<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 25th August 2025? 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 </strong>and <strong>Shimadzu!</strong></p><h3><strong>1. Agilent Technologies: A More Sustainable Analysis of Ethylene Oxide and 1,4-Dioxane</strong><br><strong>in Surfactants with Hydrogen Carrier Gas&nbsp;</strong></h3><p><strong>Using an Agilent </strong><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=5977B+GC%2FMSD"><strong>5977B GC/MSD</strong></a><strong> with an Agilent HydroInert Source</strong></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_ethylene_oxide_1_4_dioxane_surfactants_hydrogen_carrier_gas_5994_8335en_agilent_886a988649.pdf"><strong>Full PDF for download</strong></a></li></ul><p>EO and 1,4-dioxane are key industrial chemicals, frequently found in the production of surfactants. During alkoxylation processes, residual raw materials or byproducts, such as EO and 1,4-dioxane, may remain in the final surfactant product (Figure 1). Although manufacturers have made significant strides in reducing these byproducts, increasing regulatory scrutiny on EO and 1,4-dioxane underscores the need for precise analytical methods to detect these compounds at low concentrations.1–4 Thus, there is an urgent need to develop methods that can accurately quantify these compounds at levels as low as 0.1 ppm in consumer products.</p><p>This study presents a method for the detection of EO and 1,4-dioxane using GC/MS with an HS sampler and a HydroInert source for hydrogen carrier gas. The use of hydrogen instead of helium not only addresses the global helium shortage but also ensures excellent sensitivity and linearity, while maintaining the integrity of the analytical process. The HydroInert source further eliminates chemical reactions often associated with hydrogen in mass spectrometry, offering a sustainable and reliable solution. The method developed in this study successfully quantifies both EO and 1,4-dioxane at the low concentrations required by current regulations, offering an accurate, reliable approach for compliance in surfactant manufacturing.</p><h4><strong>Experimental&nbsp;</strong></h4><p>This work was carried out using an Agilent <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=7890+GC"><strong>7890 GC</strong></a> with helium carrier gas and an Agilent <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890+GC"><strong>8890 GC</strong></a> with hydrogen carrier gas. Both GC systems were configured with an Agilent <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=5977B+GC%2FMSD"><strong>5977B GC/MSD</strong></a> and <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=PAL3+autosampler"><strong>PAL3 autosampler</strong></a> for headspace sampling. For the analysis using hydrogen carrier gas, the GC/MSD was fitted with a HydroInert source. The HydroInert source produces spectra in hydrogen that closely match those from helium-based libraries, such as NIST. This ensures spectral fidelity, allowing the same quantification and qualifier ions used in helium methods to be applied in SIM and MRM modes with hydrogen. Method parameters are shown in Table 1.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>This work establishes a first of its kind method using hydrogen carrier gas to reliably measure ethylene oxide and 1,4-dioxane in surfactants. Mass spectrometry detection was optimized for use with hydrogen by installing an Agilent HydroInert source. The HydroInert source helps to avoid sensitivity loss and spectral anomalies that are common with hydrogen carrier gas applications, resulting in suitable linearity, precision, accuracy, and LOQs for this analysis.</p><h3><strong>2. Shimadzu: How Long Does A Perfume Last on Skin? – Fragrance Analysis by </strong><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GCMS-QP2050"><strong>GCMS-QP2050</strong></a><strong> and 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_04_ad_0309_en_60c887beed.pdf"><strong>Full PDF for download</strong></a></li></ul><h4><strong>User Benefits</strong></h4><ul><li>Achieve highly accurate and reproducible analysis of aroma compounds on human skin, ensuring reliable data for evaluating perfume performance.</li><li>Smart Aroma Database simplifies the qualitative and quantitative analysis process, reducing the time and effort required for data interpretation.</li></ul><p>The duration on how long fragrance lasts on human skin is a critical factor in the development and evaluation of perfumes. Gas Chromatography Mass Spectrometry (GC-MS) is a powerful analytical technique that allows for the detailed analysis of volatile and semi-volatile compounds, making it an ideal tool for studying fragrance. In this application note, a study was performed to examine fragrance on human skin at different durations after applying a perfume. Here, we explore the use of a Monolithic Material Sorptive Extraction (MMSE) MonoTrap, a sorptive extraction device to extract fragrance from human skin, followed by analysis using Shimadzu GCMS-QP2050 (Fig.1). Additionally, Smart Aroma Database was used to simplify the method development.</p><h4><strong>Experimental</strong></h4><h5><strong>Instrumental and Analytical Conditions&nbsp;</strong></h5><p><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GCMS-QP2050"><strong>GCMS-QP2050</strong></a> (Shimadzu Corporation, Japan) was employed in this work (Fig. 1). The details of the system configuration is shown in Table 1. Sample acquisition was done by following the analytical method from Shimadzu <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=Smart+Aroma+Database"><strong>Smart Aroma Database</strong></a>. MonoTrap SG DCC18 was purchased from GL Sciences, Japan (catalog no. 1050-70002).</p><h4><strong>Results &amp; Discussion&nbsp;</strong></h4><h5><strong>Fragrance Compounds Detection&nbsp;</strong></h5><p>The scan total ion chromatogram (TIC) of the diluted perfume sample is shown in Fig. 4. A total of 60 out of the 498 fragrance compounds in Smart Aroma Database were detected. These compounds were then monitored for this study. Fig. 5 shows a few mass chromatograms of the monitored fragrance compounds.</p><h5><strong>On-skin Fragrance Study&nbsp;</strong></h5><p>The on-skin fragrance study was conducted to evaluate the persistence of perfume compounds over time. Sampling was performed at three distinct time points: 15 minutes, 1 hour, and 6 hours after applying the perfume (as described in Fig. 2). Fig. 6 shows the percentage of compounds detected (out of 60 compounds) in these three different time points.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>In this study, we demonstrate the effectiveness of using GCMSQP2050 with Smart Aroma Database and Monotrap adsorbent to analyze the behavior of perfume fragrance on human skin. The result shows decrease percentage of number of compounds detected over time. The peak area of most compounds were reduced as well. Sampling repeatability shows that 57 out of 58 detected aroma compounds exhibiting %RSD values below 20% (n=3).</p>

News from LabRulezGCMS Library - Week 35, 2025

