<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>

News from LabRulezGCMS Library - Week 25, 2026

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 6th 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 brochure by <strong>Agilent Technologies, </strong>presentation by <strong>MDCW / University of Washington </strong>and posters by <strong>Shimadzu / ASMS</strong> and <strong>Thermo Fisher Scientific</strong> <strong>/ ASMS!</strong></p><h3><strong>1. Agilent Technologies: Operational efficiency for your GC and GC/MS labs with the Agilent 8860B gas chromatography system</strong></h3><ul><li>Brochure</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/br_8860b_gc_5994_9206en_agilent_7b7b766cd2.pdf"><strong>Full PDF for download</strong></a></li></ul><section><div><div><div><div><div><div><p>The brochure presents the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8860B"><strong>Agilent 8860B GC system</strong></a> as a routine GC and GC/MS platform focused on operational efficiency, reliable performance, intelligent diagnostics, and sustainability. It is positioned as a next-generation GC workhorse for laboratories that need consistent, high-quality data while increasing throughput and reducing downtime. Key performance features include dual sample injection capabilities, improved repeatability for retention time and peak area, electronic pneumatics control, retention time locking for method transfer, and a built-in oven light to simplify maintenance and column installation.</p><p>A major theme is <strong>instrument intelligence</strong> through the Agilent GC Assist interface. The system provides browser-based access to instrument status, methods, sequences, logs, diagnostics, maintenance information, and help resources. Built-in tools such as early maintenance feedback, system health reporting, automated and user-initiated diagnostics, peak evaluation, and self-guided troubleshooting are designed to help laboratories detect issues early, maintain uptime, and reduce the need for expert-level intervention during routine operation.</p><p>The brochure also emphasizes <strong>sustainability and resource management</strong>. The 8860B GC includes gas and power usage reporting, method-based monitoring, alerts for abnormal gas use, and tools for detecting possible leaks or restrictions. Agilent highlights helium conservation options, including a helium conservation module that can reduce helium consumption by switching to an alternative gas during idle periods, as well as support for hydrogen and nitrogen carrier gases with built-in hydrogen safety features. These functions are presented as ways to reduce operating costs, conserve resources, and protect workflows from helium supply disruptions.</p><p>Finally, the brochure describes the broader <strong>Agilent GC ecosystem</strong> around the 8860B. The system supports multiple inlets, detectors, autosamplers, headspace sampling, single quadrupole GC/MS compatibility, OpenLab CDS, DA Express, MassHunter software, Agilent consumables, columns, and CrossLab services. Together, these elements are presented as a complete workflow for routine laboratories that need flexibility, compliance support, service coverage, method consulting, training, and long-term value from their GC investment.</p><h3><strong>2. MDCW / University of Washington: Implementing Tile-Based Fisher Ratio Analysis of GC×GC-TOFMS Data to Obtain a Master Peak Table of All Detected Analyte Compounds in Many Petroleum-Based Samples</strong></h3><ul><li>Presentation</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/O_9_Halvorsen_136808e314.pdf"><strong>Full PDF for download</strong></a></li></ul><section><div><div><div><div><div><div><p>The presentation describes the development of a chemometric workflow for advanced fuel sample analysis using GC×GC-TOFMS data. The work was carried out by the University of Washington in collaboration with Chevron Technical Center, with the goal of improving the characterization of complex petroleum-based samples. Moving from conventional GC to comprehensive two-dimensional GC increased peak capacity and chromatographic resolution, but also created the need for more advanced methods to generate reliable peak tables across many chemically diverse fuel samples.</p><p>The key method presented is a tile-based Fisher Ratio approach implemented through <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/348"><strong>ChromaTOF Tile</strong></a><strong>.