Photocatalytic degradation and transformation of pharmaceuticals using exfoliated metal-free g-C3N4

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>Our Library never stops expanding. What are the most recent contributions to LabRulezLCMS Library in the week of 27th July 2026? Check out new documents from the field of liquid phase, especially HPLC and LC/MS techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT LCMS 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://gcms.labrulez.com/library"><strong>LabRulezGCMS</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, Shimadzu / ASMS, Thermo Fisher Scientific / ASMS </strong>and<strong> Waters Corporation / ASMS </strong>and application note by<strong> KNAUER!</strong></p><h3><strong>1. Agilent Technologies / ASMS: Down in the Weeds: Automated Fast Screening Workflow for Cannabinoids in Whole Blood Using High Resolution Mass Spectrometry</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/po_blood_cannabinoids_lc_q_tof_mp_694_asms_2026_en_agilent_02f13ac14e.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Distinguishing psychoactive tetrahydrocannabinol (THC) isomers and their metabolites from nonpsychoactive isobars and novel semi-synthetic cannabinoids like hexahydrocannabinol (HHC) is increasingly important to forensic toxicologists, as is the ability to remain up to date with novel compounds that are introduced into the population. This study describes an automated two-step chromatographic workflow that utilizes an initial fast screen method followed by reinjection with specific chromatography to resolve isobars if a suspect is detected in the fast screen on a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=Revident"><strong>Revident LC/Q-TOF</strong></a><strong> </strong>with<strong> </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=1290+infinity+II+lc"><strong>1290 Infinity II LC</strong></a> (Figure 1). This allows for a larger number of samples to be screened more quickly while ensuring chromatographic resolution of isomers for confirmation. The data acquisition mode enables laboratories to interrogate data retrospectively to determine if novel compounds were present in any given sample.</p><h4><strong>Conclusions</strong></h4><ul><li>Clear and concise software workflow for quick screening analysis&nbsp;</li><li>Baseline resolution of THC isomers and interferences in longer method to allow for confident identification&nbsp;</li><li>All Ions acquisition method allows for retrospective data interrogation with fragment analysis</li></ul><h3><strong>2. KNAUER: Scaling up LNP formulation using a Reynolds number-based methodology</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/VPH_0084_knauer_scaling_up_lnp_formulation_using_a_reynolds_number_based_methodology_e05e67ca78.pdf"><strong>Full PDF for download</strong></a></li></ul><p>LNPs have become an essential enabling technology for RNA-based therapeutics and next-generation drug delivery systems. As these applications progress from laboratory research [1,2] to commercial manufacturing, process robustness and scalability become increasingly important. Beyond scalability, consistent product quality is critical.&nbsp;</p><p>In pharmaceutical development, predefined critical quality attributes (CQAs) such as particle size, PDI, encapsulation efficiency and active pharmaceutical ingredient (API) integrity define whether a formulation meets its intended performance and regulatory requirements. These CQAs are established during early formulation development and must be maintained throughout scaleup to ensure product consistency, pharmaceutical efficacy and reproducibility.</p><p>LNPs are typically generated by controlled mixing of a lipid phase in ethanol with an aqueous buffer containing the nucleic acid payload. The rapid solvent exchange initiates lipid self-assembly and determines the resulting nanoparticle characteristics. Because particle formation occurs on timescales comparable to the mixing process, the interplay between hydrodynamics and nanoparticle assembly is a key determinant of final product quality. Even minor variations in mixing conditions can influence particle size distribution, encapsulation efficiency, and overall formulation consistency.&nbsp;</p><p>To establish robust and scalable manufacturing processes, the underlying transport phenomena must be described independently of an operating scale. Dimensionless numbers provide a powerful framework for this purpose. The Reynolds number (Re) characterizes the flow regime and mixing intensity by relating inertial and viscous forces, while the Damköhler number (Da) describes the relationship between the characteristic timescales of mixing and nanoparticle formation. Together, these parameters provide a quantitative basis for understanding and controlling LNP self-assembly.