spare time, Craig enjoys volunteering at the local marine science center, mountain biking, hiking, and relaxing at the beach. Craig obtained a Bachelor of Science degree in chemistry from Fort Lewis College in Durango, CO.</blockquote>

Agilent technologies: Avoiding Double Charged Interferences on Single Quadrupole ICP-MS

Avoiding Double Charged Interferences on Single Quadrupole ICP-MS

How to set the half-mass measurement up in your software.

Avoiding Double Charged Interferences on Single Quadrupole

<div>This webinar will provide an overview of Chemical Exchange Saturation Transfer (CEST) MRI, from its physical principles and experimental design to the key factors influencing endogenous CEST signals in vivo. We will explore both physiological and technical sources of contrast, the complexity of in vivo CEST signals, and common artifacts such as fat contamination and field inhomogeneities.The session will also highlight essential correction strategies for achieving quantitative CEST MRI and showcase current applications in cancer and neuroimaging. Preclinical studies at ultra-high magnetic fields—such as the DKFZ’s 9.4 T Bruker system—play a key role in advancing methodological development, enabling a deeper understanding of complex CEST signal behavior in vivo and paving the way for clinical translation.<h5>What to Expect</h5>Join Dr. Philip S. Boyd for an in-depth exploration of Chemical Exchange Saturation Transfer (CEST) MRI, covering its theoretical foundations, practical implementation, and cutting-edge applications in cancer and neuroimaging. This webinar will guide attendees through the complexities of in vivo CEST signals, correction strategies for artifacts, and the translation of preclinical findings into clinical practice.<h5>Key Learning Points</h5><ul><li>Understanding the CEST Phenomenon and Theory</li><li>Applications in Cancer and Neuroimaging</li><li>Achieving Quantitative CEST imaging In Vivo</li></ul><h5>Who should attend:</h5>This webinar is ideal for researchers, clinicians, and imaging specialists working in MRI, oncology, neurology, or molecular imaging who are interested in advancing their understanding of quantitative CEST techniques and their translational potential. It will also be highly educational for graduate students and early-career scientists beginning their journey in MRI, offering foundational insights and practical guidance.<blockquote>Presenter: Dr. Philip S. Boyd (Ph.D. in Physics from Heidelberg University and leads the CEST Imaging Group at the German Cancer Research Center (DKFZ) in Heidelberg)Dr. Philip S. Boyd holds a Ph.D. in Physics from Heidelberg University and leads the CEST Imaging Group at the German Cancer Research Center (DKFZ) in Heidelberg. His research focuses on developing and refining advanced CEST imaging techniques, including pH imaging and fat artifact correction. He combines experimental imaging, mathematical modeling, and data analysis to drive CEST applications from preclinical research to clinical translation.</blockquote></div>

Bruker: Quantitative CEST MRI: From Principles to Applications in Cancer and Neuroimaging

Quantitative CEST MRI: From Principles to Applications in Cancer and Neuroimaging

Discover how CEST MRI works and how it's applied in cancer and neuroimaging. With insights from DKFZ’s cutting-edge preclinical studies.

