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

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Academy

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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.

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As we all know, the need for efficient and sustainable energy storage solutions has never been greater. With the increasing demand for electric vehicles, and storage of renewable energy, the battery industry together with academic institutes are constantly evolving and pushing the boundaries of what is possible.Bruker is at the forefront of this innovation, providing cutting-edge technologies and solutions for battery research and manufacturing. In this webinar, we will explore the latest developments in Bruker's technology and how they can be applied to optimize battery performance, reduce costs, and accelerate the path towards a cleaner energy future.Join our 75 minutes experts discussion as they dive into the fascinating world of batteries and discover how Bruker is shaping the future of it.Key Learning Topics:<ul><li>You will learn about a complete portfolio of technologies applied to battery research and production, including AFM, NMR, EPR, MS, FTIR, XRD, XRF, XRM, RAMAN, EDS and EBSD. These technologies represent the excellence of Bruker's analytical tools and are complementary in their applications. They are used in various ways to help researchers and manufacturers understand how batteries work, how they can be improved, and how they can be produced and recycled more efficiently.</li></ul>Who Should Attend?<ul><li>Battery manufacturers</li><li>Research and development organizations</li><li>Academic institutions</li><li>Material science organizations</li><li>Electrochemical and analytical chemistry organizations</li><li>Testing laboratories involved in battery research and development.</li><li>Government agencies involved in renewable energy and sustainability.</li><li>Investors interested in the battery market.</li><li>Battery technology experts and engineers</li></ul><blockquote>Presenter: Andrea Steck Ph.D. (Principal Scientist - Bruker BioSpin (Ettlingen, Germany))Andrea Steck joined BBIO Germany in 2010 to perform contract services, then stepped into food profiling development, acted as Quality Manager (ISO-17025), and now is responsible for supporting, developing, and driving AIC-DEV projects as Principal Scientist.Andrea holds a PhD in Chemistry (TU Munich). She gained extensive experience in NMR pulse sequence development and structure elucidation (Berne, Switzerland), and in leading an analytical (NMR/MS/IR) laboratory in big pharmaceutical industry (Vienna, Austria). She then joined Bruker Austria as Manager Pursuant to Trade Law, responsible for contract services and customer acquisition.Presenter: Hugues Guérault (Application Manager – Bruker Advanced X-Ray Solutions (Karlsruhe, Germany))Hugues Guérault joined Bruker in 2002 as Application Scientist. He is now leading Bruker AXS application team and manages worldwide the activities of the application laboratories for equipment demonstrations and customer training.Hugues holds a PhD in Material Science from Le Mans University (France) and made a post-doc at the University of Leuven (Belgium). Overall, he has acquired more than 25 years of experience in material characterization using X-ray diffraction.Presenter: Peter De Wolf, PhD (Sr. Director AFM Technology Development &amp; Applications, Bruker Nano Surfaces &amp; Metrology, Santa Barbara, CA, USA)Joined Bruker after obtaining Ph.D. in Electrical Engineering from the University Leuven &amp; IMEC, Belgium in 1998 focused on the development of novel AFM characterization methods. Author and co-author of over 40 publications related to property characterization using AFM, and co-inventor of several AFM methods. In his role, Peter is responsible for developing, driving, and leveraging new technology and applications for Bruker’s AFM Instrumentation.Presenter: Ph.D. Bob Galvin, FRSC (Vice President BAMS, Bruker Daltonics, London, UK)Bob Galvin obtained his PhD using mass spectrometry to investigate novel catalytic reactions and since then has always been involved in this technology. &nbsp;He joined Bruker eleven years ago and has held a number of executive positions during this period.Presenter: Rebecca Keller (Scientific Content Creator – Bruker Scientific LLC (Billerica, MA, USA))Rebecca joined Bruker Scientific in 2022 to support scientific content creation for applied markets as well as research and academia. Thanks to her extensive experience in crafting content for chemistry e-learning platforms, she excels at presenting complex ideas with exceptional clarity and precision.Rebecca graduated in Chemistry at the University of Oregon in 2019 and has since sought to improve scientific communication by producing content across multiple platforms.Presenter: Michele Gironda (Head of Global Segment Management – Bruker Nano Analytics (Berlin, Germany))Michele Gironda joined Bruker in 2017 when Bruker acquired XGLab where he was Director Sales and Marketing. He is now our Head of Global Market Segment Management in the Nano Analytics Division. In his role Michele manages worldwide activities for the key strategic market segments in cooperation with sales, marketing, application and product managers.Michele holds a Master Degree in Engineering obtained with his studies in Politecnico di Milano (Italy) and Universitat Politecnica de la Catalunya in Barcelona (Spain).</blockquote>

Bruker: Shaping the future of batteries: Bruker technologies across the entire value chain

Shaping the future of batteries: Bruker technologies across the entire value chain

Join our 75 minutes experts discussion as they dive into the fascinating world of batteries and discover how Bruker is shaping the future of it.

