Oxidative Polymerization of Organic Compounds in the Presence of Iron-Bearing Minerals: Implications for Organic Preservation on Mars

<p><strong>In the week of July 20, 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><h5><strong>1. Separation Science: Expert Answers: GC Troubleshooting and Method Development</strong></h5><ul><li>We, 22.7.2026 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6343">Registration</a></li></ul><p>Master GC troubleshooting and method development. Join Diane Turner to explore practical strategies for optimizing parameters and resolving common system issues.</p><h5><strong>2. Shimadzu Corporation: Powering Energy Security and the Energy Transition: Advanced Analytical Solutions for Petroleum and Renewable Fuels</strong></h5><ul><li>Th, 23.7.2026 08:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6387">Registration</a></li></ul><p>Discover Shimadzu workflows for sustainable aviation fuel (SAF), biodiesel, and petrochemical analysis using Nexis GC-2060, TOGAS, System GC, GC-SCD, LC, and SICRIT GC-LCMS coupling.</p><h5><strong>3. Restek Corporation: Basics. Principles of GC</strong></h5><ul><li>Th, 23.7.2026 14:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6388">Registration</a></li></ul><p>Learn the fundamentals of gas chromatography, including GC instrument components, column selection, and stationary phase selectivity for effective compound separation.</p><h5><strong>4. Agilent Technologies: The Hidden Challenges of Permanent Gas Analysis and How to Solve Them</strong></h5><ul><li>Th, 23.7.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6344">Registration</a></li></ul><p>Learn how to overcome common challenges in permanent gas analysis through practical strategies for improving accuracy, reliability, and analytical performance.</p><h5><strong>5. SelectScience: Advancing PFAS Analytics Across Complex Matrices</strong></h5><ul><li>Fr, 24.7.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6347">Registration</a></li></ul><p>Advance your PFAS analysis. Learn how automated micro solid-phase extraction (µSPE) improves sensitivity for ultra-short and long-chain PFAS across complex sample matrices.</p>