Quantitative CEST MRI: From Theory to Clinical Insight

<div>Join us for an insightful webinar on the PIPAc project, an innovative approach to pharmaceutical manufacturing that integrates AI, NMR, flow chemistry, and 3D-printed modular reactors. Attendees will explore how AI-driven process control optimizes chemical reactions in real time, while in-line NMR provides precise monitoring of active pharmaceutical ingredient (API) synthesis. Continuous flow chemistry combined with compact, 3D-printed reactors enable mobile, resource-efficient production, supporting rapid scale-up and flexible deployment. Gain in-depth insights into the convergence of automation, analytical technologies, and advanced reactor design shaping modern pharmaceutical production.<h5>Key Learning Points</h5><ul><li>Enhanced Process Control: Learn how AI, NMR, and PAT enable real-time monitoring, optimizing reactions and ensuring efficient, reliable API production.</li><li>Scalable and Flexible Production: Understand how modular 3D-printed reactors and continuous flow chemistry support rapid scale-up and mobile manufacturing.</li><li>Innovative Applications: Explore advanced applications of flow chemistry, 3D-printed reactors, and AI-driven analytics to drive innovation and improve pharmaceutical API processes.</li></ul><h5>What to Expect</h5>Discover how the PIPAc project integrates AI, NMR, flow chemistry, and 3D-printed reactors for compact, mobile API manufacturing. Learn about real-time process monitoring, continuous flow optimization, modular reactor design, and case studies showcasing efficient, scalable, and safe pharmaceutical production, providing actionable insights for modern API synthesis.<h5>Who should attend?</h5>This webinar is designed for pharmaceutical scientists, bioprocess engineers, and quality assurance professionals, as well as anyone involved in pharmaceutical manufacturing and development. Attendees will gain practical insights to enhance process control, ensure product quality, and explore innovative NMR, PAT, and AI applications.<blockquote>Presenter: Alejandro Bara-Estaún, PhD (Solution Product Manager for (bio)Process Analytical Technology, Bruker Biospin)Alejandro Bara Estaun obtained his Ph.D. in Inorganic Chemistry at the University of Bath (UK) in collaboration with Bristol University and Evonik (Germany). He then undertook a two-year postdoctoral position at Bruker, leading the PIPAc project in collaboration with Alysohpil, Novalix, and De Dietrich. Recently, he transitioned into the role of Solution Product Manager for (bio)Process and Process Analytical Technology within Bruker’s Biopharma and Applied (BPA) division.Presenter: Philippe Robin (Co-founder and CEO of Alysophil)Philippe Robin is the co-founder and CEO of Alysophil, a Strasbourg-based company developing solutions in continuous-flow chemistry enhanced by artificial intelligence for process control. Alysophil aims to improve the efficiency and sustainability of chemical production. Under his leadership, the company has launched projects such as Chempocket, modular micro-factories designed for flexible chemical synthesis, and PIPAc, a program dedicated to pharmaceutical processes, carried out with partners including De Dietrich, Bruker, and Novalix. Philippe Robin focuses on applying new technologies to support the chemical industry’s transition toward more flexible and responsible production models.Presenter: Luis Carrillo (Managing Director, De Dietrich France Dijon SAS)Luis Carrillo is the Managing Director of De Dietrich Group’s subsidiary in Dijon, dedicated to developing engineering solutions through the integration of both in-house and third-party products. Dijon also serves as the hub for the Group’s innovation program, within which the PIPA’c project plays a pivotal role as a cornerstone for the future commercial development of these solutions. A chemist by training, Luis earned his degree from the University of Barcelona (Spain) and later completed a Master at IESE Business School. Luis Carrillo has been with the De Dietrich Group for more than 10 years, holding various positions across the organization. Luis Carrillo is committed to advancing sustainable innovation and strengthening the Group’s leadership in chemical engineering solutions. &nbsp;Presenter: Guillaume Bentzinger, PhD (Flow &amp; Process department, Novalix)Guillaume Bentzinger joined Novalix as a Junior Project Manager in 2018 in the Synthetic Chemistry department. In 2019, he transitioned to the Process &amp; Flow department where he advanced to Project Manager and has been actively contributing to the development of flow chemistry at Novalix. He is leading the development of the chemistry under flow conditions for the PIPAc project. Guillaume Bentzinger studied organic chemistry in Strasbourg, at the IUT Robert Schuman Technical Institute, and later at the European School of Chemistry, Polymers and Materials (ECPM). In 2016, he completed his PhD in medicinal chemistry under the supervision of Professor Pascal Sonnet and Dr. Alexandra Dassonville-Klimpt at the University of Picardie Jules Verne in Amiens. In 2017, he pursued postdoctoral research in medicinal chemistry at Almac Discovery and the University of Belfast, under the supervision of Dr. Hugues Miel.</blockquote></div>

Bruker: Flow Chemistry Meets AI and NMR for Next-Gen API Production

Flow Chemistry Meets AI and NMR for Next-Gen API Production

Webinar on PIPAc: AI, NMR, flow chemistry & 3D-printed reactors for scalable, flexible API manufacturing with real-time monitoring and process optimization.

