<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 2nd March 2026? Check out new documents from the field of the gas phase, especially GC and GC/MS techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT GCMS AND RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><strong>LabRulezICPMS</strong></a> libraries.</p></blockquote><p>This week we bring you application notes by <strong>Agilent Technologies, BaySpec </strong>and<strong> Shimadzu </strong>and<strong> </strong>presentation by<strong> MDCW / JEOL!</strong></p><h3><strong>1. Agilent Technologies: Total Hydrocarbon Impurity Analysis in PEM Fuel Cell Grade Hydrogen Using the Agilent 8890 GC-FID System</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_hydrocarbon_impurity_analysis_pem_fuel_cell_8890_gcfid_5994_8935en_agilent_00a26949ef.pdf"><strong>Full PDF for download</strong></a></li></ul><p>High-purity hydrogen is crucial for the optimal and long-term performance of fuel cells.&nbsp;Different than the industry grade hydrogen used for chemicals, refining, and metal processing, where small amounts of impurities are acceptable. Fuel cell hydrogen is required to meet the species-specific impurity limits described in the specifications. Such impurities include hydrocarbons, sulfur-containing compounds, ammonia, permanent gases, halogens, and formaldehyde. Each group of compounds has its own regulation limit. The limits are defined based on their impact on the fuel cell lifetime and performance. ISO 14687 and SAE J2719 are the most recognized standards for regulation of fuel cell hydrogen quality.&nbsp;</p><p>Multiple testing points are implemented throughout the whole supply chain of fuel cell grade hydrogen—from its production, storage, and distribution to its final application. The analytical approaches employed depend on the impurity type and the corresponding limit. Among the varied contaminants, hydrocarbon impurity is controlled based on THC amount (excluding methane because it has a separate specific limit) and the quality limit as specified in ISO 14687 and SAE J2719 (2&nbsp;ppm).&nbsp;</p><p>There are two ways to analyze THCs in hydrogen. One is to separate and detect each hydrocarbon, then add their concentrations to get the THC amount (excluding methane). This analytical approach is recommended by the GB/T 44238-2024 test method.<sup>1</sup> The other way is by eluting all hydrocarbons as a single peak and quantitating the peak according to methane's response factor (RF). The total THC is then obtained by subtracting the methane amount, which is analyzed by a separate method.</p><p>In this application note, THC impurity was tested using the second approach. An Agilent 8890 GC with FID system were used for THC analysis, and the Agilent <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=990+Micro+GC"><strong>990 Micro GC</strong></a> was used for methane measurement. The methane analysis solution is published in application note 5994-8830EN.2 Here, we will showcase THC analysis using the 8890 GC-FID system.&nbsp;</p><h4><strong>Experimental&nbsp;</strong></h4><p>The <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890"><strong>8890 GC</strong></a> is configured with one gas sampling valve, a split/splitless (S/SL) inlet, and a flame ionization detector (FID), as shown in Figure 1. The fixed volume of gas sample is injected into the S/SL inlet and part of the sample flows into an uncoated capillary column, then elutes off as a single peak for detection. Table 1 lists experimental conditions for the analysis. The standard gases shown in Table 2 are used to verify system precision, generate methane's RF, and calculate method detection limit (MDL).</p><h4><strong>Conclusion&nbsp;</strong></h4><p>This application note demonstrates THC&nbsp;analysis in fuel cell hydrogen using the Agilent 8890 GC-FID system. The hydrocarbons eluted as a single peak on an uncoated column and were quantitated using methane's RF. The method repeatability and reproducibility were around 2%. Method accuracy was better than 120%. The MDL was 0.97&nbsp;ppm. All results met the analytical requirements of regulating THC in fuel cell grade hydrogen according to SAE&nbsp;J2719 and ISO 14687.&nbsp;</p><p>The applied analytical approach requires methane analysis by a separate method, which can be realized using the Agilent 990 Micro GC or using a coated column followed by FID detection on another channel of the 8890 GC system.</p><h3><strong>2. BaySpec: Rapid Detection of Trace Levels of Deoxynivalenol in Wheat Flour by Portable Miniature Linear Ion Trap Mass Spectrometry</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/Bay_Spec_App_Note_MS_Portability_In_Wheat_Quality_04959a96bd.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Deoxynivalenol (Cas:51481‐10‐8), also known as DON, is a trichothecene mycotoxin that is widely found in grains such as wheat, barley, and rice.&nbsp;&nbsp;The molecular structure of DON is provided in figure 1.&nbsp;&nbsp;DON is linked to two plant pathogens: Fusarium graminearum (wheat and corn), and Fusarium ear blight (corn only).&nbsp; &nbsp; DON inhibits the synthesis of DNA / RNA as well as protein synthesis at the ribosomal level, ultimately resulting in the loss of yield and contamination of seeds.&nbsp;&nbsp;An acute dose of DON can induce vomiting (emesis) in pigs, whereas at lower concentrations in the diet, it reduces growth and feed consumption (anorexia).<sup>1</sup>&nbsp;The U.S. FDA has established DON advisory levels to provide safe food and feed at concentrations of &lt; 10 ppm to &lt; 1 ppm depending on application.<sup>2</sup></p><p>Because DON is difficult to derivatize, this compound is typically analyzed via thin‐layer chromatography (TLC) or high performance liquid chromatography (HPLC).<sup>3</sup> While TLC is simple, fast, and economical, this analytical technique does not provide high accuracy nor consistent results on a day‐to‐day basis.&nbsp;&nbsp;HPLC improves on accuracy and consistency but requires large quantities of costly solvents and produces large volumes of hazardous waste.&nbsp;&nbsp; Depending on sampling requirements and system performance, the annual maintenance costs for a standard HPLC instrument can run ~$10‐20k per year.<sup>4</sup> &nbsp;&nbsp; Furthermore, although HPLC systems can be easy to use when properly configured, a trained professional is typically needed for troubleshooting, maintenance, and developing new methods.</p><p>Two samples were analyzed in a recent case study for an agricultural firm based in Canada.&nbsp;&nbsp;&nbsp;One sample contained 200 mg of wheat powder, while the other sample was 1 mg of the pure DON compound. Measurements were taken on a <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/2219"><strong>BaySpec Portability<sup>TM</sup> Mass Spectrometer</strong></a> (Figure 2) with both thermal desorption (TD) electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) methods. Samples were tested “dry” either by probing the surface of the sample vials or by spreading the powder onto a clean surface and swabbing. An enlarged image of the sampling probe with a small amount of wheat powder is shown in Figure 3.</p><h3><strong>3. MDCW / JEOL: Structural elucidation using GCxGC-TOFMS and machine learning for unknown metabolites in HeLa cell</strong></h3><ul><li>Presentation</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/O_7_Masaaki_Ubukata_2_56a67fdf00.pdf"><strong>Full PDF for download</strong></a></li></ul><p>The presentation by Masaaki Ubukata focuses on advancing structural elucidation of unknown metabolites in HeLa cells using comprehensive two-dimensional gas chromatography coupled with high-resolution time-of-flight mass spectrometry (<a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?instrumentationItems=2-13-3-5&amp;mainauthorItems=23"><strong>GC×GC-HRTOFMS</strong></a>) and machine learning. The work addresses a major limitation in metabolomics: while GC-MS offers highly reproducible EI fragmentation and strong library support, only a tiny fraction of known chemical space is represented in standard databases such as NIST (about 0.3% of compounds). To overcome this gap, the team developed an AI-based approach capable of predicting EI mass spectra and retention indices for over 200 million compounds, creating a large in-silico spectral library for unknown identification.</p><p>The workflow integrates accurate mass measurements from GC-HRTOFMS with both electron ionization (EI) and soft ionization data. Molecular formulas are first determined using isotopic patterns and fragment ion accuracy, then candidate structures are narrowed using predicted retention indices and compared against AI-predicted EI spectra ranked by cosine similarity. Model performance has steadily improved, reaching an average cosine similarity of 0.86, with correct structures ranked first in 56% of evaluation cases and within the top 10 in 87% of cases. This demonstrates strong capability for resolving unknown compounds beyond conventional library searches.</p><p>The approach was applied to HeLa cell metabolomics, a well-established human cell model. Using GC×GC separation, more than 800 metabolites were detected. Importantly, the system successfully identified N-methyl-uridine monophosphate (N-methyl UMP), a biologically relevant RNA-modification-related metabolite not registered in the NIST database. After molecular formula determination and AI ranking, N-methyl UMP was identified as the top candidate among 53 structural isomers sharing the same formula, demonstrating the practical strength of combining high-resolution MS, soft ionization, and AI-based spectral prediction.</p><p>In conclusion, the study highlights the synergistic power of three technologies: high-resolution GC-TOFMS, soft ionization techniques, and AI-driven structural analysis. Together, they significantly enhance the identification of unknown metabolites in non-targeted metabolomics and provide a scalable solution for exploring chemical space far beyond existing experimental spectral libraries.</p><h3><strong>4. Shimadzu: Analysis of Aroma Components in Apples Using the Smart Aroma Database</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_01_01016_en_e989b26b7f.pdf"><strong>Full PDF for download</strong></a></li></ul><h5><strong>User Benefits</strong></h5><ul><li>The Smart Aroma Database enables straightforward qualitative analysis of aroma components.</li><li>The HS-20 NX headspace sampler allows for high-sensitivity and convenient analysis of the aroma components in fresh apples.</li><li>Multivariate analysis facilitates an objective evaluation of aroma component differences between samples.</li></ul><p>The aroma components of fruits are one of the key factors that determine their flavor and taste, serving as a significant criterion for consumers when choosing fruits. These aroma components vary based on the type and variety of the fruit, its ripeness, production area, and cultivation environment. The complex interplay of these factors shapes the unique flavors of individual fruits. Therefore, the analysis of aroma components plays an important role in quality control and the development of new fruit varieties. The compounds that make up the aroma of fruits are diverse, including both volatile and non-volatile components, and their numbers can range from dozens to hundreds. These components, which include alcohols, esters, ketones, and acids, possess various chemical structures and contribute to the aroma of the fruit. Gas chromatography mass spectrometry (GC/MS) offers an effective method for objectively evaluating the relationship between aroma and aroma components. This article describes an example of analyzing the aroma components in apples using a <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GCMS-QP2050"><strong>GCMS-QP2050</strong></a> <strong>gas chromatograph mass spectrometer</strong> in combination with an<a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=HS20+NX"><strong> HS20 NX headspace sampler</strong></a> (Fig. 1).</p><h4><strong>Multivariate Analysis&nbsp;</strong></h4><p>Three types of apples, with five samples each (for a total of 15 samples), were measured once. The obtained data were analyzed using SIMCA17 multivariate data analysis software (Informatics Co., Ltd.) to perform principal component analysis (PCA) and hierarchical clustering analysis. The PCA score plot (Fig. 2), loading plot (Fig. 3), and the dendrogram from the hierarchical clustering analysis (Fig. 4) are shown.&nbsp;</p><p>Based on the PCA score plot, the contribution rate of the first principal component (horizontal axis) is 85.6 %, and the contribution rate of the second principal component (vertical axis) is 10.2 %, totaling 95.8 %. The clear separation of the plots by apple type indicates that there are differences in the aroma of the three varieties. Additionally, the results of the hierarchical clustering analysis show that Jonagold (A) and (B) have relatively similar compositions of aroma components.&nbsp;</p><p>Table 3 shows the aroma components that are relatively abundant in Jonagold (A) along with the sensory information for each aroma component registered in the Smart Aroma Database.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>We analyzed the aroma components of three types of commercially available apples using a GCMS-QP2050 gas chromatograph mass spectrometer. By utilizing an HS-20 NX headspace sampler, we were able to analyze the aroma components of fresh apples with high sensitivity, and the Smart Aroma Database made the process convenient.&nbsp;</p><p>We consider that scientifically analyzing the differences in aroma components based on factors such as fruit type, variety, ripeness, production area, and cultivation environment is beneficial for quality management and the development of new varieties.</p>

