<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezLCMS Library in the week of 13th October 2025? 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 application notes by <strong>Agilent Technologies,</strong> <strong>Shimadzu </strong>and<strong> Waters Corporation </strong>and poster by<strong> Thermo Fisher Scientific / HPLC!</strong></p><h3><strong>1. Agilent Technologies: Expanding Coverage for the Analysis of PFAS in Paper-Based Food Packaging Materials</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_pfas_food_contact_materials_6545_lcqtof_5994_8516en_agilent_0d3cbb1f4d.pdf"><strong>Full PDF for download</strong></a></li></ul><p>PFAS are manufactured chemicals used in food packaging for their grease- and waterproof properties. However, PFAS are persistent in the environment and may pose health risks.2 This study presents a workflow to screen for PFAS in FCMs using LC/Q-TOF. The FluoroMatch software suite was used to automate PFAS data annotation of knowns and unknowns as well as generate an interactive visualization dashboard, enhancing analysis accuracy and coverage.&nbsp;</p><p>The FluoroMatch suite is an open-source set of tools designed to streamline the suspect and nontarget screening of PFAS compounds. It automates several processes, including file conversion, chromatographic peak picking, blank feature filtering, PFAS annotation based on precursor and fragment masses, homologous series detection, compound classification (PFAS versus not PFAS), and reporting annotation confidence. The software library contains 15,643&nbsp;PFAS species and associated fragmentation patterns, with the capability to add more.3&nbsp;</p><p>Various FCM samples, including takeaway containers and microwave popcorn bags, were rigorously extracted and analyzed. Suspect screening was employed for PFAS quantitation, while nontargeted workflows enabled the identification and semi-quantitation of PFAS that were lacking&nbsp;standards.</p><h4><strong>Experimental</strong></h4><h5><strong>LC/MS analysis&nbsp;</strong></h5><p>Extracts were analyzed using an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=1290+Infinity+II+LC"><strong>Agilent 1290 Infinity II LC system</strong></a> coupled with an Agilent <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=6545+LC%2FQ-TOF"><strong>6545 LC/Q-TOF</strong></a>. An Agilent <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=PFC-Free+HPLC+Conversion+kit"><strong>PFC-Free HPLC Conversion kit</strong></a> (part number 5004‑0006) and an Agilent <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=InfinityLab+PFC+delay+column"><strong>InfinityLab PFC delay column</strong></a> (part number 5062‑8100) were used to minimize background PFAS levels. Liquid chromatographic separation was performed on a 1.8&nbsp;µm, 2.1 × 100 mm, Agilent ZORBAX RRHD StableBond SB‑C18 column (part number 858700-902) with a corresponding guard column (Agilent part number 821725-902). The mobile phases were (A) water with 20&nbsp;mM ammonium acetate and (B) methanol. The flow rate was 0.4&nbsp;mL/min. The elution gradient was: 5% B (0 to 0.5&nbsp;minutes), linear increase to 40% B (0.5 to 3 minutes), linear increase to 80% B (3 to 16 minutes), hold 80% B (16 to 18 minutes), linear increase to 100% B (18 to 22 minutes), hold 100% B (20 to 22&nbsp;minutes), decrease to 5% B (22 to 22.5 minutes), followed by a 4 minutes post‑run re‑equilibration. The injection volume was 10 μL, and the column temperature was maintained at 50 °C. For the LC/Q‑TOF, the drying gas was set to 4 L/min at 230 °C, the nebulizer to 20 psi, and the sheath gas to 12 L/min at 375 °C.</p><h4><strong>Results and discussion</strong></h4><p>PFAS identification using <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=FluoroMatch"><strong>FluoroMatch</strong></a> Using FluoroMatch Visualizer, interactive tools for visualizing PFAS data were generated, including mass defect plots, accurate mass versus retention time plots, MS/MS fragmentation plots, annotation tables, and fragment screening. Individual homologous series were selected based on nominal mass and normalized mass defect, allowing for the observation of patterns and identification of outliers. This interactive cross-filtering simplified the evaluation of PFAS features and enhanced confidence in nontargeted results.&nbsp;</p><p>FluoroMatch was used to annotate a homologous series (C3 to C14) of perfluoroalkyl carboxylic acids (PFCAs), including PFHxA (perfluorohexanoic acid), PFHpA (perfluoroheptanoic acid), PFOA (perfluorooctanoic acid), PFNA (perfluorononanoic acid), PFDA (perfluorodecanoic acid), and PFDoDA (perfluorododecanoic acid). This workflow demonstrated that the suspect screening approach successfully identified common PFAS with available standards, while FluoroMatch was able to annotate additional PFAS that were lacking standards.&nbsp;</p><p>Additionally, FluoroMatch annotated C6 and C8 perfluoroalkyl sulfonic acids (PFSAs), which were not identified by suspect screening. This highlights the value of a hybrid workflow that combines traditional suspect screening with nontargeted tools like FluoroMatch, enhancing confidence in the nontargeted results through their complementary nature. Specifically, FluoroMatch allows for homologous series detection to help annotate incomplete or noisy spectra. FluoroMatch Visualizer evaluation helps incorporate additional lines of evidence to annotation like retention time patterns and Kendrick mass defect to aid in annotation.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>This study successfully demonstrates the effectiveness of FluoroMatch software in automating the annotation and visualization of PFAS compounds in food packaging materials. The integration of FluoroMatch Visualizer provides a comprehensive approach to identifying both targeted and nontargeted PFAS compounds. The results highlight the prevalence of PFAS in various paper‑based FCMs, with clamshell to-go boxes showing the highest concentrations, particularly PFOA and PFDA, which exceed European Union regulatory limits. As PFAS can migrate into food, especially at higher temperatures, the pervasiveness of PFAS in FCMs raises concerns about potential exposure through hot meals and microwave heating. The widespread detection of PFAS in clamshell to-go boxes and other FCMs indicates a need for stricter regulations to reduce PFAS use in food packaging to protect consumer&nbsp;health.</p><h3><strong>2. Shimadzu: An Ultra-high Sensitivity Analysis of 29 PFAS Compounds in Drinking Water by Direct Injection</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_01_01026_en_dcf554dd6f.pdf"><strong>Full PDF for download</strong></a></li></ul><p>PFAS (Per- and Polyfluoroalkyl Substances) are synthetic fluorinated organic compounds. More than a few thousand compounds exist, each with a varied carbon chain length, functional groups, and structural isomers. Because of its useful qualities, such as their ability to repel water and their nonstickiness, PFAS are found in a wide range of consumer and industrial products, including firefighting foams and coatings. Their high stability and persistence raise concerns about their impact on human health and the environment. In recent years, regulations and studies regarding PFAS have been increasing globally. For example, the U.S. Environmental Protection Agency (EPA) has set a Maximum Contaminant Level (MCL) of 4 ng/L for PFOA and PFOS in drinking water. To improve the analysis of PFAS, more sensitive, accurate and faster methods are needed. This application introduces the ultra-high sensitivity analysis of 29 PFAS in drinking water by direct injection using the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=1&amp;search=LCMS-8065XE"><strong>LCMS-8065XE</strong></a> (Fig. 1) and addresses the demands of testing laboratories for PFAS quantification.</p><h4><strong>Analytical conditions</strong></h4><p>The HPLC and MS analytical conditions are shown in Table 1 and 2. The test compounds used were the 29 compounds included in methods EPA 533 and 537.1 for drinking water analysis. The <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=1&amp;search=LCMS-8065XE"><strong>LCMS8065XE</strong></a> is equipped with a new ESI probe (StreamFocus) and a new collision cell (UFsweeper IV), providing more sensitive and accurate results in PFAS analysis. A delay column was installed between the mixer and autosampler to separate PFAS from the HPLC system and those in the sample. To ease the analysis, same type of column is used as delay and analytical columns.</p><h4><strong>Conclusion&nbsp;</strong></h4><ul><li>29 of PFAS in drinking water were measured with high sensitivity (&lt;1 ng/L) by direct injection method using the LCMS-8065XE.&nbsp;</li><li>Good recovery and reproducibility were obtained in drinking water samples, confirming that this analytical method can deliver accurate quantification for PFASsin drinking water.</li></ul><h3><strong>3. Thermo Fisher Scientific / HPLC: Efficient tandem capillary flow LC-MS with short μPAC columns and a single ionization source</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/po_efficient_tandem_capillary_flow_lc_ms_short_pac_columns_po_en_f38e078c9a.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Nano-flow tandem direct injection (TDI) workflows increase sample throughput and instrument productivity with flow rates below 1 µL/min but need dual-column ESI interfacing to maintain chromatographic performance. At flow rates above 1 µL/min with capillary flow columns, post-column dispersion impacts performance less, allowing low-dispersion switching valves in the fluidic path. We demonstrate the Vanquish Neo UHPLC system TDI workflow for capillary flow LC with a high throughput short pillar array column. This dual-column, single-ESI emitter setup reduces variability, extends emitter life through efficient salt management, and ensures high reproducibility with dedicated gradient pumps and intelligent method design.</p><h4><strong>Materials and methods</strong></h4><h5><strong>Sample Preparation&nbsp;</strong></h5><p>HeLa cell digests were resuspended in 0.1% TFA and 1% ACN to obtain a 200 ng/µL stock solution, sonicated, diluted, and vortexed before use.</p><h5><strong>LC-MS configuration&nbsp;</strong></h5><p>Samples were analyzed using a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/398"><strong>Vanquish Neo UHPLC</strong></a> instrument that was configured in tandem direct injection mode with an additional pump module and a 10 µL injection loop for maximum throughput. Two µPACM Neo High-Throughput Plus columns were positioned between low-dispersion 6-port switching valves in the column compartment. A 20 µm ID nanoViper line connected the alternating eluents to an ESI emitter with an integrated liquid junction, positioned in a Thermo Scientific EASY-Spray source coupled to a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/402"><strong>Orbitrap Exploris 240 mass spectrometer</strong></a></p><h4><strong>Conclusions&nbsp;</strong></h4><ul><li>Using optimized µPAC Neo HT Plus columns in combination with the Tandem Vanquish Neo UHPLC system heightened the productivity of bottom-up proteomics measurements to 86 - 92% (gradient-dependent)&nbsp;</li><li>At these throughputs, choice of emitter only has a minor effect on identifications, FWHM and TIC. Decreasing the flow rate to 1 uL/min causes peak broadening and increases ionization efficiency which is reflected in higher TICs. In this study, reducing the flow rate only showed a positive effect on protein IDs for the longest gradient (100 SPD).&nbsp;</li><li>With the optimized methods, identifications up to 4713 protein groups for the 180 SPD and 5692 protein groups for the 100 SPD were achieved. The CVs using the same column were between 5-6% and between two columns at around 7-8% (n=6)&nbsp;</li><li>Column reproducibility was showcased for 12 columns across four different production batches. Overall, the ID rate variation between the columns was 1.4%. The median coefficient of variation of the retention times of spiked-in PRTC peptides across the tested 12 columns was 1.8%</li></ul><h3><strong>4. Waters Corporation: Oligo Mapping of sgRNA Digests: Leveraging Xevo MRT Mass Spectrometer Performance and Streamlining Data Analysis</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/720009009_en_f35f22bebc.pdf"><strong>Full PDF for download</strong></a></li></ul><h5><strong>Benefits&nbsp;</strong></h5><ul><li>Confident characterization of sgRNA digestion products with sub-ppm mass accuracy of oligonucleotide precursors, outstanding MS resolution (~100,000), and sensitivity at high acquisition speed</li><li>A compliance-ready informatics workflow featuring the waters_connect MAP Sequence App (ver 1.0) streamlines oligonucleotide mapping of sgRNA digests</li><li>RapiZyme MC1, a new ribonuclease - offers unique cleavage specificity and the opportunity to generate overlapping digestion products, enabling complete (100%) sequence coverage for sgRNAs</li></ul><p>Single guide RNAs (sgRNAs) were first described in 20121 when two RNA molecules essential for CRISPR-Cas9- mediated DNA cleavage – the trans-activating CRISPR RNA (tracrRNA), which serves as a scaffold for the Cas9 nuclease, and the CRISPR RNA (crRNA), responsible for DNA target recognition - were fused into a single RNA construct. This fusion created the sgRNA, a critical component of the CRISPR-Cas9 gene editing system.<sup>1–2</sup> The sgRNA molecule directs the Cas9 nuclease to introduce precise double-stranded breaks in DNA, enabling targeted genetic modifications.&nbsp;</p><p>Since its discovery, which was honored with the Nobel Prize in Chemistry, CRISPR technology has transformed gene editing applications. Beyond basic research, it has been adapted for rapid diagnostic tools, such as COVID19 tests developed during the 2020 global pandemic<sup>3</sup> , and holds promise for therapeutic interventions in genetic diseases, cancer, and infectious diseases. As sgRNAs are typically synthesized via solid-phase oligonucleotide synthesis, their analytical characterization requires confirmation of both the intact molecular weight<sup>4</sup> and the sequence verification to ensure functional accuracy.<sup>5</sup>&nbsp;</p><p>Traditional LC-MS workflows for sgRNA digest oligo mapping have been labor-intensive and time-consuming, relying heavily on manual data analysis and interpretation. Recently<sup>6</sup> , a UPLC-MS and informatics workflow designed for automated sgRNA sequence mapping was presented following enzymatic digestion with a panel of ribonucleases, including RNase T1, hRNAse 4 and two RNase T2 enzymes: RapiZyme MC1 and Cusativin. This application note extends the effectiveness of this workflow (Figure 1) when implemented on a Xevo MRT Mass Spectrometer (Figure 1), while focusing specifically on MC1 digestion of the Waters™ sgRNA LC-MS standard, where complete unique digested product coverage was obtained.</p><h4><strong>Experimental</strong></h4><h5><strong>LC Conditions</strong></h5><ul><li><strong>LC-MS system:</strong> <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1148"><strong>Xevo MRT</strong></a> (multi-reflecting time-of-flight) Mass Spectrometer coupled with <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/191"><strong>ACQUITY™ Premier UPLC (Binary) System&nbsp;</strong></a></li><li><strong>Column: </strong>ACQUITY Premier Oligonucleotide BEH™ C18 Column 300 Å, 1.7 µm, 2.1 x 150 mm, (p/n:186010541)</li></ul><h4>Results and Discussion&nbsp;</h4><p>An informatics workflow (Figure 1) featuring the waters_connect MAP Sequence App (version 1.0) was used to facilitate automated data processing of UPLC-MSE datasets acquired following the enzymatic digestion of an sgRNA standard with RapiZyme MC1.6–7 The informatics processing workflow consisted of three steps:&nbsp;</p><ol><li><strong>In-silico digestion:</strong> The mRNA Cleaver MicroApp was used to generate predicted, in-silico digested oligonucleotide digestion products, based on the target RNA sequence.&nbsp;</li><li><strong>Data processing and mass matching:</strong> The waters_connect MAP Sequence App processed the UPLC-MSE data, matching the predicted neutral monoisotopic masses of digested oligonucleotides to the experimentally acquired MS1 data.&nbsp;</li><li><strong>Sequence coverage visualization: </strong>The resulting sequence coverage for the RNA digest was summarized and visualized using the Coverage Viewer MicroApp.</li></ol><h4><strong>Conclusion&nbsp;</strong></h4><ul><li>An informatics workflow, incorporating the waters_connect MAP Sequence App (ver 1.0) was successfully demonstrated for UPLC-MSE digested oligo mapping analysis of sgRNA digests using the Xevo MRT QTOF Mass Spectrometer.&nbsp;</li><li>Confident peak assessments for analysis of sgRNA digests were achieved with the Xevo MRT QTOF Mass Spectrometer, which delivered excellent sensitivity, high resolution MS (100,000), and mass accuracy of less than 1 ppm.</li><li>Complete sgRNA sequence coverage (100%) was achieved by employing RapiZyme MC1, a novel endonuclease introduced by Waters, which provided unique cleavage specificity and predictable missed cleavages to generate longer, unique, overlapping digestion products.</li><li>Oligonucleotide isomeric sequences resulting from enzymatic digestion were effectively differentiated using the waters_connect CONFIRM Sequence App, which matched elevated energy fragment ions patterns to their respective sequences, allowing unambiguous isomer identification.</li></ul>