</p><h4><strong>RESULTS&nbsp;</strong></h4><h5><strong>R&amp;D Evaluation and Hydrodynamic Characterization&nbsp;</strong></h5><p>The experimental study was initiated on <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=503&amp;search=IJM+NanoScaler"><strong>KNAUERs IJM NanoScaler</strong></a>, where multiple LNP formulations were developed and characterized under defined process conditions. During this phase, formulation parameters such as lipid composition, flow rate ratio (FRR), and total flow rate (TFR) were systematically varied to establish target CQAs, particularly particle size and PDI. In addition to recording volumetric flow parameters, the corresponding hydrodynamic conditions were quantified by calculating Re for each experimental setting, thereby the prevailing flow regime within the impingement zone.&nbsp;</p><h5><strong>Determination of a Critical Reynolds Number&nbsp;</strong></h5><p>Particle size was evaluated to depend on the Re using the <strong>IJM NanoScaler </strong>(Fig. 1). At Re below 500 particle sizes of 100 nm and larger were observed, indicating insufficient mixing and heterogeneous supersaturation conditions. With increasing Re, particle size decreased until reaching a plateau region at around 52 nm. Above a critical Reynolds number of ~ 750, further increases in flow rates did not significantly affect particle size. This plateau defines the hydrodynamic condition required to achieve minimal particle size for the given formulation.</p><h4><strong>CONCLUSION&nbsp;</strong></h4><p>A critical Reynolds number defining stable particle size and PDI was successfully identified on the R&amp;D-scale IJM NanoScaler. Operating above this threshold ensured consistent nanoparticle characteristics within a defined plateau region.</p><p>By transferring these hydrodynamic conditions to the benchtop system, predefined CQAs were reliably maintained across scales. The data demonstrate reproducible particle size and PDI during scale-up while enabling a substantial increase in throughput. These findings highlight that a Reynolds number driven approach provides a robust and scalable framework for predictable LNP manufacturing using IJM technology.</p><h3><strong>3. Shimadzu / ASMS: High-Throughput Ultra-Short-Chain PFAS Analysis in Drinking Water using LC-MS/MS with Automated Sample Preparation</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/TP_125_High_Throughput_Ultra_Short_Chain_PFAS_Analysis_in_Drinking_Water_using_LC_MSMS_with_Automated_Sample_Preparation_69e7985cce.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Ultra-short- and short-chain PFAS are highly mobile and persistent contaminants that are challenging to measure in drinking water due to high polarity, low molecular weight, poor chromatographic retention, and susceptibility to laboratory background contamination. This study evaluates a high-throughput LC–MS/MS workflow with automated sample preparation for targeted quantification of ultra-short and short-chain PFAS in drinking water. Method performance was assessed using native background, matrix spike recovery, precision, LOQ accuracy, calibration performance, and continuing calibration verification.</p><h4><strong>Method</strong></h4><p>Nine target PFAS were evaluated: TFA, TFMS, PFPrA, PFMOAA, PFEtS, PFBA, PFPrS, TFSI, and PFBS. Samples and calibrants were prepared in acidified 50:50 PFAS-grade water/methanol using PFAS-grade water provided by MilliporeSigma and an automated ePrep sample preparation system equipped with PFAS-free accessories.</p><p>Chromatographic separation was performed on a polar-embedded IBD column with a delay column to improve retention and minimize background interference. Analysis was performed on a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=1&amp;search=LCMS-8065XE"><strong>Shimadzu LCMS-8065XE triple quadrupole system</strong></a> within an 8-minute total cycle time with a 10 µL injection volume (figure 2). Drinking-water samples were collected from seven local household sources and spiked at multiple concentration levels. Samples were ran in replicates to evaluate recovery, precision, and method robustness.