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 20th October 2025? 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 applicaton notes by <strong>Agilent Technologies, EST Analytical, Shimadzu </strong>and <strong>Thermo Fisher Scientific!</strong></p><h3><strong>1. Agilent Technologies: FAMEs Analysis of Oils by GC-FID Coupled with Fully Automated Sample Preparation using a PAL3 Series 2 RTC</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_fame_oil_gc_pal3_5994_8543en_agilent_418da94d17.pdf"><strong>Full PDF for download</strong></a></li></ul><p>The analysis of fatty acid methyl esters (FAMEs) is a widely used technique for characterizing lipid profiles in various food products, including oils, meats, and seeds. Fats are composed of a complex mixture of saturated, monounsaturated, and polyunsaturated fatty acids, each with varying carbon chain lengths.2 This type of analysis is routinely performed in governmental, quality control (QC), and contract research laboratories worldwide. The resulting data often informs product labeling. Among the analytical techniques available, gas chromatography (GC) with flame ionization detection (GC-FID) is one of the most common methods for determining fatty acid composition in&nbsp;foods.&nbsp;</p><p>This application note describes the use of automated sample preparation and analysis of FAMEs using the PAL3 Series&nbsp;2 RTC Autosampler system coupled with Agilent 8890 GC system equipped with an FID. The results shown here focus on two different methods of derivatization for FAMEs extraction: (1) base catalyzed reactions using potassium hydroxide (KOH) (part&nbsp;number M5795-14000) and (2) base plus acid catalyzed reactions using boron trifluoride (BF3 ) 1 (part number M5795-14001). For ease of use, both processes have been transcribed into dedicated sample preparation methods. These methods are part of the Agilent automated sample preparation workflow suite of solutions. These workflows improve process safety, optimizes throughput, and minimizes&nbsp;errors.</p><h4><strong>Experimental&nbsp;</strong></h4><p>The 37 component FAME mix standard was purchased from Sigma-Aldrich (part number CRM47885), and three consumer oil products were purchased from a local grocery store. The samples were prepared and injected into the GC using the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=PAL3"><strong>PAL3 Series 2-RTC system</strong></a>. The analysis was performed using an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890+GC"><strong>8890 GC</strong></a> equipped with an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=DB%E2%80%91FastFAME"><strong>Agilent DB‑FastFAME GC column</strong></a>, 30&nbsp;m × 250 µm, 0.25&nbsp;µm, (part number G3903‑63011) and configured with an FID using Agilent&nbsp;<a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=OpenLab+CDS+v2.7"><strong>OpenLab CDS v2.7+</strong></a>.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>In summary, the current study demonstrated excellent reproducibility and accuracy using automated sample preparation and analysis of FAMEs. Two different sample preparation methods were demonstrated, both delivering comparable and reliable results. The base-catalyzed method enables rapid analysis but is not suitable for samples containing free fatty acids. In contrast, the acid-catalyzed method, while more extensive, is compatible with a broader range of lipid classes, including free fatty acids, phosphoglycerides, and triglycerides. The Agilent automated sample preparation workflow suite of solutions deliver a comprehensive package by combining preconfigured hardware, optimized analytical methods, and the necessary consumables to ensure efficient and reliable results.</p><h3><strong>2. EST Analytical: Unregulated Contaminant Monitoring Rule 3 for USEPA Method 524.3 and 524.4</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/Purge_and_Trap_Unregulated_Contaminant_Monitoring_Rule_3_for_USEPA_Method_524_3_and_524_4_b774e6ab4c.pdf"><strong>Full PDF for download</strong></a></li></ul><p>The third Unregulated Contaminant Monitoring Rule (UCMR 3) was finalized in April of 2012. UCMR 3 requires public water systems to monitor for a specific list of 30 contaminants under three separate lists: list one, assessment monitoring, list two, screening survey, and list three, pre-screen testing. This application note will address the volatile organic compounds found in list one, assessment monitoring contaminants. USEPA Method 524.3 and 524.4 will be the methods evaluated for sampling and analysis.</p><h4><strong>Discussion&nbsp;</strong></h4><p>The amendments to the Safe Drinking Water Act (SDWA) require the EPA to list no more than 30 unregulated contaminants to be monitored by public water systems. Every five years, this list needs to be updated. List one contaminants include seven volatile organic compounds to be analyzed by USEPA Method 524.3. The detection limits for these compounds are much lower; therefore, Single Ion Monitoring (SIM) must be used for compound detection. USEPA Method 524.3 and 524.4 allow for modification of purge and trap parameters in order to take advantage of purge and trap improvements. Thus, method parameters can be modified in order to optimize purge and trap cycle times. Since the purge and trap parameters were established for these methods previously, refer to application note Drinking Water Analysis Conditions for USEPA Method 524.3 and the Newly Proposed Method 524.4, purge and trap method development was not required for this application. For this study, Helium and Nitrogen purge gases were compared utilizing the same purge volume then comparing experimental results for the linearity, precision, accuracy and overall compound response for the low level requirements set by UCMR 3.&nbsp;</p><h4><strong>Experimental&nbsp;</strong></h4><p>The <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/2160"><strong>EST Analytical Encon Evolution purge and trap concentrator</strong></a> and <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/2159"><strong>Centurion WS autosampler </strong></a>were interfaced to an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=7890%2F5975"><strong>Agilent 7890/5975 GC/MS</strong></a>. The purge and trap concentrator was configured with a Vocarb 3000 (K) analytical trap. A chiller unit capable of keeping the sample vials cooled below 10°C was installed on the Centurion WS autosampler. The experimental parameters are listed in Tables 1 and 2.</p><h4><strong>Conclusion</strong></h4><p>The Encon Evolution and Centurion WS in conjunction with the Agilent 7890/5975 GC/MS performed very well using both the Helium and Nitrogen purge gases and employing SIM for compound detection. The Nitrogen and the Helium purge gases met USEPA Method 524.3 curve linearity criteria and produced comparable results for precision and accuracy at the low and mid-levels of the calibration curve. Overall, the principal difference between the two purge gases was exhibited in the compound response. When examining the overall compound response factors over the curve range, it is evident that the analytes’ responses are slightly lower with the Nitrogen purge gas as opposed to the Helium purge gas.</p><h3><strong>3. Shimadzu: Comparison of Metabolites in Rice from Different Production Areas Using GC-MS/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_01000_en_9c1d7cfe70.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Metabolomics is a research method for comprehensively analyzing metabolites contained in an organism. It is used for a wide variety of fields, such as medical science and food. Because food quality is affected by many components complexly, comprehensive analysis of metabolites can help improve food development and manufacturing processes. Rice contains metabolites, such as sugars, amino acids, and fatty acids. In recent years, development of more flavorful rice has been studied.&nbsp;</p><p>This article describes simultaneous analysis of 502 metabolites and multivariate analysis of a variety of rice from different production areas. The <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GCMS-TQ8040+NX"><strong>GCMS-TQ8040 NX</strong></a> with the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=Smart+Metabolites+Database+ver.