Webinars LabRulezGCMS Week 30/2026

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 20th July 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 posters by <strong>Agilent Technologies / ASMS,&nbsp;</strong> <strong>Bruker / ASMS</strong>, presentation by <strong>MDCW / University of North Dakota </strong>and application note by <strong>Shimadzu!</strong></p><h3><strong>1. Agilent Technologies / ASMS: Extractables Analysis of Food Contact Materials Using High-Resolution GC/MS and LC/MS</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/po_fcm_extractables_lc_q_tof_wp_311_asms_2026_en_agilent_f5d83c8730.pdf"><strong>Full PDF for download</strong></a></li></ul><section><div><div><div><div><div><div><p>Chemicals residing in food contact materials (FCM) can migrate from packaging and containers into food. The FCM include a variety of materials including paper and plastic among others. The substances that migrate from FCM include volatile, semi-volatile and non-volatile compounds and therefore a combination of GC/MS and LC/MS techniques is needed for comprehensive analysis of potential migrants. In this study we evaluated different types of FCM including food vacuum sealer bags, heavy duty plastic food containers as well as lined paperboard containers. Various solvents were assessed for their ability to extract different classes of food packaging-derived chemicals. For increased confidence in compound annotation, high-resolution GC and LC MS platforms were used in this study in combination with application-specific accurate mass libraries.</p><h4><strong>Experimental</strong></h4><h5><strong>GC/Q-TOF&nbsp;</strong></h5><ul><li><strong>MS:</strong> <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?from=1990&amp;mainauthorItems=10&amp;search=7250&amp;to=2026"><strong>Agilent 7250 GC/Q-TOF</strong></a></li><li><strong>GC: </strong><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?from=1990&amp;mainauthorItems=10&amp;to=2026&amp;search=8890"><strong>Agilent 8890 GC</strong></a></li><li><strong>Column: </strong><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?from=1990&amp;mainauthorItems=10&amp;to=2026&amp;search=DB-5Q"><strong>Agilent DB-5Q</strong></a>, 30 m, 0.25 mm, 0.25 µm</li></ul><h5><strong>LC/Q-TOF</strong></h5><ul><li><strong>LC: </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=1290+Infinity+II"><strong>Agilent 1290 Infinity II</strong></a></li><li><strong>MS: </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=Revident"><strong>Agilent Revident LC/Q-TOF</strong></a></li><li><strong>Analytical column:</strong> <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=Poroshell+Aq-C18"><strong>Agilent Poroshell Aq-C18</strong></a> 2.1 x 150 mm, 2.7µm column</li></ul><h4><strong>Conclusions</strong></h4><p>FCM extractions were optimized and successfully analyzed using a variety techniques based on highresolution GC/MS and LC/MS. Combination of different high resolution MS techniques helped to ensure a comprehensive E&amp;L compound coverage. E&amp;L focused accurate mass libraries were key to efficient data analysis.</p><h3><strong>2. Bruker / ASMS: Novel data processing workflow including in-silico derivatization for integrated CI &amp; EI MS data acquired with the GC-ecTOF instrument</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/asms_2026_thp_429_in_silico_derivatization_for_integrated_ci_ei_ectof_fb022d26ba.pdf"><strong>Full PDF for download</strong></a></li></ul><section><div><div><div><div><div><div><p>Combined suspect and non-target GC-MS analysis of volatile and semi-volatile compounds holds relevance for environmental monitoring &amp; research, food, flavor &amp; fragrance analysis as well as metabolomics studies. The combination of Chemical Ionization (CI) and Electron Ionization (EI) in the ecTOF instrument (Bruker Daltonics, Bremen, Germany) can improve the identification confidence of unknown compounds, especially in complex samples and when no standards are available. The simultaneous usage of two complementary ionization techniques brings additional advantages for quantification workflows. To leverage these benefits, a novel data processing approach has been developed, and applicability is shown in two study designs.</p><h4><strong>Methods</strong></h4><p>Derivatized samples from two studies were analyzed using the GC-ecTOF instrument. Data were converted to TSF format and processed with prototype versions of MetaboScape and TASQ. Untargeted feature detection was performed on the CI data stream, including de-isotoping, de-adducting for CI-specific ions [M-H]⁺, [M]⁺, [M+H]⁺, [M+NH₄]⁺, [M-CH3 ] + and retention time alignment across all samples.</p><h4><strong>Conclusion</strong></h4><ul><li>Untargeted feature finding and streamlined annotation of ecTOF supported by in-silico derivatization and in-silico fragmentation extends GC-MS analysis for metabolomics and non-target screening.&nbsp;</li><li>In-silico derivatization permits complementary annotation for compounds lacking reference standards.&nbsp;</li><li>Simplified process from identified markers in profiling experiments to target screening and quantitation methods.</li></ul><h3><strong>3. MDCW / University of North Dakota: Identifying the transition from ante-mortem to post-mortem odor in cadavers cadavers in an outdoor environment</strong></h3><ul><li>Presentation</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/O_23_Patel_2a1bb7a2fa.pdf"><strong>Full PDF for download</strong></a></li></ul><section><div><div><div><div><div><div><p>This presentation investigates how the characteristic odor of a human body changes during the transition from life (ante-mortem) to decomposition (post-mortem). The researchers focused on identifying volatile organic compounds (VOCs) released during the early post-mortem period and determining when the scent profile changes from that of a living person to that associated with human remains. Understanding this transition is particularly important for improving search and rescue operations, where distinguishing between living victims and deceased individuals is essential for deploying search-and-rescue dogs and human remains detection dogs effectively.</p><p>To study this process, VOC samples were collected from body donors at both a morgue and an outdoor decomposition research facility (REST). Air samples were collected using sorbent tubes and ACTI-VOC pumps after controlled VOC accumulation and sampling periods. Chemical analysis was performed using <strong>thermal desorption comprehensive two-dimensional gas chromatography coupled with mass spectrometry (TD-GC×GC-MS)</strong>. The analytical system employed a Restek <strong>Rxi®-624Sil MS</strong> first-dimension column and a <strong>Stabilwax®</strong> second-dimension column, with electron ionization (70 eV) mass spectrometry covering a mass range of <strong>29–300 amu</strong> at an acquisition rate of <strong>250 spectra/s</strong>. Data processing combined <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/41"><strong>ChromaTOF</strong></a> software with <strong>RStudio</strong> for feature alignment, normalization, filtering, and manual verification of VOC profiles.