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>This 8-minute LC–MS/MS method enabled high-throughput analysis of ultrashort- and short-chain PFAS in drinking water. TFA background observed in blanks and unspiked samples emphasized the need for contamination control and matrix-specific background assessment. Practical LOQs were supported at 10 ng/L for most analytes and 50 ng/L for PFMOAA. Recovery and precision were generally acceptable from 100–1000 ng/L, with higher variability at 10 ng/L and for PFMOAA, indicating areas for further optimization. Calibration and CCV performance supported reliable quantification across the reportable range.</p><h3><strong>4. Thermo Fisher Scientific / ASMS: Unlocking the archived proteome: High-throughput, deep FFPE proteome profiling using the Orbitrap Astral Mass spectrometer</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/po_004694_lsms_protein_ffpe_orbitrap_astral_proteomics_po004694_asms2026_na_en_7cd59d64aa.pdf"><strong>Full PDF for download</strong></a></li></ul><p>FFPE tissue specimens are central to clinical pathology and translational cancer research, enabling long-term storage while preserving morphology for histology and molecular analysis. Widely available through biobanks, they support retrospective studies, biomarker discovery, and precision oncology—especially when paired with detailed clinical data. Compared to fresh tissues, FFPE samples are more accessible, scalable, and cost-effective for proteomics.</p><p>However, FFPE proteomics is technically challenging. Formaldehyde-induced crosslinking complicates protein extraction and digestion, while paraffin removal and crosslink reversal add complexity. Traditional workflows are labor-intensive, time-consuming, and prone to variability, limiting reproducibility and throughput. Although recent advances in sample preparation have improved performance, residual contaminants can still affect instrument robustness and scalability.&nbsp;</p><p>To address these challenges, we implemented a streamlined FFPE proteomics workflow that simplifies processing and improves peptide yield and reproducibility. Using FFPE lung tissue and the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/2465"><strong>Thermo Scientific OptiSpray Ion source</strong></a> with the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/836"><strong>Orbitrap Astral Mass spectrometer</strong></a><strong> </strong>across two LC platforms, we achieved sensitive detection of low-abundance peptides from 20– 200 ng inputs. Combined with fast LC methods and acquisition rates of 60, 180, and 500 samples per day, this approach enables deep, scalable profiling. The automated OptiSpray Ion source also reduces instrument contamination, supporting robust, high-throughput analysis of archived clinical tissues for biomarker discovery and translational research.</p><h4><strong>Experimental procedure&nbsp;</strong></h4><h5><strong>Sample preparation&nbsp;</strong></h5><p>Lung tumor and lung normal samples were de-paraffinized using xylene and sequential ethanol washes. The optimized protein extraction protocol and Thermo Scientific EasyPep Mini MS sample prep kit was used to prepare the digest samples from FFPE sections of normal and tumor lung samples. Protein concentration was measured using Thermo Scientific Pierce Rapid Gold BCA Protein Assay kit. The peptides were quantified using the Thermo Scientific Pierce Fluorometric Peptide Assay Kit before LC-MS/MS analysis. For <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=291&amp;search=Evosep+ENO"><strong>Evosep ENO</strong></a>, peptides were loaded on EvoTips .&nbsp;</p><h5><strong>LC-MS analysis&nbsp;</strong></h5><p>Samples were injected onto an Thermo Scientific OptiSpray µPAC Neo Cartridge (P/N OS-UPAC050NAN) and Thermo Scientific OptiSpray µPAC Neo High-Throughput Cartridge (P/N OS-UPAC005CAP) and separated using 20 min (60 SPD) and 6.8 min (180 SPD) gradients, respectively, in direct injection mode at 55°C on a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/398"><strong>Thermo Scientific Vanquish Neo UHPLC System</strong></a>. For 500 SPD (2.3 min) separation, samples were processed on Evosep ENO using an Evosep EV1182 Performance Column at 40 °C. Detailed LC and MS parameters are provided in Tables 1–2.&nbsp;</p><h5><strong>Data analysis Spectronaut® Software&nbsp;</strong></h5><p>The raw DIA files from both the labeled and unlabeled samples were analyzed together using Biognosys Spectronaut® Software in directDIA mode. Exported output files were imported to R Studio (2023.09.0 Build 463) with R (v4.3.1) for downstream data analysis and visualization.</p><h4><strong>Conclusions&nbsp;</strong></h4><ul><li>End-to-end FFPE proteomics is completed in under one day, integrating rapid sample preparation, fast LC–MS, and streamlined data analysis.