+2"><strong>Smart Metabolites Database Ver. 2</strong></a> was used for measurement. <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=LabSolutions+Insight"><strong>LabSolutions Insight </strong></a>was used for data processing, and <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=eMSTAT+Solution"><strong>eMSTAT Solution</strong></a> was used for multivariate analysis. The process flow, from pretreatment to data analysis, is shown in Fig. 1.</p><h4><strong>eMSTAT Solution&nbsp;</strong></h4><p>eMSTAT Solution is statistical analysis software that enables multivariate and discriminant analysis of chromatogram data. For multivariate analysis, it can discriminate between samples, and it can search for the marker peaks that contribute to those differences. For discriminant analysis, it can create a discriminant model based on training data and use the model for discriminant analysis. Users can easily switch both modes with just a single click. Workflow of the data analysis is shown in Fig. 2.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>Metabolites in same variety of rice from different production areas were analyzed, and the differences between samples were identified by multivariate analysis. Score plots were used to visualize differences between the samples, and loading plots were used to confirm the characteristic compounds. Smart Metabolites Database Ver. 2, LabSolutions Insight, and eMSTAT Solution make metabolites analysis, data processing, and multivariate analysis easy for beginner users.</p><h3><strong>4. Thermo Fisher Scientific: Automated, multi-parameter gasoline characterization using GC-VUV and ASTM D8071</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_003957_gc_vuv_trace_1610_vga_industrial_an003957_na_en_3c0a64e3b2.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Gasoline is a complex hydrocarbon blend whose composition directly impacts combustion behavior, emissions, and regulatory compliance. Accurately quantifying components such as aromatics, olefins, ethanol, and benzene is critical, but traditional ASTM methods require multiple techniques (FIA, GC-FID, GC-MS, etc.) to measure all relevant parameters. Table 1 summarizes several test methods and their respective scopes.&nbsp;</p><p>ASTM D8071 introduces a consolidated method using GC-VUV, offering improved precision, spectral resolution, and reduced operational burden. This approach is now recognized as an EPA- and CARB-approved alternative to several legacy test methods, including ASTM D1319, D5599, D5769, and D3606.</p><h4><strong>Experimental&nbsp;</strong></h4><p>Gasoline samples were analyzed on the VUV Analyzer Platform for Fuels with no sample preparation required. The VUV Analyzer consists of the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/486"><strong>Thermo Scientific™ TRACE™ 1610 gas chromatograph</strong></a> coupled to the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=3&amp;search=VGA-100"><strong>VGA-100™ spectrometer detector </strong></a>(VUV Analytics, Inc.).&nbsp;</p><p>Data are acquired and processed with the VUVision™ Software and VUV Analyze™ Software (VUV Analytics, Inc), respectively, specifically configured to run ASTM D8071.&nbsp;</p><h5><strong>Workflow overview&nbsp;</strong></h5><p>The VUV Analyzer Platform for Fuels performs gasoline PIONA class analysis using a streamlined five-step workflow:&nbsp;</p><ol><li>System validation – Verifies instrument performance using standard hydrocarbons.&nbsp;</li><li>Sample prep – No preparation required.&nbsp;</li><li>Data acquisition – Performed using VUVision Software.&nbsp;</li><li>Spectral matching – Automated deconvolution with VUV Analyze Software.&nbsp;</li><li>Quantitation – Volume % and mass % calculated with high accuracy using built-in response factors and density data.</li></ol><h4><strong>Conclusion&nbsp;</strong></h4><p>GC-VUV with ASTM D8071 enables complete hydrocarbon group and compound-level analysis of gasoline in a single method. Its ability to automate spectral deconvolution and report mass and volume percentages simplifies operations while meeting strict compliance standards. This solution not only enhances analytical accuracy and repeatability but also drastically reduces operating costs and lab complexity.&nbsp;</p><ul><li>Short analysis time with full gasoline class and compound profiling in 34 minutes&nbsp;</li><li>Faster throughput with full automation from injection to reporting&nbsp;</li><li>12× lower cost-per-analysis, due to reduced labor, no calibration standards, and consolidated workflow</li></ul>

News from LabRulezGCMS Library - Week 43, 2025

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 1st December 2025? 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 presentation by<strong> LECO /MDCW!</strong></p><h3><strong>1. Agilent Technologies: Analysis of 197 Pesticides in Durian by Agilent PAL 3 Autosampler and 7000E Triple Quadrupole GC/MSD</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_197_pesticides_durian_pal3_7000e_gc_msd_5994_8702en_agilent_e5a68eaf99.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Pesticide residue analysis in food products is critical to ensuring consumer safety and regulatory compliance. Durian (Durio zibethinus), known as the "king of fruits" and widely exported across Southeast Asia, China, and beyond, presents unique analytical challenges due to its sulfur-rich compounds, high fat content, and complex volatile matrix. Comprehensive pesticide analysis in such matrices demands highly sensitive, selective, and robust analytical solutions. The European Union Reference Laboratories (EURL) SANTE/11312/2021 guidelines set rigorous performance criteria for pesticide residue analysis, including strict requirements for method accuracy, precision, and sensitivity.1 Laboratories need to achieve recoveries between 70% to 120%, precision (RSD) below 20%, and quantification limits at or below regulatory maximum residue limits (MRLs), even in complex food matrices such as durian. This application note demonstrates a high-performance workflow for the analysis of 197 pesticides in durian using an Agilent PAL3 Autosampler combined with an Agilent 7000E Triple Quadrupole GC/MSD system. The PAL3 Autosampler provides high-throughput, precise sample handling, while the 7000E GC/MSD offers exceptional sensitivity and reproducibility for trace-level pesticide quantification. Optimized sample preparation and instrumental conditions ensure reliable performance, meeting and exceeding SANTE criteria for method validation.</p><h4><strong>Experimental</strong></h4><h5><strong>PAL 3 RTC and 7000E GC/TQ parameters&nbsp;</strong></h5><p>The analysis parameters are shown in Table 1. The target and ISTD compound MRM parameters are listed in Appendix&nbsp;1. Figure 1 shows a typical MRM chromatogram of targeted pesticides spiked in durian at a concentration of 100 ppb.</p><ul><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=PAL+3"><strong>Agilent PAL 3 (Liquid Tool)</strong></a></li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890"><strong>Agilent 8890 GC</strong></a></li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=7000E"><strong>Agilent 7000E</strong></a></li></ul><h4><strong>Conclusion&nbsp;</strong></h4><p>This study successfully demonstrated a robust and sensitive method for the quantitative analysis of 197&nbsp;pesticides in durian using an Agilent PAL3 Autosampler combined with an Agilent&nbsp;7000E Triple Quadrupole GC/MSD system. The optimized workflow, including sample extraction with an Agilent Bond Elut QuEChERS EN kit followed by cleanup with the Highly Pigmented dSPE kit, provided excellent recovery and precision. All target pesticides showed analysis accuracy between 80% and 120% and RSD values below 10% at a spiked level of 10 ppb. The results confirm the method's suitability for routine high-throughput pesticide quantification in complex matrices such as durian. The use of matrix-matched calibration and matrix‑optimized MRMs further ensured accurate and reproducible quantitation, reinforcing the method's applicability for regulatory and food safety testing.