News from LabRulezLCMS Library - Week 42, 2025

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezICPMS Library in the week of 13th October 2025? 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 posters by <strong>Shimadzu / AOAC</strong> and <strong>Thermo Fisher Scientific!</strong></p><h3><strong>1. Shimadzu / AOAC: Determination of Toxic Elements in Chilli Powder using Shimadzu ICPMS-2050</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/aoac_2025_m026_c76104ed94.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Spices, particularly red chillies, are essential and integral part of cuisines, offering not only distinctive flavour and aroma but also provides nutritional and preservative benefits. However, the growing concern of heavy metal contamination in chillies presents a significant threat to food safety, public health, and international trade. Effective monitoring and stringent quality control are essential to safeguard consumer well-being and maintain economic stability.</p><p>This study details a precise ICPMS method with <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=1&amp;search=ICPMS-2050"><strong>ICPMS-2050</strong></a> for quantifying toxic elements in chilli powder, developed in strict adherence to Food Safety and Standards Authority of India (FSSAI)1 regulations. The complex matrix of chilli powder presents significant analytical challenges for the accurate and efficient recovery of trace heavy metal elements. The presence of diverse organic compounds and high oil content can interfere with standard digestion procedures, leading to suboptimal extraction efficiencies and compromised analytical recovery of critical elements such as lead, cadmium and arsenic.</p><h4><strong>Results&nbsp;</strong></h4><p>Quantitation results for As, Cd, Hg &amp; Pb in chilli samples found to be BLOQ. Validation parameters like linearity, recovery and precision were studied to establish LOQs. This method successfully achieved LOQ of 0.250 ppm in sample. The summary results and system stability are shown in Table 4, 5, 6, 7 &amp; 8 respectively. As per FSSAI guideline. BLOQ – Below limit of quantitation, LOQ – Limit of quantitation&nbsp;</p><h5><strong>Linearity&nbsp;</strong></h5><p>NIST traceable calibration standards were used for linearity study and quantification of spiked samples. Six level calibrations curve was plotted for 0.5, 1.0, 2.5, 5.0, 10 &amp; 20 ppb concentration levels. For all calibration standards accuracy was found within 80 to 120 % range.&nbsp;</p><h5><strong>Recovery&nbsp;</strong></h5><p>Recovery was studied at 0.250 ppm spiked samples against calibration curve. Six preparations for each brand of samples were prepared. Mean recoveries were found to be within 80 -120 % at LOQ level (Refer Table 5).</p><h5><strong>Precision&nbsp;</strong></h5><p>For precision, repeatability and within-laboratory reproducibility studies were carried out. RSDr : The % RSD for 3 replicates of each sample aspiration at LOQ (0.250 ppm) levels was found to be less than 20 % (Refer Table 6). RSDR : Reproducibility experiment for recoveries was performed on 6 different spiked samples at 0.250 ppm concentration levels. The % RSD of 6 spiked samples at their respective LOQ level was found to be less than 10 % (Refer Table 7).&nbsp;</p><h4><strong>Conclusion</strong></h4><ul><li>This study demonstrates that the Shimadzu ICPMS system is a reliable and effective instrument for quantifying toxic elements in chilli powder samples.</li><li>Because of the complex nature of chilli powder, higher dilution factor needed to be applied in conjunction with Shimadzu<span>’</span>s Octa-plate Collision Cell technology to minimizes spectral interferences for achieving lower LOQs.</li><li>The Shimadzu ICPMS enables trace-level detection in samples, contributing to enhanced method ruggedness and ensuring consistent, reproducible analyte detection.</li><li>The combination of a highly sensitive instrument and a robust analytical method makes it wellsuited for use in testing laboratories for the analysis of toxic elements in chilli powder.</li></ul><h3><strong>2. Thermo Fisher Scientific: High sensitivity tin speciation using a new GC interface with Sector Field High Resolution ICP-MS</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/labrulez-bucket-strapi-h3hsga3/po_43431_EWCPS_2017_high_sensitivity_tin_speciation_hr_icp_ms_gc_interface_po43431_en_ef893ded0e.pdf"><strong>Full PDF for download</strong></a></li><li>Often the total elemental concentration of an analyte is not sufficient to accurately assess its impact on the environment or human health.&nbsp;</li><li>That is because toxicity and mobility are dependent on the species of the analyte.&nbsp;</li><li>Tin, for example, can be found in a variety of molecules, each with different degrees of toxicity and persistence.&nbsp;</li><li>Tributyltin (TBT) is widespread in the environment due to its mobile and persistent nature.&nbsp;</li><li>As TBT is toxic at very low concentrations, there are strict legislative limits (e.g. the European Water Framework Directive)</li></ul><h4><strong>MATERIALS AND METHODS&nbsp;</strong></h4><p>The <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/products/1670"><strong>Thermo Scientific™ ELEMENT XR™ HR-ICP-MS</strong></a> and the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/3"><strong>Thermo Scientific™ TRACE™ 1310 GC</strong></a> were coupled with the Thermo Scientific™ GCI 200 Interface.</p><h4><strong>CONCLUSIONS&nbsp;</strong></h4><ul><li>Because of the high acceleration voltage of Sector Field ICP-MS this technique is extremely sensitive.&nbsp;</li><li>In combination with its low backgrounds, this leads to the low detection limits required for sensitive tin speciation analysis.&nbsp;</li><li>The stable temperature profile and the absence of cold spots avoids condensation and peak broadening.&nbsp;</li><li>Minimal tailing on high boiling compounds.&nbsp;</li><li>Minimal memory and carryover effects.&nbsp;</li><li>By means of the flexible and light design of the heated transfer line, the ICP-MS torch position can be easily tuned.</li></ul>