&nbsp;</li><li>Deep proteome coverage is achieved from FFPE lung tissue, with up to ~8,600 protein groups and &gt;100,000 peptides identified from 200 ng input in 20 min.</li><li>Increasing throughput by up to ~8× (60 to 500 SPD) with moderate loss in depth, retaining ~70% of proteins at 180 SPD and ~45% at 500 SPD.&nbsp;</li><li>Robust quantitative performance is maintained at low sample input (20 ng) and across acquisition speeds, with median CVs ≤10%.&nbsp;</li><li>The workflow enables reliable differential expression and pathway analysis at scale, demonstrating its utility for biological insight into lung tumor and normal tissues.</li></ul><h3><strong>5. Waters Corporation / ASMS: Identification of Novel Per-and-Polyfluoroalkyl Substance (PFAS) Isoform in Textile Using a Multi-Reflecting Time-ofFlight Mass Spectrometer Technology</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/720009415_0b95241dfd.pdf"><strong>Full PDF for download</strong></a></li></ul><div><div><section><div><div><div><div><div><div><p>The poster presents a non-targeted LC-MS/MS workflow for identifying <strong>per- and polyfluoroalkyl substances (PFAS)</strong> in textile materials using high-resolution mass spectrometry. As concerns over PFAS exposure continue to grow, conventional targeted methods often capture only a limited number of compounds. The authors therefore combined <strong>data-dependent acquisition (DDA)</strong> with high-resolution accurate-mass analysis to characterize PFAS profiles more comprehensively, enabling the identification of novel PFAS isoforms and halogenated contaminants with high confidence.</p><p>The analytical workflow was based on a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/191"><strong>Waters ACQUITY Premier UPLC system</strong></a> equipped with a PFAS solution installation kit and an <strong>ACQUITY Premier BEH C18 (2.1 × 50 mm, 1.7 µm) column</strong>, coupled to the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/2433"><strong>Waters Xevo MRT P10 multi-reflecting time-of-flight (MRT) mass spectrometer</strong></a>. Textile reference material was extracted according to <strong>EN 17681-1:2025</strong>, and LC-MS/MS data were acquired in <strong>data-dependent acquisition (Top 5 DDA)</strong> mode. Data processing and compound identification were performed using the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1544"><strong>waters_connect™ Software Platform</strong></a>, combining accurate precursor and fragment masses with isotopic information.</p><p>A key innovation of the study was the implementation of <strong>mass defect-directed DDA</strong>. By creating a database of nearly <strong>19,600 unique PFAS-related compounds</strong> and using their characteristic mass defects to guide precursor selection, the workflow reduced the number of non-specific MS/MS spectra by approximately <strong>25%</strong>. This allowed the instrument to focus on PFAS-like compounds more efficiently, increasing the number of informative fragmentation spectra and improving the identification of previously unknown PFAS species. The approach successfully identified compounds such as <strong>N-ethyl perfluorooctane sulfonamidoethanol (N-EtFOSE)</strong> in textile extracts with excellent mass accuracy (1.1 ppm).</p><p>The authors conclude that <strong>mass defect-driven DDA</strong> significantly enhances non-targeted PFAS screening by reducing unnecessary MS/MS acquisitions while increasing the number of confidently identified PFAS and PFAS-like compounds. They also suggest that this strategy can be extended beyond PFAS analysis to other classes of persistent environmental contaminants, including <strong>polychlorinated biphenyls (PCBs)</strong> and <strong>polybrominated biphenyls (PBBs)</strong>, making it a promising approach for broader environmental and materials analysis.</p></div></div></div></div></div></div></section></div></div>

News from LabRulezLCMS Library - Week 31, 2026

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezICPMS Library in the week of 27th July 2026? Check out new documents from the field of spectroscopy/spectrometry and related techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT SPECTROSCOPY/SPECTROMETRY RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><strong>LabRulezGCMS</strong></a> libraries.</p></blockquote><p>This week we bring you application notes by <strong>Agilent Technologies,</strong> <strong>Shimadzu </strong>and <strong>Thermo Fisher Scientific!