</p><h3><strong>2. LECO / MDCW: Applying statistical data processing tools for GC×GC differentiation of alternative aviation fuels</strong></h3><ul><li>Presentation</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/FL_18_Sebastiano_b4cf417f82.pdf"><strong>Full PDF for download</strong></a></li></ul><p>The presentation introduces LECO’s long-standing role in separation science and its evolution from elemental analyzers to advanced mass spectrometry platforms. A key emphasis is placed on LECO’s innovations in <strong>time-of-flight mass spectrometry (TOFMS)</strong>, including the Pegasus series and the new <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=24&amp;search=Pegasus+BTX"><strong>Pegasus BTX</strong></a>, a benchtop TOFMS offering high sensitivity, rugged detector technology, fast spectral acquisition (1–500 spectra/s), and broad mass range (10–1500 m/z). This technological foundation supports comprehensive <strong>GC×GC-MS</strong> workflows essential for analyzing chemically complex matrices such as aviation fuels.</p><p>A major focus of the talk is on <strong>software tools</strong> for non-targeted data processing. LECO’s software ecosystem—<a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=24&amp;search=ChromaTOF"><strong>ChromaTOF</strong></a><strong>, ChromaTOF Tile, and </strong><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=24&amp;search=ChromaTOF+Sync"><strong>ChromaTOF Sync</strong></a>—enables detailed deconvolution, quantitation, high-resolution spectral analysis, and especially <strong>statistical comparison of GC×GC datasets</strong>. ChromaTOF Tile uses a chromatographic “tiling” strategy to link datasets and detect differences between sample groups using three statistical metrics: <strong>Fisher Ratio</strong>, <strong>Coefficient of Variation (CoV)</strong>, and <strong>Fold-Change</strong>. Each metric serves a different experimental purpose, from comparing traditional vs. synthetic jet fuels (Fisher Ratio) to exploring variability among multiple alternative fuel processes (CoV), or identifying additive components in two-sample comparisons (Fold-Change).</p><p>The presentation demonstrates how raw GC×GC-MS data are curated into <strong>feature tables</strong>, statistically evaluated, and visualized in <strong>PCA plots, bar charts, and chromatographic overlays</strong>. For example, Fisher Ratio comparison highlights statistically significant chemical differences between conventional Jet A and synthetic fuels, while CoV analysis reveals clustering patterns among diverse synthetic fuel production pathways such as <strong>LT-FT SPK, HT-FT SPK, HEFA, SIP, ATJ, and CHJ</strong>. These workflows enable analysts to rapidly identify biomarkers or distinguishing compositional features within highly complex hydrocarbon matrices.</p><p>Ultimately, the talk demonstrates that choosing the correct statistical processing method can dramatically simplify interpretation of complex GC×GC-MS datasets. LECO’s integrated instrumentation—particularly the Pegasus BTX TOFMS—and software platforms together provide a powerful toolkit for fuel characterization, quality evaluation, and differentiation of emerging <strong>alternative aviation fuels</strong>. By combining comprehensive chromatography with robust statistical approaches, researchers can gain deeper insights into chemical variability, production signatures, and additive packages in modern aviation fuel technologies.</p><h3><strong>3. Shimadzu: Analysis of Formic Acid in Acetone Using GC/MS 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_01_00957_en_e8b083b86e.pdf"><strong>Full PDF for download</strong></a></li></ul><p>In research on artificial photosynthesis, the analysis of impurities in chemical products and raw materials has increased the demand for high-sensitivity analysis of formic acid. Previous examples of formic acid analysis using GC-BID and GC-FID (Jetanizer ) have been presented, but in this article high-sensitivity analysis of formic acid using the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GCMS-QP2050"><strong>GCMS-QP2050</strong></a> (see Fig. 1) isintroduced.</p><h4><strong>Insert, Column Phosphoric Acid Treatment&nbsp;</strong></h4><p>Formic acid is known to adsorb onto the injection port and column, making peak detection difficult. However, by performing phosphoric acid treatment on the glass insert and column before measurement, good peaks can be obtained. The procedure for phosphoric acid treatment of the glass insert is shown in Fig. 2, and the procedure for phosphoric acid treatment of the column isshown in Fig. 3.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>By performing phosphoric acid treatment on the insert and column, it became possible to analyze formic acid in SIM mode down to 0.2 ppm. Furthermore, good results could be obtained for both linearity and repeatability. Additionally, by analyzing in Scan mode, identification of unknown peaks other than formic acid was also achieved.</p><h3><strong>4. Thermo Fisher Scientific: Uninterrupted analysis of VOCs according to U.S. EPA Method 8260C using purge and trap and single quadrupole GC-MS technology</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_001018_gc_voc_analysis_gc_ms_epa_8260c_an001018_na_en_269857401c/an-001018-gc-voc-analysis-gc-ms-epa-8260c-an001018-na-en.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Volatile organic compounds, or VOCs, are human-made contaminants used and produced in the processing of, or as, paints, adhesives, petroleum products, pharmaceuticals, and refrigerants. Many of these compounds contaminate our environment and may cause negative health effects in humans and other living beings. Analytical laboratories must monitor a variety of sample types from the environment to ensure the public are not exposed to elevated levels of VOCs. The latest version of applicable method in the United States, U.S. EPA Method 8260C, is applicable when monitoring a variety of solid waste matrices for the presence of VOCs.</p><p>To perform U.S. EPA Method 8260C, all method acceptance criteria must be achieved. These criteria include calculating the mean response factor and the relative standard deviation (RSD) of the response factors for target analytes. The RSD should be &lt;20%, with minimum response factors (RF) and MDLs for a wide range of target compounds. The analytical method must produce consistent results and be reproducible from day to day, with a continuing calibration verification (CCV) analyzed every 12 hours while samples are run. As the method covers varying matrices, it is important that the performance criteria are met in all samples of interest. The following evaluation describes the use of the ISQ 7610 GCMS coupled to the Atomx XYZ P&amp;T for U.S. EPA Method 8260C.