<div>Pharmaceutical manufacturing faces growing demands for faster, more reliable testing while maintaining strict quality standards. Raman spectroscopy is transforming how laboratories meet these challenges with rapid, non-destructive analysis that requires little to no sample preparation.This webinar will showcase how this technology supports efficient, compliant and cost-effective testing across manufacturing workflows. Our expert speaker will also share insights into upcoming innovations that could further streamline processes and strengthen decision making.Designed for professionals at all levels, this session will provide valuable knowledge to help you stay ahead in pharmaceutical testing.<h5>Attend this webinar to:</h5><ul><li>Understand the importance of testing in pharmaceutical manufacturing and the challenges encountered</li><li>Learn about comprehensive services such as data compliance, service and support to enhance testing processes</li><li>Understand the advanced capabilities of Raman spectroscopy in pharmaceutical manufacturing testing</li><li>Discover the benefits of Raman technology, including higher throughput, cost savings, time savings and higher uptime</li></ul><blockquote>Presenter: Sudhir Dahal, PhD (Product Manager at Thermo Fisher Scientific)Dr. Sudhir Dahal is the product manager of research Raman products at Thermo Fisher Scientific. The products include Raman microscopes and benchtop Raman spectrometers. He has worked with several spectroscopy techniques in the industry and has over 7 years of experience. He has a PhD from University of Maryland Baltimore County, where he researched and collaborated on developing a novel spectroscopy-based technique for brain tumor cell detection.</blockquote></div>

Technology Networks: Enhancing Pharmaceutical Manufacturing Using Raman Spectroscopy

Enhancing Pharmaceutical Manufacturing Using Raman Spectroscopy

Webinar on Raman spectroscopy in pharma. Explore rapid, non-destructive testing that boosts compliance, efficiency, and cost savings in manufacturing workflows.

Pharmaceutical Manufacturing by Raman Spectroscopy

<div>Join us for an introduction to KnowItAll's Trendfinder, a new tool that applies Principal Component Analysis (PCA) to reveal hidden patterns in large analytical datasets that traditional analysis misses—all through an intuitive interface that any researcher can use.This webinar will quickly familiarize you with basic pattern recognition so that basic chemometric analysis can become part of your routine analytical process.<h4>What you’ll learn</h4><h5>Pattern discovery made simple</h5><ul><li>How Trendfinder applies PCA to uncover meaningful patterns in complex datasets</li><li>Working with diverse data types: NMR, IR, MS, Raman, UV-Vis, &amp; chromatography</li></ul><h5>Advanced analysis without the complexity</h5><ul><li>Unknown sample projection for classification and marker compound discovery</li><li>Interactive data mining with clear, actionable visualizations</li><li>Live step-by-step workflow demonstrations</li></ul><h4>Who should attend:</h4><ul><li>Current KnowItAll users ready for advanced pattern analysis</li><li>Researchers with large analytical datasets seeking hidden insights</li><li>Anyone interested in accessible, user-friendly PCA approaches</li></ul><h4>About KnowItAll Software</h4>KnowItAll offers a unified, vendor neutral solution for data processing, analysis, searching, and databasing. KnowItAll 2026 has tools for workflows across techniques (IR, Raman, GC-MS, LC-MS, NMR and UV-Vis), as well as tools for structure drawing, report publishing, and more. Combined with Wiley’s high-quality spectral reference library databases, it provides an unparalleled solution for fast, reliable spectral analysis.<blockquote>Presenter: Michelle D’Souza, PhD (Product Manager, Software Products, Wiley Science Solutions, Wiley)Dr. D’Souza brings years of insight and knowledge in the area of spectral informatics with leadership roles at both Wiley and Bio-Rad Laboratories. In addition to her multiple years as a scientific researcher at Abbott (now AbbVie) and DuPont, she has a Ph.D. in Chemistry from Northern Illinois University and a Masters in Analytical Chemistry from the Chinese Academy of Preventative Medicine. She earned a BS degree from Chemistry Department of Beijing University. &nbsp;</blockquote></div>

Wiley: Discover hidden trends in spectral & chromatographic datasets

Discover hidden trends in spectral & chromatographic datasets

Introduction to KnowItAll's Trendfinder, a new tool that applies Principal Component Analysis (PCA) to reveal hidden patterns in large analytical datasets