News from LabRulezICPMS Library - Week 42, 2025

<p><strong>Hops (</strong><i><strong>Humulus lupulus</strong></i><strong>) are essential for brewing due to their resins and aromatic oils. In this study, the chemical profiles of 76 commercial hop cultivars were analyzed using GC–MS and metabolomic approaches to explore their ancestral relationships. Unsupervised statistical analyses revealed distinct clustering between North American and European lineages.</strong></p><p>Molecular networking enabled the annotation of 26 metabolites that distinguished the two groups. American hops were characterized by mono- and sesquiterpenoids, ketones, and esters, while European varieties showed higher abundances of selinenes, trans-α-bergamotene, humulene epoxide II, neophytadiene, and tocopherols. These results establish metabolomic signatures as reliable markers for hop cultivar differentiation and enhance understanding of their chemical diversity and lineage-based classification.</p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c06162"><strong>Mapping Metabolomic Relationships of Hop Cultivars in an Ancestral Lineage Context</strong></a></h4><p>Guilherme Silva Dias, Marília Elias Gallon, Leonardo Gobbo-Neto*</p><p>ACS Omega 2025, 10, 40, 47281–47291</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acsomega.5c06162">https://doi.org/10.1021/acsomega.5c06162</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><p>Highly valued in the global brewing industry, hops are perennial, dioecious, herbaceous, liana-like plants that belong to the Rosales order and to the Cannabaceae family. <a href="javascript:void(0);">(1,2)</a> The genus <i>Humulus</i>, which consists of three species─<i>Humulus lupulus</i> L. (<i>H. lupulus</i>, common hops), <i>Humulus japonicus</i> Siebold &amp; Zucc., and <i>Humulus yunnanensis</i> Hu─ is believed to have originated in China, although wild populations of <i>H. lupulus</i> are known to be widely distributed across the Northern Hemisphere. <a href="javascript:void(0);">(3,4)</a> Accordingly, the history of hops along with their domestication and use in brewing remains surrounded by uncertainties. <a href="javascript:void(0);">(1,4,5)</a></p><p><i>Humulus lupulus</i> is the most economically and culturally significant species within the genus, having been used in beer production for centuries. <a href="javascript:void(0);">(3)</a> Initial hop cultivars were derived through the selective breeding of wild European populations. <a href="javascript:void(0);">(6,7)</a> A general agreement posits that North American and European wild varieties diverged from a common ancestor more than a million years ago. <a href="javascript:void(0);">(4,8)</a> Currently, five geographically and morphologically distinct botanical varieties of <i>H. lupulus</i> are recognized: var. <i>humulus</i> (Europe and Asia), var. <i>cordifolius</i> (East Asia, particularly Japan), var. <i>neomexicanus</i> (southwestern North America), var. <i>pubescens</i> (eastern and north-central USA), and var. <i>lupuloides</i> (northeastern North America and Canada). <a href="javascript:void(0);">(5,9)</a> Over time, cultivar development has evolved from open-pollinated crosses to controlled hybridization, incorporating North American germplasm and thus broadening the genetic base. <a href="javascript:void(0);">(7)</a></p><p>The importance of hop cultivation is highlighted by global production, which ranges from 80,000 to 130,000 tons annually, with Germany and the United States being the world’s largest producers. <a href="javascript:void(0);">(10,11)</a> The increasing demand for aromatic hops, driven by the American craft beer revolution dating back to the 1980s, has accelerated the development of new cultivars. Currently, approximately 300 commercial cultivars are available in the brewing market. <a href="javascript:void(0);">(12−14)</a> Beyond imparting bitterness, flavor, and aroma, hops also exhibit antimicrobial and antioxidant properties, playing a crucial role in the organoleptic stability of beer. <a href="javascript:void(0);">(15−17)</a></p><p>The main compounds in hops that are valuable for beer production are biosynthesized and accumulated in the inflorescences (strobiles, also referred as cones) of female plants, specifically in the glandular trichomes (lupulin glands) located at the bases of the bracteoles of the cones. <a href="javascript:void(0);">(2,3)</a> The resins contain compounds and precursors that contribute to the bitterness of beer (e.g., α-acids and β-acids), while the essential oils are the main contributors to the aromatic profile, especially in beer styles that emphasize hop character. <a href="javascript:void(0);">(18)</a> The amount of essential oils in hops can range from 0.5 to 4.0% of the dry cone weight and is primarily composed of terpenes (up to 90% of the essential oil), aliphatic hydrocarbons, oxygenated compounds (such as terpenoid, ester, ketone, alcohol, carboxylic acid, aldehyde, and epoxide derivatives), and organosulfur compounds. <a href="javascript:void(0);">(19−21)</a></p><p>Analytical approaches such as gas chromatography coupled to mass spectrometry (GC-MS), liquid chromatography coupled to ultraviolet detectors and/or mass spectrometry (LC-UV-MS), and nuclear magnetic resonance (NMR) have been widely employed for hop characterization. <a href="javascript:void(0);">(22−26)</a> For aroma profiling and quality control, GC-MS techniques are employed to analyze volatile compounds, whereas LC-UV-MS techniques are used to characterize bitter acids, polyphenols, and flavonoids. <a href="javascript:void(0);">(22)</a> Volatile and semivolatile metabolites in hops are largely determined by genetic factors and, therefore, define characteristic phytochemical profiles for each hop cultivar. <a href="javascript:void(0);">(2,27−29)</a> In this regard, a comprehensive GC-MS approach encompassing a wide variety of metabolites is essential for capturing lineage-associated differences in metabolite composition that may be overlooked by traditional workflows focusing solely on volatile compounds. <a href="javascript:void(0);">(21,30)</a></p><p>Metabolomic approaches are powerful tools for investigating the chemotaxonomic diversity, including that of hop cultivars from various geographical origins. <a href="javascript:void(0);">(26,31−33)</a> Despite the commercial significance of hop cultivars, comprehensive studies utilizing metabolomic techniques to analyze a broad spectrum of commercial varieties remain scarce. Given that beer quality is intrinsically linked to the chemical composition of its raw materials and ingredients (malted barley, hops, yeast, and water), comprehensive analyses of hop metabolites are helpful in selecting the best varieties to produce beers with desirable flavor profiles, balanced bitterness, and optimal aroma intensity. In this context, such metabolomic knowledge may provide valuable support for the brewing industry in cultivar selection, quality standardization, and product development. In this study, 76 hop cultivars, marketed in a pelletized form, were analyzed by using GC-MS metabolomic profiling. The resulting data were subjected to multivariate statistical analyses and molecular network techniques to identify chemotaxonomic patterns linked to the cultivars’ geographical origins. These findings provided novel insights into the chemical diversity of hops and offered frameworks for mapping relationships among cultivars based on their metabolomic signatures.</p><h4><strong>Methods</strong></h4><h5><strong>Extract Preparation and GC-MS Analysis</strong></h5><p>The methodologies used for extract preparation and the GC-MS analytical conditions were the same as those previously employed by our research group. <a href="javascript:void(0);">(74)</a> Blank samples (dichloromethane) and hydrocarbon standard solution (C<sub>8</sub>–C<sub>40</sub>, Supelco, Sigma-Aldrich, St. Louis, MO, USA) were also injected during the chromatographic analysis.</p><p>Analyses were conducted using a <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=QP2010+Ultra"><strong>gas chromatograph coupled to a quadrupole mass spectrometer (QP2010 Ultra</strong></a>, Shimadzu Corporation, Kyoto, Japan). The chromatograms and mass spectra were visualized using <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GC+Solutions"><strong>GC Solutions software</strong></a> (version 4.20 for Windows, Shimadzu Corp., Kyoto, Japan).</p><h4><strong>Results and Discussion</strong></h4><h5><strong>Exploring the Hop Chemical Content</strong></h5><p>To explore variations in the chemical profiles of hops based on the clustering patterns observed in the HCA, a molecular network was generated using the same GC-MS data (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsomega.5c06162/suppl_file/ao5c06162_si_001.pdf">Figure S2, Supporting Information</a>). Each node in the network represents a detected metabolite, which are arranged into clusters according to their MS spectral similarities. This approach enabled the annotation of key metabolites responsible for differentiation between the two main groups observed in the dendrogram.</p><p>The clusters containing the major annotated metabolites are shown in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c06162#fig4">Figure 4</a>. The largest cluster is primarily composed of sesquiterpenoids (dark blue border), one diterpenoid (pink border), and several unidentified metabolites. Other clusters are composed of monoterpenoids (light blue border), aliphatic esters (green border), ketones (brown border), and tocopherols (yellow border).</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2025_10_40_47281_47291_Figure_4_Clusters_containing_annotated_metabolites_selected_from_the_molecular_network_ded5c3e6c3.jpg" alt="ACS Omega 2025, 10, 40, 47281–47291: Figure 4. Clusters containing annotated metabolites selected from the molecular network. The numerical labels inside the nodes indicate the respective identification numbers (node IDs). The nodes are colored according to the groups obtained from the unsupervised hierarchical cluster analysis (HCA), and the border colors correspond to the metabolite classes." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2025_10_40_47281_47291_Figure_4_Clusters_containing_annotated_metabolites_selected_from_the_molecular_network_ded5c3e6c3.jpg 137w," sizes="100vw" width="1000" height="1141"></p><p>Twenty-six metabolites were annotated in level 2 of confidence according to the minimum reporting standards for chemical analysis (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c06162#tbl1">Table 1</a>). <a href="javascript:void(0);">(65,66)</a> The group 1 of the HCA dendrogram, composed predominantly of North American hops and their descendants, was characterized by a higher abundance of monoterpenoids, sesquiterpenoids, aliphatic esters, and methyl ketones, annotated as β-myrcene (<strong>17</strong>), 2,6-octadiene, 2,7-dimethyl (<strong>18</strong>), <i>trans</i>-geranic acid, methyl ester (<strong>65</strong>), linalool (<strong>36</strong>), calarene (<strong>79</strong>), α-cubebene (<strong>67</strong>), α-copaene (<strong>70</strong>), β-caryophyllene (<strong>78</strong>), α-humulene (<strong>82</strong>), β-farnesene (<strong>83</strong>), germacrene D (<strong>90</strong>), γ-cadinene (<strong>110</strong>), farnesol (<strong>187</strong>), isobutyl isobutyrate (<strong>7</strong>), 2-methylbutyl isobutyrate (<strong>22</strong>), 2-undecanone (<strong>59</strong>), 2-tridecanone (<strong>101</strong>), and 2-pentadecanone (<strong>181</strong>). The group 2, consisting of European hops and their descendants, was distinguished by higher prevalence of the monoterpenoid geranyl acetate (<strong>71</strong>), the sesquiterpenoids α- and β-selinene (<strong>95</strong> and <strong>93</strong>), <i>trans-</i>α-bergamotene (<strong>80</strong>), humulene epoxide II (<strong>139</strong>), the diterpenoid neophytadiene (<strong>219</strong>), and β- and γ-tocopherols (<strong>614</strong> and <strong>615</strong>).</p><p>Group 1 hop cultivars were mainly characterized by the presence of the sesquiterpenoids α-humulene and β-caryophyllene, as well as the monoterpene β-myrcene. These three compounds are recognized as the main constituents of hop essential oils and account together for up to 90% of the total composition, depending on the cultivar. <a href="javascript:void(0);">(2)</a> The predominance of β-myrcene in North American hops, consistently reported in the literature, was confirmed in this study. <a href="javascript:void(0);">(67)</a> Alongside β-myrcene, a higher concentration of linalool was also observed, a monoterpenoid with floral aromatic properties that shares the same biosynthetic pathway as β-myrcene, <a href="javascript:void(0);">(68)</a> which explains their co-occurrence and prominence in the North American lineage group.</p><p>In addition to this chemical profile, the presence of several other sesquiterpenoids (calarene, α-cubebene, α-copaene, germacrene D, γ-cadinene, and farnesol) was also observed in group 1 hops. The biosynthesis of sesquiterpenes generates a wide diversity of chemical structures, which are primarily modulated by genetic factors through the action of specific sesquiterpene synthase enzymes. <a href="javascript:void(0);">(69)</a> The biosynthetic transformation pathway of this metabolite class may explain the simultaneous and abundant presence of these compounds within the same group, corresponding to hops of North American lineage.</p><p>Also, group 1 cultivars exhibited high levels of β-farnesene, a sesquiterpene initially isolated from the Czech hop Saaz and traditionally reported as a chemical marker of European hops. <a href="javascript:void(0);">(67,70)</a> Despite this long-standing association, the presence of this metabolite is highly variable among hop cultivars, and its absence has been documented in several traditional European varieties such as Hallertau, Goldings, and Fuggles. <a href="javascript:void(0);">(19)</a> Our results, comprising 76 different hop cultivars, revealed a high predominance of β-farnesene in the group of North American hops. Nevertheless, the results are consistent with previous research demonstrating an inverse relationship between farnesene and selinene levels in hops. These findings were also observed in our study, considering that α- and β-selinenes were predominantly detected in the European hop group. <a href="javascript:void(0);">(67)</a> Interestingly, selinenes have been described as effective chemical markers for the identification of hop cultivars, with several studies reporting high concentrations of these compounds in hops of European genetic background. <a href="javascript:void(0);">(41,51,67,70−72)</a> Thus, our findings reinforce the evidence that selinenes are potential metabolites for distinguishing hops from European lineages.</p><h4><strong>&nbsp;Conclusions</strong></h4><p>Our metabolomic approach of hops cultivars based on GC-MS analyses and unsupervised statistical methods demonstrated a consistent correlation with their genetic origin (North American and European lineages). Molecular networking analysis enabled the annotation of 26 metabolites that contributed to differentiating North American from European lineage hop cultivars. Overall, hops of North American lineage exhibited chemical profiles characterized by mono- and sesquiterpenoids, ketones, and esters. Furthermore, the results reinforced the evidence supporting selinenes as relevant markers for European-derived hops and highlighted <i>trans-</i>α-bergamotene as an important chemical marker. This metabolomic technique proved to be an effective strategy for mapping relationships among hops based on their chemical profiles and provided a powerful and comprehensive scientific foundation for the characterization of different hop cultivars commercially available to the brewing industry.</p>