News from LabRulezGCMS Library - Week 10, 2026

News from LabRulezLCMS Library - Week 10, 2026

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezICPMS Library in the week of 2nd March 2026? Check out new documents from the field of spectroscopy/spectrometry and related techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT SPECTROSCOPY/SPECTROMETRY RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><strong>LabRulezGCMS</strong></a> libraries.</p></blockquote><p>This week we bring you application notes by <strong>Agilent Technologies</strong>, <strong>Metrohm,</strong> <strong>Shimadzu </strong>and<strong> Thermo Fisher Scientific!</strong></p><h3><strong>1. Agilent Technologies: Routine Analysis of Rare Earth Elements in Basalt using ICP-MS</strong></h3><p><strong>Accurate, precise, and stable results in a basalt sample matrix with the </strong><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=7850+ICP-MS"><strong>Agilent 7850 ICP-MS</strong></a><strong> in helium collision mode&nbsp;</strong></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_rare_earth_metals_7850_icp_ms_5994_8963en_agilent_07d5eb637c.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Rare Earth Elements (REEs) play a vital role in numerous industrial applications, including advanced materials, electronics, renewable energy technologies, and geochemical research<sup>.1</sup> Precise and routine quantification of REEs in geological matrices such as basalt is essential for understanding magmatic processes, resource assessment, and environmental monitoring. ICP-MS is suitable for the analysis of trace REEs in basalt. However, the sample poses significant analytical challenges due to its complex matrix, high concentrations of major elements, and the risk of polyatomic interferences such as oxides and hydroxides of barium (Ba) and REEs that can compromise accuracy.<sup>1–3 </sup>Because it contains high levels of alumina, silica, and refractory metals, basalt can also compromise plasma robustness due to matrix-induced signal suppression.</p><p>Various techniques have been used to measure REEs in geological samples, including multicollector (MC-) ICP-MS detection following α-hydroxyisobutyric acid (HIBA) separation.<sup>4</sup> Instrumental Neutron Activation Analysis (INAA) offers excellent sensitivity for many lanthanides (and long lived actinides like thorium and uranium) but is constrained by long irradiation times and the need to access nuclear reactors.<sup>5</sup> Thermal Ionization Mass Spectrometry (TIMS) provides highly precise isotopic measurements; however, it requires complex sample preparation and is unsuitable for routine multi-element analysis.<sup>6</sup> Laser Ablation ICP-MS (LA-ICP-MS) enables direct, spatially resolved measurements of geological samples but demands careful matrix matching of standards and is sensitive to variations in ablation behavior.<sup>7</sup> High-Resolution ICP-MS (HR-ICP-MS) improves spectral resolution, yet its high cost, lower throughput, and operational complexity limit its widespread use. While these techniques remain valuable for specialized applications, they often fall short when laboratories require rapid, routine, and interference-free determination of lanthanides and actinides in rock matrices.&nbsp;</p><p>ICP-MS has become the preferred technique for routine REE analysis due to its exceptional sensitivity, wide linear dynamic range, and multi-element capability. In this study, REE measurements were performed using an Agilent 7850 ICP-MS with an Agilent SPS 4 autosampler and controlled using Agilent ICP-MS MassHunter software. A preset method enabled the accurate and precise determination of 16 lanthanide and actinide elements in a single run, supporting high sample throughput. The 7850 includes Octopole Reaction System (ORS⁴) cell technology and optimized helium (He) collision mode to effectively remove polyatomic ion interferences using Kinetic Energy Discrimination (KED). Common interferences can be eliminated by the 7850 using default He KED tuning conditions, ensuring reliable analysis in complex matrices.<sup>8,9</sup> As polyatomic ions pass through the ORS⁴ cell with an optimized helium flow, their larger collisional cross sections cause them to lose more kinetic energy via frequent collisions. Upon exiting the cell, these lower energy polyatomic ions are filtered out by the KED barrier, while analyte ions retain enough energy to pass through the quadrupole for detection by the electron multiplier detector. This process enables accurate multi element analysis using a single gas mode.</p><h4><strong>Experimental&nbsp;</strong></h4><h5><strong>Instrumentation&nbsp;</strong></h5><p>The <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=7850+ICP-MS"><strong>Agilent 7850 ICP-MS</strong></a> equipped with the ORS4 cell and an Agilent SPS 4 autosampler was used for all the measurements of the basalt sample. (The same 7850 ICP-MS setup is also installed at Geochemistry and Geochronology facility of the Institute of Seismological Research, India.) Because ammonium fluoride (NH4 F) was used during sample preparation, the 7850 ICP-MS was fitted with the optional PFA kit and platinum sampling and skimmer cones. All 16 elements were measured using one set of He KED collision cell mode conditions. He KED ensures effective control of most background and matrix-based polyatomic interferences, such as ArO, ArCl, and BaO. The instrument was controlled using ICP-MS MassHunter software. Typical instrument operating parameters are listed in Table 1. The highlighted parameters were predefined by selecting the General Purpose preset method, while lens voltages were automatically tuned for optimal performance using the software’s autotune feature.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>The Agilent 7850 ICP-MS successfully quantified all 16 lanthanides and actinide elements in the basalt CRM using a single helium KED cell method. The use of a General Purpose preset method and automated lens tuning routine within the Agilent ICP-MS MassHunter software streamlined the analytical workflow, minimizing instrument setup time and ensuring consistent instrument performance. These ease of use features simplified instrument operation while maintaining accurate, interference free results. Internal standard stability over three hours of continuous operation demonstrated the robustness of the 7850 under routine, high throughput conditions. This level of instrument stability is important for maintaining productivity, as it reduces drift, QC failures, sample reanalysis, and instrument maintenance. The 7850 ICP-MS method supports laboratories conducting routine, high-throughput multi-element analyses of demanding geological matrices.</p><h3><strong>2. Metrohm: Flour analysis by near-infrared spectroscopy (NIRS)</strong></h3><p><strong>NIR flour analysis determines moisture, protein, ash, gluten, starch, and rheological properties within seconds</strong></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_nir_123_download_f35ec480b3.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Monitoring ash content, along with key quality parameters such as protein and moisture content, can significantly enhance the milling yield of flour. Next to these chemical parameters, rheological parameters like baking strength or tenacity influence the product quality. Near-infrared (NIR) spectroscopy enables chemical-free quality control of both chemical and rheological parameters, producing results within seconds. This simple, efficient, and rapid analysis method is ideal for continuous quality checks and can be implemented in laboratory settings or atline, requiring minimal training for effective use.</p><h4><strong>EXPERIMENTAL EQUIPMENT&nbsp;</strong></h4><p>A total of 237 flour samples, including wheat flour, spelt flour, and other types, were analyzed on a <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=220&amp;search=omnis+nir"><strong>Metrohm OMNIS NIR Analyzer Solid</strong></a> (Figure 1) with the large cup OMNIS NIR, 100 mm and OMNIS software. The samples were filled into the sample cup and analyzed in diffuse reflection mode. To include sample variety, the sample cup rotated during measurement to collect spectra from different locations. The automatically averaged spectra were used for model development. Reference values for moisture, protein, and ash content were obtained with the respective primary methods: moisture analysis followed AOAC 953.10, protein according to AOAC 2001.11, and ash content followed AOAC 923.03.</p><h4><strong>CONCLUSION</strong></h4><p>This Application Note shows the feasibility of using NIR spectroscopy for the analysis of several quality parameters in flour. With no chemicals involved, nearinfrared spectroscopy is an ideal way to avoid timeconsuming sample preparation and reduce costs. NIRS instruments from Metrohm allow users to not only to monitor the flour milling process, but also to predict the rheological properties of the dough the flour is produced with.</p><h3><strong>3. Shimadzu: Observation of Expansion/Contraction Process of Bubbles in PVA Gel</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_01_00855_en_d5da0bf713.pdf"><strong>Full PDF for download</strong></a></li></ul><h4><strong>User Benefits</strong></h4><ul><li>The <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=1&amp;search=HPV-X3"><strong>HPV-X3</strong></a>, with a maximum framerate of 20 Mfps, is suitable for observation of high-speed phenomena such as cavitation.</li><li>The HPV-X3 provides 3 times higher resolution than the conventional device, enabling detailed observation.</li><li>Since the image sensor of HPV-X3 is burst-type, the HPV-X3 enables image acquisition with constant resolution, regardless of the recording speed.</li></ul><p>When laser-induced shock waves and cavitation are applied in the medical field, it isimportant to understand the actual phenomena. Here, a polyvinyl alcohol (PVA) gel was irradiated with a laser, and the condition of the shock wave and cavitation generated upon laser light condensation (LC) was observed. PVA gel has high biocompatibility and is known as a promising biomaterial which is suitable for tissue mimicking. In this experiment, the newlydeveloped Hyper Vision HPV-X3 high-speed video camera was used to observe bubble expansion/contraction in PVA gel. In comparison with the conventional device, the recording speed (framerate) of the HPV-X3 is 2 times faster. The new HPV-X3 also provides 3 times higher resolution, supporting more detailed observation.</p><h4><strong>Comparison of HPV-X3 and HPV-X2</strong></h4><p>Fig. 2 shows images captured by the <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=1&amp;search=HPV-X3"><strong>HPV-X3</strong></a> and <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=1&amp;search=HPV-X2"><strong>HPV-X2</strong></a>. The images show the condition of the bubble and shock wave after laser irradiation captured at 500 kfps (HP mode of HPV-X2). As can be seen in Fig. 2 (a) and (b), assuming the same device composition, the HPV-X3 can capture a wider field due to its larger sensor size. In Fig. 2 (c), the image has been partially cropped from Fig. 2 (b) to show the same field of view as the HPV-X2. It can be understood that the information in the cropped image is also clearer due to the three-fold improvement of the resolution of the HPV-X3. Thus, when a wide field of view is captured in order to check the phenomena and the image is then cropped to show only the phenomenon of interest, the HPV-X3 is the more suitable device thanks to its excellent resolution.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>Hyper Vision and HPV are trademarks of Shimadzu Corporation or its affiliated companies in Japan and/or other countries. Using the new HPV-X3 high-speed video camera, the expansion/contraction of a bubble and shock wave when a laser was irradiated on PVA gel were observed. Because the resolution of the HPV-X3 is 3 times higher than that of the conventional device, resolution is adequate, and it is possible to obtain clear and distinct images, even when a wide angle of view is observed and the image is partially cropped. The HPV-X3 also has a maximum recording speed of 20 Mfps, which enabled detailed observation of the shock wave and the process of bubble collapse.</p><h3><strong>4. Thermo Fisher Scientific: Analysis of rare earth elements in clay using XRF and XRD</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/analysis_of_rare_earth_elements_an41526_en_df78e144e1.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Rare earth elements (REEs) are 17 elements used in dozens of high-tech applications. The global demand for REEs has surged in recent years, driven by advancements in technology and the transition towards green energy solutions. REE magnets are compact, efficient, and hard to replace. Electric vehicles (EVs) and wind power are the main growth industries for these use cases.&nbsp;</p><p>Although rare earth elements are relatively abundant in the earth’s crust, they are rarely concentrated into mineable ore deposits. REEs are associated with alkaline rocks, carbonatite (bastnäsite, monazite, parisite, and synchysite), pegmatite, and placer deposits (residual deposits formed from deep weathering) and are often discovered via geochemical exploration. They may also be absorbed in clay minerals or ion adsorption clays (IACs) such as kaolinite, illite and smectite. The ores of rare earth elements are mineralogically and chemically complex and commonly radioactive. REE mining is challenging because REEs are concentrated in more than one mineral, and each mineral requires a different costly extraction technology and mineral processing.&nbsp;</p><p>For companies operating in REE exploration and mining, the accuracy of geochemical analysis is critical to assess the viability of deposits, respectively targeting REE rich areas for extraction. The Thermo Scientific™ ARL™ X’TRA Companion X-ray Diffractometer detects and quantifies mineral phases that contain REEs such as kaolinite, smectite, monazite and bastnasite. Thermo Scientific™ ARL™ PERFORM’X WDXRF Spectrometer on the other hand provides fast, accurate major/minor oxides analysis on the REE ores.</p><h4><strong>Instrument and software&nbsp;</strong></h4><p>The <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/products/2296"><strong>ARL X’TRA Companion X-Ray Diffractometer</strong></a> (Figure 1) is a simple, easy-to-use benchtop instrument for routine phase analysis as well as more advanced applications. The ARL X’TRA Companion XRD uses a θ/θ goniometer (160 mm radius) in Bragg-Brentano geometry coupled with a 600 W X-ray source (Cu or Co). The radial and axial collimation of the beam is controlled by divergence and Soller slits, while air scattering is reduced by a variable beam knife. An integrated water chiller is available as an option. Thanks to the state-of-the art solid state pixel detector (55x55 μm pitch), the ARL X’TRA Companion XRD provides very fast data collection and comes with single-click Rietveld quantification capabilities and automated result transmission to a LIMS (Laboratory Information Management System). Both capabilities are seamlessly integrated into <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/products/2297"><strong>Thermo Scientific™ SolstiX™ Pronto Instrument Control Software</strong></a>.&nbsp;</p><p>The <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/products/1211"><strong>ARL PERFORM’X series spectrometer</strong></a> (Figure 2) used in this analysis was a 2500-watt system. This system is configured with 6 primary beam filters, 4 collimators, up to nine crystals, two detectors and our 5GN+ Rh X-ray tube for best performance from ultra- light to heaviest elements thanks to its 50 microns Be window. This innovative, ultralight X-ray tube fitted with a low current filament ensures an unequalled analytical stability month after month. When paired with industry-leading Thermo Scientific™ UniQuant™ Software the ARL PERFORM’X spectrometer provides the best limits of detection and accuracy in standardless analysis up to element Am.</p><h4><strong>Your benefits&nbsp;</strong></h4><p>The ARL X’TRA Companion XRD workflow delivers answers in a few minutes, quantifying the mineral phases available in the ion adsorption clay samples. Users are able to identify the type of mineral phases associated with REEs such as kaolinite, halloysite, smectite, illite. They are also able to verify the ion adsorption clay (IAC) mechanism due to absence of monazite/ xenotime peaks &amp; availability of kaolinite &amp; smectite which supports ion-adsorbed REE.&nbsp;</p><p>ARL PERFORM’X WDXRF spectrometer together with UniQuant standardless analysis software enables the users to screen through REE ores for up to 79 elements without the need for conventional calibrations. Well suited for mining ore analysis which will have varying sample matrices. UniQuant software is fully calibrated and installed from the factory. Hence the ARL PERFORM’X spectrometer is ready to perform meaningful analysis of unknown samples directly after installation at the customer’s site.</p>