</strong></p><h3><strong>1. Agilent Technologies: High-Precision Determination of Phosphorus and Potassium in Fertilizers by ICP-OES</strong></h3><p><strong>Accurate nutrient analysis of fertilizers using an </strong><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=5800"><strong>Agilent 5800 ICP-OES</strong></a><strong> and standard bracketing</strong></p><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_fertilizers_standard_bracketing_5800_icp_oes_5994_9311en_agilent_83cbca87fd.pdf"><strong>Full PDF for download</strong></a><strong>&nbsp;</strong></li></ul><p>Accurate characterization of fertilizer nutrient content is critical for optimizing plant growth, maximizing yield, and ensuring sustainable agricultural practices. Fertilizers must comply with strict regulatory specifications, particularly for declared NPK (nitrogen–phosphorus–potassium) ratios, which define the relative nutrient content supplied to crops. Even small deviations from the specified ratio can impact plant yield, regulatory compliance, customer confidence in the product, as well as its commercial value.&nbsp;</p><p>Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) is a well-established technique for multi-element analysis of complex samples, so is ideally suited to meet the precision and accuracy requirements of fertilizer testing.1,2 However, applications that require very tight tolerances, such as NPK verification, benefit from enhanced calibration approaches as even small deviations from reported values can have large financial implications for the manufacturer.</p><p>Using Agilent ICP-OES instruments, standard bracketing calibration based on a standard–sample–standard measurement sequence, minimizes the impact of sample-to-sample variability and matrix effects.3,4 This approach further improves analytical precision and accuracy compared to conventional external calibration, making it a particularly valuable method for analyzing fertilizers with tightly controlled specifications.&nbsp;</p><p>In this study, an Agilent 5800 Vertical Dual View (VDV) ICP-OES, equipped with an Agilent SPS 4 autosampler and controlled using Agilent ICP Expert Pro software,5 was used to determine P and K concentrations and corresponding NPK ratios in a standard reference material (SRM) and two commercially available fertilizers. The standard bracketing method was adapted from ISO methods 11494 and 114956,7 and adjusted for fertilizer analysis. The performance of the method, when combined with real-time data processing tools, was evaluated for accuracy and precision.</p><h4><strong>Experimental&nbsp;</strong></h4><h5><strong>Instrumentation&nbsp;</strong></h5><p>The <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=5800"><strong>Agilent 5800 VDV ICP-OES </strong></a>was configured with the <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=10&amp;search=SPS+4+autosampler"><strong>Agilent SPS 4 autosampler</strong></a>, which provided automated sample delivery to the instrument (Figure 1). The 5800 ICP-OES was equipped with an Agilent SeaSpray nebulizer, double-pass cyclonic spray chamber, and one-piece VDV torch with a 1.8 mm internal diameter (ID) injector. All components were controlled by Agilent ICP Expert Pro* software. Instrument operating parameters are listed in Table 1.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>This study demonstrates the effectiveness of the Agilent 5800 VDV ICP-OES standard bracketing method for high-precision determination of phosphorus and potassium in fertilizers. The method delivered excellent performance, with relative standard deviations below 0.1% and excellent agreement with expected NPK values, with recoveries ranging from 99 to 102%. The combination of gravimetrically prepared standards, internal standard correction, and bracketing calibration minimizes analytical variability and ensures reliable results for fertilizer quality control.&nbsp;</p><p>In addition, Agilent ICP Expert Pro software streamlines analysis through real-time calculations and automated quality control tools, improving laboratory efficiency and reducing the risk of reporting errors. This approach provides a robust and practical solution for high throughput fertilizer testing laboratories, enabling precise NPK verification that strengthens regulatory compliance, reduces the risk of mislabeling, and supports accurate product pricing.</p><h3><strong>2. Shimadzu: Multifaceted Evaluation of Frozen Tempura Batter Coating Focusing on Food Texture</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_01_00987_en_f919b540e7.pdf"><strong>Full PDF for download</strong></a></li></ul><p>The “deliciousness” of foods consists of multiple factors, including taste, smell, and visual appeal. However, texture, sometimes called “mouthfeel,” is also one extremely important factor. Mouthfeel refers to the physical sensations experienced when food is placed in the mouth or chewed, and is expressed by various onomatopoeic words such as “crisp” and “chewy.” Among these, the packaging of some foods uses onomatopoeic terms to emphasize the appeal of their distinctive textures, and this has become an important “selling point” for consumers when deciding which product to select.