</p><p>The study identified <strong>827 volatile organic compounds</strong>, representing a wide range of chemical classes including nitrogen-containing compounds, esters, halogenated compounds, aromatics, alcohols, ketones, aldehydes, sulfur-containing compounds, ethers, and acids. By comparing experimentally detected VOCs with compounds previously reported in the literature for both living humans and decomposing remains, the researchers identified <strong>33 trans-mortem VOCs</strong> that characterize the transition between ante-mortem and post-mortem odor. VOC profiles were then monitored throughout decomposition for individual donors, allowing the team to visualize how the relative contributions of ante-mortem, trans-mortem, and post-mortem compounds evolved over time.</p><p>The results showed that ante-mortem and trans-mortem VOCs remained detectable during the earliest stages after death, while post-mortem odor compounds became increasingly dominant after approximately <strong>Accumulated Degree Days (ADD) 73.4</strong>, corresponding to <strong>Experimental Day 3</strong>. The authors conclude that although these findings improve our understanding of early decomposition odor chemistry, additional studies across different environments and seasonal conditions are needed to standardize VOC-based approaches and further support forensic investigations and search-and-rescue applications.</p><h3><strong>4. Shimadzu: Gas Analysis for CO2 Conversion Using a GI-30 Auto Gas Injector</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_00964_en_2482908145.pdf"><strong>Full PDF for download</strong></a></li></ul><p>The catalytic conversion of carbon dioxide (CO2) to methanol (MeOH) and to hydrocarbons has garnered significant attention as a strategy to realize a sustainable chemical industry. Analytical targets in CO2 conversion studies typically include carbon monoxide (CO), hydrocarbons, alcohols, and other reaction products. Selection of appropriate column and detector combinations must therefore be guided by the nature and concentrations of target analytes.</p><p>In this application news, we demonstrate simultaneous analysis on two parallel columns by using INJ2-way branch unit to permit detection of CO and hydrocarbons together with alcohols such as MeOH. We also present a simplified measurement approach employing a single-column configuration equipped with a thermal conductivity detector(TCD).</p><h4><strong>System Configuration and Analysis Conditions</strong></h4><p>Two reaction schemes using CO2 as feedstock were envisaged: (1) MeOH synthesis and (2) conversion to hydrocarbons. The instrumentation comprised the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?from=1990&amp;mainauthorItems=1&amp;to=2026&amp;search=GI-30"><strong>Auto Gas Injector GI-30</strong></a> and the SPI inlet, which minimizes air ingress and sample adsorption (Fig. 1).&nbsp;</p><p>For the MeOH synthesis application, a Jetanizer -FID—which permits detection of CO and CO2 that are not observable by a conventional FID—was employed. A MICROPACKED-ST packed column provides separation of CO from O2 (ambient contamination); however, higher-boiling hydrocarbons and alcohols such as MeOH are not eluted from this column. To achieve comprehensive analysis, the injector was splitted and an SH-Q-BOND capillary column was used to resolve hydrocarbons and MeOH concurrently. The injection-port splitting is implemented using dedicated hardware (Application News No. 01-00661-EN).&nbsp;</p><p>For the conversion to hydrocarbons scenario, when analytes are permanent gases and C3-or-smaller hydrocarbons, quantitative analysis can be performed with a single MICROPACKED-ST column coupled to a TCD. The TCD responds to differences in thermal conductivity between carrier and analyte gases; measuring low–thermal-conductivity species such as hydrocarbons requires a carrier gas with high thermal conductivity (helium or hydrogen) (Table 1). The <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?from=1990&amp;mainauthorItems=1&amp;search=gc-2050&amp;to=2026"><strong>Brevis</strong> <strong>GC-2050</strong></a><strong> TCD</strong> uses a single filament design, resulting in rapid baseline stabilization (~10 minutes), which is advantageous for routine operation.</p><h4><strong>Conclusion</strong></h4><p>Using INJ2-way branch unit enables simultaneous analyses using distinct column-detector combinations within a single chromatographic cycle, permitting comprehensive quantification of reaction products from CO2 conversion— ranging from CO and hydrocarbons to alcohols such as MeOH. For analyses restricted to hydrocarbons up to C3, a streamlined single-column TCD configuration provides sufficient separation and sensitivity. It should be noted that MeOH and hydrocarbons of carbon number ≥ C4 may adsorb or be retained on the MICROPACKED-ST column; periodic column conditioning is therefore recommended.</p></div></div></div></div></div></div></section></div></div></div></div></div></div></section></div></div></div></div></div></div></section>

News from LabRulezGCMS Library - Week 30, 2026

<p><strong>In the week of July 27, 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><h5><strong>1. Thermo Fisher Scientific: Powerful Isotopic Insights, Elevated</strong></h5><ul><li>Tu, 28.7.2026 10:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6366">Registration</a></li></ul><p>Be among the first to discover the next generation of Thermo Scientific Orbitrap IRMS and explore new possibilities for high-performance isotope ratio mass spectrometry.</p><h5><strong>2. Agilent Technologies: PFAS &amp; Our Planet: Textiles and Materials</strong></h5><ul><li>Tu, 28.7.2026 11:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6142">Registration</a></li></ul><p>Learn how evolving PFAS regulations affect textile and material testing. Discover LC-MS/MS workflows for extraction, contamination control, certification, and supply chain compliance.</p><h5><strong>3. Agilent Technologies: Fast, Non-Destructive Pharmaceutical Analysis with the Agilent TRS100</strong></h5><ul><li>We, 29.7.2026 07:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6390">Registration</a></li></ul><p>Accelerate pharmaceutical quality control with the Agilent TRS100. Learn how non-destructive analysis of intact tablets and capsules eliminates sample preparation while improving workflow efficiency.</p><h5><strong>4. Thermo Fisher Scientific: Drive Lab Collaboration and Efficiency with a Networked Chromatography and Mass Spectrometry Data System</strong></h5><ul><li>We, 29.7.2026 19:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6405">Registration</a></li></ul><p>Learn how deploying Thermo Scientific Chromeleon CDS in a networked environment centralizes laboratory data, simplifies software administration, strengthens compliance, and supports scalable multi-instrument chromatography and mass spectrometry workflows.</p>