</p><h4><strong>Experimental</strong></h4><h5><strong>Instrument control and data processing&nbsp;</strong></h5><p>Data were acquired, processed, and reported using <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/76"><strong>Chromeleon CDS software</strong></a>, version 7.2. This software can control both the GC-MS system and the Tekmar Atomx XYZ P&amp;T. This enables a single software solution to support the full workflow, simplifying the instrument operation. The optimized method used within this application note is available for download via the Thermo Scientific™ AppsLab library. AppsLab contains all the parameters needed to acquire, process, and report the analytical data for U.S. EPA Method 8260C.2</p><h5><strong>GC-MS parameters&nbsp;</strong></h5><p>A <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/486"><strong>TRACE 1610 GC</strong></a> was coupled to the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/484"><strong>ISQ 7610 MS </strong></a>equipped with the Thermo Scientific™ NeverVent™ vacuum probe interlock (VPI) and an ExtractaBrite™ ion source. Expanded method parameters for the GC-MS system are displayed in Table 3</p><h4><strong>Conclusion&nbsp;</strong></h4><p>The combined analytical solution with the TRACE 1610 GC coupled with the ISQ 7610 system and the Atomx XYZ P&amp;T system provides clear advantages for analytical testing laboratories that analyze environmental samples following the U.S. EPA Method 8260C requirements. The modularity of the TRACE 1610 GC as well as the ISQ 7610 VPI and ExtractaBrite ion source allows users to easily service the injection ports and to exchange ionization sources and analytical columns without venting the mass spectrometer, significantly reducing instrument downtime and minimizing sample analysis interruptions. The Atomx XYZ concentrator’s efficient trap cooling design reduces sample cycle time and allows for increased sample throughput. The moisture control system improves water vapor removal thereby reducing peak interference and increasing GC column life span.&nbsp;</p><p>The experiments performed clearly demonstrate the suitability of this analytical configuration for the analysis of VOCs in various environmental samples in accordance with U.S. EPA Method 8260C with the following performance parameters as evidence:&nbsp;</p><ul><li>The ISQ 7610 VPI coupled with the Tekmar Atomx XYZ P&amp;T exceeds all the requirements outlined in U.S. EPA Method 8260C for analysis of VOCs in wastewater and solid waste.</li><li>Linearity was achieved with &lt;20%,<span>&nbsp;</span>relative standard deviation for both water and soil calibration curves for the majority of compounds.&nbsp;</li><li>The MDL and precision were assessed using n=7 replicates of a 0.2 ppb water standard and n=7 replicates of a 0.5 ppb soil standard. Calculated MDLs were &lt;0.2ppb and RSDs of calculated results were &lt;10% for most compounds in both the soil and water matrices.</li><li>System robustness was tested by continuously acquiring 240 injections of environmental samples over three days with no user intervention at all. The average %RSD of the calculated concentration was 8.30% with an average compound recovery of 90%.</li></ul>

News from LabRulezGCMS Library - Week 49, 2025

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 12th January 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 brochure by<strong> Thermo Fisher Scientific!</strong></p><h3><strong>1. Agilent Technologies: Volatile PFAS in Cosmetics Using PAL3 Coupled with Triple Quadrupole 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_pfas_cosmetics_pal3_gc_tq_5994_8752en_agilent_52b56afd36.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Per- and polyfluoroalkyl substances (PFAS) are a large family of synthetic organic chemicals containing carbon chains where most or all the hydrogen atoms are replaced by fluorine. Due to the strength and stability of the carbon‑fluorine bond, PFAS tend to be very stable and chemically inert, which makes them both very useful in various applications and resistant to degradation. This persistence causes environmental contamination and bioaccumulation in humans and wildlife; as a result, PFAS are often labeled "forever chemicals".<sup>1</sup>&nbsp;</p><p>In cosmetics, PFAS are valued for their functional properties, including emulsification, stabilization, and water or sweat resistance. Despite these benefits, concerns have grown over their safety due to direct exposure from repeated use through skin, eyes, and mouth. The OECD's 2024 report underscores the risks associated with PFAS in cosmetic formulations, particularly given their potential for long-term health and environmental impacts.<sup>2,3</sup> Regulators around the world are taking decisive steps to ban or restrict PFAS in cosmetics. For example, in the EU, various types of PFAS have been regulated under REACH and POPs regulations that span most industries, including cosmetics.<sup>4,5</sup> EU Cosmetics Regulation (EC) No. 1223/2009 has listed the five types of PFAS as the substances prohibited.<sup>6</sup> A broader EU-wide ban is underway, with France having passed its own ban on PFAS in cosmetics effective 1 January 2026, as part of a larger proposal to ban PFAS in consumer products.<sup>7,8</sup> The US has not banned the use of PFAS in cosmetics at the federal level yet. The USFDA has been evaluating the use of PFAS in cosmetics under the authority of the Cosmetic Regulatory Modernization Act (MoCRA), and is expected to release a report on safety and risk by the end of 2025.<sup>9</sup> Although the federal government is still on the sidelines, many states in the US have been rapidly enacting or implementing the ban and reporting requirements for PFAS in cosmetics, with effective dates ranging from 2025 to 2032.<sup>10-13</sup> Canada has proposed a ban on the use of PFAS in various consumer products, including cosmetics.<sup>14</sup> South Korea has added 12 PFAS into a restricted substances list for cosmetic products in 2024.<sup>15</sup> The Environmental Protection Authority (EPA) of New Zealand has officially announced a ban on the use of PFAS in cosmetic products, effective from 31 December 2026.<sup>16&nbsp;</sup></p><p>As regulations surrounding PFAS continue to evolve, developing a sensitive and robust analytical method is crucial to meet stringent guidelines. The objective of this study was to demonstrate a fully automated workflow using PAL3&nbsp;Series&nbsp;2 RTC autosampler coupled with an Agilent 7010D triple quadrupole GC/MS to quantify more than 30&nbsp;volatile PFAS analytes in cosmetics. The automation method performance includes sensitivity, accuracy, and precision studies.</p><h4><strong>Experimental</strong></h4><h5><strong>Instrumentation&nbsp;</strong></h5><p>An <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890+GC"><strong>Agilent 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 HES 2.0 ion source, coupled with a <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=PAL3"><strong>PAL3</strong></a> Series 2 RTC autosampler, was used for this analysis. An MMI inlet and splitless liner (part number 5190-2293) were used and chromatographic separation was performed using an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=J%26W+DB-624"><strong>Agilent J&amp;W DB-624</strong></a>, 30 m × 0.25 mm, 1.40 μm column (part number 122-1334UI). The instrument setup is shown in Figure 1. The acquisition method for 34 native PFAS and four ISTDs, including GC condition, TQ parameters were described in a previous application note.17</p><h4><strong>Sample analysis&nbsp;</strong></h4><p>Seven cosmetic samples from various brands—including foundations, lipsticks, and mascaras—were analyzed. One liquid foundation was designated as a quality control (QC) sample, while the remaining six were treated as unknowns. According to the OECD report published in 2024, cosmetic products such as shampoo, eye makeup, foundation, facial cleansers, lipsticks, and lip glosses may contain PFAS, which serve functional or performance-enhancing roles.2,19 In this study, several PFAS compounds were detected above the method detection limit (MDL) in the unknown samples, including 10:2 FTOH, MeFHxSA, MeFOSE, EtOSE and 1H,1H‑perfluorooctyl acrylate. The results also demonstrated that the automated workflow is effective for PFAS extraction and quantitation in cosmetic matrices.