&nbsp;</p><p>In the development of food products, the method of evaluating texture has become a key point. Sensory methods have long been used, but because sensory evaluations depend on the human senses, they are easily influenced by differences between individuals conducting the evaluation and their physical condition.</p><p>Thus, the difficulty in ensuring repeatability is an issue. As an additional issue, technical training for the panelists who conduct evaluations also requires time and labor. To compensate for these problems, evaluation methods based on measurement of physical properties with instruments may be used. This approach eliminatesthe human error that had been a problem with sensory evaluations, enabling objective evaluations.&nbsp;</p><p>Food texture is also complexly influenced by the interactions of various factors, such as the ingredients contained in the food, their amounts, and the cooking method. Since differences in these factors may appear in the structure and surface condition of foods, observation and measurement of the internalstructure and surface condition of foods make it possible to analyze and understand the factors that contribute to texture, allowing more efficient food product development from the physical viewpoint. This article introduces an example of an analysis of the differencesin texture that occur due to differences in the heating method from the aspects of evaluation of physical properties and structural and surface observation, using frozen tempura asthe testsample.</p><h4><strong>Experiment&nbsp;</strong></h4><p>In this experiment, four instruments were used for evaluation of mechanical properties and structural and surface observation. Table 1 shows the names of the instruments, the purpose of the experiment, and the corresponding sectionsin this article. The test samples used here were commercially-available frozen tempura, which features “moistness” when prepared by microwave oven cooking and “crispness” after microwave oven + oven cooking. The “Moist” type is prepared by heating for 1 min in a microwave oven, and the “Crisp” type is prepared by additional heating in an oven after microwave heating. Since the heating time in the oven is adjusted depending on the sample size required by each instrument, the specific sample preparation procedure and the flow of the tests will be described in the sections concerning each instrument.</p><h5><strong>Evaluation of Coating Surface Roughness by Laser Microscope&nbsp;</strong></h5><p>The laser microscope was used in high-magnification measurements of the roughness of the sample surface and color observation (color images). It is possible to grasp the differences in the batter coatings of the “Moist” and “Crisp” types from changes in roughness and also changes in color. Fig. 11 shows the appearance of the <strong>OLS5500 laser microscope</strong> used here. In this instrument, optical resolution is enhanced by using a singlewavelength 405 nm laser beam, and topographical information can be acquired by reflective confocal laser microscopy. Color images of the same field can also be obtained by using a white LED.</p><p>In this experiment, the samples were prepared by the following procedure in order to observe the same areas of the “Moist” and “Crisp” samples. First, the entire kabocha tempura was heated for 1 min in the microwave oven, after which part of the sample was cut off and observed on the stage (Fig. 12). Following this, the observed sample was heated in the oven and placed on the stage again, and the “Crisp” sample was observed (Fig. 13). To observe the shape of a wide area of the sample, an alignment (“tile-stitching”) function was used. The image acquisition condition was the ultra-high speed mode using a 20x objective lens.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>A sensory evaluation and evaluation of physical properties using a texture analyzer, and structural observations from the macro to the micro level using an X-ray CT, laser microscope, and SEM were conducted for frozen tempura with different food textures depending on the heating conditions. The impression of the food texture, or “mouthfeel,” obtained in the sensory evaluation was quantified in the form of physical property values by using the texture analyzer, and the factors that formed the grounds for those numerical values were then evaluated based on the results of various types of observation. As a result, it was suggested that differences in food texture correspond to changes in the food structure and oil content.