Webinars LabRulezGCMS Week 31/2026

Thermal Dry Reforming of Bio-Oil Model Compounds

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 27th July 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 </strong>and<strong> Thermo Fisher Scientific, </strong>poster by <strong>MDCW / University of Washington </strong>and brochure by <strong>Shimadzu!</strong></p><h3><strong>1. Agilent Technologies: Routine Trace‑Level Analysis of m‑Xylene in High‑Purity p‑Xylene</strong></h3><p><strong>Using the </strong><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890B"><strong>Agilent 8890B GC system</strong></a></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_trace_analysis_m_xylene_high_purity_p_xylene_5994_9329en_agilent_508bcfb48c.pdf"><strong>Full PDF for download</strong></a></li></ul><section><div><div><div><div><div><div><p>The Agilent 8890B GC system builds on the exceptional performance of the Agilent 8890A GC, with the addition of many features designed to enhance the user experience for both new and expert‑level operators. This application note explores several use cases of these features applied to a challenging GC purity method—quantifying trace‑level m‑xylene (MX) in p‑xylene (PM). This separation requires careful balancing of optimized chromatographic parameters— speed, resolution, and sensitivity. Leveraging Agilent GC Assist features, including early maintenance feedback (EMF) counters and automated peak evaluation capabilities integrated into the 8890B GC, helps maximize method robustness and instrument uptime.&nbsp;</p><p>Though conceptually simple, separating and measuring small quantities of m‑xylene in p‑xylene is a challenge that requires precise instrument control and the highest‑quality GC parts and consumables. As both compounds are positional isomers and have nearly identical boiling points, separation has historically been achieved using a long and highly polar column, such as a polyethylene glycol "wax" phase. ASTM D7504 recommends a wax column with dimensions 60&nbsp;m × 0.320 mm and 0.25 µm phase thickness. A 0.50 µm phase thickness can be used for increased resolution.1 The separation is validated with a p‑xylene standard containing approximately 1,000 ppm m‑xylene. Measuring m‑xylene at significantly lower concentrations requires an increase in resolution between MX and PX, which can be accomplished by increasing the phase thickness of the column at the cost of increased peak broadening. This broadening negatively impacts the limit of detection (LOD) and the limit of quantification (LOQ) for MX and must be offset by reducing the inner diameter of the column to resharpen the peak. This application note demonstrates the use of 0.200 mm and 0.100 mm id wax columns to yield optimized separations, presenting the associated benefits and limitations of both&nbsp;separations.</p><h4><strong>Experimental</strong></h4><p>An <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890B"><strong>8890B GC</strong></a> was configured with an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=7650A"><strong>Agilent 7650A automatic liquid sampler</strong></a> (ALS), split/splitless (SSL) inlet, and flame ionization detector (FID). Two columns were used to explore two different separation speeds—a faster separation with less sample capacity using an Agilent J&amp;W DB‑WAX&nbsp;FF column, 20 m × 100 µm, 0.2 µm (p/n 127‑7023FF) and a higher‑resolution separation with more sample capacity using an Agilent <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=J%26W+HP%E2%80%91INNOWax"><strong>J&amp;W HP‑INNOWax</strong></a> column, 50 m × 200 µm, 0.4 µm (p/n 19091N‑205I). Both methods used hydrogen carrier gas, and Agilent Gas Clean filters were used to remove moisture, hydrocarbons, and oxygen from the carrier gas and FID hydrogen. The FID air was filtered for moisture and hydrocarbons. The GC configuration and method details can be found in Tables 1 and 2, respectively.</p><h4><strong>Results and discussion</strong></h4><p>Establishing and ensuring the method’s long‑term stability requires protecting the column stationary phase by limiting the amount of oxygen in the system. While carrier gas contamination is typically the largest source of unwanted oxygen, the inlet septum can also contribute to oxygen ingress as successive syringe injections create a hole, necessitating regular changing. The Agilent portfolio of consumables and supplies has several solutions specifically designed to overcome these challenges. The Gas Clean purification system features a carrier gas filter that removes oxygen, moisture, and hydrocarbons and includes a color‑changing visual indicator of filter life, which can be monitored remotely by the 8890B GC using an optional optical sensor. Advanced Green septa are engineered for low bleed and extended durability, further enhanced by using a Blue Line autosampler syringe with a tapered needle to reduce physical coring of the septum. Regular maintenance of these parts maximizes instrument uptime. The 8890B GC has several features designed to warn when maintenance is approaching, assist when maintenance is required, and track when maintenance is completed.</p><p>The 8890B GC features intelligent tracking of the ages of consumables using injection‑ and time‑based counters. These EMF counters feature two optional warning thresholds—"Service Warning" and "Service Due"—that are user‑configurable and function like the oil light on the dashboard of a vehicle, telling users of approaching maintenance. The EMF counters can be accessed directly through the GC touchscreen or through the GC Assist interface. Figure 1 shows an overview of the EMF counters for the front inlet, and Figure 2 presents the detailed history of septum maintenance, including a running tally of injections on the current septum. When performing maintenance on the 8890B GC using the guided maintenance process on the touch screen or GC Assist interface, the EMF counters are automatically reset at the end of the procedure and can also be reset manually. For this application, the EMF counters and appropriate warning thresholds for the septum, liner, syringe, column, inlet gold seal, and carrier gas filter will be explored.</p><h4><strong>Conclusion</strong></h4><p>The Agilent 8890B GC system—powered by the highest‑quality Agilent columns and supplies—delivers a robust, sensitive solution for measuring trace‑level m‑xylene (MX) in p‑xylene (PX). The Agilent J&amp;W HP‑INNOWax column produced the highest‑resolution separation and the best retention time stability, with an S/N ratio of 98.5 for 50&nbsp;ppm MX. The narrower Agilent J&amp;W DB‑WAX FF column yielded a 40% faster run time at the cost of lower resolution and retention time stability, with an S/N ratio of 27.7 for 50&nbsp;ppm MX. The integrated Agilent GC Assist features, peak evaluation and early maintenance feedback (EMF) counters, provide intelligent, automated monitoring of system and separation health, maximizing instrument uptime and supporting long‑term success with routine trace analysis.