News from LabRulezICPMS Library - Week 10, 2026

<p><strong>This study reports the development of a sustainable heterogeneous catalyst derived from a composite of potassium hydroxide, eggshell powder, and coffee husk char for biodiesel production from waste frying oil. Calcination at 700 °C enabled the formation of active CaO and K₂O phases while significantly lowering the temperature typically required for eggshell-based catalysts.</strong></p><p>The optimized catalyst achieved biodiesel yields up to 97.5% after process optimization. Although catalytic activity gradually decreased over multiple reuse cycles, the approach demonstrates a promising strategy for converting agricultural and food waste into valuable biofuels while reducing production costs and environmental impact.</p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c10478"><strong>KOH-Promoted Catalyst Derived from Coffee Husk and Eggshell Composite for Biodiesel Production from Waste Frying Oil</strong></a></h4><p>Seid Mohammed Seid, Girma Gonfa, Sintayehu Mekuria Hailegiorgis, and Demelash Tilahun Bekele*</p><p>ACS Omega 2025, 10, 51, 63501–63514</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acsomega.5c10478">https://doi.org/10.1021/acsomega.5c10478</a></p><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6></blockquote><p><strong>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.</strong></p><div><p>Energy has always been and remains fundamental to human history, driving economic advancement and representing national strength in the modern era. <a href="javascript:void(0);">(1)</a> Therefore, ensuring energy access and promoting sustainable energy are key priorities in alignment with the United Nations’ Sustainable Development Goals. <a href="javascript:void(0);">(2)</a> Achieving this goal requires replacing petroleum fuels with renewable and eco-friendly alternatives like biodiesel. <a href="javascript:void(0);">(3)</a> Biodiesel is a mixture of fatty acid monoalkyl esters with varying carbon chain lengths and degrees of unsaturation. <a href="javascript:void(0);">(4)</a> Its benefits include low sulfur, a high flashpoint, efficient combustion, and biodegradability. <a href="javascript:void(0);">(5)</a> Biodiesel can be produced from domestic feedstock and mitigates greenhouse gas emissions. <a href="javascript:void(0);">(6)</a> Despite its disadvantages, such as a lower energy density than fossil fuels and the emission of nitrogen oxides during combustion, <a href="javascript:void(0);">(7)</a> the main obstacle to biodiesel’s large-scale use is its higher production cost compared to fossil diesel. <a href="javascript:void(0);">(8)</a></p><p>The economic viability of biodiesel production is significantly impacted by feedstock costs, which currently account for over 70% of the total expenditure. <a href="javascript:void(0);">(9)</a> While transesterification remains the prevalent method for converting these feedstocks, <a href="javascript:void(0);">(4)</a> the dominant industrial practice (exceeding 95%) relies on edible oils such as soybean, rapeseed, sunflower, and palm. <a href="javascript:void(0);">(10)</a> However, the utilization of these resources raises concerns regarding food security and economic feasibility, rendering this approach increasingly unsustainable. Consequently, contemporary research efforts are predominantly directed toward exploring nonedible alternatives, including nonedible vegetable oils, animal fats, and algal oils, <a href="javascript:void(0);">(11)</a> with waste frying oil (WFO) presenting a particularly advantageous option due to its low cost and status as a waste stream, thereby mitigating both feedstock expenses and environmental disposal issues. <a href="javascript:void(0);">(12)</a></p><p>While addressing the challenge of feedstock is a major step, the transformation of these nonedible oils into biodiesel faces another significant obstacle, namely the need for efficient and cost-effective catalysts. <a href="javascript:void(0);">(4)</a> A variety of catalysts were investigated for the synthesis of biodiesel, including alkali, acid, bifunctional, and enzyme catalysts. <a href="javascript:void(0);">(13)</a> The catalysts may be generally classified as homogeneous and heterogeneous catalysts. <a href="javascript:void(0);">(14)</a> The employment of homogeneous catalysts in biodiesel manufacture elevates costs due to the need for extensive product purification to meet quality standards. Furthermore, these catalysts are corrosive to reactors and cannot be recovered for reuse. <a href="javascript:void(0);">(15)</a> While researchers have also explored enzymes for biodiesel synthesis due to their efficiency and nonpolluting nature, enzymatic catalysts have been found to be inhibited by alcohol, costly, and require extended transesterification times for maximum conversion. <a href="javascript:void(0);">(16)</a> Consequently, current research increasingly focuses on heterogeneous catalysts, as they offer the advantages of high reusability and simple separation from the final reaction mixture. <a href="javascript:void(0);">(17)</a> These properties of heterogeneous catalysts contribute to lowering biodiesel production costs.</p><p>Despite the advantages of reusability and easy separation offered by heterogeneous catalysts, issues such as high cost, low stability, low activity, small pore size, and limited surface area still persist. <a href="javascript:void(0);">(17)</a> Therefore, much of the current research on heterogeneous catalyst synthesis for biodiesel production aims to address one or more of these limitations, with solutions including the selection of suitable catalyst precursors. <a href="javascript:void(0);">(18,19)</a> These precursors can include biomasses, chemicals, or a combination thereof. <a href="javascript:void(0);">(4,20)</a> While chemical precursors can yield highly active catalysts, their synthesis processes are often costly and environmentally hostile. <a href="javascript:void(0);">(21)</a> Consequently, the utilization of biomasses has become a prevalent approach in numerous catalyst synthesis investigations, <a href="javascript:void(0);">(22)</a> encompassing lignocellulosic biomasses (LBs), animal bones, teeth, and shales, and eggshells. <a href="javascript:void(0);">(4)</a> Due to their renewable origin and ability to reduce net CO<sub>2</sub> emissions in catalyst synthesis, LBs are becoming more popular as precursors. <a href="javascript:void(0);">(23)</a> Furthermore, utilizing LBs can also reduce the overall cost of the resulting catalyst. <a href="javascript:void(0);">(21)</a></p><p>Given the significantly higher reaction rates they exhibit compared to acidic and bifunctional catalysts, alkali catalysts have garnered considerable attention for transesterification reactions. <a href="javascript:void(0);">(24)</a> Researchers have successfully developed highly active alkali catalysts from various LB sources, including the ashes of passion fruit peel, <a href="javascript:void(0);">(25)</a> palm bunch, <a href="javascript:void(0);">(26)</a> <i>Musa paradisiaca</i> plant parts, <a href="javascript:void(0);">(27)</a> walnut shell, <a href="javascript:void(0);">(21)</a> orange peel, <a href="javascript:void(0);">(28)</a> and acai seed. <a href="javascript:void(0);">(29)</a> These ash catalysts, often rich in compounds like K<sub>2</sub>CO<sub>3</sub>, K<sub>2</sub>Ca(CO<sub>3</sub>), CaCO<sub>3</sub>, and KCl, can be obtained through LB calcination processes. <a href="javascript:void(0);">(30)</a> A crucial factor in this process is that the decomposition temperature of these compounds in a mixture differs from their individual values. For example, CaCO<sub>3</sub> decomposes at a lower temperature when mixed with K<sub>2</sub>CO<sub>3</sub>, <a href="javascript:void(0);">(31)</a> and the decomposition temperature of K<sub>2</sub>CO<sub>3</sub> into K<sub>2</sub>O is also lowered in the presence of carbon (a product of LB decomposition). <a href="javascript:void(0);">(32)</a><sub>.</sub> By leveraging this phenomenon, highly active metal oxide-containing catalysts can be produced more efficiently and economically. <a href="javascript:void(0);">(33)</a></p><p>Although LB ashes are appropriate for this purpose due to their mixed compound content, their low ash (catalyst) yield compared to CaCO<sub>3</sub> rich biomasses like eggshells presents a challenge. <a href="javascript:void(0);">(34,35)</a> For example, the ash content of pineapple leaves was 6 and 2.6% for cupuacu seeds. <a href="javascript:void(0);">(36)</a> This is very small compared to the ash content (45.29%) of biomasses such as eggshells. <a href="javascript:void(0);">(41)</a> Thus, blending alkali-rich (primarily K) LB ash with CaCO<sub>3</sub>-rich biomasses ash presents a promising route to enhance catalyst yield. Achieving active CaO from bare eggshells requires high calcination temperatures (800–1000 °C), but a blending approach can produce active mixed oxides at more moderate temperatures. <a href="javascript:void(0);">(31,37,38)</a> This is a notable advantage, as mixed oxides often demonstrate enhanced catalytic performance compared to single-oxide catalysts. <a href="javascript:void(0);">(39)</a> Additionally, a synergy between Ca and K has been reported to enhance feedstock transesterification. <a href="javascript:void(0);">(40)</a> The activity of ash catalysts derived from this blended biomass can also be further enhanced through chemical modification. <a href="javascript:void(0);">(41)</a> Ultimately, by combining the complementary properties of K-rich LB and eggshell biomasses with chemical modification, we can potentially develop highly efficient and sustainable catalysts for biodiesel manufacturing.