Bruker technologies - Shaping future of batteries

<div>Discover how Infrared (IR) and Electron Paramagnetic Resonance (EPR) spectroscopies enable rapid, multi-parameter soil analysis. This webinar covers practical sample preparation, instrument setup, and calibration strategies for IR, followed by EPR applications in detecting free radicals, transition metals, and environmentally persistent radicals, advancing soil health assessment and contamination monitoring at scale.Join us for an in-depth webinar on accelerating soil health assessment using Infrared (IR) and Electron Paramagnetic Resonance (EPR) spectroscopy. Learn how IR enables rapid, multi-parameter analysis of soil properties such as carbon content, clay, pH, and cation exchange capacity from a single spectrum, along with strategies for robust calibration and transferability. Explore EPR applications for detecting free radicals, transition metal ions, and surface-stabilized environmentally persistent free radicals (EPFRs) in soil, which impact pollutant transformation and environmental health. This session will demonstrate how IR and EPR deliver fast, cost-effective, high-throughput soil characterization to support classification, management decisions, and sustainable soil health monitoring. &nbsp;<h4>What to Expect</h4>Discover how IR and EPR spectroscopy enable rapid, high-throughput soil analysis. Learn practical sample preparation, calibration strategies, and applications for assessing carbon, clay, pH, and contaminants. Explore EPR’s role in detecting free radicals, transition metals, and environmentally persistent radicals - advancing soil health monitoring and sustainable management.<h4>Key Learning Points</h4><ul><li>Practical tips for sample preparation and instrument setup for IR and EPR spectroscopy</li><li>Strategies for building robust calibrations and ensuring transferability across Bruker IR spectrometers</li><li>Applications for determining carbon, clay content, pH, and more, all from a single spectrum</li><li>How EPR reveals free radicals, pollutant degradation pathways, and transition metal ions</li><li>Insights into environmentally persistent free radicals (EPFRs) and their role in soil health</li></ul><h4>Who should attend?</h4><ul><li>Environmental researchers studying contaminants, free radicals, and transition metals in soils</li><li>Laboratory professionals and technicians interested in high-throughput IR and EPR spectroscopy workflows</li><li>Soil scientists and agronomists seeking advanced tools for soil health assessment&nbsp;</li></ul><blockquote>Presenter: Dr. Kalina Ranguelova (Senior EPR Applications Scientist, Bruker BioSpin)Dr. Kalina Ranguelova has been an EPR Applications Scientist at Bruker BioSpin Corporation since 2011. She completed her Ph.D. at the Bulgarian Academy of Sciences, where her research focused on the structure of inorganic copper complexes using electron paramagnetic resonance (EPR) spectroscopy. After holding research positions at CUNY and the National Institute for Environmental Sciences, where she studied free radical biology and EPR spin trapping as a method for measuring reactive oxygen species (ROS), she joined Bruker. In her current role as an Applications Scientist, she focuses on developing new applications for EPR in various fields and providing customer support and training. Presenter: Dr. Sergey Shilov (Product Manager, &nbsp;Bruker Optics)Dr. Sergey V. Shilov is a Product Manager for North America at Bruker Optics. Sergey joined Bruker in 2001. He is responsible for the support and development of new applications for the Bruker research FTIR systems. He received his Ph.D. in 1992 from the Russian Academy of Sciences in Polymer Physics and his M.S. from St. Petersburg State University (Russia) in Physics in 1986. Alexander Von Humboldt Foundation (Germany) awarded him a research fellowship in 1996. Sergey published 37 papers in peer-reviewed journals. His research interests include time-resolved FTIR spectroscopy, surface science, polymer, and life-science applications.&nbsp;</blockquote></div>

Bruker: Accelerating Soil Health Assessment: High-Throughput Analysis with IR and EPR Spectroscopy

Accelerating Soil Health Assessment: High-Throughput Analysis with IR and EPR Spectroscopy

IR and EPR spectroscopy for fast soil health assessment, covering calibration strategies, free radical detection, metals analysis.