&nbsp;</p><p>In this experiment, different samples were examined with four types of instruments. However, if physical property tests can be carried out with the samples as-is after observation of the same areas, a more direct and high accuracy analysis is considered to be possible. Moreover, in this experiment, the food texture was changed by using different heating methods, but in cases where the ingredients (flour, oil) or the deep-frying method is changed, there is a possibility that different factors from those in this study may contribute to the texture. As demonstrated in this experiment, although “food texture” is often grasped sensorily, as suggested by the term “mouthfeel,” this property can be visualized scientifically in terms of the structure and physical properties of the food and the condition of the oil content by combining multifaceted evaluations using multiple instruments. This technique is expected to become an effective approach for reproducing and controlling the target texture in food product development and quality design.</p><h3><strong>3. Thermo Fisher Scientific: Bauxite analysis with Niton XRF analyzers</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/bauxite_analysis_with_niton_xrf_analyzers_an1795_en_93b319a76e.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Globally, bauxite is the primary source of aluminum (Al) ore and anchors a major industry in many countries, including China, Australia, and Brazil. As such, grading Al concentration is of paramount interest in the mine as is the need to determine concentrations of penalty elements. The desired goal is to conduct all the analysis in a way that maximizes productivity.&nbsp;</p><h4><strong>Application&nbsp;</strong></h4><p>Analysis of aluminum (Al), silicon (Si), and iron (Fe) presents unique challenges. Accurate analysis of all three is critical for ore grading and understanding their influence on the processing and production of the primary metal of interest. Relying on lab-analysis only in bauxite mining operation often results in costly time delays and reduced productivity while waiting hour if not days and weeks for the results.&nbsp;</p><p>With the ruggedized, dust- and splash-proof <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/products/1997"><strong>Thermo Scientific™ Niton™ XL3t GOLDD+ XRL Analyzer</strong></a>, near lab-quality analysis of Al, Si and Fe can be generated on sites, enabling quick decisions in at remote mines. Indeed, the Niton XL3t GOLDD+ analyzer provides rapid and accurate elemental analyses of bauxite ore enabling to map chemical concentrations in realtime, identify excavation hotspots and detect penalty elements.&nbsp;</p><h4><strong>Handheld XRF analyzer&nbsp;</strong></h4><p>Thermo Scientific Niton Handheld XRF analyzers, including the Niton XL3 GOLDD+ analyzer, easily analyze elements from magnesium (Mg) to uranium (U) to fill all exploration and mining needs. These instruments make it easy to perform trend analysis by averaging readings in real-time or by downloading results later to a PC. They deliver fast, accurate elemental analysis for intensive metals exploration and production whether base metals, precious metals, or even rare earth elements.</p><h4><strong>Comments&nbsp;</strong></h4><p>The correlation coefficients and repeatability data for the key elements in bauxite analysis demonstrate the excellent accuracy and precision of the handheld Niton XL3 950 GOLDD+ analyzer, indicating that the Niton XL3 GOLDD+ instrument is ideal for fast mine or field analysis. The instant chemical information it provides allows the user to make critical decisions with minimal downtime, keeping projects running and productive. Additionally, they provide information that minimizes the expense and time of shipping samples for analysis and increases savings. The Thermo Scientific Niton XRF analyzer is a great addition to any process in the life of the mine.</p>