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>An accurate and robust automated workflow was successfully developed using the PAL3 Series 2 RTC autosampler coupled with the Agilent 7010D GC/TQ system for the analysis of volatile PFAS in cosmetic products. Most PFAS targets achieved an LOQ of 50 µg/kg and MDL below 1.5 µg/kg, with recoveries falling within the acceptable range of 60% to 110%. These results demonstrate excellent extraction efficiency and reliability of the automated workflow. Furthermore, automation significantly reduces human error and enhances productivity, while maintaining high sensitivity in PFAS analysis.</p><h3><strong>2. Shimadzu: Simplifying Multicomponent Quantitative Analysis of Organic Compounds with the Polyarc Microreactor for GC</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_00945_en_9f7adeedc4.pdf"><strong>Full PDF for download</strong></a></li></ul><h4><strong>User Benefits&nbsp;</strong></h4><ul><li>The Polyarc system converts organic compounds eluting from the column into methane, enabling sensitivity to be normalized to carbon concentrations.&nbsp;</li><li>Even for compounds containing heteroatoms or unsaturated bonds, which tend to show lower sensitivity with FID, the Polyarc reduces response differences.&nbsp;</li><li>Because the response is normalized, fewer calibration curves are required even for multicomponent sample analysis.</li></ul><p>The Flame Ionization Detector (FID), the most widely used detector for GC, is used for quantitative analysis across a wide range of fields because it can detect almost all organic compounds. However, FID can exhibit sensitivity differences depending on the compound type, such as compounds containing heteroatoms (e.g., oxygen or nitrogen) or those with unsaturated bonds (for details, refer to Application News No.01-01033-EN). As a result, conventional quantitative methods using calibration curves— including external standard methods— typically require a separate calibration curve for each target analyte. This application introduces a case study analyzing a mixed solution of eleven compounds with different functional groups using the Polyarc, a GC microreactor. While compounds exhibit varying sensitivity with FID detection, the Polyarc system reduces sensitivity differences between compounds and facilitates quantitative analysis through simplified calibration curve creation.</p><h4><strong>Overview of the Polyarc</strong></h4><p>The <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?search=Polyarc"><strong>Polyarc</strong></a> is a post-column microreactor installed between the column and the FID. The main unit is mounted on the GC’s top panel. A schematic isshown in Fig. 1. Organic compounds introduced into the Polyarc via the column are fully converted to methane in two steps—oxidation followed by reduction (Fig. 2)—and are ultimately detected by FID. Because the FID detects methane, sensitivity is determined by the number of carbons, regardless of the original organic compound’s functional groups. For example, 1 mol of 1- propanol (C<sub>3</sub>H<sub>8</sub>O) is detected as 3 mol of methane.</p><h4><strong>Analytical Conditions&nbsp;</strong></h4><p>In this application, the sample was prepared by dissolving nheptane, cyclohexane, toluene, o-xylene, methyl ethyl ketone (MEK), tetrahydrofuran (THF), N,N-dimethylformamide (DMF), butyl acetate, propylene glycol monomethyl ether acetate (PMA), pyridine, and 1,2-dichloroethane in methanol so that each compound was 500 ppm (v/v%). Analytical conditions are shown in Table 1. The instrument used was a <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=Nexis+GC-2030"><strong>Nexis GC-2030</strong></a> equipped with the Polyarc Ultra was used.(Fig. 3) Polyarc can be installed on both the Nexis GC-2030 and the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=Brevis+GC-2050"><strong>Brevis GC-2050</strong></a>. Additionally, in this application, N2 was used as the carrier gas for affordability and safety, enabling cost-effective analysis.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>Analyzing multicomponent samples with a Polyarc confirmed that sensitivity differences due to functional groups can be reduced. Compounds containing heteroatoms or unsaturated bonds can be analyzed with relative response comparable to hydrocarbons when a Polyarc is used. Peak area reproducibility was excellent, with %RSD &lt; 1. Additionally, it was confirmed that analyzing at least one compound of known concentration enables quantitation of compounds with unknown concentration—i.e., calibration curve preparation can be omitted.</p><p>Table 5 summarizes the benefits of using a Polyarc system. The Polyarc simplifies multicomponent quantitative analysis and enables high-sensitivity analysis of compounds that are poorly detected by FID. Note that for certain compounds, adsorption in the inlet or similar effects may prevent achieving a relative response equivalent to that of saturated hydrocarbons.</p><h3><strong>3. Thermo Fisher Scientific: Targeted MS quantitation - Controlled and accessed from anywhere (Thermo Scientific™ Chromeleon™ 7.4 software)</strong></h3><ul><li>Brochure</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/BR_70660_CDS_Chromeleon_BR_70660_EN_a0bf1ab440.pdf"><strong>Full PDF for download</strong></a></li></ul><p><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/76"><strong>Thermo Scientific™ Chromeleon™ 7.4 software</strong></a> is presented as a centralized, server-based data system designed to consolidate mass spectrometry laboratories by connecting instruments, users, and data within a single, scalable platform. It enables secure access to data and instruments from anywhere, while centrally managing methods, templates, and reports to streamline daily laboratory operations.</p><p>The software is fully optimized for targeted MS quantitation workflows, offering native control of Thermo Scientific single and triple quadrupole as well as high-resolution accurate mass (HRAM) MS instruments. Advanced data processing tools support targeted quantitation, screening, intact mass deconvolution, MSⁿ library searching, and customizable reporting, making Chromeleon suitable for biopharma, environmental, and food safety applications.</p><p>A strong emphasis is placed on compliance and data integrity. Chromeleon 7.4 supports GxP, ISO, and 21 CFR Part 11 requirements through granular user controls, audit trails, electronic signatures, and versioned results. Built-in network failure protection, centralized databases, and secure remote access ensure high availability, resilience, and scalability from small on-premise installations to multi-site or cloud deployments.</p><p>The brochure also highlights Chromeleon’s role in advanced bioanalysis and environmental workflows, including intact protein characterization, multi-attribute methods (HR-MAM), PFAS analysis, pesticides, dioxins, and PCBs. Integration with complementary Thermo Scientific software further enables end-to-end workflows from compliant data acquisition to targeted processing, reporting, and long-term data management.</p>

News from LabRulezGCMS Library - Week 03, 2026