Mapping Metabolomic Relationships of Hop Cultivars in an Ancestral Lineage Context

Lab-on-a-Scalpel: Medical Tool Incorporating a Disposable Fully 3D-Printed Electrochemical Cell Promoting Drop-Volume Chemical Analysis in the Operating Theater

<p><strong>Mechanochemistry offers a green, solid-state pathway for designing nanomaterials, while chemical aging provides precise control under mild conditions. This study combines both methods to create nonstoichiometric bismuth oxide nanosheets with exceptional adsorption and photocatalytic performance toward persistent organic pollutants.</strong></p><p>Detailed structural and compositional analyses revealed that strain-induced defect formation during grinding followed by chemical delamination under aging leads to the formation of defect-rich Bi₂O₂.₃₃ nanosheets. This mechanochemical-aging synthesis provides new insight into two-dimensional metal oxide design and expands the potential for sustainable nanomaterial production.</p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsmaterialsau.5c00104"><strong>Mechanochemical-Aging Synthesis of Bismuth Oxide Nanosheets for Photocatalysis</strong></a></h4><p>Delaney J. Hennes, Luke T. Coward, Chase G. Thurman, Oksana Love*, and Pin Lyu*</p><p>ACS Mater. Au 2025, XXXX, XXX, XXX-XXX</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acsmaterialsau.5c00104">https://doi.org/10.1021/acsmaterialsau.5c00104</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><p>Mechanochemistry, old techniques with new perspectives, has been reawakening the passion for exploring solid-state approaches toward chemical transformations and materials synthesis in a green and sustainable manner, due to its intrinsic solvent-free and eco-friendly nature. <a href="javascript:void(0);">(1−8)</a> More importantly, the driving force of the mechanochemical process, mechanical force, has provided a fundamentally different reaction pathway by promoting intensive, well-oriented, and effective molecular collisions and creating molecular strains and structural defects, <a href="javascript:void(0);">(6,9−13)</a> compared to the conventional thermal or electrostatic driving forces. This perspective has opened new avenues for well-defined nanomaterial synthesis with unique structure–property relationships that the conventional solution-based methods cannot achieve, as well as in a greener way. <a href="javascript:void(0);">(4,14−17)</a> Recent reports have demonstrated great potential in designing metal and metal oxide nanoparticles, <a href="javascript:void(0);">(17,18)</a> nanocomposites, <a href="javascript:void(0);">(19)</a> and hybrid porous materials such as metal–organic frameworks (MOFs) and covalent organic frameworks (COFs) with desired properties. <a href="javascript:void(0);">(20−22)</a></p><p>In terms of 2D nanostructure design, two traditional approaches─bottom-up and top-down synthesis─have been widely developed in various synthesis strategies, offering precise control over size, shape, morphology, and dimensions. <a href="javascript:void(0);">(23,24)</a> The formation mechanism behind the scenes can be monitored and reasonably interpreted by advanced in situ spectroscopic <a href="javascript:void(0);">(25−27)</a> or microscopy methods, <a href="javascript:void(0);">(28−30)</a> to identify the critical factors in the structure transformation that lead to property-on-demand synthesis. Specifically, in 2D metal oxide nanosheet synthesis (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsmaterialsau.5c00104#sch1">Scheme 1</a>), chemical vapor deposition, solvothermal method, and chemical exfoliation represent three typical methods. The first two methods start with molecular or atomic precursors for self-assembly growth, while the last method utilizes bulk layered host materials for layer-by-layer delamination. However, these methods rely on sophisticated instrumentation, harsh synthesis conditions, excess solvents, or toxic exfoliating chemicals, which limit their potential scalability.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Mater_Au_2025_Scheme_1_Comparison_of_Conventional_and_Mechanochemical_Aging_Methods_for_Bismuth_Oxide_Nanosheet_Synthesis_536967aa25.jpg" alt="ACS Mater. Au 2025: Scheme 1. Comparison of Conventional and Mechanochemical-Aging Methods for Bismuth Oxide Nanosheet Synthesis" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Mater_Au_2025_Scheme_1_Comparison_of_Conventional_and_Mechanochemical_Aging_Methods_for_Bismuth_Oxide_Nanosheet_Synthesis_536967aa25.jpg 245w," sizes="100vw" width="1000" height="487"></p><p>Mechanochemical synthesis, with its all-solid-state, solvent-free nature, provides an alternative approach. This approach introduces an external applied physical force to initiate intense molecular interactions for mixing and growing (bottom-up) or to spread the shear stress or shock impact uniformly for deformation or delamination (top-down). It has been elegantly demonstrated in various traditional two-dimensional materials syntheses, such as graphene, <a href="javascript:void(0);">(31)</a> MXenes, <a href="javascript:void(0);">(32)</a> and transition-metal dichalcogenides. <a href="javascript:void(0);">(33)</a> Specifically, for bismuth-based materials, nanosheets of bismuthene, <a href="javascript:void(0);">(34)</a> bismuth oxyhalides, <a href="javascript:void(0);">(35)</a> and bismuth nitrates <a href="javascript:void(0);">(36)</a> have been reported previously with the mechanochemical methods. Meanwhile, very few reports are focused on metal oxide 2D nanostructures, probably due to the relatively higher interlayer interactions in those host materials. Thus, a follow-up process is needed to accelerate delamination of the mechanochemically produced bulk materials into the desired 2D nanosheet structure. Recently, Moores’s and Friščić’s groups have successfully demonstrated the combination of mechanochemistry and aging for the extraction and functionalization of biomass derivatives, <a href="javascript:void(0);">(37,38)</a> and functionalized inorganic metal or binary nanoparticle synthesis. <a href="javascript:void(0);">(39,40)</a> Aging, as a spontaneous diffusion-controlled process, can be controlled by the chemical reactivity and solution environment to induce material transformation, further advancing to the targeted structures while minimizing reagent and energy use. <a href="javascript:void(0);">(40)</a></p><p>In this work, we developed a mechanochemical-aging process to synthesize nonstoichiometric bismuth oxide (Bi<sub>2</sub>O<sub>2.33</sub>) nanosheets, which demonstrated excellent performance in the adsorption and photodegradation of perfluorooctanoic acid (PFOA). Through the observation of morphological, crystal structure, and surface chemistry changes during the aging process, we propose a strain-to-defect growing mechanism. Mechanical force exerted on metal precursors and reducing agents during solid-state grinding can induce rapid and intense molecular collisions, leading to the generation of strain-rich metallic nanostructures. The following aging process, occurring in an aqueous surfactant-deficient environment, can delaminate the bulk structure into well-defined 2D nanosheets over time with the assistance of ambient oxygen. This approach could potentially be applied to other 2D metal oxide nanostructures.</p><h4><strong>Experimental Methods</strong></h4><h5><strong>Chemicals and Characterizations</strong></h5><p>All chemicals and reagents were used without any purification. Bismuth(III) nitrate pentahydrate (99.999%, trace metal basis), PVP (M.W. 40,000), and sodium borohydride (99%, powder) were purchased from Thermo Scientific Chemicals. The morphology and elemental mapping analysis of bismuth oxide nanosheets (Bi<sub>2</sub>O<sub>2.33</sub> nanosheets) was examined by scanning electron microscopy (SEM, JSM-IT700HR, 15 kV, JEOL) with energy dispersive X-ray spectroscopy (EDS, 0–20 kV energy window, Ultim Max 40: UVA13205 detector, Oxford Instruments). The evolution of the local crystalline structure of Bi<sub>2</sub>O<sub>2.33</sub> nanosheets was monitored by a powder X-ray diffraction pattern (<strong>PXRD, Bruker D2 PHASER Benchtop XRD</strong>, Cu tubes, 30 kV, 10 mA) and was processed with DIFFRAC.EVA data analysis software with the Crystallography Open Database (rev.278581). The surface status of functional groups was determined by Fourier transform infrared spectroscopy (<strong>FTIR</strong>, <strong>Shimadzu </strong><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library?mainauthorItems=1&amp;search=IRSpirit"><strong>IRSpirit</strong></a>, 16 scans collected with a resolution of 4 cm<sup>–1</sup>) with the attenuated total reflectance (ATR) mode. The quantification of the PFOA (C<sub>7</sub>F<sub>15</sub>–COOH) and its degradation intermediates, perfluoroheptanoic acid (PFHpA, C<sub>6</sub>F<sub>13</sub>–COOH) and perfluorohexanoic acid (PFHxA, C<sub>5</sub>F<sub>11</sub>–COOH), was determined by liquid chromatography–mass spectrometry (LC-MS, <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?manufacturerItems=3&amp;search=LCMS-8040"><strong>LCMS-8040 Triple Quad LC-MS/MS</strong></a>, Shimadzu Scientific Instruments) in negative electrospray ionization mode. Separation of analytes occurred with the use of a binary solvent gradient between 5 mM ammonium acetate in H<sub>2</sub>O and methanol that ramped from 5% methanol at 0–3 min to 40% methanol from 3 to 16 min and 80% methanol after 16 min. Each liquid was passed through a Phenomenex C18 column (1.8 μm, 100 × 2.1 mm) at a constant oven temperature of 40 °C with a solvent flow rate of 0.25 mL per min. The elution of PFOA occurred at 15.7 min, PFHpA at 13.2 min, and PFHxA at 11.6 min. A <sup>13</sup>C isotope-labeled PFOA internal standard (Wellington Laboratories) was paired with a <sup>12</sup>C native PFOA solution to quantify each sample’s concentration. The standard curve for PFOA quantification ranges from 0.5, 1, 5, 10, 25, 50, and 100 ppb, with a limit of detection of 3.6 ppb and a limit of quantification of 11.1 ppb.</p><h4><strong>Results and Discussion</strong></h4><p>To pinpoint the growing mechanism behind the mechanochemical-aging process, morphological, crystal structure, and surface chemistry changes are monitored by using SEM, XRD, and FTIR, respectively. First, after freshly grinding, the gray powder was sent for XRD testing, as shown in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsmaterialsau.5c00104#fig2">Figure 2</a>a as Sample (Day 1). All of the observed diffraction peaks match well with the standard PDF card of metallic bismuth, indicating the successful reduction of molecular bismuth precursors. There is a small peak around 12 degrees, which matches one of the broad peaks of PVP powder (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsmaterialsau.5c00104/suppl_file/mg5c00104_si_001.pdf">Figure S1</a>), which is anticipated at this stage since the PVP used in the precursor mixture is 5 times the weight of the bismuth salts and has not been washed away. There is another small peak around 29° that matches nonstoichiometric bismuth oxide, which will be discussed below. According to the previous report, <a href="javascript:void(0);">(50)</a> the overall hexagonal crystal structure with a rhombohedral unit cell (as shown by the gray connections in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsmaterialsau.5c00104#fig2">Figure 2</a>b) is commonly observed at ambient conditions for metallic bismuth. Two bilayers within the hexagonal structure are separated by relatively weak van der Waals-like interactions, which provide space and relatively low energy barriers for the following aging process. As follows, during the aging process, with the assistance of PVP surfactant solutions and dissolved ambient oxygen, the metallic Bi gradually oxidizes, and the crystal structure becomes more amorphous, as observed with 3 broad peaks of XRD patterns in Day 4’s and Day 7’s samples. The PVP peaks are not observed in these samples in the XRD, possibly due to the disruptions of the ordered structure in the powder form when they are dispersed in a low concentration solution (0.5 mM). Eventually, on Day 10, a fully oxidized sample is formed, with a crystal structure matching the nonstoichiometric Bi<sub>2</sub>O<sub>2.33</sub> standard card, and no distinct peaks are observed for metallic Bi anymore. Additionally, <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsmaterialsau.5c00104/suppl_file/mg5c00104_si_001.pdf">Figure S2</a> compares standard patterns for bismuth subcarbonate and three distinct phases of stoichiometric bismuth oxide with those of the Day 10 sample. None of these reference patterns match the observed pattern of the Day 10 sample, ruling out the presence of these phase impurities in our material. This mixed-valent (Bi<sup>2+</sup> and Bi<sup>3+</sup>) electron-rich structure of nonstoichiometric Bi<sub>2</sub>O<sub>2.33</sub> was previously reported in research using traditional synthesis methods mentioned above, which demonstrated excellent properties, such as UV-emitting photoluminescence, supercapacitance, ferromagnetism, and photocatalysis. <a href="javascript:void(0);">(41,43,47)</a> To the best of our knowledge, there have been no reports on the mechanochemistry-driven synthesis of this unique structure. To be specific, as shown in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsmaterialsau.5c00104#fig2">Figure 2</a>c, the overall tetragonal structure consists of a mixture of Bi<sub>2</sub>O<sub>3</sub> and Bi<sub>2</sub>O<sub>2</sub> layers within the lattice, possibly coming from the oxidation of metallic bismuth in the original bilayer structures before aging. This unique structure, featuring the stereochemically active lone pair of Bi<sup>3+</sup> and the electrostatically electron-rich site of Bi<sup>2+</sup>, could potentially contribute to interlayer flexibility and defect formation, ultimately leading to the final nanosheet structure. This has been observed in other bismuth-based materials with preferred layered structures as well. <a href="javascript:void(0);">(51−53)</a></p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Mater_Au_2025_Figure_2_Structural_evolution_for_the_mechanochemical_aging_synthesis_process_a6c739235e.jpg" alt="ACS Mater. Au 2025: Figure 2. Structural evolution for the mechanochemical-aging synthesis process. (a) XRD spectra of samples collected on Day 1 (freshly made) and Days 4, 7, and 10 with the standard PDF reference cards for metallic Bi and nonstoichiometric Bi2O2.33. Schematic presentation of the crystal structures of (b) metallic Bi and (c) nonstoichiometric Bi2O2.33." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Mater_Au_2025_Figure_2_Structural_evolution_for_the_mechanochemical_aging_synthesis_process_a6c739235e.jpg 245w," sizes="100vw" width="2100" height="1168"></p><p>Moving forward, the SEM images of freshly made (Day 1) samples and samples at different intervals during the aging process were collected for tracking morphological changes, along with EDS mapping to confirm the elemental composition and compare the spatial distribution of these elements. As shown in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsmaterialsau.5c00104#fig3">Figure 3</a>, the bulk rod microstructure of metallic Bi after grinding and washing on Day 1 was observed with a relatively small amount of well-defined hexagonal thin nanosheets. These nanosheets have a relatively smooth surface, and the edge length is about 1 μm with a lateral width of 2 μm. The EDS full-range scan results also confirmed the dominant element compositions of carbon, oxygen, and bismuth in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsmaterialsau.5c00104/suppl_file/mg5c00104_si_001.pdf">Figure S3</a>, in which the carbon comes from both the carbon tape used in the sample preparation and the PVP polymer residues. For the EDS mapping in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsmaterialsau.5c00104/suppl_file/mg5c00104_si_001.pdf">Figure S4</a>, the distributions of Bi and O are relatively and consistently uniform across the sample, while the oxygen amount is significantly higher than the bismuth (estimated based on the spectra intensity counts and relative atomic mass). It is possible due to the residual PVP polymer still adsorbed on the surface, and is ready to participate in the next delamination process. This is also observed in the FTIR spectrum of O–H bending, C–H bending, and C–N stretching, possibly from the PVP, as shown in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsmaterialsau.5c00104/suppl_file/mg5c00104_si_001.pdf">Figure S5</a>, compared to the FTIR spectrum of PVP powder. It is noteworthy that very weak Bi–O bonding and a hydrophobic surface with almost no O–H stretching are also observed in Day 1’s sample, combined with the evidence of PVP, dominant metallic Bi peaks, and a small peak of Bi<sub>2</sub>O<sub>2.33</sub> from the XRD analysis above. It is suggested that after freshly grinding, the metallic Bi bulk microrods formed as the aging precursor for the subsequent delamination process, and small amounts of oxide nanosheet structure began to form adjacent to the bulk rod, indicating a delamination pathway rather than nucleation from the aging solution.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Mater_Au_2025_Figure_3_Morphology_evolution_for_the_mechanochemical_aging_synthesis_process_9a69a3b684.jpg" alt="ACS Mater. Au 2025: Figure 3. Morphology evolution for the mechanochemical-aging synthesis process. SEM images of samples collected on (a–d) Day 1 (freshly made), (e–h) Day 4, (i–l) Day 7, and (m–p) Day 10." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Mater_Au_2025_Figure_3_Morphology_evolution_for_the_mechanochemical_aging_synthesis_process_9a69a3b684.jpg 205w," sizes="100vw" width="3000" height="2285"></p><h4><strong>Conclusions</strong></h4><p>In summary, we developed a mechanochemical-aging approach for the synthesis of nonstoichiometric Bi<sub>2</sub>O<sub>2.33</sub> nanosheets, exhibiting excellent adsorption capacity and photocatalytic degradation performance toward forever chemicals. Different stages of morphological, crystal structure, and surface composition changes were observed and correlated to our proposed growth mechanism. Our mechanistic interpretation focuses on the effects of transient strain accumulation and relaxation resulting from applied mechanical forces during grinding, as well as controllable chemical delamination through capping ligands and oxygen amount during aging. This mechanism features strain-to-defect transformations at the molecular-to-crystal level, which could potentially extend to other 2D metal oxide nanostructure designs.</p>