News from LabRulezICPMS 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><strong>In the weeks of August 3 and 10, the following webinars await you in the field of liquid phase and especially HPLC and LC/MS.</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 500 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. Agilent Technologies: Characterising Advanced Materials with the Agilent UV-Vis-NIR: From Thin Films and Solar Cells to Glass and Optical Coatings</strong></h5><ul><li>Th, 6.8.2026 07:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.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><strong>2. Waters Corporation: LC Coffee Breaks: Mastering Overpressure - Prevention and Solutions that Work</strong></h5><ul><li>Th, 6.8.2026 14:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6410">Registration</a></li></ul><p>Take a practical LC coffee break and learn how to identify the causes of excessive system pressure, prevent overpressure, and resolve common problems efficiently.</p><h5><strong>3. US HUPO: Spatial Imaging Series: More Than Mass Spec</strong></h5><ul><li>Tu, 11.8.2026 20:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6362">Registration</a></li></ul><p>Explore advances in mass spectrometry imaging and discover innovative spatial analysis approaches that extend beyond conventional MS techniques.</p><h5><strong>4. SCIEX: PFAS Asia Summit 2026</strong></h5><ul><li>We, 12.8.2026 09:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6355">Registration</a></li></ul><p>Explore evolving PFAS regulations, major industry trends, and LC-MS/MS sample preparation workflows for robust and reliable PFAS detection.</p><h5><strong>5. Technology Networks: Unlocking New Insights Into PFAS Distribution and Biological Impact</strong></h5><ul><li>We, 12.8.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6397">Registration</a></li></ul><p>Learn how MALDI-TIMS-MS maps PFAS distribution in tissues, differentiates isomers, and reveals associated changes in the hepatic lipidome.</p><h5><strong>6. Agilent Technologies: Why Your Column Isn’t Always the Culprit: Smarter HPLC Troubleshooting</strong></h5><ul><li>We, 12.8.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/6349">Registration</a></li></ul><p>Learn practical diagnostic steps to identify the true causes of retention shifts, pressure spikes, and poor peak shapes without automatically blaming the LC column.</p>

Webinars LabRulezLCMS Weeks 32-33/2026

<p><strong>In the weeks from August 3 and 10, the following webinars await you in the field of atomic and molecular spectroscopy and spectrometry</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 500 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. Agilent Technologies: Elemental Analysis of Foods by Agilent 9500 ICP-QQQ with an Autodilutor</strong></h5><ul><li>Tu, 4.8.2026 21:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/6399">Registration</a></li></ul><p>Streamline food safety testing with the Agilent 9500 ICP-QQQ and automated dilution. Learn how the workflow supports efficient determination of toxic elements in food samples.</p><h5><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></h5><ul><li>Th, 6.8.2026 07:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.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><strong>3. Agilent Technologies: Optimizing ADS 2 Autodilutor: Operation, Troubleshooting, &amp; Best Practices</strong></h5><ul><li>Th, 6.8.2026 20:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/6400">Registration</a></li></ul><p>Learn the key operating principles of the ADS 2 autodilutor, including troubleshooting strategies for carryover, precision issues, and routine workflow optimization.</p><h5><strong>4. Thermo Fisher Scientific: Food Authenticity Uncovered: Using Isotope Fingerprints to Detect Adulteration and Verify Origin</strong></h5><ul><li>Tu, 11.8.2026 18:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/6406">Registration</a></li></ul><p>Discover how stable isotope ratio mass spectrometry uses isotope fingerprints to verify the geographical origin of food and beverages and detect adulteration.</p><h5><strong>5. Agilent Technologies: Analysis of Environmental Waters by 9500 ICP-QQQ in Advanced Helium Mode</strong></h5><ul><li>Tu, 11.8.2026 21:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/6401">Registration</a></li></ul><p>Learn how the Agilent 9500 ICP-QQQ uses advanced helium mode to control complex spectral interferences and improve elemental analysis of environmental water samples.</p><h5><strong>6. Thermo Fisher Scientific: From Spectra to Mechanism: Using DRIFTS to Understand CO₂ Catalysis</strong></h5><ul><li>We, 12.8.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/6404">Registration</a></li></ul><p>Learn how in situ DRIFTS reveals surface species and reaction mechanisms during dry reforming of methane over ceria-supported catalysts.</p>

Webinars LabRulezICPMS 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

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