Hidden trends in spectral & chromatographic datasets

<div>From industrial coatings to ancient fossils, layer thickness analysis using micro-XRF is a powerful technique applied across diverse fields. Bruker micro-XRF for SEM (XTrace 2), combined with XMethod software, enables precise, non-destructive quantification of composition and thickness in complex multilayer structures.In this webinar, we will introduce the physical principles behind micro-XRF-based layer thickness analysis and demonstrate the layer thickness calculation procedures. You will also see practical workflows using XTrace 2 in object, line, and mapping modes.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Bruker_Elemental_distribution_of_a_printed_circuit_board_above_and_the_corresponding_elemental_distribution_of_its_layer_structure_build_on_Cu_Ni_and_Au_bottom_2d0d23a7ff.jpg" alt="Bruker: Elemental distribution of a printed circuit board (above) and the corresponding elemental distribution of its layer structure build on Cu, Ni and Au (bottom)." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Bruker_Elemental_distribution_of_a_printed_circuit_board_above_and_the_corresponding_elemental_distribution_of_its_layer_structure_build_on_Cu_Ni_and_Au_bottom_2d0d23a7ff.jpg 210w," sizes="100vw" width="608" height="451"><h4>We will discuss real-world examples from multiple application fields:</h4><ul><li>Multilayer structures in printed circuit boards&nbsp;</li><li>Thin silver layers in photographic samples&nbsp;</li><li>Fossilized trilobite exoskeletons&nbsp;</li><li>Palladium coatings on nickel&nbsp;</li><li>Coatings on silicon wafers&nbsp;</li><li>Standard reference samples with known thicknesses</li></ul>We will also compare the traditional destructive SEM- and EDS-based methods with the non-destructive micro-XRF method in SEM, highlighting advantages in accuracy, efficiency, and sample preservation.<h4>Who should attend?</h4><ul><li>Scientists and researchers from all analytical fields interested in coating thickness calculation in SEM;</li><li>Micro-XRF users;</li><li>Experienced professionals managing electron microscopy labs.</li></ul><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Bruker_Non_destructive_thickness_evaluation_of_Trilobite_exoskeleton_gathered_with_XTRACE_2_Micro_XRF_in_SEM_Petrographically_well_kept_calcite_exoskeleton_has_10_m_in_thickness_446804baf4.jpg" alt="Bruker: Non-destructive thickness evaluation of Trilobite exoskeleton gathered with XTRACE 2 Micro-XRF in SEM. Petrographically, well-kept calcite exoskeleton has ~ 10 µm in thickness." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Bruker_Non_destructive_thickness_evaluation_of_Trilobite_exoskeleton_gathered_with_XTRACE_2_Micro_XRF_in_SEM_Petrographically_well_kept_calcite_exoskeleton_has_10_m_in_thickness_446804baf4.jpg 226w," sizes="100vw" width="608" height="420"><blockquote>Presenter: Stephan Boehm (Product Manager - micro-XRF on SEM and WDS, Bruker Electron Microscope Analyzers)Presenter: Dr. Yang Yang (Application Scientist - micro-XRF on SEM and EDS, Bruker Electron Microscope Analyzers)</blockquote></div>

Bruker: Exploring Multi-Field Layer Thickness Capabilities with Micro-XRF in Scanning Electron Microscope

Exploring Multi-Field Layer Thickness Capabilities with Micro-XRF in Scanning Electron Microscope

We will introduce physical principles behind micro-XRF-based layer thickness analysis and demonstrate the layer thickness calculation procedures.