Mechanochemical-Aging Synthesis of Bismuth Oxide Nanosheets for Photocatalysis

<p><strong>In the week of October 20, the following webinars await you in the field of gas / solid phase and especially Raman, FTIR, GC and GC/MS.</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 000 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. SelectScience: Advancing Gas Chromatography Workflows with Smarter and Smaller Systems</strong></h5><ul><li>Mo, 20.10.2025 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5595">Registration</a></li></ul><p>Join James Cain, PhD (Agilent Technologies), as he showcases the latest innovations in GC–MS, focusing on smarter, smaller, and more efficient chromatography systems.</p><h5><strong>2. Restek Corporation: The Challenge in Column Selection for GC</strong></h5><ul><li>Tu, 21.10.2025 14:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5623">Registration</a></li></ul><p>Join Jaap de Zeeuw for an expert webinar on GC column selection — learn how to replace, optimize, or improve separations using modeling tools, new phases, and smarter column choices.</p><h5><strong>3. Metrohm: Time is Money – How Digitalized Workflows Enhance Laboratory Efficiency</strong></h5><ul><li>Tu, 21.10.2025 15:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5624">Registration</a></li></ul><p>Learn how seamless integration between instruments and LIMS software can save time and increase laboratory efficiency through digital transformation.</p><h5><strong>4. The Analytical Scientist: State-of-the-Art Sample Preparation – Innovation to Sustainability</strong></h5><ul><li>Tu, 21.10.2025 15:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5571">Registration</a></li></ul><p>Join a live roundtable on innovative and sustainable sample preparation technologies, featuring tools and workflows shaping the future of analytical chemistry.</p><h5><strong>5. Separation Science: Ask the Agilent Experts Series – Part 7: The Mass Spec Edition</strong></h5><ul><li>Tu, 21.10.2025 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5514">Registration</a></li></ul><p>Join Agilent experts for a GC/GC–MS Q&amp;A session covering sensitivity, solvent focusing, column installation, and best practices for instrument performance.</p><h5><strong>6. Agilent Technologies: Seminar 3 – OpenLab CDS – Custom Calculator and Reporting</strong></h5><ul><li>Tu, 21.10.2025 18:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/557">Registration</a></li></ul><p>Stop using Excel! Learn how to set up calculations in Custom Calculator, create intelligent reports, and customize sequence and injection outputs in OpenLab CDS.</p><h5><strong>7. Wasson-ECE Instrumentation: Vaporizers</strong></h5><ul><li>Tu, 21.10.2025 21:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5523">Registration</a></li></ul><p>Discover how Wasson-ECE vaporizers enhance gas analysis through reliable, precise sample introduction in petrochemical, refining, and environmental applications.</p><h5><strong>8. New Food Magazine: Fermentation Elevated – Precision Analytics with Mass Spectrometry in the Biofood Revolution</strong></h5><ul><li>We, 22.10.2025 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5375">Registration</a></li></ul><p>Explore how advanced mass spectrometry and automation are transforming fermentation processes and analytics in the biofood industry.</p><h5><strong>9. Agilent Technologies: A Discussion on Sample Preparation of Water Samples for Analysis of Microplastics</strong></h5><ul><li>Th, 23.10.2025 20:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/2365">Registration</a></li></ul><p>Learn about Agilent’s turnkey workflow for microplastic analysis using the 8700 LDIR system, from sample preparation to detection and data interpretation.</p><h5><strong>10. Agilent Technologies: Carbon Capture and Utilization – Enabling a Low-Carbon Future</strong></h5><ul><li>Fr, 24.10.2025 07:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5541">Registration</a></li></ul><p>Discover how Agilent GC supports precise analysis of CO₂, syngas, and trace contaminants, empowering reliable carbon capture and utilization workflows.</p>