</p><p>The abundance of coffee husk in Ethiopia, along with the high concentration of K compounds in its ash, presents a promising opportunity for developing an alkali catalyst. <a href="javascript:void(0);">(41)</a> This research specifically focused on developing a novel, highly active heterogeneous alkali catalyst by creating a composite from coffee husk and eggshell, and then promoting it with KOH. The primary aim was to assess the overall effectiveness of this novel catalyst as a sustainable solution for producing biodiesel from readily available WFO.</p><h4><strong>Materials and Methods</strong></h4><h5><strong>Catalyst Materials and Catalysts Characterization</strong></h5><p>To guide the selection of CCMC calcination temperatures, thermal analysis (thermogravimetric analysis (TGA) and differential thermal analysis (DTA)) was carried out with a <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=1&amp;search=DTG+60"><strong>Shimadzu DTG 60H</strong></a> (Japan). This analysis was conducted under a limited air environment (50 mL/min), with the temperature ramped at 10 °C/min from 25 to 1000 °C. The crystalline phases within the catalysts were identified via X-ray diffraction (XRD) using a <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=1&amp;search=XRD-7000"><strong>Shimadzu XRD-7000</strong></a> (Japan) instrument. The analysis was conducted with Cu Kα radiation (λ = 0.15406 nm) at 30 mA and 40 kV. Diffraction patterns were recorded within a 2θ value of 10° to 80° with a scan speed of 3°/min and a step size of 0.02°. Crystalline phases were identified by comparing observed peak 2θ values with literature data. The specific surface area of the catalysts was determined via the Brunauer–Emmet–Teller (BET) method using a surface area analyzer (Horiba Instruments, Inc. SA-9600 series, USA). Prior to the surface area examination, catalyst samples were dried at 110 °C overnight after being ground with a mortar and pestle. Furthermore, degassing of the catalysts was made at 150 °C for 3 h using the analyzer’s degassing procedure. Measurements for nitrogen adsorption isotherms were performed at a temperature of 77 K. Using data points at relative pressures of 0.1, 0.2, and 0.3 from the linear portion of the isotherm, the BET surface area was calculated. <a href="javascript:void(0);">(41)</a> Using a scanning electron microscope (SEM) (JCM-6000Plus, German) with an accelerating voltage of 20 kV, the surface morphology of the catalysts was visualized. A Fourier transform infrared spectrometer (FTIR) (<strong>Thermo Scientific Nicolet, IiS50 ABX smartiTX</strong>) was used to identify functional groups within the catalysts and intermediate products. The instrument, which featured an attenuated total reflectance (ATR) diamond crystal and a DTGS KBr detector, collected spectra from 400 to 4000 cm<sup>–1</sup> at a resolution of 2 cm<sup>–1</sup> and with 32 scans. In line with the procedure described by Al-Hamamre et al., <a href="javascript:void(0);">(43)</a> the catalysts total basicity of the was measured via the Hammett indicator method with phenolphthalein. A suspension of 0.15 g of catalyst in 2 mL of a 0.1 mg/mL phenolphthalein/toluene solution was prepared and stirred for 30 min. The resulting mixture was then titrated using a 0.01 M solution of benzoic acid in toluene until the color turned from pink to colorless, indicating the end point.</p><h4><strong>Results and Discussion</strong></h4><h5><strong>Qualitative Analysis of the Biodiesel Using FTIR</strong></h5><p><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c10478#fig8">Figure 8</a> presents the FTIR spectra of WFO and WFO biodiesel (BD) produced using the C-Optimal catalyst assisted transesterifiction. The presence of strong characteristic peaks observed within the 2922–2853 cm<sup>–1</sup> range are attributed to the C–H stretching of the methyl group. The BD showed a CH<sub>3</sub> asymmetric bending peak at 1433 cm<sup>–1</sup>, indicating the presence of (CO)–O–CH<sub>3</sub>. Additionally, a peak between 1180 and 1220 cm<sup>–1</sup> was observed, attributed to −O–CH<sub>3</sub> stretching within the biodiesel’s structure. Notably, both of these peaks were absent in the WFO FTIR spectrum, highlighting their formation during the transesterification process. The presence of −C–O ester groups is further supported by a peak at 1169 cm<sup>–1</sup>. The peak at 721 cm<sup>–1</sup> for both spectra corresponds to the rocking of the CH<sub>2</sub> group. These findings are consistent with previous studies on biodiesel production from waste cooking oil (WFO) using KNO<sub>3</sub>-loaded CH ash catalyst <a href="javascript:void(0);">(41)</a> and from Argemone seed oil using CaO catalysts. <a href="javascript:void(0);">(63)</a></p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2025_10_51_63501_63514_Figure_8_FTIR_of_biodiesel_and_the_WFO_cbfb97ad33.jpeg" alt="ACS Omega 2025, 10, 51, 63501–63514: Figure 8. FTIR of biodiesel and the WFO." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2025_10_51_63501_63514_Figure_8_FTIR_of_biodiesel_and_the_WFO_cbfb97ad33.jpeg 175w," sizes="100vw" width="894" height="796"></p><h5><strong>Biodiesel Analysis Using GC-MS</strong></h5><p>The GC–MS analysis performed on the biodiesel sample provided a detailed relative composition of its 14 identified fatty acid methyl ester (FAME) constituents (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c10478#tbl7">Table 7</a> and <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c10478#fig9">Figure 9</a>). This was achieved through the normalization of chromatographic peak areas, where the area of each identified FAME peak was calculated as a percentage of the total area of all detected FAME peaks. It is crucial to highlight that, due to the methodological limitations of the GC–MS system (specifically the oven’s maximum programmed temperature of 240 °C and the MS scan range limited to 550 <i>m/z</i>), this analysis does not include unconverted components such as triglycerides, diglycerides, and the full spectrum of monoglycerides. Consequently, the calculated total FAME content of 100.0% represents the sum of the identified FAMEs relative only to each other, and not the overall purity of the biodiesel in terms of residual acylglycerols or other impurities.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2025_10_51_63501_63514_Table_7_Fatty_Acid_Methyl_Ester_FAME_Composition_of_the_Biodiesel_Sample_8cf079d910.jpg" alt="ACS Omega 2025, 10, 51, 63501–63514: Table 7. Fatty Acid Methyl Ester (FAME) Composition of the Biodiesel Sample" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2025_10_51_63501_63514_Table_7_Fatty_Acid_Methyl_Ester_FAME_Composition_of_the_Biodiesel_Sample_8cf079d910.jpg 201w," sizes="100vw" width="1054" height="817"></p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2025_10_51_63501_63514_Figure_9_GC_MS_chromatograph_of_WFO_biodiesel_a0d26312d3.jpeg" alt="ACS Omega 2025, 10, 51, 63501–63514: Figure 9. GC–MS chromatograph of WFO biodiesel." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2025_10_51_63501_63514_Figure_9_GC_MS_chromatograph_of_WFO_biodiesel_a0d26312d3.jpeg 245w," sizes="100vw" width="1417" height="714"></p><p>Focusing on the main components, the biodiesel sample is primarily characterized by 13-Octadecenoic acid, methyl ester (C18:1 isomers), comprising 48.49% of the total FAMEs, and Hexadecanoic acid, methyl ester (C16:0), at 38.41%. Methyl stearate (C18:0) further contributes 7.57% to this composition. This dominant profile, rich in both monounsaturated and saturated FAMEs, suggests a beneficial balance of fuel properties. The high proportion of C18:1 typically aids in achieving desirable cold flow characteristics, while the substantial presence of C16:0 and C18:0 enhances the biodiesel’s oxidative stability, which is vital for fuel storage and long-term performance. The minor presence of polyunsaturated FAMEs (e.g., C18:2 isomers at combined approximately 0.70% and C18:3 at 0.22%) further contributes positively to the oxidative stability profile.</p><h4><strong>Conclusions</strong></h4><p>This study successfully developed and characterized a highly active heterogeneous alkali catalyst derived from KOH-promoted coffee husk and eggshell composites for biodiesel production from waste frying oil. The comprehensive characterization elucidated the optimal catalyst synthesis conditions. It was found that a calcination temperature of 700 °C effectively promotes the formation of key active phases like CaO and K<sub>2</sub>O, while also enhancing the catalyst’s basicity, which is crucial for catalytic activity. The research achieved an optimum biodiesel yield of 97.5 ± 0.52%. However, the catalyst’s reusability was significantly limited, with biodiesel yield dropping from 71 to 52% by the second round. This necessitates further research into more robust catalyst designs or efficient regeneration for practical application. The research underscores the synergistic effect of K and Ca components from the coffee husk and eggshell, further boosted by KOH promotion, offering a promising solution for converting low-cost waste frying oil into biodiesel through a single-step transesterification process.</p></div>