</strong> This method identifies analytes that show statistically significant concentration differences between sample classes. Instead of relying only on peak detection or manual alignment, the workflow uses chromatographic “tiles” to reduce the impact of retention-time shifting and to capture both major and trace-level components. The study included multiple fuel classes, including hydrobate, reformate, naphtha, FCC gasoline, and blanks.</p><p>Because Fisher Ratio values alone do not directly indicate whether a compound is truly detectable, the authors added a blank-based p-testing strategy. Three blank chromatograms were used to estimate background signal distributions for each tile, and confidence intervals were then applied to determine whether each detected hit was present in individual sample classes. This produced a master peak table covering 719 hits across nine fuel sample classes. The results showed good reproducibility, with only 6.3% of classifications being heterogeneous across replicates.</p><p>Overall, the presentation concludes that the tile-based workflow can generate comprehensive and reproducible peak tables with reduced user intervention, while preserving the ability to recover trace analytes in complex petroleum samples. The approach should be broadly applicable to other complex sample types and could also be adapted using chemometric metrics other than Fisher Ratio, depending on the experimental design and analytical goals.</p><h3><strong>3. Shimadzu / ASMS: Is Your Next Sip Safe? A Simple, Rapid Method for Measuring volatile PFAS in Juices.</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/TP_143_Is_Your_Next_Sip_Safe_A_Simple_Rapid_Method_for_Measuring_volatile_PFAS_in_Juices_a6ed9414c0.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Per- and polyfluoroalkyl substances (PFAS) pollution is a growing global concern due to links with adverse health effects, many of which remain poorly understood. 1 Accurate detection and quantification are therefore essential. While PFAS analysis has traditionally focused on water, attention is rapidly expanding to food and beverages, where testing remains limited despite high stakes and increasing regulations. 2 A recent PFAS lawsuit against a juice manufacturer underscored the heightened public scrutiny of PFAS in juices, placing food safety and brand reputation at risk. 3 This study presents a Headspace Solid-Phase Microextraction– Triple Quadrupole Gas Chromatography/Mass Spectrometry (HS-SPME GC/MS/MS) method for PFAS quantitation in juices. GC/MS enables analysis of volatile PFAS unsuitable for LC/MS, while HS-SPME offers rapid analysis with minimal sample preparation in complex matrices.</p><h4><strong>Methods</strong></h4><p>A volatile PFAS analysis method was developed on a <strong>Shimadzu </strong><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 an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=AOC-6000+Plus"><strong>AOC-6000 Plus multifunctional autosampler</strong></a> equipped with a solid phase microextraction (SPME) module (Figure 1).</p><h4><strong>Results&nbsp;</strong></h4><p>The system was deemed free of contaminants and inferences. None of the target PFAS in the method blank were found in quantifiable concentration. In the study, the calibration curve for each target included at least seven calibrators. Calibration curve results showed a good linear fit for all compounds with coefficient of determination (R2 ) ≥ 0.993. The linear range and R2 of each PFAS target are shown in Table 3.</p><h4><strong>Conclusion</strong></h4><p>Overall, these results demonstrate the robustness and reliability of the method for PFAS analysis in two carton apple juices (Brands X and Y), one plastic bottled apple juice (Brand X), and a berry blend carton juice (Brand X). Given the diversity of matrices evaluated, the method may also be suitable for other beverages, including sports drinks and vitamin-enhanced waters</p><h3><strong>4. Thermo Fisher Scientific / ASMS: Enhanced sensitivity for the quantitative analysis of pesticides using a GC Orbitrap MS</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/po_004706_lsms_pesticides_exploris_gc_efs_po004706_asms2026_na_en_5f51b18742.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Detection of pesticide residues in fruits and vegetables is essential for food safety, but it can be challenging in complex, highly pigmented matrices due to interferences. Orbitrap technology provides high resolution and mass accuracy, enabling confident identification of coeluting and isobaric compounds while reducing false results. Furthermore, the FS-HRAM acquisition enables simultaneous quantitation and screening within a single analysis with the capability of retrospective data analysis, allowing laboratories to reprocess datasets for additional or emerging compounds without re-injecting samples. The <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/2419"><strong>Orbitrap Exploris GC S mass spectrometer</strong></a><strong> </strong>features the Thermo Scientific NeverVent Advanced Electron Ionization Source (NVAEI) which offers an improved design providing enhanced sensitivity and robustness, allowing for increased instrument uptime and maximized sample throughput for rapid return on investment (ROI).