Webinars LabRulezGCMS Week 43/2025

<p><strong>In the week of October 20, 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>5 000 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. US HUPO: Sugar – The Sweetest Molecule in Imaging</strong></h5><ul><li>Tu, 21.10.2025 12:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5433">Registration</a></li></ul><p>Celebrate all things sugar in this glycan imaging seminar. Join expert speakers to discuss the role of sugars in molecular imaging and biomedical research.</p><h5><strong>2. Metrohm: Time is Money – How Digitalized Workflows Enhance Laboratory Efficiency</strong></h5><ul><li>Tu, 21.10.2025 15:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5624">Registration</a></li></ul><p>Learn how seamless device and software integration can save valuable time and transform your lab into a connected digital ecosystem.</p><h5><strong>3. The Analytical Scientist: State-of-the-Art Sample Preparation – Innovation to Sustainability</strong></h5><ul><li>Tu, 21.10.2025 15:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5571">Registration</a></li></ul><p>Join a roundtable on greener and more efficient sample preparation workflows, with experts sharing insights into the next generation of analytical tools.</p><h5><strong>4. Waters Corporation: Optimization and Validation of the Kairos Amino Acid Kit in a Hospital Laboratory</strong></h5><ul><li>Tu, 21.10.2025 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5621">Registration</a></li></ul><p>Discover current and upcoming optimizations of the Kairos Amino Acid Kit. Learn about validation and implementation in clinical laboratories.</p><h5><strong>5. Waters Corporation: Empower Tips – Data-Driven Approaches to Minimize Risk and Promote Data Quality</strong></h5><ul><li>Tu, 21.10.2025 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5582">Registration</a></li></ul><p>Explore comparative testing, continuous monitoring, and Empower cloud tools for robust and compliant analytical results across multiple labs.</p><h5><strong>6. Technology Networks: A Modern Approach for Reliable Protein Denaturing Electrophoresis</strong></h5><ul><li>Tu, 21.10.2025 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5449">Registration</a></li></ul><p>See how capillary electrophoresis outperforms SDS-PAGE. Learn about fast, reproducible protein analysis using Agilent’s ProteoAnalyzer system.</p><h5><strong>7. C&amp;EN: Multi-Attribute Monitoring of mRNA Medicines Using LC-MS</strong></h5><ul><li>Tu, 21.10.2025 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5556">Registration</a></li></ul><p>Explore how Multi-Attribute Monitoring (MAM) with partial RNase T1 digest and LC-MS improves mRNA medicine analysis and quality control.</p><h5><strong>8. Agilent Technologies: Seminar 3 – OpenLab CDS – Custom Calculator and Reporting</strong></h5><ul><li>Tu, 21.10.2025 18:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/557">Registration</a></li></ul><p>Learn to replace Excel-based calculations with OpenLab CDS Custom Calculator. Create intelligent and sequence reports directly within the software.</p><h5><strong>9. Phenomenex: LC Columns for Prescribed (TDM) Drug Methods</strong></h5><ul><li>We, 22.10.2025 10:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5469">Registration</a></li></ul><p>Discover how polar C18 and biphenyl chemistries enhance LC-MS/MS analysis for therapeutic drug monitoring (TDM) applications.</p><h5><strong>10. SCIEX: Understanding the Difference Between Single and Triple Quadrupole MS</strong></h5><ul><li>We, 22.10.2025 11:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5557">Registration</a></li></ul><p>Understand SIM, MRM, and MRM³ scan modes in SQ, TQ, and QTRAP systems. Learn when QTRAP technology adds value beyond quantitation.</p><h5><strong>11. Thermo Fisher Scientific: Multiplex Targeted Metabolite Panel Development for the Gut Microbiome</strong></h5><ul><li>We, 22.10.2025 13:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5513">Registration</a></li></ul><p>Discover how empirical databases accelerate LC-MS method development for gut microbiome research, boosting lab productivity tenfold.</p><h5><strong>12. Technology Networks: AI-Powered ASMS Ligand Identification</strong></h5><ul><li>We, 22.10.2025 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5625">Registration</a></li></ul><p>Learn how AI/ML combined with ASMS accelerates ligand discovery, reduces costs, and reshapes drug screening efficiency.</p><h5><strong>13. Waters Corporation: Session 1 – Identifying the Need for Method Adjustment and Mitigating Risk</strong></h5><ul><li>We, 22.10.2025 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5589">Registration</a></li></ul><p>An introduction to key principles of analytical method adjustment and strategies to mitigate regulatory and quality risks.</p><h5><strong>14. Waters Corporation: Impact of Low pH Affinity Chromatography Elution on AAV Transduction</strong></h5><ul><li>We, 22.10.2025 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5471">Registration</a></li></ul><p>Understand how low-pH elution affects AAV capsid stability and transduction. Includes SEC-MALS insights for viral characterization.</p><h5><strong>15. Waters Corporation: Becoming a SEC-MALS &amp; ASTRA Expert – Part 10</strong></h5><ul><li>Th, 23.10.2025 11:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5330">Registration</a></li></ul><p>Conclude the series by mastering result reporting, mass recovery, and data export techniques in ASTRA software.</p><h5><strong>16. Waters Corporation: Redefining Mass Spectrometry Imaging</strong></h5><ul><li>Th, 23.10.2025 15:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5587">Registration</a></li></ul><p>Get updates on Waters’ MS Imaging portfolio, including DESI XS spatial visualization and Xevo MRT high-speed analysis.</p><h5><strong>17. Wiley: Streamlining Forensic Toxicology Workflows for Smarter Drug Screening and Confirmation</strong></h5><ul><li>Th, 23.10.2025 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5626">Registration</a></li></ul><p>Learn LC-MS/MS workflows that enhance forensic toxicology testing accuracy and reduce turnaround times in drug screening.</p><h5><strong>18. Evosep Biosystems: Deep Visual Proteomics</strong></h5><ul><li>Th, 23.10.2025 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5573">Registration</a></li></ul><p>Discover how imaging and LC-MS merge to reveal protein expression patterns with unmatched spatial depth and biological insight.</p><h5><strong>19. Thermo Fisher Scientific: Ultrasensitive, High-Throughput nanoHDX-MS for Protein Dynamics</strong></h5><ul><li>Th, 23.10.2025 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5622">Registration</a></li></ul><p>Explore key innovations of the nHDX-MS platform, providing robust, reproducible insights into protein dynamics and interactions.</p><h5><strong>20. Waters Corporation: Intact and Subunit LC-MS Characterization of mAbs and msAbs</strong></h5><ul><li>Th, 23.10.2025 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5586">Registration</a></li></ul><p>Learn about BioResolve Protein A Affinity Columns for pH-gradient elution and improved mAb and msAb variant separations.</p><h5><strong>21. Technology Networks: Analytical Strategies for Oligonucleotide Stability Studies</strong></h5><ul><li>Th, 23.10.2025 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5559">Registration</a></li></ul><p>Understand LC-MS and automation strategies for accurate stability testing and bioanalysis of therapeutic oligonucleotides.</p><h5><strong>22. Waters Corporation: Becoming an ASTRA Expert – Part 10</strong></h5><ul><li>Fr, 24.10.2025 20:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5335">Registration</a></li></ul><p>Finalize your ASTRA training by mastering DLS in flow mode using Rh and Burchard-Stockmayer plots for SEC-DLS analysis.</p>

Webinars LabRulezLCMS Week 43/2025

<p><strong>In the week from October 20, 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>5 000 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. Metrohm: Time is Money – How Digitalized Workflows Enhance Laboratory Efficiency</strong></h5><ul><li>Tu, 21.10.2025 15:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5624">Registration</a></li></ul><p>Learn how seamless integration of devices and software through 1LIMS and Metrohm saves time, increases efficiency, and transforms your lab into a connected digital ecosystem.</p><h5><strong>2. The Analytical Scientist: State-of-the-Art Sample Preparation – Innovation to Sustainability</strong></h5><ul><li>Tu, 21.10.2025 15:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5571">Registration</a></li></ul><p>Join a roundtable discussion on innovative and sustainable sample preparation tools, focusing on greener workflows and analytical efficiency.</p><h5><strong>3. Agilent Technologies: Intelligent Analysis of Wastewaters Using an Agilent ICP-MS with Integrated Autodilutor</strong></h5><ul><li>Tu, 21.10.2025 21:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/4542">Registration</a></li></ul><p>Discover how integrated autodilution in Agilent ICP-MS simplifies wastewater analysis, boosts accuracy, and minimizes manual handling.</p><h5><strong>4. Bruker: Optical Tweezers – Advanced Applications in Biology and Materials Science</strong></h5><ul><li>We, 22.10.2025 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5596">Registration</a></li></ul><p>Explore nanoscale manipulation with Bruker’s NanoTracker 2 optical tweezers and learn their applications in biological and material sciences.</p><h5><strong>5. Thermo Fisher Scientific: Simple, Fast and Robust Analysis of Whole Blood, Serum and Urine Using ICP-MS</strong></h5><ul><li>Th, 23.10.2025 13:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/4702">Registration</a></li></ul><p>Join a virtual demo of the Thermo Scientific iCAP MX Series ICP to see simplified workflows for elemental analysis in biological samples.</p><h5><strong>6. Evosep Biosystems: Deep Visual Proteomics</strong></h5><ul><li>Th, 23.10.2025 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5573">Registration</a></li></ul><p>See how imaging and LC-MS technologies merge to map protein expression patterns with unmatched precision and biological depth.</p><h5><strong>7. SPECTRO Analytical Instruments: iCAL 2.0 – Smart Standardization for Efficient and Reliable Metal Analysis</strong></h5><ul><li>Th, 23.10.2025 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5572">Registration</a></li></ul><p>Learn how patented iCAL 2.0 diagnostics revolutionizes standardization, ensuring consistent and efficient elemental metal analysis.</p><h5><strong>8. Agilent Technologies: A Discussion on Sample Preparation of Water Samples for Analysis of Microplastics</strong></h5><ul><li>Th, 23.10.2025 20:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/2365">Registration</a></li></ul><p>Discover Agilent’s turnkey approach for microplastics analysis using the 8700 LDIR, covering sample prep, identification, and data interpretation.</p><h5><strong>9. Anton Paar: From MPDS 5 to Edge &amp; L-Cor Mass Flow Sensor</strong></h5><ul><li>Fr, 24.10.2025 10:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinar/5597">Registration</a></li></ul><p>Experience the new Edge Evaluation Unit and L-Cor sensor innovations from Anton Paar designed to enhance process control, precision, and efficiency.</p>