KOH-Promoted Catalyst Derived from Coffee Husk and Eggshell Composite for Biodiesel Production from Waste Frying Oil

<p><strong>This study investigates the relationship between fruit development and seed quality in the “Hua Rue” hot chili cultivar. Seeds harvested at 35, 45, and 50 days after flowering were evaluated for physical traits, germination performance, tissue-specific chemical composition using FTIR microspectroscopy, and biochemical activity during imbibition.</strong></p><p>Seeds collected at 50 days after flowering showed the highest weight, germination rate, and germination speed, accompanied by increased endosperm-associated chemical accumulation and enhanced metabolic activity. FTIR analysis clearly distinguished developmental stages based on tissue-specific chemical signatures, identifying 50 DAF as the optimal harvest stage for producing high-quality chili seeds with stable storage viability.</p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c05947"><strong>Chemical Composition and Biochemical Changes during Fruit Development on Seed Quality in Hot Chili (Capsicum annuum L.)</strong></a></h4><p>Wissanee Pola*, Songsin Photchanachai, and Papungkorn Sangsawad</p><p>ACS Omega 2026, 11, 1, 562–571</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acsomega.5c05947">https://doi.org/10.1021/acsomega.5c05947</a></p><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6></blockquote><p><strong>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.</strong></p><div><p>Hot chili (<i>Capsicum annuum</i> L.), specifically the “Hua Rue” cultivar, is popular in the northeast region of Thailand due to its distinctive pungency and high yield. <a href="javascript:void(0);">(1)</a> Thailand ranks among the top five chili producers in Asia and is a leading exporter worldwide, with an export volume of approximately 60,000 kg and a value of 805 million baht. It is evident that chili seeds play a significant role in the country’s agricultural economy. <a href="javascript:void(0);">(2)</a> Seed production is a critical process that ensures the availability of high-quality seeds for sustainable crop production. Generally, in the large-scale production of this chili cultivar, mature fruits are harvested manually at the fully red-ripe stage, and the seeds are extracted from sun-dried fruits. However, the seed quality tends to decline rapidly during storage, particularly after six months. <a href="javascript:void(0);">(2)</a></p><p>Typically, harvesting chili fruits at the onset of ripening is necessary for producing high-quality seeds. <a href="javascript:void(0);">(3)</a> Seeds achieve physiological maturity (PM) when they attain maximum dry weight and vigor, which vary with the variety. <a href="javascript:void(0);">(4)</a> In <i>Capsicum</i> species, high seed quality was achieved in fruits harvested at 50–60 days after flowering (DAF). <a href="javascript:void(0);">(5)</a> Research on sweet pepper and hot chili varieties suggested that seeds extracted at 60 DAF provided the highest germination and vigor. <a href="javascript:void(0);">(6)</a> Furthermore, enzymatic hydrolysis of storage macromolecules, particularly starch breakdown by α-amylase, is crucial for seed germination. <a href="javascript:void(0);">(7)</a> This enzyme hydrolyzes starch in the cotyledon and endosperm into simple sugar units that are then synthesized into sucrose for transport to the embryonic axis. <a href="javascript:void(0);">(8)</a></p><p>Fourier transform infrared microspectroscopy (FTIR) is a technique used to obtain an infrared spectrum of absorption or emission of solids, liquids, and gases. <a href="javascript:void(0);">(9)</a> An FTIR spectrometer collects high-resolution spectral data over a wide spectral range simultaneously, providing a significant advantage over a dispersive spectrometer, which measures the intensity over a narrow range of wavelengths at a time. This instrument is effective for identifying biochemical compositions in living cells and tissues. <a href="javascript:void(0);">(10)</a> FTIR spectra typically reveal absorption bands corresponding to lipids (3000–2800 cm<sup>–1</sup>), proteins (1700–1480 cm<sup>–1</sup>), carbohydrates, and nucleic acids (1450–600 cm<sup>–1</sup>). <a href="javascript:void(0);">(11)</a> The measurement of chemical compositions in chili seeds using FTIR, particularly concerning the physiological maturity (PM) stage of the “Hua Rue” variety, has not been documented in recent years. The measurement of chemical compositions in chili seeds using FTIR, particularly in relation to the physiological maturity (PM) stage of the “Hua Rue” variety, has not been reported in recent years. Previous studies have mainly evaluated seed quality based on whole-seed analyses and standard germination tests. In contrast, this study provides the first detailed characterization of chemical composition profiles of individual seed organs in the “Hua Rue” variety. For this purpose, fruits were harvested at different developmental stages to investigate biochemical changes during ripening. Although the general postharvest handling and storage methods used in this study (manual extraction, shade drying, and sealed storage) slightly differ from the traditional practices employed by local seed producers, they were designed to ensure consistent sample quality for analysis. Therefore, this study aims to investigate the biochemical and chemical composition profiles of seed organs (embryonic axis, endosperm, and seed coat) as extracted from “Hua Rue” chili at various fruit developmental stages and to explore their potential relationship with seed vigor and storability.</p><h4><strong>2. Materials and Methods</strong></h4><h5><strong>2.3. Fourier-Transform Infrared (FTIR) Microspectroscopy of Seed Tissues</strong></h5><p>Seeds were collected from chili pods at three fruit developmental stages: 35, 45, and 50 DAF. Immediately after extraction, ten seeds per stage were embedded in optimal cutting temperature (OCT) compound (Tissue-Tek O.C.T. Compound, USA) and snap-frozen to preserve biochemical integrity. The embedded seeds were sectioned at −20 °C into cross sections of 8 ± 1 μm using a Leica CM1950 microtome cryostat (Cambridge Scientific). Sections were mounted on calcium fluoride (CaF<sub>2</sub>) infrared-transparent windows to facilitate FTIR analysis. Chemical imaging was performed using a <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=10&amp;search=HYPERION"><strong>HYPERION 3000 FTIR microscope </strong></a>(Bruker Optik GmbH) equipped with a focal plane array (FPA) detector, operating in the spectral range of 4000–600 cm<sup>–1</sup>, with 64 scans per spectrum. Spectral acquisition and preliminary processing were carried out by using <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?manufacturerItems=10&amp;search=OPUS+software"><strong>OPUS 7.5 software</strong></a> (Bruker Optics, Ettlingen, Germany). The spectra were subsequently exported to Unscrambler X 10.5 for multivariate analysis, including the Savitzky–Golay second-derivative transformation, extended multiplicative signal correction (EMSC) normalization, and principal component analysis (PCA). The FTIR microspectroscopy was used to observe spectral pattern differences among tissues and maturation stages. Anatomical regions analyzed included the seed coat, endosperm, and embryonic axis.</p><h4><strong>3. Results and Discussion</strong></h4><h5><strong>3.1. Effect of Fruit Development on Seed Anatomy and 1000-Seed Weight</strong></h5><p>Visual observations of the ″Hua Rue” chili fruits showed mature green, breaker, and mature red colors at 35, 45, and 50 DAF, respectively (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c05947#fig1">Figure 1</a>A). This closely aligns with the ripening stages of the red pepper “Zunla-1” cultivar, as reported by Song et al. <a href="javascript:void(0);">(17)</a> where the ripening stages were divided into mature green (30 DAF), breaker (35 DAF), first immature red (38 DAF), second immature red (43 DAF), and mature red (MR, approximately 50 DAF).</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2026_11_1_562_571_Figure_1_Appearance_of_Hua_Rue_chili_fruits_and_the_interior_seed_structure_including_seed_coat_endosperm_and_embryonic_axis_cd5e87f491.jpeg" alt="ACS Omega 2026, 11, 1, 562–571: Figure 1. Appearance of “Hua Rue” chili fruits and the interior seed structure, including seed coat, endosperm, and embryonic axis (A), and the 1000-seed weight (B) as extracted from the harvested fruits at 35, 45, and 50 days after flowering (DAF). Values are means ± SD (n = 4). Different letters (a, b) denote significant differences among treatments according to Tukey’s HSD Test (P &lt; 0.05)." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2026_11_1_562_571_Figure_1_Appearance_of_Hua_Rue_chili_fruits_and_the_interior_seed_structure_including_seed_coat_endosperm_and_embryonic_axis_cd5e87f491.jpeg 245w," sizes="100vw" width="1000" height="518"></p><p>After the seeds were extracted from each fruit development stage, the interior structure of the seeds, including the endosperm and embryonic axis (cotyledons and radicle), was found to be fully developed at 45 and 50 DAF. In contrast, seeds from 35 DAF exhibited shorter cotyledons, indicating incomplete development (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c05947#fig1">Figure 1</a>A). This interior structure of chili seeds can determine seed physical integrity and predict seedling emergence. A previous study on bell pepper found that the structural integrity of seeds, as assessed by X-ray analysis, was linked to germination performance. It was discovered that a decrease in the internal area occupied by the embryo and endosperm was directly related to the incidence of abnormal seedlings and nongerminated seeds. <a href="javascript:void(0);">(18)</a> Nevertheless, the most crucial structure of the seed is the embryonic axis, which develops into the seedling. Therefore, a fully developed embryonic axis is essential for seed production.