</p><h3><strong>2. MDCW / University of Washington: Developing 2D mzCompare for single GC×GC-TOFMS chromatograms: Substantial resolution enhancement in the context of statistical overlap theory</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/P_4_Wenjing_899f31a19e.pdf"><strong>Full PDF for download</strong></a></li></ul><section><div><div><div><div><div><div><p>Accurate identification of all detectable analyte components in a single comprehensive twodimensional (2D) gas chromatography time-of-flight mass spectrometry (<strong>GC×GC-TOFMS</strong>) chromatogram is a fundamental interest in the field. Herein, we developed a new algorithmic software approach called 2D mzCompare to generate accurate peak tables for GC×GCTOFMS. Extending from our original method for one-dimensional GC-MS data, the 2D mzCompare algorithm discovers selective mass channels (m/z) for each analyte to resolve overlapping peaks and improve analyte identification, leveraging the similarity in retention time and peak shape across m/z of the same analyte. The 2D mzCompare algorithm calculates the peak shape similarity between m/z at every modulation via lack-of-fit (LOF), followed by clustering and focusing steps, to generate a final peak table. To evaluate this software, we simulated realistic GC×GC-TOFMS data in the context of the statistical overlap theory (SOT), so the exact number and identities of analytes are known a priori. Utilizing an in-house mass spectrum library of similar compounds, GC×GC-TOFMS chromatograms were simulated with varying degrees of chromatographic saturation (𝛼2𝐷). First, we provide a new algorithmic approach, 2D mzCompare, to resolve overlapped analytes in GC×GCTOFMS data, and second, we validate the accuracy of the software performance using SOT.</p><h4><strong>Conclusions and Future Work</strong></h4><p>An extended algorithm, 2D mzCompare designed for intra-chromatogram comparison to enable rigorous analyte discovery and identification, was developed for GC×GC-TOFMS data. Within the context of SOT, 2D mzCompare increases separation resolution by computationally minimizing the 2D peak widths, enhancing 2D peak capacity and reducing the saturation factor. At low saturation factors (𝛼2𝐷= 0.01, 0.03, and 0.1), over 95% of the simulated components are found to be mathematically resolved singlets (pure analyte components) by 2D mzCompare, while approximately 62% were found at 𝛼2𝐷 = 1, exceeding predictions made by SOT. Using optimized 2D mzCompare parameters, improvements in 2Rs and 𝛼2𝐷 are about 12-fold, empirically validating SOT expectations. Furthermore, 2D mzCompare can be used as a preprocessing tool to determine or validate the “rank” (the number of analyte components) in overlapped regions of GC×GC-TOFMS chromatograms when combined with chemometric methods such as MCR-ALS or PARAFAC. Future studies will focus on applying the algorithm to real sample datasets.</p><h3><strong>3. Shimadzu: Meet The World’s First Multi-Mode FID In </strong><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GC-2060"><strong>Nexis GC-2060</strong></a></h3><ul><li>Brochure</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/s_gc_f33_3f7f48eead.pdf"><strong>Full PDF for download</strong></a></li></ul><h4><strong>High Performance And Low Maintenance Multi-Mode FID&nbsp;</strong></h4><p>The new FID-U (2.0) in the Nexis <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GC-2060"><strong>GC-2060</strong></a> reengineers conventional FID to maximize uptime and efficiency. With new Air and O2 makeup gas options, you can streamline your gas supply – saving cylinder costs and lab space. Its capabilities can be further expanded with Shimadzu’s proprietary Jetanizer and Polyarc microreactors.</p><h4><strong>Cylinder-Free FID Operation With Hy/Ox and Hy/Air Modes</strong>&nbsp;</h4><p>Routine operation with traditional FIDs is often costly and complex, requiring a three-gas setup: a He or N<sub>2</sub> makeup gas combined with H<sub>2</sub> and Air. The new FID simplifies your infrastructure by introducing Air and O<sub>2</sub> as makeup gas alternatives, unlocking true cylinder-free operation.* This helps to reduce running cost and cut helium usage.</p><h4><strong>Keep Your Bench Space As You Expand Your Analyte Coverage&nbsp;</strong></h4><p>Seamlessly integrate Jetanizer and Polyarc microreactors to boost detector response for weak or undetectable compounds. The new FID delivers simpler quantitation and broader analysis capabilities with zero extra footprint.</p><h4><strong>Jetanizer Mode (CO and CO2 Detection)&nbsp;</strong></h4><ul><li>Converts CO and CO2 to CH4 for detection&nbsp;</li><li>Enabled by simply replacing the FID nozzle&nbsp;</li></ul><h4><strong>Polyarc Mode (Single-Calibration Approach)&nbsp;</strong></h4><ul><li>Converts hydrocarbons, CO and CO2 to CH4 for detection&nbsp;</li><li>Provides universal response across compounds&nbsp;</li><li>Quantitates the above using just one calibration curve</li></ul><h3><strong>4. Thermo Fisher Scientific: Measuring destruction efficiency of greenhouse gases released by semiconductor fabrication tools</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/AN_54654_MAX_i_R_Semi_Febrication_EN_9ce9475305.pdf"><strong>Full PDF for download</strong></a></li></ul><h4><strong>Background&nbsp;</strong></h4><p>Modern materials processing activities involve the use of cold plasmas employing fluorinated gases as reactive species. Some of these gases have been demonstrated to exhibit deleterious environmental consequences resulting in their being labelled as greenhouse gases or GHGs. Among the list of GHGs undergoing intense review are those of fluorinated gases, such as NF<sub>3</sub>, CF<sub>4</sub> , SF<sub>6</sub>, CH<sub>2</sub>F<sub>2</sub> , etc. Many of these gases are either reactants or are generated as by-products of semiconductor wafer fabrication processes, such as etching and chemical vapor deposition. Therefore, semiconductor fabrication plants (SemiFabs) employ abatement tools to destroy and dilute these fluorinated gases before they reach a stack scrubber. This process assures that they will meet EPA regulations which require yearly facility-dependent GHG emission audits. European and Asian semiconductor manufacturers must meet similar regulations as well.&nbsp;</p><h4><strong>Problem&nbsp;</strong></h4><p>To ensure that the abatement process occurs efficiently, SemiFabs are required to audit selected abatement devices (one per each wafer processing tool employed) such that each device gets periodically reviewed for efficiency in destroying these GHGs before they are released to the scrubber. Since there are hundreds of abatement devices within a single SemiFab, the monitoring process must be accurate, fast (one or two hours), and able to monitor multiple fluorinated species simultaneously. Most SemiFabs utilize a series of devices to perform the necessary measurements required to calculate an overall destruction efficiency for each fluorinated species. Among the measurements required are the dilution factor (the overall ratio of the flowrate into the abatement device to that of the flowrate out of the abatement device). In most cases, this requires the use of a krypton gas tracer and a mass spectrometer (for measurement of flowrate out) in addition to an FTIR to measure a separate infrared-active gas tracer (for measurement of flowrate in). Also required is another more sensitive FTIR to measure the residual fluorinated gases which survived destructive processes within the abatement device. The result is a very bulky and cumbersome system to measure input and output flows and concentrations. What is needed is a much simpler and fully integrated measurement system capable of performing ALL these tasks.</p><h4><strong>Solution&nbsp;</strong></h4><p>Thermo Fisher Scientific has developed a new methodology for measuring abatement destruction efficiencies with a much simpler system. The system uses the <strong>Thermo Scientific™ MAX-iR™ FTIR Gas Analyzer</strong> with DTGS detector in conjunction with the <strong>Thermo Scientific™ Automated Sample Console (ASC-10™)</strong>. The MAX-iR analyzer can monitor the entire IR spectral range (500-5000 cm-1) without the need for liquid nitrogen. The ASC-10 allows for the precise measurement of post-abatement flow by determining the dilution of a tracer infrared gas or gases; this obviates the need for a spacious and costly mass spectrometer and krypton gas utilized in the previous system.</p></div></div></div></div></div></div></section></div></div></div></div></div></div></section>