Soil Health analysis with IR and EPR Spectroscopy

<div>Learn about how Fourier-Transform Infrared (IR) and Electron Paramagnetic Resonance (EPR) spectroscopies enable in-depth understanding of polymer reactions. This webinar will review two main topics:<ul><li>The curing process of polymers and how FT-IR allows for real time monitoring of kinetics and degree of cure, with calibration protocols to measure conversion percentages.</li><li>The use of EPR spectroscopy to study radical mechanisms involved in polymerization, degradation, and stability of polymer materials.</li></ul><h4>Webinar Overview</h4>Polymers are an integral part of everyday life, from household goods to various fields of research and industrial applications. The ability to study the formation, degradation and stability of polymers is an important endeavor in the development of materials with better performance and longevity. Join us for this informative webinar on understanding the mechanisms and kinetics of various polymer processes via Fourier-Transform Infrared (FT-IR) and EPR Spectroscopy.The polymer curing process, from reaction kinetics to quantification of the process, is important to understand for new materials. FT-IR is highly suited for tracking the curing process due to its sensitivity to changes in functional groups We will showcase the ability of FT-IR in monitoring reaction kinetics and quantifying the degree of cure. Attendees will also gain technical insights into optimized workflows for R&amp;D and QA environments. &nbsp; Polymerization or degradation of polymer materials can often involve the formation of free radicals. The best suited method for unambiguous detection of free radicals in polymer processes is EPR Spectroscopy, which is a high-sensitivity, versatile and non-destructive technique. We will showcase the ease-of-use the Magnettech ESR5000 benchtop spectrometer and how users can incorporate workflows to identify radicals/impurities, track kinetics, and stress test polymer materials. &nbsp;&nbsp;<h4>What to Expect</h4>In this webinar, we will show how FT-IR and EPR methods provide valuable information during polymer formation and degradation processes. Learn how FT-IR can track reaction kinetics in real time and provide calibration procedures for the curing process. Dive into EPR as a robust, non-destructive technique for studying radical driven mechanisms in polymer materials under diverse conditions.<h4>Key Learning Points</h4>This webinar demonstrates how FT-IR and EPR are suitable for studying polymer reactions and kinetics under various conditions<ul><li>FT-IR workflows for kinetics of curing and quantifying degree of cure</li><li>Case studies using UV treated acrylates and calibration procedures for curing percentages</li><li>EPR for tracking free radical driven processes in polymer reactions, degradation and testing of polymers exposed to various stimuli</li></ul><h4>Who Should Attend?</h4><ul><li>Polymer chemists and researchers developing new materials</li><li>Industry professionals working with polymer materials looking to add screening tools to their workflows</li><li>Polymer scientists wanting to understand the radical mechanisms that drive processes such as polymerization or degradation</li></ul><blockquote>Presenter: Alvaro Montoya (Ph.D. in chemistry from the University of Florida, EPR Application Scientist, Bruker BioSpin)Alvaro Montoya began his EPR career as a Ph.D. student at the University of Florida after obtaining his B.S. in Chemistry from Susquehanna University. Early in his graduate career, he made use of CW and High Field EPR in studying the catalytic mechanisms of metalloenzymes. He then grew a profound appreciation for FT EPR and expanded his EPR toolbox for his research endeavors. After completing his Ph.D., Alvaro joined Bruker in January of 2023 working as an Applications Scientist.Presenter: Dr. Sergey Shilov (Product Manager, &nbsp;Bruker Optics)Dr. Sergey V. Shilov is a Product Manager for North America at Bruker Optics. Sergey joined Bruker in 2001. He is responsible for the support and development of new applications for the Bruker research FTIR systems. He received his Ph.D. in 1992 from the Russian Academy of Sciences in Polymer Physics and his M.S. from St. Petersburg State University (Russia) in Physics in 1986. Alexander Von Humboldt Foundation (Germany) awarded him a research fellowship in 1996. Sergey published 37 papers in peer-reviewed journals. His research interests include time-resolved FTIR spectroscopy, surface science, polymer, and life-science applications.&nbsp;</blockquote></div>

Bruker: Understanding Polymer Reactions and Degradation with FT-IR and EPR Spectroscopy

Understanding Polymer Reactions and Degradation with FT-IR and EPR Spectroscopy

Use FT-IR and EPR to study polymer curing, reaction kinetics, and radical mechanisms in polymerization and degradation.

ICPMS webinars focusing on NMR - page 1