</p><p>Generally, harvesting seeds at the physiological maturity (PM) stage, which indicates the highest seed vigor and viability, is essential for cultivation. The major indicators of the PM stage are maximum seed dry weight, high seed vigor, and germination percentage. <a href="javascript:void(0);">(6)</a> In this study, the 1000-seed weight of “Hua Rue” chili ranged from 3563 to 4983 mg (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c05947#fig1">Figure 1</a>B). A significant difference in seed weight was observed between the fruit developmental stages. The lowest value was found in seeds extracted from fruit harvested at 35 DAF. Meanwhile, seeds obtained from fruit harvested at 45 and 50 DAF showed a gradual increase in weight. This indicates that early harvested chili fruit, whose seeds have reached the PM stage, should be at 45–50 DAF. Similarly, Yisa et al. <a href="javascript:void(0);">(19)</a> studied the influence of fruits at different stages (12–48 DAF) on seed quality. Their results revealed a continual increase in dry seed weight throughout the maturation process, particularly in seeds extracted from fruits harvested at 48 DAF. Similarly, Pagamas and Nawata <a href="javascript:void(0);">(20)</a> reported increasing dry seed weight in chili pepper cultivars “Huay Si Thon” and “Shishito” from 35 to 45 DAF that remained until 60 DAF. Hence, they recommended that the optimal harvest maturity period for “Huay Si Thon” and “Shishito” was at 45 DAF and 55 DAF, respectively. This suggests that harvesting during this period could yield good seed quality based on seed weight parameters, which may indicate the accumulation of nutrients in the seeds.</p><h5><strong>3.2. Effect of Fruit Development on Chemical Composition Profiles of Seeds Analyzed by FTIR Microspectroscopy</strong></h5><p>Hyperspectral images of the interior organs (embryonic axis, endosperm, and seed coat) extracted from different stages of fruit development in “Hua Rue” chili are shown in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c05947#fig2">Figure 2</a>. The color-coded regions represent variations in intensity, possibly indicating differences in chemical composition, thermal properties, or structural variations in various seed tissues. The 35 DAF seed exhibited a higher abundance of chemicals in the endosperm region, as indicated by the red color in the tissue, while it showed a lower composition in the seed coat and embryonic axis (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c05947#fig2">Figure 2</a>A). The seeds from 45 and 50 DAF contained the highest concentrations of chemicals in the endosperm, followed by the embryonic axis and seed coat (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c05947#fig2">Figure 2</a>B,C). These results indicate that the chemical compositions in each region of the seed vary, depending on the stages of seed development. In a previous study, a Raman hyperspectral imaging system was applied for online quality control of maize seeds based on the rapid and visual detection of chemical compositions. <a href="javascript:void(0);">(21)</a></p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2026_11_1_562_571_Figure_2_Hyperspectral_imaging_of_chili_seed_tissues_at_different_fruit_developmental_stages_f9a7b4a922.jpeg" alt="ACS Omega 2026, 11, 1, 562–571: Figure 2. Hyperspectral imaging of chili seed tissues at different fruit developmental stages: 35 days after flowering (DAF, A), 45 DAF (B), and 50 DAF (C). Seed coat, endosperm, and embryonic axis regions are indicated. The overlaid false-color maps represent the relative chemical abundance detected by hyperspectral analysis, with a color scale from −200 (blue, lowest intensity) to 1000 (white-pink, highest intensity)." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2026_11_1_562_571_Figure_2_Hyperspectral_imaging_of_chili_seed_tissues_at_different_fruit_developmental_stages_f9a7b4a922.jpeg 245w," sizes="100vw" width="2088" height="593"></p><p>The FTIR spectrum was recently applied to identify the intensity of biochemical compositions in various materials. <a href="javascript:void(0);">(22)</a> In the FTIR absorption spectrum, three major biochemical composition regions of interest have been identified according to prior studies. <a href="javascript:void(0);">(23)</a> The absorption bands of 3000–2800 cm<sup>–1</sup> represent lipid regions, the bands of 1800–1400 cm<sup>–1</sup> exhibit protein regions (amide I and amide II), and the spectra absorption bands of 1300–1000 cm<sup>–1</sup> reveal carbohydrates, phospholipids, and nucleic acids. <a href="javascript:void(0);">(24,10)</a> In this study, distinctive spectral patterns were observed among the embryonic axis, endosperm, and seed coat (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c05947#fig3">Figure 3</a>A–C). Additionally, significant differences in absorption intensities were found among seeds extracted from fruit at 35, 45, and 50 DAF (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c05947#fig3">Figure 3</a>D–F).</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2026_11_1_562_571_Figure_3_FTIR_analysis_of_chili_seed_tissues_harvested_at_different_developmental_stages_62c5db783d.jpeg" alt="ACS Omega 2026, 11, 1, 562–571: Figure 3. FTIR analysis of chili seed tissues harvested at different developmental stages. (A–C) Mean absorption spectra of the seed coat (A), endosperm (B), and embryonic axis (C) obtained from seeds at 35, 45, and 50 days after flowering (DAF). Major absorption peaks are indicated: 2927–2850 cm–1 (C–H stretching of lipids), 1745–1660 cm–1 (amide I of proteins), 1543–1380 cm–1 (amide II of proteins), and 1234–1090 cm–1 (C–O stretching of carbohydrates/polysaccharides). (D–F) Quantitative comparisons of relative absorbance intensities at these peaks for the seed coat (D), endosperm (E), and embryonic axis (F). Bars represent the mean ± standard deviation (SD). Different letters (a–c) above bars indicate statistically significant differences among fruit developmental stages according to Tukey’s HSD test (P &lt; 0.05)." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2026_11_1_562_571_Figure_3_FTIR_analysis_of_chili_seed_tissues_harvested_at_different_developmental_stages_62c5db783d.jpeg 237w," sizes="100vw" width="2088" height="1372"></p></div>

Chemical Composition and Biochemical Changes during Fruit Development on Seed Quality in Hot Chili (Capsicum annuum L.)

Pilot study of screening method for pancreatic cancer using lipidomic profiling of plasma or serum

<p><strong>In the week of March 9, the following webinars await you in the field of gas / solid phase and especially Raman, FTIR, GC and GC/MS.</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 500 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><div><div><div><div><div><div><h5><strong>1. Separation Science: Raman Spectroscopy for Li-ion Battery Material Diagnostics</strong></h5><ul><li>We, 11.3.2026 15:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5952">Registration</a></li></ul><p>This presentation explores Raman spectroscopy as a non-destructive, high-resolution diagnostic tool for characterizing electrode materials in lithium-ion batteries.</p><h5><strong>2. C&amp;EN: Explode into AI-Driven Automation with Stuntman</strong></h5><ul><li>We, 11.3.2026 16:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5989">Registration</a></li></ul><p>Discover how Stuntman integrates native AI into laboratory automation, translating scientific intent into executable experiments with automated design, execution, and data-driven iteration.</p><h5><strong>3. Agilent Technologies: Mastering SPME – A Practical Guide for GC Analysts for a SOLID Foundation</strong></h5><ul><li>We, 11.3.2026 17:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5724">Registration</a></li></ul><p>Explore Agilent SPME fibers and Arrow solutions for efficient analyte extraction and learn how to select the optimal phase for headspace or direct immersion in GC workflows.</p><h5><strong>4. Metrohm: Full-Spectrum Raman for Research, Development, and Process Understanding</strong></h5><ul><li>We, 11.3.2026 19:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5966">Registration</a></li></ul><p>Learn how Metrohm i-Raman NxG and Duo systems deliver molecular-level insight for APIs, polymers, and reaction monitoring with full-spectrum Raman coverage and 21 CFR Part 11-ready software.</p><h5><strong>5. Agilent Technologies: Automation at the Next Level – Never Lose Track of Your Sample</strong></h5><ul><li>Th, 12.3.2026 06:30 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5965">Registration</a></li></ul><p>Discover how digital lab automation manages the full sample lifecycle—from request and registration to chromatography workflows, reporting, and secure data archiving.</p><h5><strong>6. C&amp;EN: Microplastic Analysis in Water Using Vibrational Spectroscopy – Navigating ISO/FDIS 16094-2 Standards</strong></h5><ul><li>Th, 12.3.2026 11:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5940">Registration</a></li></ul><p>Learn how to implement ISO/FDIS 16094-2 for microplastics analysis using vibrational spectroscopy, including best practices, validation strategies, and quality control approaches.</p><h5><strong>7. Waters Corporation: PFAS in the Environment – A Deep Dive into Analysis, Regulation, and Real-World Data</strong></h5><ul><li>Th, 12.3.2026 15:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5920">Registration</a></li></ul><p>Explore PFAS analysis, regulation, and environmental monitoring insights under the revised EU Water Framework Directive in Episode 2 of the Waters Environmental Webinar Series.</p></div></div></div></div></div></div>