News from LabRulezGCMS Library - Week 31, 2026

<p><strong>In the weeks of August 3 and 10, 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><h5><span><strong>1. Agilent Technologies: Essential Techniques for Gas Chromatography Troubleshooting</strong></span></h5><ul><li>We, 5.8.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6354">Registration</a></li></ul><p>Master GC troubleshooting with a logical, systematic approach to diagnosing changing peak shapes and system issues by efficiently eliminating unlikely causes.</p><h5><span><strong>2. Agilent Technologies: Characterising Advanced Materials with the Agilent UV-Vis-NIR: From Thin Films and Solar Cells to Glass and Optical Coatings</strong></span></h5><ul><li>Th, 6.8.2026 07:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6396">Registration</a></li></ul><p>Discover how Agilent UV-Vis-NIR spectrophotometers support the characterization of thin films, solar cells, glass, optical coatings, and other advanced materials.</p><h5><span><strong>3. Thermo Fisher Scientific: From Spectra to Mechanism: Using DRIFTS to Understand CO₂ Catalysis</strong></span></h5><ul><li>We, 12.8.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6404">Registration</a></li></ul><p>Learn how in situ DRIFTS can reveal surface species and reaction mechanisms during dry reforming of methane over ceria-supported catalysts.</p>

Webinars LabRulezGCMS Weeks 32-33/2026

<p><span><strong>This study evaluates the translation of helium-based methods to hydrogen carrier gas in cryogenically modulated comprehensive two-dimensional gas chromatography–mass spectrometry (GC×GC-MS). Three translated methods were assessed using standard mixtures and validated with authentic fingermark residues for forensic nontargeted analysis.</strong></span></p><p><span>A method combining flow and temperature adjustments maintained comparable peak capacity, signal-to-noise ratio, peak shape, and resolution. Hydrogen also allowed the modulation period to be reduced by 50% and shortened total analysis time by up to 60%, improving sample throughput, energy efficiency, and the overall sustainability of GC×GC-MS workflows.</span></p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/ancham/article/doi/10.1021/acs.analchem.6c03350/5214748/Hydrogen-Carrier-Gas-Method-Translation-in"><strong>Hydrogen Carrier Gas Method Translation in Comprehensive Two-Dimensional Gas Chromatography for Sustainable Nontargeted Analysis</strong></a></h4><p>Kira M. Fisher; Emma L. Macturk; Katelynn A. Perrault Uptmor*</p><p>Anal. Chem. (2026)</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acs.analchem.6c03350">https://doi.org/10.1021/acs.analchem.6c03350</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><div><p>Carrier gas serves as the mobile phase that transports analytes through the column for separation in one-dimensional gas chromatography (1D GC) and comprehensive two-dimensional gas chromatography (GC×GC). Helium is traditionally used due to its inertness, but it is a finite resource obtained from natural gas with associated environmental impacts, including CO<sub>2</sub> emissions and potential water contamination. (<a href="javascript:;">1, 2</a>) Additional costs arise from extraction, transport, and handling of pressurized cylinders. As helium reserves decline and demand increases, prices have risen, limiting accessibility, particularly for routine or remote laboratory operations, and creating disparities across applications. (<a href="javascript:;">1, 3</a>) Although experienced users can translate methods from helium to hydrogen using advanced knowledge and tools, there is a growing need for simplified workflows to support end users in this transition.</p></div><div><p>Hydrogen carrier gas offers distinct advantages for GC compared to helium. As described by the van Deemter equation, hydrogen enables comparable efficiency to helium at a faster optimal linear velocity due to its lower viscosity and higher diffusivity. (<a href="javascript:;">4, 5</a>) This allows shorter analysis times without the loss of efficiency typically accompanied by increased helium flow rates, as observed by a flatter van Deemter curve for hydrogen than helium. For GC systems that use mass spectrometry (MS) detection, hydrogen is considered to be the most practical alternative to helium. Although nitrogen can be used in some specialized GC-MS applications, it is typically accompanied by a substantial decrease in S/N for conventional electron ionization. (<a href="javascript:;">6</a>) Hydrogen is increasingly recognized as a critical alternative to helium for GC and GC×GC, mitigating challenges associated with helium’s limited availability and escalating cost. (<a href="javascript:;">7</a>)</p></div><div><p>The flammability risk associated with hydrogen can be minimized through generation in a laboratory rather than obtaining it in compressed cylinders. Cylinders of hydrogen are typically produced through the process of steam-methane reforming. Hydrogen generators typically use electrolysis, where water is split into oxygen gas and hydrogen gas using an electric current. (<a href="javascript:;">8, 9</a>) This generation process is more sustainable compared to nonrenewable, fossil fuel-derived alternatives for hydrogen gas production. (<a href="javascript:;">8</a>) Gas transportation costs are eliminated with in-house generation since the gas is produced and subsequently consumed in real time. The flammability risk is lower with in-house generation due to the reduced storage in pressurized cylinders avoiding the accumulation of flammable gas. (<a href="javascript:;">9</a>) Additionally, hydrogen poses a higher risk of reactivity with analytes in the sample. While analyte conversion is not well documented in the literature with hydrogen carrier gas, chemical reactivity considerations dictate that there could be a possible risk of reduction of oxygen-containing groups or hydrogenation of double bonds in aromatic or vinyl groups. Especially for nontargeted analyses performed using GC×GC, monitoring analyte identification during the translation process can help characterize challenges for the annotation of components.</p></div><div><p>While tools exist for translating 1D GC methods to hydrogen carrier gas, no established approaches are available for GC×GC. (<a href="javascript:;">10−12</a>) One study compared key GC parameters for helium and hydrogen but did not provide translation guidance. (<a href="javascript:;">13</a>) Existing 1D translation approaches do not account for the additional programmable parameters of GC×GC separations. The modulator and fast secondary separation introduce zones with parameters not addressed in 1D GC studies converting helium to hydrogen carrier gas, leaving a gap in understanding how to optimize hydrogen carrier gas for GC×GC-MS separations.</p></div><div><p>The purpose of this work was to develop and evaluate an approach for converting cryogenically modulated GC×GC-MS systems from helium to hydrogen carrier gas. Chemical standards and a 1D translation tool were used to investigate parameters governing second dimension separations and chromatographic performance. The approach was subsequently tested on authentic fingermark samples as a forensic nontargeted profiling application.</p><h4><strong>Materials and Methods</strong></h4><h5><strong>Method Translation</strong></h5><p>Compound reactivity, resolution values for peak pairs, and other component metrics (e.g., peak area, S/N, tailing factor) were compared. The Pro EZGC Method Translator (Restek Corporation, Bellefonte, PA, USA) was implemented to provide three options: translate, efficiency, and speed. Standards were analyzed using helium and all three hydrogen method options. The helium method and its three respective hydrogen methods are shown below for the indoor air standard (<a href="javascript:;">Table 1</a>) and in the <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/ancham/article-supplement/5214748/pdf/ac6c03350_si_001/">Supporting Information</a> for Grob and linear alkane standards (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/ancham/article-supplement/5214748/pdf/ac6c03350_si_001/">Tables S1–S2</a>). Resulting parameters from the tool were entered as whole values into ChromaTOF software 5.58. The first-dimension peak capacity, second-dimension peak capacity, and net peak capacity of the method were calculated using the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/83"><strong>Simply GC×GC software</strong></a> (LECO Corporation).