Webinars LabRulezICPMS Week 43/2025

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 20th October 2025? Check out new documents from the field of the gas phase, especially GC and GC/MS techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT GCMS AND RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><strong>LabRulezICPMS</strong></a> libraries.</p></blockquote><p>This week we bring you applicaton notes by <strong>Agilent Technologies, EST Analytical, Shimadzu </strong>and <strong>Thermo Fisher Scientific!</strong></p><h3><strong>1. Agilent Technologies: FAMEs Analysis of Oils by GC-FID Coupled with Fully Automated Sample Preparation using a PAL3 Series 2 RTC</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_fame_oil_gc_pal3_5994_8543en_agilent_418da94d17.pdf"><strong>Full PDF for download</strong></a></li></ul><p>The analysis of fatty acid methyl esters (FAMEs) is a widely used technique for characterizing lipid profiles in various food products, including oils, meats, and seeds. Fats are composed of a complex mixture of saturated, monounsaturated, and polyunsaturated fatty acids, each with varying carbon chain lengths.2 This type of analysis is routinely performed in governmental, quality control (QC), and contract research laboratories worldwide. The resulting data often informs product labeling. Among the analytical techniques available, gas chromatography (GC) with flame ionization detection (GC-FID) is one of the most common methods for determining fatty acid composition in&nbsp;foods.&nbsp;</p><p>This application note describes the use of automated sample preparation and analysis of FAMEs using the PAL3 Series&nbsp;2 RTC Autosampler system coupled with Agilent 8890 GC system equipped with an FID. The results shown here focus on two different methods of derivatization for FAMEs extraction: (1) base catalyzed reactions using potassium hydroxide (KOH) (part&nbsp;number M5795-14000) and (2) base plus acid catalyzed reactions using boron trifluoride (BF3 ) 1 (part number M5795-14001). For ease of use, both processes have been transcribed into dedicated sample preparation methods. These methods are part of the Agilent automated sample preparation workflow suite of solutions. These workflows improve process safety, optimizes throughput, and minimizes&nbsp;errors.</p><h4><strong>Experimental&nbsp;</strong></h4><p>The 37 component FAME mix standard was purchased from Sigma-Aldrich (part number CRM47885), and three consumer oil products were purchased from a local grocery store. The samples were prepared and injected into the GC using the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=PAL3"><strong>PAL3 Series 2-RTC system</strong></a>. The analysis was performed using an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890+GC"><strong>8890 GC</strong></a> equipped with an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=DB%E2%80%91FastFAME"><strong>Agilent DB‑FastFAME GC column</strong></a>, 30&nbsp;m × 250 µm, 0.25&nbsp;µm, (part number G3903‑63011) and configured with an FID using Agilent&nbsp;<a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=OpenLab+CDS+v2.7"><strong>OpenLab CDS v2.7+</strong></a>.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>In summary, the current study demonstrated excellent reproducibility and accuracy using automated sample preparation and analysis of FAMEs. Two different sample preparation methods were demonstrated, both delivering comparable and reliable results. The base-catalyzed method enables rapid analysis but is not suitable for samples containing free fatty acids. In contrast, the acid-catalyzed method, while more extensive, is compatible with a broader range of lipid classes, including free fatty acids, phosphoglycerides, and triglycerides. The Agilent automated sample preparation workflow suite of solutions deliver a comprehensive package by combining preconfigured hardware, optimized analytical methods, and the necessary consumables to ensure efficient and reliable results.</p><h3><strong>2. EST Analytical: Unregulated Contaminant Monitoring Rule 3 for USEPA Method 524.3 and 524.4</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/Purge_and_Trap_Unregulated_Contaminant_Monitoring_Rule_3_for_USEPA_Method_524_3_and_524_4_b774e6ab4c.pdf"><strong>Full PDF for download</strong></a></li></ul><p>The third Unregulated Contaminant Monitoring Rule (UCMR 3) was finalized in April of 2012. UCMR 3 requires public water systems to monitor for a specific list of 30 contaminants under three separate lists: list one, assessment monitoring, list two, screening survey, and list three, pre-screen testing. This application note will address the volatile organic compounds found in list one, assessment monitoring contaminants. USEPA Method 524.3 and 524.4 will be the methods evaluated for sampling and analysis.</p><h4><strong>Discussion&nbsp;</strong></h4><p>The amendments to the Safe Drinking Water Act (SDWA) require the EPA to list no more than 30 unregulated contaminants to be monitored by public water systems. Every five years, this list needs to be updated. List one contaminants include seven volatile organic compounds to be analyzed by USEPA Method 524.3. The detection limits for these compounds are much lower; therefore, Single Ion Monitoring (SIM) must be used for compound detection. USEPA Method 524.3 and 524.4 allow for modification of purge and trap parameters in order to take advantage of purge and trap improvements. Thus, method parameters can be modified in order to optimize purge and trap cycle times. Since the purge and trap parameters were established for these methods previously, refer to application note Drinking Water Analysis Conditions for USEPA Method 524.3 and the Newly Proposed Method 524.4, purge and trap method development was not required for this application. For this study, Helium and Nitrogen purge gases were compared utilizing the same purge volume then comparing experimental results for the linearity, precision, accuracy and overall compound response for the low level requirements set by UCMR 3.&nbsp;</p><h4><strong>Experimental&nbsp;</strong></h4><p>The <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/2160"><strong>EST Analytical Encon Evolution purge and trap concentrator</strong></a> and <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/2159"><strong>Centurion WS autosampler </strong></a>were interfaced to an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=7890%2F5975"><strong>Agilent 7890/5975 GC/MS</strong></a>. The purge and trap concentrator was configured with a Vocarb 3000 (K) analytical trap. A chiller unit capable of keeping the sample vials cooled below 10°C was installed on the Centurion WS autosampler. The experimental parameters are listed in Tables 1 and 2.</p><h4><strong>Conclusion</strong></h4><p>The Encon Evolution and Centurion WS in conjunction with the Agilent 7890/5975 GC/MS performed very well using both the Helium and Nitrogen purge gases and employing SIM for compound detection. The Nitrogen and the Helium purge gases met USEPA Method 524.3 curve linearity criteria and produced comparable results for precision and accuracy at the low and mid-levels of the calibration curve. Overall, the principal difference between the two purge gases was exhibited in the compound response. When examining the overall compound response factors over the curve range, it is evident that the analytes’ responses are slightly lower with the Nitrogen purge gas as opposed to the Helium purge gas.</p><h3><strong>3. Shimadzu: Comparison of Metabolites in Rice from Different Production Areas Using GC-MS/MS</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_01_01000_en_9c1d7cfe70.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Metabolomics is a research method for comprehensively analyzing metabolites contained in an organism. It is used for a wide variety of fields, such as medical science and food. Because food quality is affected by many components complexly, comprehensive analysis of metabolites can help improve food development and manufacturing processes. Rice contains metabolites, such as sugars, amino acids, and fatty acids. In recent years, development of more flavorful rice has been studied.&nbsp;</p><p>This article describes simultaneous analysis of 502 metabolites and multivariate analysis of a variety of rice from different production areas. The <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GCMS-TQ8040+NX"><strong>GCMS-TQ8040 NX</strong></a> with the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=Smart+Metabolites+Database+ver.+2"><strong>Smart Metabolites Database Ver. 2</strong></a> was used for measurement. <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=LabSolutions+Insight"><strong>LabSolutions Insight </strong></a>was used for data processing, and <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=eMSTAT+Solution"><strong>eMSTAT Solution</strong></a> was used for multivariate analysis. The process flow, from pretreatment to data analysis, is shown in Fig. 1.</p><h4><strong>eMSTAT Solution&nbsp;</strong></h4><p>eMSTAT Solution is statistical analysis software that enables multivariate and discriminant analysis of chromatogram data. For multivariate analysis, it can discriminate between samples, and it can search for the marker peaks that contribute to those differences. For discriminant analysis, it can create a discriminant model based on training data and use the model for discriminant analysis. Users can easily switch both modes with just a single click. Workflow of the data analysis is shown in Fig. 2.</p><h4><strong>Conclusion&nbsp;</strong></h4><p>Metabolites in same variety of rice from different production areas were analyzed, and the differences between samples were identified by multivariate analysis. Score plots were used to visualize differences between the samples, and loading plots were used to confirm the characteristic compounds. Smart Metabolites Database Ver. 2, LabSolutions Insight, and eMSTAT Solution make metabolites analysis, data processing, and multivariate analysis easy for beginner users.</p><h3><strong>4. Thermo Fisher Scientific: Automated, multi-parameter gasoline characterization using GC-VUV and ASTM D8071</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_003957_gc_vuv_trace_1610_vga_industrial_an003957_na_en_3c0a64e3b2.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Gasoline is a complex hydrocarbon blend whose composition directly impacts combustion behavior, emissions, and regulatory compliance. Accurately quantifying components such as aromatics, olefins, ethanol, and benzene is critical, but traditional ASTM methods require multiple techniques (FIA, GC-FID, GC-MS, etc.) to measure all relevant parameters. Table 1 summarizes several test methods and their respective scopes.&nbsp;</p><p>ASTM D8071 introduces a consolidated method using GC-VUV, offering improved precision, spectral resolution, and reduced operational burden. This approach is now recognized as an EPA- and CARB-approved alternative to several legacy test methods, including ASTM D1319, D5599, D5769, and D3606.</p><h4><strong>Experimental&nbsp;</strong></h4><p>Gasoline samples were analyzed on the VUV Analyzer Platform for Fuels with no sample preparation required. The VUV Analyzer consists of the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/486"><strong>Thermo Scientific™ TRACE™ 1610 gas chromatograph</strong></a> coupled to the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=3&amp;search=VGA-100"><strong>VGA-100™ spectrometer detector </strong></a>(VUV Analytics, Inc.).&nbsp;</p><p>Data are acquired and processed with the VUVision™ Software and VUV Analyze™ Software (VUV Analytics, Inc), respectively, specifically configured to run ASTM D8071.&nbsp;</p><h5><strong>Workflow overview&nbsp;</strong></h5><p>The VUV Analyzer Platform for Fuels performs gasoline PIONA class analysis using a streamlined five-step workflow:&nbsp;</p><ol><li>System validation – Verifies instrument performance using standard hydrocarbons.&nbsp;</li><li>Sample prep – No preparation required.&nbsp;</li><li>Data acquisition – Performed using VUVision Software.&nbsp;</li><li>Spectral matching – Automated deconvolution with VUV Analyze Software.&nbsp;</li><li>Quantitation – Volume % and mass % calculated with high accuracy using built-in response factors and density data.</li></ol><h4><strong>Conclusion&nbsp;</strong></h4><p>GC-VUV with ASTM D8071 enables complete hydrocarbon group and compound-level analysis of gasoline in a single method. Its ability to automate spectral deconvolution and report mass and volume percentages simplifies operations while meeting strict compliance standards. This solution not only enhances analytical accuracy and repeatability but also drastically reduces operating costs and lab complexity.&nbsp;</p><ul><li>Short analysis time with full gasoline class and compound profiling in 34 minutes&nbsp;</li><li>Faster throughput with full automation from injection to reporting&nbsp;</li><li>12× lower cost-per-analysis, due to reduced labor, no calibration standards, and consolidated workflow</li></ul>