Webinars LabRulezGCMS Week 11/2026

<p><strong>In the week of March 9, the following webinars await you in the field of liquid phase and especially HPLC and LC/MS.</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 500 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. Agilent Technologies: Simplifying Liquid Chromatography Applications for Petrochemical Products by the New Agilent Infinity III LC Series Technology</strong></h5><ul><li>Tu, 10.3.2026 10:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5986">Registration</a></li></ul><p>Part 3 explores how the Agilent Infinity III LC Series simplifies HPLC workflows for petrochemical products, supporting ASTM methods with robust and compliant analytical performance.</p><h5><strong>2. Thermo Fisher Scientific: IC Nitrite Analysis – Streamlined Workflows for Reliable Quantification</strong></h5><ul><li>Tu, 10.3.2026 12:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5982">Registration</a></li></ul><p>Discover how ion chromatography enables reliable nitrite quantification across pharmaceutical workflows, including water, excipients, and finished drug products.</p><h5><strong>3. SelectScience: Supercharge LNP EE% and Size Characterization on Stunner AF</strong></h5><ul><li>Tu, 10.3.2026 17:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5988">Registration</a></li></ul><p>Learn how a surfactant-free, single-instrument workflow enables measurement of LNP size, payload, and encapsulation efficiency for RNA and pDNA using the Stunner AF platform.</p><h5><strong>4. Thermo Fisher Scientific: Optimizing Every Step – An End-to-End Workflow for High-Confidence Single-Cell Proteomics</strong></h5><ul><li>Tu, 10.3.2026 19:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5949">Registration</a></li></ul><p>Kick off the Single-Cell Proteomics Webinar Series with a complete workflow overview from sample preparation to LC-MS and data analysis.</p><h5><strong>5. C&amp;EN: Explode into AI-Driven Automation with Stuntman</strong></h5><ul><li>We, 11.3.2026 16:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5989">Registration</a></li></ul><p>Discover how Stuntman integrates native AI into laboratory automation, translating scientific intent into executable experiments with automated design, execution, and iterative data-driven optimization.</p><h5><strong>6. Thermo Fisher Scientific: Real-World Breakthroughs – Expert-Led Applications in Single-Cell Proteomics</strong></h5><ul><li>We, 11.3.2026 19:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5950">Registration</a></li></ul><p>Part 2 of the Single-Cell Proteomics Master Class presents real-world case studies and strategies for maximizing data quality and biological insights.</p><h5><strong>7. Agilent Technologies: Automation at the Next Level – Never Lose Track of Your Sample</strong></h5><ul><li>Th, 12.3.2026 06:30 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5965">Registration</a></li></ul><p>Learn how to create a fully digital laboratory by managing the entire sample journey—from request and registration to chromatography workflows, reporting, and secure data archiving.</p><h5><strong>8. Agilent Technologies: Veterinary Drugs Edition</strong></h5><ul><li>Th, 12.3.2026 08:30 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5954">Registration</a></li></ul><p>Part 1 of the Food Safety Webinar Series explores LC-MS/MS strategies for monitoring veterinary drug residues in seafood, dairy, and meat under Codex, EU, and FSSAI frameworks.</p><h5><strong>9. Agilent Technologies: Improve Your NGS Workflow with the Magnis</strong></h5><ul><li>Th, 12.3.2026 14:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6010">Registration</a></li></ul><p>Learn how the Agilent Magnis system supports automated NGS library preparation in clinical diagnostics laboratories.</p><h5><strong>10. Thermo Fisher Scientific: Optimizing for Impact – Expert Strategies for Single-Cell Preparation and Data Analysis</strong></h5><ul><li>Th, 12.3.2026 19:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5951">Registration</a></li></ul><p>Part 3 of the Single-Cell Proteomics Master Class delivers practical strategies for sample preparation and data analysis with insights from Cellenion and Proteome Discoverer experts.</p><h5><strong>11. Agilent Technologies: Comprehensive Workflow for Automated Sample Cleanup and Sensitive Quantitation of GLP-1 Analogs from Plasma</strong></h5><ul><li>Th, 12.3.2026 19:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5815">Registration</a></li></ul><p>Learn how an automated LC-MS workflow enables sensitive antibody-free quantification of GLP-1 analogs in human plasma to accelerate PK/TK studies.</p><h5><strong>12. Agilent Technologies: Development of Long-Read Sequencing Methods Leveraging Target Enrichment</strong></h5><ul><li>Fr, 13.3.2026 08:30 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5953">Registration</a></li></ul><p>Explore long-read sequencing strategies using target enrichment for DNA methylation analysis and full-length cDNA characterization.</p><h5><strong>13. Agilent Technologies: Designing Integrated Analytical Workflows for GLP-1 and Peptide Therapeutics</strong></h5><ul><li>Fr, 13.3.2026 11:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5943">Registration</a></li></ul><p>Episode 2 of the Peptide 360 series explores integrated LC-MS and informatics workflows supporting development and lifecycle management of GLP-1 and peptide therapeutics.</p><h5><strong>14. SCIEX: Extractables and Leachables – The Complete Workflow Using the SCIEX X500R QTOF System</strong></h5><ul><li>Fr, 13.3.2026 15:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5991">Registration</a></li></ul><p>Discover a comprehensive extractables and leachables workflow using the SCIEX X500R QTOF system for advanced materials testing and regulatory compliance.</p>

Webinars LabRulezLCMS Week 11/2026

<p><strong>In the week from March 9, the following webinars await you in the field of atomic and molecular spectroscopy and spectrometry</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 500 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. SelectScience: Supercharge LNP EE% and Size Characterization on Stunner AF</strong></h5><ul><li>Tu, 10.3.2026 17:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5988">Registration</a></li></ul><p>Discover a surfactant-free, single-instrument workflow to measure LNP size, payload, and encapsulation efficiency for RNA and pDNA in one assay using the Stunner AF platform.</p><h5><strong>2. Separation Science: Raman Spectroscopy for Li-ion Battery Material Diagnostics</strong></h5><ul><li>We, 11.3.2026 15:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5952">Registration</a></li></ul><p>This presentation explores Raman spectroscopy as a non-destructive, high-resolution diagnostic tool for characterizing electrode materials in lithium-ion batteries.</p><h5><strong>3. C&amp;EN: Explode into AI-Driven Automation with Stuntman</strong></h5><ul><li>We, 11.3.2026 16:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5989">Registration</a></li></ul><p>Discover how Stuntman embeds native AI into laboratory automation, translating scientific intent into executable experiments with automated design, execution, and data-driven iteration.</p><h5><strong>4. Anton Paar: Unlock Nanoparticle Analysis – Advanced DLS and Zeta Potential Solutions</strong></h5><ul><li>We, 11.3.2026 17:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5990">Registration</a></li></ul><p>Learn how the Litesizer DLS series enables precise particle size, zeta potential, and molecular mass measurements in a single platform for nanoparticle characterization.</p><h5><strong>5. Bruker: From Crude to Petrochemical Product – Enhancing Quality Control with Smarter XRF Solutions</strong></h5><ul><li>We, 11.3.2026 17:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5847">Registration</a></li></ul><p>Discover how XRF spectrometry enables rapid, standards-compliant elemental analysis for petrochemical processing and quality control.</p><h5><strong>6. Anton Paar: Polymer Rheology – Testing Behavior Across Time and Temperature</strong></h5><ul><li>We, 11.3.2026 17:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5799">Registration</a></li></ul><p>Learn how oscillatory rheology reveals polymer melt behavior beyond viscosity using techniques such as LVER analysis and frequency sweeps.</p><h5><strong>7. Metrohm: Full-Spectrum Raman for Research, Development, and Process Understanding</strong></h5><ul><li>We, 11.3.2026 19:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5966">Registration</a></li></ul><p>Discover how Metrohm i-Raman NxG and Duo provide molecular insight for APIs, polymers, and reaction monitoring with full-spectrum Raman coverage.</p><h5><strong>8. Agilent Technologies: Automation at the Next Level – Never Lose Track of Your Sample</strong></h5><ul><li>Th, 12.3.2026 06:30 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5965">Registration</a></li></ul><p>Learn how a fully digital laboratory environment can manage the entire sample lifecycle—from registration through chromatography workflows to reporting and secure archiving.</p><h5><strong>9. C&amp;EN: Microplastic Analysis in Water Using Vibrational Spectroscopy – Navigating ISO/FDIS 16094-2 Standards</strong></h5><ul><li>Th, 12.3.2026 11:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5940">Registration</a></li></ul><p>Discover best practices for implementing ISO/FDIS 16094-2 for microplastics analysis using vibrational spectroscopy, including validation and quality control strategies.</p>