</p><p>Analysis was performed on a <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/37"><strong>Pegasus BT 4D GC×GC</strong></a> with time-of-flight MS (TOFMS) and dual-stage quad-jet cryogenic modulation (LECO Corporation, Saint Joseph, MI) using liquid injection. The syringe was rinsed with solvent and sample twice, and 1 μL of sample was injected, followed by five rinses. The inlet split ratio was 20:1, and the inlet temperature was 250 <span>°</span>C. Helium was of ultra high purity at 99.999% (Airgas, Radnor, PA, USA). Hydrogen was supplied at the specified flow rate and was generated by an NM Plus 600 Hydrogen Generator with a purity of 99.9996% (VICI DBS, Houston, TX) connected to the GC with stainless steel tubing, which is highly recommended for employing hydrogen carrier gas to reduce flammability risk.</p><p>Samples were analyzed by using <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/41"><strong>ChromaTOF</strong></a> version 5.58 (LECO Corporation). Spectra were searched in the NIST MS Library Version 3.0, 2023. Samples were processed with a minimum S/N of 400 and a stick count of 3. The minimum spectral similarity was 700, and the relative abundance threshold was 10. Putative identifications were compared between methods to check the reactivity of components.</p><h4><strong>Results and Discussion</strong></h4><h5><strong>Fingermark Residue Application</strong></h5><div><p>Seven analytes (fatty acids and esters) were used to form an artificial fingermark residue and assess peak shape and reproducibility. These compounds were selected due to their known variability in the peak shape. Although acids often exhibit tailing without derivatization, derivatization was not used to reflect nontargeted workflows.</p></div><div><p>The analytes (<a href="javascript:;">Figure 5</a>A–C) showed mixed trends for tailing factor, exhibiting both improved and worsened tailing across methods (<a href="javascript:;">Figure 5</a>). Increased peak tailing was found in the analysis of adulterated drugs in traditional Chinese medicines using hydrogen carrier gas compared to helium. (<a href="javascript:;">9</a>) Conversely, hydrogen produced the best peak shape among the three tested carrier gases in another study on permanent gas detection in human blood. (<a href="javascript:;">21</a>) The results of this study demonstrated comparable tailing factors relative to helium depending on analyte chemistry.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2026_Figure_5_Analytical_ion_current_AIC_contour_plots_of_fingermark_standards_run_using_hydrogen_carrier_gas_fac4cf91e8.jpg" alt="Anal. Chem. (2026): Figure 5. Analytical ion current (AIC) contour plots of fingermark standards run using hydrogen carrier gas: (A) H2 translate, (B) H2 efficiency, (C) H2 speed. D) Peak areas normalized to seven analytes (n = 9). 1) myristic acid, 2) octisalate, 3) palmitoleic acid, 4) palmitic acid, 5) oleic acid, 6) stearic acid, and 7) methyl nonadecanoate." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2026_Figure_5_Analytical_ion_current_AIC_contour_plots_of_fingermark_standards_run_using_hydrogen_carrier_gas_fac4cf91e8.jpg 245w," sizes="100vw" width="1600" height="794"></p><div><p>A key difference between the three hydrogen methods was the flow rate of the carrier gas. The helium flow rate of 1.00 mL/min was translated to 1.25 mL/min of gas flow for hydrogen. The speed method resulted in a flow of 2.50 mL/min, while the efficiency method resulted in a flow rate of 1.75 mL/min. The translate, efficiency, and speed method options had the same improved respective chromatographic run times as the standards reported above (<a href="javascript:;">Table 2</a>). Studies using GC-MS that investigated drug samples found that switching to hydrogen carrier gas from helium decreased run time by more than half, thereby benefiting throughput. (<a href="javascript:;">2, 9</a>) Decreased first-dimension retention times (faster elution) were expected with higher flow rates and provided similar results as above.</p></div><div><p>Significant differences were observed across methods for squalene, cholesterol, octisalate, myristic acid, palmitic acid, and methyl nonadecanoate using a one-way ANOVA test (<i>p</i> &lt; 0.05) (<a href="javascript:;">Figure 5</a>D). The translate method generally indicated a stronger response for many analytes and improved reproducibility for some analytes (<a href="javascript:;">Figure 5</a>D). These trends align with previous 1D GC-MS studies reporting comparable reproducibility between hydrogen and helium for pesticide analysis. (<a href="javascript:;">20</a>) The translate method was selected for the analysis of authentic fingermark samples.</p></div><div><p>Fingermark residue from five volunteers was analyzed using all three hydrogen methods to confirm method selection. The translate method showed the least peak tailing (<a href="javascript:;">Figure 6</a>A–C) and improved suitability for quantitative analysis. Several analytes exhibited significant first-dimension tailing with the efficiency method (<a href="javascript:;">Figure 6</a>B). The proposed modulation period avoided wraparound based on second-dimension retention times (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/ancham/article-supplement/5214748/pdf/ac6c03350_si_001/">Figure S6</a>). Wraparound peaks that do not reflect true first or second dimension retention times should be avoided in GC×GC analysis to avoid retention index challenges and second-dimension broadening. (<a href="javascript:;">22</a>) The modulation period was reduced by 50%, similar to the standards tested above (<a href="javascript:;">Table 3</a>, <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/ancham/article-supplement/5214748/pdf/ac6c03350_si_001/">Figure S6</a>). The same metrics used for standards were also applied to authentic fingermark samples, yielding consistent results.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2026_Figure_6_Analytical_ion_current_AIC_contour_plots_of_fingermark_residue_analytes_6da2b89241.jpg" alt="Anal. Chem. (2026): Figure 6. Analytical ion current (AIC) contour plots of fingermark residue analytes using A) hydrogen translate, B) hydrogen efficiency, and C) hydrogen speed methods." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2026_Figure_6_Analytical_ion_current_AIC_contour_plots_of_fingermark_residue_analytes_6da2b89241.jpg 119w," sizes="100vw" width="1000" height="1318"></p></div></div><h4><strong>Conclusion</strong></h4><div><p>Helium has long been the standard carrier gas for GC-MS due to its inertness but has become increasingly expensive and challenging to acquire. Hydrogen is an attractive alternative carrier gas because of its lower viscosity and higher diffusivity relative to helium, allowing comparable chromatographic efficiency to be maintained over a wider range of linear velocities. Consequently, hydrogen can support faster separations with reduced loss of efficiency than helium at elevated flow rates. This characteristic has made hydrogen an increasingly viable carrier gas for GC and GC×GC applications. This study used analytical standards to develop a translation workflow from helium to three hydrogen methods using GC×GC-TOFMS with a cryogenic modulator and existing 1D GC translation tools. The translate option displayed the best peak shape and reproducibility over the speed or efficiency options. The run time was reduced by 60% using hydrogen compared to helium, and the modulation period could be reduced by 50%. This translation was performed with fingermark standards and authentic fingermark samples to verify the workflow. This study is the first to propose a retention time reduction ratio for translating a GC×GC-TOFMS helium method to hydrogen in cryogenically modulated systems.</p></div><div><p>Faster analyses using hydrogen carrier gas align with the green chemistry principle of energy efficiency. Shorter run times reduce electricity use per sample and increase overall throughput. The hydrogen method was comparable to its helium counterpart while reducing per-run energy consumption and nearly doubling hourly sample throughput. This provides clear advantages for routine, high-throughput laboratories. Hydrogen also offers potential sustainability benefits through on-site generation via electrolysis, in contrast to the nonrenewable sourcing of helium. The overall sustainability impact reflects a balance of factors including energy use, gas sourcing, safety considerations, and operational efficiencies. Hydrogen presents a compelling option when evaluated through this broader lens. The findings from this study were found to be replicated in real fingermark samples, making this applicable to other authentic samples analyzed using GC×GC-TOFMS.</p></div></div></div>