Multi-Field Layer Thickness Capabilities with Micro-XRF

<div>Electron Backscatter Diffraction (EBSD) has long been a key technique for microstructural analysis in Scanning Electron Microscopy (SEM), widely adopted across both academic research and industrial applications. From mapping grain orientations in high performance alloys to probing deformation mechanisms in geological samples, EBSD continues to unlock critical insights into material properties.Our groundbreaking EBSD detector eWARP, which uses Direct Electron Detection (DED) technology, has been changing the EBSD landscape since its launch earlier this year. If you are not yet up to speed with eWARP now is the time to catch up!This webinar will show you how eWARP, powered by a custom hybrid pixel sensor designed for EBSD applications, redefines EBSD performance by dramatically increasing signal efficiency and acquisition speed.Curious about how eWARP can enhance your research? We will explore the use of eWARP in a range of applications, from materials science to nanotechnology, to show you what is now possible with the latest EBSD technology.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Bruker_Figure_1_Grain_Average_Misorientation_map_5e4fe4eeaa.jpg" alt="Bruker: Figure 1: Grain Average Misorientation map (false color) of bainitic steel, identifying regions with higher plastic deformation and dislocation density in green and yellow (&gt;6° misorientation)." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Bruker_Figure_1_Grain_Average_Misorientation_map_5e4fe4eeaa.jpg 235w," sizes="100vw" width="608" height="404"><h4>What to Expect</h4><ul><li>Materials Science: See how eWARP enables ultra-fast phase and orientation mapping in complex metallic microstructures, revealing fine precipitates and phase transformation products at unprecedented clarity.</li><li>Battery Research: Discover how high-resolution EBSD measurements quantitatively characterize boundary, grain and texture distributions in battery collector materials.</li><li>Geoscience Applications: EBSD combined EDS phase identification helps you deciphering mineral deformation histories and crystallographic fabrics.</li><li>Nanotechnology: Learn how direct detection pixelated sensor enhances TKD analysis of nanostructured thin films.</li><li>Live Demo: Witness eWARP in action with a real-time EBSD acquisition showcasing its speed and precision.</li></ul>Whether you're advancing your research or exploring new analytical capabilities, this webinar provides a timely opportunity to learn how next-generation EBSD technology can support and elevate your research.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Bruker_Figure_2_Grain_Size_Distribution_map_random_coloring_of_NMC_cathode_material_used_in_Lithium_ion_battery_f16c7ee3be.jpg" alt="Bruker: Figure 2: Grain Size Distribution map (random coloring) of NMC cathode material used in Lithium-ion battery. In this measurement, 8500 grains were measured with eWARP in only 9 minutes (:measurement speed of 10 000 fps). The average grain size is less than 500 nm. The measurement was done at low accelerating voltage (10 kV) and probe current (13 nA) to reach the required fine step size of 20 nm" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Bruker_Figure_2_Grain_Size_Distribution_map_random_coloring_of_NMC_cathode_material_used_in_Lithium_ion_battery_f16c7ee3be.jpg 100w," sizes="100vw" width="608" height="955"><blockquote>Presenter: Dr. Laurie Palasse (Global Application Manager, Bruker Electron Microscope Analyzers)Presenter: Dr. Meriem Ben Haj Slama (Application Scientist EBSD, Bruker Electron Microscope Analyzers)</blockquote></div>

Bruker: Catch Up with eWARP: Unmatched EBSD Performance

Catch Up with eWARP: Unmatched EBSD Performance

This webinar will show you how eWARP, powered by a custom hybrid pixel sensor designed for EBSD applications, redefines EBSD performance

<div><div id="inner_content_body_text" data-content-id="394785">The Litesizer DIF 500 was designed to make laser diffraction analysis as simple and intuitive as possible, without compromising precision.In this webinar, we’ll explore how every aspect of the instrument and its workflow was engineered for true user accessibility, including:<h5>Quick-Click Measuring Modules</h5><ul><li>Learn how the Quick-Click system allows you to switch seamlessly between liquid and dry dispersion in a single motion—no cables, tools, or complex setup required.</li></ul><h5>Modular Design</h5><ul><li>See how the modular design streamlines cleaning and maintenance, helping you move from one sample type to another in minutes.</li></ul><h5>Intuitive Software</h5>Kalliope™ software makes comparing datasets, reviewing trends, and reporting results effortless, thanks to its one-page workflow and smart QC tools.<h5>Widest Particle Size Range</h5><ul><li>With a range from 10 nm to 3.5 mm and best-in-class optical components, the Litesizer DIF is designed for precise, accessible measurements that enable accurate analysis of both small particles and complex mixtures.</li></ul>Whether in R&amp;D, quality control, or production, the Litesizer DIF 500 removes the typical barriers to efficient particle size analysis.See for yourself how we have simplified every step, from setup to cleaning to data evaluation, to deliver an effortless and accurate particle size analysis experience from start to finish.<blockquote>Presenter: Brian RodenhausenDr. Brian Rodenhausen is the Principal Application Scientist in the Particle and Porous Materials Characterization group at Anton Paar USA. He has over a decade of experience teaching users the theory and practice of analytical instruments, as well as advising them on the design of experiments and interpretation of results. His research background focused on label-free characterization of asorbate layers at the solid-liquid interface. He received his Ph.D. in chemical engineering from the University of Nebraska-Lincoln (UNL) and did post-doctoral work at UNL and the Leibniz Institute of Polymer Research in Dresden, Germany.&nbsp;</blockquote></div></div>

Anton Paar: Effortless Particle Size Analysis – See the Difference

Effortless Particle Size Analysis – See the Difference

Learn how the Litesizer DIF 500 makes laser diffraction easy and precise with Quick-Click modules, modular design, smart software, and broad size range.