Webinars LabRulezICPMS Week 11/2026

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 9th March 2026? Check out new documents from the field of the gas phase, especially GC and GC/MS techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT GCMS AND RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><strong>LabRulezICPMS</strong></a> libraries.</p></blockquote><p>This week we bring you application notes by <strong>Agilent Technologies, Shimadzu </strong>and <strong>Thermo Fisher Scientific</strong> and<strong> </strong>poster by<strong> MDCW / C³AL!</strong></p><h3><strong>1. Agilent Technologies: Quantitative Volatile PFAS Analysis in Textiles</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_tq_ms_volatile_pfas_textiles_8890_7010d_5994_8966en_agilent_cf4eb4ce36.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Per- and polyfluoroalkyl substances (PFAS) are a group of manmade chemicals widely used in textiles for their water, stain, and oil-repellent properties. For decades, the textile industry has been using PFAS for enhancing fabric durability and performance.<sup>1,2</sup> Scientific studies have raised concerns about its potential risks to&nbsp;health.<sup>3-5&nbsp;</sup></p><p>As awareness of these risks has intensified, regulations like REACH/POPs have introduced stringent limits and, in many cases, initiated phase-outs of PFAS usage.<sup>6</sup> Industry-driven standards, such as the ZDHC Manufacturing Restricted Substances List, OEKO-TEX Standard 100, AFIRM Restricted Substance List, and Bluesign standards and criteria complement regulations and reflect a global shift toward stricter compliance.<sup>7-10</sup> Analytical standards like EN 17681-1:2025 provide test methods for PFAS in textiles.11 To keep pace with evolving regulations and industry initiatives, robust and highly sensitive analytical methods are essential for accurate PFAS detection and quantification in complex textile matrices. This study demonstrates the ability of the Agilent 8890 GC coupled with the Agilent&nbsp;7010D GC/TQ system to detect and quantify more than 30 volatile PFAS analytes across various textile matrices, with comprehensive evaluation of sensitivity, accuracy, and precision.</p><h4><strong>Experimental</strong></h4><p>Instrumentation An<a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890"><strong> 8890 GC</strong></a> with a <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=7010D"><strong>7010D GC/TQ</strong></a> equipped with an HES 2.0 ion source was used for this analysis. An Agilent MMI inlet and splitless liner (part number 5190-2293) were used, and chromatographic separation was performed using an Agilent J&amp;W DB-624 column, 30 m × 0.25 mm, 1.40 μm (part number 122-1334UI). The instrument setup is shown in Figure 1. The acquisition method for 34 native PFAS and four internal mix standards (ISTD), including GC condition and TQ parameters, were described in a previous application note.<sup>12</sup></p><h4><strong>Sample analysis</strong></h4><p>PFAS are widely used in textile materials due to their exceptional resistance to heat, water, and oil.1,2,13 In this study, PFAS compounds—specifically 8:2 FTOH and 10:2&nbsp;FTOH, were detected above MDLs in sample waterproof shorts, as shown in Figure 5. However, the concentrations of these two compounds remained within the formulation limits set by ZDHC. Although FTOHs are not explicitly listed as individual compounds under the EU POPs regulation, they fall under restrictions applied to related substances such as PFOA, PFCA, and PFHxA. These results demonstrate that the developed method enables accurate and reliable detection of PFAS in apparel products, providing valuable data to support regulatory bodies in risk management and the establishment of appropriate limits.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>An accurate and robust method was developed using an Agilent 8890 GC coupled with an Agilent 7010D GC/TQ system for the analysis of volatile PFAS in textiles, following the established analytical guidelines. The workflow delivered excellent performance, achieving sub-ppb MDLs for all targets and LOQs of 10&nbsp;µg/kg for more than 80% of compounds. These results confirm high extraction efficiency and exceptional sensitivity for PFAS in textile matrices. Recovery precision (%RSD) remained within 20% across sample preparations, underscoring method reproducibility and suitability for routine, high-throughput PFAS analysis in materials such as textiles</p><h3><strong>2. MDCW / C³AL: Microplastics as Vectors of Organic Contaminants on Southern California Beaches: A TD/Py-GC×CG-TOFMS Study</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/P_18_Nathan_Venegas_C3_AL_2db714dd9b.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Microplastics are increasingly recognized as widespread environmental pollutants that can act as carriers of organic contaminants in marine ecosystems. In this study, researchers from California State University, Los Angeles investigated microplastics collected from several Southern California locations—including Santa Monica State Beach, Doheny State Beach, the Los Angeles River, and the Salton Sea—to better understand the types of organic compounds associated with these particles. The analysis was performed using thermal desorption/pyrolysis comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (<strong>TD/Py-</strong><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/1097"><strong>GC×GC-TOFMS</strong></a>), a powerful analytical approach for characterizing complex mixtures of organic compounds.</p><p>The results revealed a wide range of organic compounds adsorbed onto microplastic particles, including alkanes, alkenes, alcohols, aromatic and polyaromatic compounds, as well as nitrogen- and sulfur-containing species. Significant variability in contaminant profiles was observed across sampling sites, reflecting differences in local pollution sources and environmental conditions. For example, Santa Monica State Beach samples showed the highest total number of detected compounds, while other sites exhibited distinct chemical signatures linked to their surrounding environments.</p><p>Overall, the study highlights the important role microplastics can play as vectors for transporting organic contaminants in aquatic environments. The findings demonstrate the usefulness of advanced GC×GC-TOFMS techniques for detailed characterization of contaminants associated with microplastics and contribute to a better understanding of their environmental impact and potential risks to marine ecosystems.</p><h3><strong>3. Shimadzu: Effectiveness of the MonoTrap Collection Method for VOC Analysis in Exhaled Breath Using GC-MS</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_01_01140_en_076528bbaa.pdf"><strong>Full PDF for download</strong></a></li></ul><h5><strong>User Benefits</strong></h5><ul><li>Comprehensive analysis of VOCs from non-invasive breath samples is feasible with this system.</li><li>No equipment such as sampling pumps is required, enabling breath collection in remote locations.</li><li>Internal standards support consistent comparison of analytical results across sample groups.</li></ul><p>Exhaled breath is a non-invasive sample that is easy to collect and imposes minimal burden on subjects. It is known to contain volatile organic compounds (VOCs) that reflect metabolic states and disease conditions within the body. More than 1,000 types of VOCs exist in breath, and numerous studies have reported the search for breath markers across various disease areas, including inflammatory diseases¹) , cancer²) , and metabolic disorders³) . Consequently, extensive research is being conducted in the field of breathomics.&nbsp;</p><p>While GC-MS is widely used for comprehensive and highly sensitive analysis of trace components in breath, differences in pretreatment steps, such as sample collection, affect measurement results. Therefore, optimizing analytical protocols to enhance reproducibility and consistency is essential.&nbsp;</p><p>This Application Note compares breath collection methods using Tenax tubes and MonoTrap using a thermal desorption-GC-MS system (Fig. 1) to determine the optimal collection method. Additionally, breath samples from healthy subjects and subjects with inflammatory conditions were analyzed using this analytical system to evaluate the usefulness of measuring and comparing VOC profiles with this approach.</p><h4><strong>Analytical Conditions</strong></h4><p>After collection, MonoTrap and Tenax collection tubes were thermally desorbed using the<a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=TD-30R"><strong> TD-30R thermal desorption</strong></a> device and analyzed by GC-MS (<a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GCMS-QP2020+NX"><strong>GCMS-QP2020 NX</strong></a>). Toluene-d8 was added as an internal standard to confirm analytical stability. Detailed analytical conditions are shown in Table 1.</p><h4><strong>Summary</strong></h4><p>This application news evaluated a breath VOC analysis system using thermal desorption–GC–MS with MonoTrap. MonoTrap detected a larger number of VOCs in exhaled breath from healthy subjects compared with the conventional Tenax tube method. Optimization of collection conditions indicated that static collection using one MonoTrap for 24 h is a practical and efficient protocol. Under these conditions, differences in VOC profiles were observed between healthy subjects and subjects with inflammatory conditions. MonoTrap enables breath collection without sampling pumps, and collected samples can be easily stored and transported, making the method suitable for remote sampling. Overall, this system demonstrated the capability for comprehensive VOC profiling of exhaled breath.</p><h3><strong>4. Thermo Fisher Scientific : Rapid analysis of organochlorine pesticides (OCPs) in soil samples using the EXTREVA ASE accelerated solvent extractor</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_004311_ic_extreva_ocp_soil_testing_an004311_na_en_81a2272b67.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Organochlorine pesticides (OCPs) are persistent environmental contaminants historically used to control pests in agriculture and other applications. Due to their long-term stability and toxicity, many OCPs have been banned or strictly regulated following international agreements such as the Stockholm Convention. Nevertheless, these compounds can remain in environmental matrices like soil for long periods, making reliable analytical methods essential for environmental monitoring. This application note describes a workflow for the determination of OCPs in soil samples using the Thermo Scientific EXTREVA ASE accelerated solvent extraction system, designed to automate and streamline the traditionally labor-intensive sample preparation process.</p><h4><strong>Experimental approach</strong></h4><p>Soil samples were prepared by mixing clean loamy soil with diatomaceous earth to improve extraction efficiency and prevent sample compaction. The samples were extracted using the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=3&amp;search=EXTREVA+ASE"><strong>EXTREVA ASE</strong></a> system with an acetone–hexane solvent mixture under controlled temperature and pressure conditions. The system integrates gas-assisted accelerated solvent extraction with automated solvent evaporation, enabling simultaneous extraction of multiple samples with minimal operator intervention. After extraction and concentration to a defined final volume, the analytes were quantified using gas chromatography with electron capture detection (GC-ECD). Calibration standards were prepared across a concentration range of 0.01–0.2 µg/mL to ensure accurate quantification of 20 target OCP compounds.</p><h4><strong>Results and performance</strong></h4><p>The developed workflow demonstrated excellent analytical performance. All target pesticides were well separated in the GC-ECD analysis with a total run time of less than 27 minutes. Extraction recoveries for soil samples fortified at 250 µg/kg ranged between 80% and 121%, meeting the US EPA recommended acceptance criteria of 70–130%. Reproducibility was also strong, with relative standard deviations below 20% for all analytes. Carryover between samples remained very low (&lt;0.6%), indicating effective rinsing and minimal cross-contamination. Additional tests confirmed that thermally sensitive compounds such as endrin and DDT showed minimal degradation during extraction.</p><h4><strong>Conclusion</strong></h4><p>The EXTREVA ASE system provides a fast and highly automated workflow for the determination of organochlorine pesticides in soil samples. By integrating extraction, solvent evaporation, and endpoint volume control in a single instrument, the system reduces manual handling, lowers solvent consumption, and significantly shortens sample preparation time. The method enables reliable determination of 20 OCPs with high recovery, low carryover, and excellent reproducibility, supporting rapid environmental monitoring workflows and compliance with established US EPA analytical methods.</p>

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