</p><h4><strong>Materials and methods</strong></h4><h5><strong>Data analysis&nbsp;</strong></h5><p>Data was acquired, processed and reported using the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/76"><strong>Thermo Scientific Chromeleon Chromatography Data System (CDS) software</strong></a>, which provides integrated instrument control, automated workflows, and an intuitive interface for data analysis, customizable reporting, and compliant data management in accordance with FDA 21 CFR Part 11 and European Commission (EU) Annex 11. Its advanced reprocessing capability streamlines sequence setup, data review, and reporting offering the possibility to easily flag and check compliance with the current regulations.</p><p>Results Compliant analyte identification The use of HRAM-GCMS reduces the matrix interferences ensuring a confident and selective identification of analytes (Figure 1). All target compounds satisfied the SANTE criteria at the default MRL of 10 µg/kg and more than 90% were confirmed at concentrations of 1 µg/kg following the SANTE/11312/2021v2026 guidance criteria of:&nbsp;</p><ul><li>two ions were detected for each pesticide with mass accuracy ≤ 5 ppm with precursor and product ions in the extracted ion chromatograms fully overlapped,&nbsp;</li><li>due to the added value of accurate mass measurement, matching ion ratios is not necessary, however, an ion ratio (IR) deviation within ± 30% (relative) of the average of calibration standards from the same sequence was considered to provide additional support for identification</li><li>retention times (RT) within a tolerance of ± 0.1 minutes</li></ul><p>Sensitivity performance (IDL) and analytical linearity Instrument sensitivity was evaluated using calculated IDLs derived from replicate injections of low-level, matrix-matched standards. The Orbitrap Exploris GC S demonstrated detection limits at levels at or below 0.5 µg/kg for most of the investigated pesticides (Figure 2). Linear dynamic range was evaluated using matrix-matched calibration curves ranging 0.5–200 µg/kg, with each calibration level injected in triplicate. All target analytes demonstrated excellent linearity, with coefficients of determination (R²) &gt; 0.993, response factor (%RSD) values below 20% across the calibration range, and ion ratios (IRs) within ±30% of the average calibration standard values. System suitability for quantitative analysis was confirmed by calculated concentrations within ±20% of expected values and recoveries ranging from 96% to 104%. An example of calibration curve for Aldrin is shown in Figure 3.</p><h4><strong>Conclusions&nbsp;</strong></h4><p>The results obtained in these experiments demonstrate that the Orbitrap Exploris GC S mass spectrometer equipped with NeverVent AEI ion source represents a reliable tool for analysis of pesticides in complex matrices.&nbsp;</p><ul><li>The Orbitrap Exploris GC S offers a simple approach for the multiresidue analysis of pesticides allowing for full-scan acquisition combined with high mass resolving power&nbsp;</li><li>The NeverVent AEI ion source is designed for ultra-trace concentration detection, making it ideal for challenging applications ensuring detection limits at levels at or below 0.5 µg/kg for most of the investigated pesticides&nbsp;</li><li>Confident identification of compounds can be easily achieved through i). high spectral quality, ii). high spectral fidelity, ensuring consistent spectrum independently from concentration, and iii). consistent mass accuracy irrespectively of analyte concentration and time&nbsp;</li><li>System suitability for quantitative analysis was demonstrated with R2 &gt;0.993, RF %RSD across the entire calibration curve &lt; 20, and IRs within ± 30% of the average of calibration standards, calculated amounts within 20% the expected values, and percentage recovery (%) ranging from 96 to 104.</li></ul></div></div></div></div></div></div></section></div></div></div></div></div></div></section>

News from LabRulezGCMS Library - Week 28, 2026

<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

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