The Thermo Scientific Hypulse Surface Analysis System delivers a new approach to XPS depth profiling. It combines traditional ion beam milling with femtosecond laser ablation technology to help you accurately examine thin films, coatings, and multi-layer structures, all without the risk of chemical damage to the sample.Join us as we introduce the Hypulse System and highlight how it can help you revolutionize XPS depth profiling.<h5>In this webinar, you will:</h5><ul><li>Learn how femtosecond laser ablation delivers depth profiling to over 30 µm</li><li>Discover advanced depth profiling capabilities available with the Hypulse System</li><li>See how the combination of laser ablation and ion milling makes it possible to analyze a wider variety of materials</li></ul><blockquote>Presenter: Tim NunneyTim is an applications development and marketing manager for the Thermo Scientific surface analysis (X-ray photoelectron spectroscopy) product line. He has been with Thermo Fisher Scientific since 2004, previously holding positions as an applications scientist, product manager, and in operations. Prior to joining Thermo Fisher, Tim worked as a post-doctoral research fellow at the University of Southampton investigating the dynamics of molecular dissociation on metal surfaces.</blockquote>

Thermo Fisher Scientific: Explore damage-free XPS depth profiling with the Hypulse Surface Analysis System

Explore damage-free XPS depth profiling with the Hypulse Surface Analysis System

Join us as we introduce the Hypulse System and highlight how it can help you revolutionize XPS depth profiling.

Damage-free XPS depth profiling with Hypulse Surface

Understand how TGA (thermogravimetric analysis) and DSC (differential scanning calorimetry) advance quality testing of biofuel end-products, including fatty acid decomposition at high temperatures, and freezing point determination in hydrocarbon mixtures for SAF applications. You'll learn about the benefits of Pyris™ DSC and HyperDSC®- providing high precision and super fast heating/cooling cycles. &nbsp;Plus we highlight the role of IR (infrared) and multi-position sample preparation units, which combined with thermal analysis, help you achieve comprehensive fuel and biofuel laboratory workflows.<h4>Highlights</h4><ul><li>Biofuel market - testing techniques overview &amp; thermal analysis deep dive</li><li>Fatty acid decomposition at higher temperatures using TGA (research example from Alberta University)</li><li>Determining the freezing point of hydrocarbon mixtures for SAF applications using DSC (research example from Alberta University)</li><li>Role of IR featuring Spectrum Two™ and multi-position sample preparation units such as OilExpress</li></ul><blockquote>Presenter: Bernardo Araujo Souto (PhD candidate) (Lecturer, University of Alberta)Bernardo is part of the Biorefining Conversions and Fermentation Laboratory at the University of Alberta, where he works at the intersection of academia and industry to advance sustainable fuel technologies. He is a member of the group led by Dr. David C. Bressler, which focuses on developing and scaling bio-based solutions. Bernardo has been closely involved in collaborations with PerkinElmer, applying advanced analytical platforms to support innovation, scale-up, and industry-driven solutions in biomass conversion. Presenter:&nbsp;Dr. Krystelle Mafina PhD (Product Line Leader, PerkinElmer)Dr. Krystelle Mafina is a product leader at PerkinElmer, overseeing the thermal (TEA) analysis business. She holds a PhD in Biomedical Biomaterials Science and is a Chartered Engineer (CEng) and Chartered Scientist (CSci) with a strong background in materials science. A member of the Institute of Materials, Minerals, and Mining (IOM3) since 2009; a committee member since 2019, Krystelle is committed to continuous professional development and was recently made 'Fellow' of the institute. Her blend of scientific knowledge and industry experience makes her a valuable contributor to PerkinElmer and the wider scientific community. Presenter:&nbsp;Lucy Jenner (Sr. Marketing Manager &amp; Programs Lead)Lucy Jenner is a CIM qualified marketing professional working at PerkinElmer since 2020. She develops strategy and manages marketing campaigns for industrial end-market sectors, across PerkinElmer's global customer base. Lucy is a graduate of Reading University and postgrad of Oxford College of Marketing.</blockquote>

PerkinElmer: Thermal & IR Studies Advancing Biofuel Production & Performance

Thermal & IR Studies Advancing Biofuel Production & Performance

Learn how TGA, DSC, and IR thermal analysis optimize biofuel testing, from fatty acid stability to SAF freezing point determination with PerkinElmer.

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