Hydrogen Carrier Gas Method Translation in Comprehensive Two-Dimensional Gas Chromatography for Sustainable Nontargeted Analysis

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 3rd August 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 </strong>and<strong> Shimadzu </strong>and presentation by<strong> MDCW / University of Alberta!</strong></p><h3><strong>1. Agilent Technologies: Analysis of Trace Impurities in Monocyclic Aromatic Solvents Following ASTM D7504</strong></h3><p><strong>Dual simultaneous analysis using the Agilent 8860B gas chromatograph</strong></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_trace_impurity_aromatic_solvents_analysis_astm_d7504_8860_gc_5994_9316en_agilent_c9fa6868e6.pdf"><strong>Full PDF for download</strong></a></li></ul><section><div><div><div><div><div><div><p>The production of high-purity monocyclic aromatic hydrocarbons, such as benzene, toluene, ethylbenzene, and xylenes (BTEX), is a cornerstone of the modern petrochemical industry. These compounds serve as essential feedstocks for the synthesis of plastics, resins, and textiles. Because even trace impurities can adversely affect downstream chemical reactions and product quality, rigorous analytical testing is required to ensure these intermediates meet strict commercial specifications.&nbsp;</p><p>ASTM D7504 is the industry-standard test method for determining the purity of, and trace impurities in, monocyclic aromatic hydrocarbons using gas chromatography (GC) with flame ionization detector (FID).1 This method is favored for its streamlined workflow; it utilizes effective carbon number (ECN) correction factors for area normalization. This eliminates the need for labor-intensive, multipoint calibrations for every individual impurity, allowing laboratories to calculate purity and quantify trace nonaromatics and aromatics with high precision.&nbsp;</p><p>The application scope of ASTM D7504 covers a wide array of aromatic liquids, including benzene, toluene, mixed xylenes, and styrene. To comply with the method's stringent performance requirements, the GC system must&nbsp;demonstrate:&nbsp;</p><ul><li><strong>High sensitivity: </strong>A limit of quantitation (LOQ) of at least 0.0006% by mass.</li><li><strong>Good resolution: </strong>Maintaining a valley-to-peak ratio of no more than 50% for critical separations (such as p-xylene and m-xylene).&nbsp;</li><li><strong>Strict precision: </strong>Highly reproducible peak areas to ensure accurate purity calculations.</li></ul><p>Implementing ASTM D7504 on a dual-channel GC/FID platform—where two independent analytical channels configured with identical injectors, columns, and detectors operate within a single GC oven—provides significant operational advantages:&nbsp;</p><ol><li>Enhanced laboratory throughput: By performing two injections simultaneously, the test lab can double its sample capacity per instrument, effectively reducing the cost-per-analysis and maximizing hardware ROI.&nbsp;</li><li>Method flexibility and redundancy: A dual-channel set up allows a lab to run different sample types (such as toluene on the front channel and xylene on the back) in a single oven cycle. Furthermore, it provides an immediate "back up" channel to maintain uptime during routine&nbsp;maintenance.&nbsp;</li></ol><p>For the system to be considered reliable, both channels should meet ASTM D7504 sensitivity, resolution, and precision requirements. In addition, both channels should yield consistent quantitative results for the same sample. The reproducibility limit (R) demonstrated in ASTM D7504 interlaboratory testing will be used to evaluate the result consistency between the two channels.</p><p>ASTM D7504 recommends helium and hydrogen as carrier gas. In China, major Chinese petrochemical companies often align their internal quality control standards directly with ASTM D7504 when testing for export of high-purity chemical intermediates. Because nitrogen is commonly used in China, they commonly adapt the ASTM D7504 method to use nitrogen carrier gas.&nbsp;</p><p>This application note demonstrates how dual-channel analysis on the Agilent 8860B GC, following ASTM D7504, delivers consistent and high-precision data using three types of carrier gas.</p><h4><strong>Experimental</strong></h4><p>An <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8860B"><strong>Agilent 8860B GC</strong></a><strong> </strong>was configured with dual split/splitless inlets and dual flame ionization detectors (FIDs). The sample introduction was made by dual <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=7693A"><strong>Agilent 7693A automatic liquid samplers (ALS)</strong></a> with high density turrets (16-vial). The analytical parameters and consumables are summarized in Tables 1 and 2. Data acquisition and analysis were conducted using <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=OpenLab+CDS"><strong>Agilent OpenLab CDS version 2.8</strong></a></p><h4><strong>Conclusion&nbsp;</strong></h4><p>The Agilent 8860B gas chromatography system configured with two identical analytical channels are applied for impurity analysis in monocyclic aromatic solvents using three carrier gases. Each analytical channel was evaluated according to the ASTM D7504 method in terms of resolution, sensitivity, quantitation precision, and recovery with satisfactory results. The quantitation results between the two channels are consistent with each other.&nbsp;</p><ul><li>Column resolution compounds pair demonstrated good separation with H/V no less than 5:1 for 300 ppm m-xylene and p-xylene solvent.&nbsp;</li><li>The LODs achieved for benzene on each analytical channel are less than 0.0001%, exceeding the 0.0002% LOD required by ASTM D7504.&nbsp;</li><li>The response and mass concentration precisions of most impurities in check standards are below 1%, meeting or exceeding the precision requirements in D7504.&nbsp;</li><li>Excellent recovery results, ranging from 93 to 105%, was achieved for added impurities, indicating good quantification accuracy based on the 8860B GC system.&nbsp;</li><li>The quantitation difference of all probe impurities between two channels is less than the reproducibility thresholds (R), demonstrating excellent across channel consistency</li></ul><p>Besides great instrument performance, the Agilent OpenLab CDS software can realize ECN based normalization for easy and fast quantitation and report generation. The 8860B dual channel GC system coupled with the OpenLab CDS software provides an accurate and reliable analysis of impurities in monocyclic aromatic solvents with satisfactory precision. Lab productivity can be improved significantly compared to the single channel analytical system.</p><h3><strong>2. MDCW / University of Alberta: Leveraging Local Libraries for Positively Parsimonious Peak Tables</strong></h3><ul><li>Presentation</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/O_6_Harynuk_f005bdafaf.pdf"><strong>Full PDF for download</strong></a></li></ul><section><div><div><div><div><div><div><p>James J. Harynuk’s presentation, <strong>“Leveraging Local Libraries for Positively Parsimonious Peak Tables,”</strong> explores how custom mass spectral libraries can simplify and improve compound identification in complex GC×GC-(HR)MS datasets. GC×GC-MS is widely applied in petroleum, environmental, food/flavour, and omics research, where samples can contain hundreds or thousands of peaks. While expanded separation space, cleaner spectra, retention patterns, and high-resolution accurate-mass data provide strong identification capabilities, converting large datasets into coherent peak tables with consistent compound assignments across multiple samples remains challenging.</p><p>The presentation demonstrates the approach using a field pea study investigating how nitrogen availability influences plant metabolism and volatile organic compounds. A conventional workflow based on peak finding and library searching can generate very large peak tables and inconsistent assignments. Incorporating retention indices (RI) and LECO’s Identification Grading System (IGS) substantially reduces the number of questionable peaks. In one example, a pea sample containing <strong>789 detected peaks was reduced to 146 retained peaks</strong> after RI filtering and IGS scoring, producing a much more manageable dataset. However, conventional libraries still struggle with isomers and with compounds that repeatedly occur in a laboratory’s samples but cannot yet be confidently identified—the presentation calls these <strong>“unknown knowns.”</strong></p><p>Harynuk therefore proposes building a <strong>custom local HRMS library</strong> containing not only standards and confidently identified compounds, but also reproducible unknown features. To qualify for inclusion, a peak should have a high-quality spectrum, S/N &gt;100, chromatographic purity, occurrence in multiple technical replicates, an assigned retention index, and a unique identifier. Crucially, the exact chemical identity does not need to be known: an unknown but reproducible feature can receive an internal identifier such as “JJH-001” and be updated later as more information becomes available. This allows laboratories to retain analytically meaningful recurring signals instead of discarding them simply because a definitive library identification is unavailable.</p><p>The results show that combining a custom library with local RI data and IGS filtering improves both the consistency and efficiency of peak-table generation. Compounds with IGS scores ≥3.0 were generally assigned the same identification across samples when the custom library was used, while reliance on NIST and IGS alone produced less consistent results. After correcting only a small number of problematic identifications per peak table, retention-index errors for custom-library entries dropped dramatically—in the evaluated samples, typically to around <strong>0.5–1.9 RI units</strong>. The key recommendation is therefore straightforward: <strong>build a custom MS library, include recurring “unknown knowns,” collect local retention-index data, and apply identification-quality filters</strong> to obtain cleaner and more consistent GC×GC-MS peak tables with substantially less manual effort.</p><h3><strong>3. Shimadzu: Simultaneous Analysis of Pesticide Residues in Food Using Triple Quadrupole GC-MS/MS with SPL Mode of a Multimode injection Unit (MMI)</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_01234_en_d8cff47c74.pdf"><strong>Full PDF for download</strong></a></li></ul><h4><strong>User benefits</strong></h4><ul><li>The MMI’s rapid heating and cooling technology significantly reduces waiting time during inlet maintenance, improving instrument uptime.&nbsp;</li><li>The Smart Pesticides Database enables automatic creation of analytical methods without the need for pesticide standards.&nbsp;</li><li>Peakintelligence for GCMS uses AI-based peak processing to deliver highly accurate analysis with no parameter settings required</li></ul><p>GC-MS/MS is an indispensable tool for the simultaneous analysis of pesticide residues in food. However, improving productivity in high-throughput workflows remains a persistent challenge. With the increasing use of simplified sample preparation methods such as QuEChERS, contamination of the inlet by matrix components is unavoidable, and frequent inlet maintenance, including liner replacement, is often required. Because this maintenance involves both cooling the inlet and waiting for temperature re-stabilization afterward, it can become a major source of instrument downtime.&nbsp;</p><p>The newly developed Multi-Mode Inlet (MMI) incorporates Shimadzu’s proprietary thermal insulation technology, providing excellent temperature stability together with rapid heating and cooling performance. While maintaining high data compatibility with conventional split/splitless inlets, the MMI significantly reduces the waiting time associated with inlet maintenance.</p><p>In this Application News, simultaneous multiresidue analysis in SPL mode is demonstrated for four food matrices with different characteristics - spinach, orange, avocado, and ginger - using the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GCMS-TQ+8040+RX"><strong>GCMS-TQ 8040 RX triple quadrupole</strong> </a>GC-MS/MS equipped with the MMI.</p><h4><strong>Data Analysis&nbsp;</strong></h4><p>LabSolutions Insight, a quantitative data processing software package designed for high-throughput sample analysis, was used for data analysis, with Peakintelligence for GCMS applied as the peak integration algorithm (Fig. 6). Peakintelligence is an AI-based waveform processing algorithm that uses machine learning to emulate the peak processing performed by experienced analysts. It requires no operator-defined parameter settings and provides peak integration performance comparable to that of skilled users.&nbsp;</p><p>For more information on improving the efficiency of pesticide data analysis using Peakintelligence for GCMS, please refer to Application News 01-00585-EN, “<a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_01_00585_en_7e311a3c77/an_01-00585-en.pdf"><strong>Time-Saving Data Processing for Pesticide Residues with Peakintelligence for GCMS</strong></a>.”</p><h4><strong>Conclusion&nbsp;</strong></h4><p>In this Application News, an example of simultaneous multiresidue pesticide analysis in food using a triple quadrupole GC-MS/MS equipped with a Multi-Mode Inlet (MMI) was presented. By adopting the MMI, instrument downtime associated with inlet maintenance can be significantly reduced while maintaining high quantitative performance. In addition, by combining automated method creation with the Smart Pesticides Database and efficient data analysis using the AIbased waveform processing algorithm Peakintelligence for GCMS, highly accurate results were obtained even for complex food matrices. This system optimizes the overall analytical workflow, from method development and maintenance to data analysis, and can make a substantial contribution to improving productivity in high-throughput pesticide residue analysis.</p></div></div></div></div></div></div></section></div></div></div></div></div></div></section>

News from LabRulezGCMS Library - Week 32, 2026

Analytical Challenges and Strategies for Compound Identification Using Gas Chromatography–Ion Mobility Spectrometry

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