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 15th June 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 brochure by <strong>Agilent Technologies, </strong>application note<strong> </strong>by<strong> Shimadzu</strong>, presentation by <strong>MDCW / Institut d’Investigació Sanitària Pere Virgili </strong>and poster by<strong> Waters Corporation!</strong></p><h3><strong>1. Agilent Technologies: </strong><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8860B"><strong>Agilent 8860B Gas Chromatograph</strong></a></h3><ul><li>Brochure</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/ds_8860_gas_chromatograph_5994_9066en_agilent_f4d445178f.pdf"><strong>Full PDF for download</strong></a></li></ul><section><div><div><div><div><div><div><p>The <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8860B"><strong>Agilent 8860B gas chromatograph</strong></a> delivers reliable, repeatable performance for routine analyses, combining proven GC expertise with simplified operation. A bright color touchscreen provides quick access to system setpoints, configuration details, flowpath information, and live signal plots to easily monitor run progress. For deeper control, the built‑in Agilent GC Assist interface—optimized for tablets, PCs, and mobile devices—offers advanced system intelligence, including remote status checks, self‑guided diagnostics, maintenance tools, and method and sequence&nbsp;editing. The 8860B supports full electronic pneumatics control (EPC) or electronic pneumatics regulation (EPR), enabling precise, automated or electronically adjusted gas management. Both EPC and EPR use robust 7th‑generation microchannel architecture, designed for superior protection against contaminants and improved long-term reliability.</p><h4><strong>GC system capabilities&nbsp;</strong></h4><ul><li><strong>Retention time repeatability: </strong>&lt; 0.03% or 0.003 minutes&nbsp;</li><li><strong>Area repeatability:&nbsp;</strong><ul><li>&lt; 1.0% RSD&nbsp;</li><li>The 8860B display comes with physical start/stop buttons for manual analysis&nbsp;</li><li>Easy access to maintenance and service modes from the GC&nbsp;Assist interface, including autonomous leak checks&nbsp;</li><li>The GC Assist interface provides remote connectivity enabling you to monitor your smart GC system, check system logs, and perform diagnostics tests, from inside or outside the laboratory&nbsp;</li><li>Atmospheric pressure and temperature compensation are built into every system, so results do not change, even when the laboratory environment does.</li></ul></li><li><strong>Simultaneously supports&nbsp;</strong><ul><li>Two inlets&nbsp;</li><li>Three detectors &nbsp;</li><li>Support for up to any combination of three valves total:&nbsp;<ul><li>Up to four heated gas sample valves&nbsp;</li><li>Up to two liquid sampling valves&nbsp;</li></ul></li><li>Dual sample introduction capabilities:&nbsp;<ul><li>Supports two <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=7693A"><strong>7693A</strong></a> autoinjectors with capacity for 16&nbsp;sample vials&nbsp;</li><li>Supports one 7693A autoinjector and automatic sampler tray with capacity for 150 sample vials&nbsp;</li><li>Supports one 7650A autoinjector with capacity for 50 sample vials with one 7693A with capacity for 16&nbsp;sample vials&nbsp;</li><li>Supports one <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=PAL3"><strong>PAL3</strong></a> autosampler&nbsp;</li></ul></li></ul></li><li><strong>Instrument dimensions&nbsp;</strong><ul><li><strong>Height:</strong> 49 cm (19.2 in)&nbsp;</li><li><strong>Width:</strong> 58 cm (22.9 in), 68 cm with side-mounted detector&nbsp;</li><li><strong>Depth</strong>: 54 cm (21.3 in)&nbsp;</li><li><strong>Typical weight</strong>: 51 kg (112 lb)</li></ul></li></ul><h3><strong>2. MDCW / Institut d’Investigació Sanitària Pere Virgili: GcDUO: A Batch Processing Framework Integrating PARAFAC and PARAFAC2 for GC×GC-MS Data Analysis</strong></h3><ul><li>Presentation</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/O_10_Llambrich_54914668f8.pdf"><strong>Full PDF for download</strong></a></li></ul><section><div><div><div><div><div><div><p>The presentation introduces <strong>GcDUO</strong>, an open-source batch-processing framework developed for the analysis of comprehensive two-dimensional gas chromatography–mass spectrometry (GC×GC-MS) data. The tool was designed to address one of the main challenges in GC×GC-MS workflows: extracting meaningful chemical information from highly complex multidimensional datasets while reducing dependence on proprietary software. GcDUO combines the strengths of <strong>PARAFAC</strong> and <strong>PARAFAC2</strong> chemometric algorithms to perform automated peak detection, deconvolution, compound annotation, and quantification across large batches of samples.</p><p>The workflow begins with raw GC×GC-MS data imported from CDF files and converted into a four-dimensional matrix. Regions of interest (ROIs) are automatically selected using a watershed algorithm, allowing relevant chromatographic features to be isolated from the background. PARAFAC decomposition is then applied to separate overlapping compounds into their individual first-dimension retention times, second-dimension retention times, and mass spectra. Compound identification is performed using spectral similarity calculations, retention index information, and comparison against reference libraries, creating a consensus-based annotation strategy that improves confidence in identifications.</p><p>To further improve quantitative performance, GcDUO incorporates a constrained PARAFAC2 approach that can model chromatographic peak shifts between samples while preserving accurate peak integration. The framework was evaluated using benchmark GC×GC datasets containing fragrances, allergens, food-related compounds, and breath-analysis samples. Validation studies showed strong detection and annotation performance, including successful identification of most compounds in independent datasets such as FruityBeer and BreathMix. Quantitative comparisons with the widely used <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/41"><strong>ChromaTOF software</strong></a> demonstrated highly comparable retention times and peak areas for a range of volatile compounds, indicating that GcDUO can deliver results similar to established commercial platforms.</p><p>The authors conclude that GcDUO provides a powerful open-source alternative for GC×GC-MS data processing. The framework supports automated deconvolution, annotation, and quantification without requiring strict trilinearity assumptions often associated with traditional chemometric approaches. Although computational cost and user expertise remain important considerations, GcDUO offers performance comparable to gold-standard commercial software while expanding access to advanced GC×GC-MS data analysis for metabolomics, environmental, food, fragrance, and other analytical applications. The software is freely available through GitHub, supporting broader adoption and further development by the scientific community.</p><h3><strong>3. Shimadzu: Discrimination of Coffee Bean Species Based on Aroma Compounds</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_01123_en_c8ac025ba9.pdf"><strong>Full PDF for download</strong></a></li></ul><h5><strong>User Benefits</strong></h5><ul><li>Qualitative analysis of aroma compounds can be easily performed using the Smart Aroma Database.</li><li>Intuitive statistical analysis and exploration of characteristic compounds are possible using eMSTAT Solution.</li><li>The AOC -6000 multifunctional autosampler system enables the analysis of aroma compounds without sample pretreatment.</li></ul><p>Common coffee bean types are broadly classified into two types: Coffea arabica (Arabica) and Coffea canephora (Robusta). Among them, Arabica is superior in flavor and is highly favored as a specialty beverage. However, in recent years, there have been multiple reports of products sold claiming to be 100% Arabica while being adulterated with Robusta<sup>1)</sup>. A reported method for discriminating between the two is the analysis of lipophilic extracts of coffee beans using a benchtop NMR spectrometer<sup>1)</sup>. This method uses 16-O-Methylcafestol, which is present in Robusta but almost undetectable in Arabica, as a marker. However, it requires complicated pretreatment such as extraction and concentration.&nbsp;</p><p>Therefore, in this Application News, we investigated a method to discriminate between Arabica and Robusta more easily and rapidly using GC-MS/MS and the statistical analysis software eMSTAT Solution.</p><h5><strong>Sample and Analytical Methods&nbsp;</strong></h5><p>Commercially available coffee beans roasted at the same roastery were used as samples. Four brands of Arabica (Kilimanjaro, Brazil Bourbon, Mandheling G1, Brazil No.2 #18) and two brands of Robusta (Vietnam Robusta, Java Robusta) were prepared (Table 1). Each brand was individually crushed with a mill, and 1 g was weighed and sealed in a screw vial.</p><p>Volatile compounds were concentrated and introduced into the GC-MS using the HS-SPME method and then analyzed under the conditions registered in the GC-MS(/MS) Smart Aroma Database (Table 2). The <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GCMSTQ8040+NX"><strong>GCMS-TQTM8040 NX</strong></a> and the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=AOC-6000"><strong>AOC-6000 multifunctional autosampler</strong></a> system were used as the analytical instruments (Fig. 1). To verify whether rapid analysis is possible, a temperature ramp of 10˚C/min was adopted, and a low-polarity column was used to obtain stable retention times for each compound. Data acquisition was performed in Scan mode or MRM mode, and each sample was analyzed three times.</p><h4><strong>Exploration of Characteristic Aroma Compounds for Arabica and Robusta&nbsp;</strong></h4><p>Next, we investigated which compounds contribute to the discrimination between Arabica and Robusta. The PCA score plot (Fig. 4) reflects the differences in the tendencies of each group, with Arabica distributed on the left side and Robusta on the right side, clearly separated along the first principal component (PC1) axis. Referring to the corresponding loading plot, compounds located on the left side of the origin tend to have higher area values in Arabica, which is also positioned on the left in the score plot. On the other hand, compounds on the right side tend to show higher values in Robusta, which is located on the right in the score plot. In other words, the difference in the balance of these compoundsisthe main factorseparating the two groups. First, Arabica was commonly rich in compounds such as 5-Methyl furfural, Acetoin, and Furaneol acetate. MS chromatograms analyzed using LabSolutions Insight GCMS are shown in Fig. 7. In eMSTAT Solution, not only score plots and loading plots but also box plots can be easily drawn, making it possible to easily visualize and compare the distribution tendencies of each compound. From the box plots of the above compounds (Fig. 8), it was visually confirmed that all of them are contained in abundance in Arabica. These compounds are sometimes described as having a roasted or creamy quality, and it can be inferred that this result supports the characteristics of Arabica, which issuperior in aroma and acidity.&nbsp;</p><p>On the other hand, a compound found in abundance in Robusta was p-Vinylguaiacol. This compound is known to cause an offflavor similar to a medicinal odor in sake, and its content was low in Arabica. From this, it was suggested that p-Vinylguaiacol may be one of the compounds contributing to the bitterness and offtastes characteristic of Robusta.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>In this Application News, we investigated the discrimination of coffee bean types based on aroma compounds using the triple quadrupole gas chromatograph mass spectrometer <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GCMSTQ8040+NX"><strong>GCMSTQ8040 NX</strong></a> and the GC-MS(/MS) <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=Smart+Aroma+Database"><strong>Smart Aroma Database</strong></a> for aroma analysis.&nbsp;</p><p>Four types of Arabica and two types of Robusta were analyzed as samples. Analysis using Scan data confirmed a tendency for the two types to separate. Subsequently, data was acquired in MRM mode, which offers higher sensitivity and selectivity, and detailed analysis was performed using the statistical analysis software eMSTAT Solution. As a result, the two groups were clearly separated in PCA and cluster analysis, demonstrating the effectiveness of discrimination by this method. Additionally, a discrimination model was developed and validated, confirming that highly accurate discrimination is possible.&nbsp;</p><p>From the above results, we conclude that the discrimination of coffee beans by aroma compound analysisis highly feasible using this method. Furthermore, this method enables a comprehensive workflow, from discrimination to the identification of characteristic compoundsfor each type.</p><h3><strong>4. Waters Corporation: Improvements to the Analysis of PBDEs in Environmental Matrices: Transitioning from EI Magnetic Sector to GC-APCI TQ MS/MS</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/720009372_7abfa9f0e9.pdf"><strong>Full PDF for download</strong></a></li></ul><p>This poster evaluates the transition of polybrominated diphenyl ether (PBDE) analysis in environmental samples from traditional electron ionization high-resolution magnetic sector GC-MS to a modern <strong>GC-APCI triple quadrupole MS/MS (GC-APCI TQ MS/MS)</strong> workflow. PBDE flame retardants are highly regulated due to their environmental persistence and potential health risks, making accurate and reliable analytical methods essential. The study investigated whether a GC-APCI MS/MS approach could match or exceed the performance of established GC-HRMS methods while offering greater flexibility and modernization opportunities.</p><p>The method was developed on a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/554"><strong>Waters Xevo TQ Absolute mass spectrometer</strong> </a>equipped with APCI ionization and an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890"><strong>Agilent 8890 GC</strong></a>. A key innovation was the use of <strong>nitrogen as the carrier gas instead of helium</strong>, helping laboratories reduce dependence on helium supplies and mitigate increasing helium costs. By applying nitrogen flow ramping, the authors maintained chromatographic resolution and runtime comparable to the reference helium-based method without requiring changes in column dimensions. The approach also reduced the risk of thermal degradation of highly brominated compounds such as BDE 209 and achieved faster elution while preserving peak shape and separation quality.</p><p>For quantitative analysis, up to six MRM transitions per analyte were monitored, taking advantage of the characteristic isotope patterns of brominated compounds. The use of multiple transitions improved selectivity and sensitivity, while Waters waters_connect software enabled summation of MRM signals to enhance signal-to-noise ratios near detection limits. Excellent calibration performance was achieved across more than three orders of magnitude, with correlation coefficients above 0.999 for all analytes. Internal standards and recovery standards demonstrated strong reproducibility, and quality control samples showed precision typically below 15% RSD and acceptable accuracy across low, medium, and high concentration levels.</p><p>The authors conclude that an all-nitrogen GC-APCI TQ MS/MS configuration can successfully meet the performance criteria established for PBDE analysis by reference EI GC-HRMS methods. The workflow maintains critical chromatographic separations, delivers accurate quantitative results, and offers a platform that could potentially combine PBDE determination with other halogenated flame retardants in a single analytical method. These findings demonstrate that GC-APCI TQ MS/MS represents a robust and practical modernization strategy for environmental PBDE analysis.</p></div></div></div></div></div></div></section></div></div></div></div></div></div></section>

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