News from LabRulezGCMS Library - Week 43, 2025

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezLCMS Library in the week of 20th October 2025? 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 / AOAC,</strong> <strong>Shimadzu / AOAC </strong>and<strong> Thermo Fisher Scientific / HPLC Symposium </strong>and application note by <strong>Waters Corporation!</strong></p><h3><strong>1. Agilent Technologies / AOAC: Evaluating System Robustness of a High-Sensitivity Triple Quadrupole LC/MS for PFAS Analysis in Food Matrix Over an Extended Period&nbsp;</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/ps_pfas_salmon_6495d_robustness_aoac_2025_t004_en_agilent_9b7b469a22.pdf"><strong>Full PDF for download</strong></a></li></ul><p>Due to the rapidly evolving regulatory environment of per- and polyfluoroalkyl substances (PFAS), many analytical laboratories are opting to use highsensitivity triple quadrupole mass spectrometers for the targeted analysis of such compounds to ensure meeting present and potential future requirements for sensitivity and PFAS coverage. These assays are regularly conducted in a high-throughput manner involving complex matrices such as food, soil, wastewater or biological samples. Therefore, system robustness and instrument uptime are crucial for such applications to maintain productivity and profitability. In this work, we present results from an expedited robustness testing of a high-sensitivity triple quadrupole LC/MS system using select PFASs in one of the most challenging food matrices.</p><h4><strong>Experimental</strong></h4><h5><strong>Instrumentation</strong></h5><p>Data was collected using an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=Agilent+1290+Infinity+II+LC"><strong>Agilent 1290 Infinity II LC</strong></a> system coupled to an <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=10&amp;search=6495D+LC%2FTQ"><strong>Agilent 6495D LC/TQ mass spectrometer.</strong></a> Instrument parameters are summarized in Tables 1 and 2.</p><h4><strong>Conclusions</strong></h4><p>The robustness of a 6495D LC/TQ was tested using undiluted salmon extract, a complex and challenging food matrix. During the experiment, the system was exposed to more than 130 mL of the matrix over a period of ~3 weeks of continuous operation, without any maintenance. System performance was monitored by injections of a mixture of native and isotopically labelled PFAS samples. The monitored signals exhibited low variations (RSD&lt;6%) throughout the entire experiment. No obvious performance degradation or significant contamination of the inner ion optics elements were observed after the conclusion of the test.&nbsp;</p><p>Although no loss of instrument performance was observed during this expedited robustness test, a routine maintenance of ion source and optics is recommended to ensure prolonged instrument operation.</p><h3><strong>2. Shimadzu / AOAC: Analysis of Chlordane by DUIS (Dual Electrospray/Atmospheric Pressure Chemical Ionization) Liquid Chromatography Mass Spectrometry&nbsp;</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/aoac_2025_w050_036db56f51.pdf"><strong>Full PDF for download</strong></a></li></ul><p>The legalization of cannabis has led to many laboratories developing methods to meet local cannabis testing regulatory requirements. One of the challenging residual pesticides to quantitate is chlordane, an organochlorine compound used as a pesticide on crops until 1983 and for termite treatment in homes until 1988. Chlordane is highly persistent in the environment and has been linked to cancers. Gas chromatography mass spectrometry and atmospheric pressure chemical ionization (APCI) – liquid chromatography mass spectrometry (LCMS) methods were published for analysis of chlordane. However, for laboratories without APCI functionality or who prefer not to switch between two different ionization sources, chlordane remains a challenging target for LCMS analysis. This study demonstrates the successful quantitation of chlordane using additive-free DUIS electrospray ionization – LCMS at concentrations below the New York State testing limits.</p><h4><strong>Methods&nbsp;</strong></h4><p>Technical chlordane (CAS 57-74-9) was obtained from Restek, diluted in water, and analyzed on a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library?mainauthorItems=1&amp;search=LCMS-8060"><strong>Shimadzu LCMS-8060</strong></a> triple quadrupole mass spectrometer equipped with a DUIS ionization source. The DUIS source was utilized in APCI mode. Technical chlordane is a mixture of transchlordane, cis-chlordane, and related chemicals. The LC parameters shown in Table 1 allowed separation of the cis- and trans-chlordane isomers.</p><h4><strong>Results&nbsp;</strong></h4><p>Initial MS data was collected in Q1 and Q3 Scan mode. Due to the 8 chlorine atoms per chlordane molecule, a distribution of isomers is expected in the mass spectrum. LabSolutions Insight Explore was used to predict isotopic distributions for chlordane with and without adducts. The predicted spectra for the [M-H]- and [M+CH3OH]- are shown in Figure 1A and 1B, respectively. The experimentally observed isotopic distributions for the [M-H]- and [M+CH3OH]- ions are shown in Figure 1C and 1D, respectively. Figure 1E shows the relative intensity of the [M+CH3OH]- versus the [M-H]- isotope clusters. As the [M+CH3OH]- showed the greatest intensity, it was selected for optimization.</p><p>Voltage optimization was performed for the 441.80 to 441.80 MRM with the CID gas turned off. Even after voltage optimization, the signal-to-noise from the primary species in the technical chlordane (in this case, trans-chlordane) was insufficient. Automated source optimization using LabSolutions MRM Connect was used to improve signal by optimizing Interface Temperature, Heating Gas Flow, Nebulizing Gas Flow, Drying Gas Flow, DL Temperature, Heat Block Temperature, and Interface Voltage. As a representative example, Figure 3 shows the impact of Interface Temperature on the MRM intensity for the 441.80 m/z.</p><h3><strong>3. Thermo Fisher Scientific / HPLC Symposium: HPLC transfer and optimization of deoxycholic acid analysis using HPLC – Charged Aerosol Detector</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/po_hplc_transfer_optimization_deoxycholic_acid_analysis_po_en_55bc47dc90.pdf"><strong>Full PDF for download</strong></a></li></ul><p>The United States Pharmacopeial Convention monograph outlines a high-performance liquid chromatography with charged aerosol detection (HPLC-CAD) method [1] for the accurate measurement of deoxycholic acid (also known as desoxycholic acid) and its primary impurity, cholic acid. Key detector settings that influence detection performance metrics such as detection limit, resolution, and linearity include:&nbsp;</p><ul><li>The evaporation temperature (EvapT) for setting the temperature of the evaporation tube and influencing sensitivity related to volatility factors.&nbsp;</li><li>The filter constant for balancing noise and adjusting the detector's response time to changes in analyte concentration.&nbsp;</li><li>The PV for optimizing the linear range within the detector's dynamic range for a given application.&nbsp;</li></ul><p>These parameters are crucial for successful method transfer and optimization. Consequently, this work offers guidelines for method transfer and optimization from the Vanquish CAD to the Vanquish CAD HP</p><p><strong>Methods:</strong> A <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/743"><strong>Thermo Scientific Vanquish Flex UHPLC system</strong></a> equipped with both the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/2176"><strong>Vanquish Charged Aerosol Detector </strong></a>and HP was used to perform method transfer and optimization for deoxycholic acid analysis. Chromatographic separation was achieved using a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/2005"><strong>Thermo Scientific Acclaim 120 C18 column</strong></a> under gradient elution with formic acid-modified aqueous and organic phases</p><h5><strong>Chromatography Data System&nbsp;</strong></h5><p>The <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/76"><strong>Thermo Scientific Chromeleon 7.3.2 Chromatography Data System (CDS) software</strong></a> was used for data acquisition and analysis.</p><h4><strong>Conclusions&nbsp;</strong></h4><p>This study highlights the successful optimization and method transfer of the USP-NF deoxycholic acid assay using Vanquish CAD detectors. Through careful evaluation of chromatographic performance, detector settings, and calibration parameters, the Vanquish CAD HP was shown to deliver enhanced performance across multiple criteria:&nbsp;</p><h5><strong>Key Takeaways:&nbsp;</strong></h5><ul><li><strong>Excellent Sensitivity and Response:</strong> Vanquish CAD HP demonstrated significantly lower LOD/LOQ values and higher peak responses compared to Vanquish CAD, making it the detector of choice for low-level analyte quantification.&nbsp;</li><li><strong>Enhanced method optimization Flexibility: </strong>Vanquish CAD HP allows simultaneous data collection for multiple PVs, ensuring faster method development and optimization.&nbsp;</li><li><strong>Seamless Method Transfer:</strong> Transitioning from Vanquish CAD to CAD HP was achieved by optimizing power value (PV), EvapT, and signal filter settings, ensuring improved performance.&nbsp;</li></ul><p>Together, these findings demonstrate that the Vanquish CAD HP not only supports efficient method transfer but also elevates performance, sensitivity, and usability—making it an ideal solution for modern HPLC applications.</p><h3><strong>4. Waters Corporation: Multi-Residue Analysis of Pharmaceuticals, Personal Care Products (PPCPs) and Pesticides in Water by Direct Injection Using LC-MS/MS</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/720008819_en_4c0e9bc91e.pdf"><strong>Full PDF for download</strong></a></li></ul><h5><strong>Benefits&nbsp;</strong></h5><ul><li>Sensitivity of Xevo TQ Absolute allows for the trace level detection of PPCPs and pesticides in drinking and surface waters without the need for lengthy clean-up or concentration steps</li><li>The direct injection approach increases productivity and provides faster turn-around time for reporting of results while being well aligned with green analytical chemistry principles</li><li>More than 150 analytes reach limits of quantification of 10 ng/L, making this method suitable for screening for multi-class analytes in water matrices&nbsp;</li></ul><p>In recent years, there has been increasing concern about the presence of pesticides, pharmaceuticals and personal care products (PPCPs) in water bodies throughout the world.1 The effect of these emerging contaminants on human health and their potential impact on the environment is not yet fully understood. The updated Drinking Water Directive entered into force in January 2021 and is the EU's main law for drinking water. The Directive applies to all water, either in its original state or after treatment, intended for drinking, cooking, food preparation or other domestic purposes, regardless of its origin and whether it is supplied from a distribution network, supplied from a tanker or put into bottles or containers.2 It further protects human health thanks to updated water quality standards, in accordance with World Health Organisation (WHO) recommendations, addressing emerging pollutants, such as endocrine disruptors, and promoting a preventive, risk-based approach to reduce pollution at its source.</p><p>Water bodies such as rivers, lakes and groundwaters have their status defined in the EU Water Framework Directive.3 An amendment to Directive 2013/39/EU sets environmental quality standards for hazardous substances that require monitoring in these waters. A Commission Implementing Decision4 document, 2022/1307, includes Watch List analytes with Maximum Acceptable Method Detection Limits for compounds of concern across multiple chemical classes. Numerous studies have demonstrated that PPCPs are present at parts-per-trillion (PPT) levels in rivers and streams highlighting the need for methods that are able to detect compounds at these trace levels.5-10 In addition to the low-level detection of these compounds, a major analytical challenge lies in the wide chemical diversity of chemicals of concern. Furthermore, to establish a more complete understanding of water pollution it is necessary to monitor a wide variety of types of water. This application note demonstrates the direct injection, separation and detection of PPCPs and pesticides including acidic, basic, and neutral compounds from multiple regulated analyte lists in a variety of water types.</p><h4><strong>Experimental</strong></h4><ul><li><strong>LC system:</strong> <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/191"><strong>ACQUITY Premier</strong></a> FTN</li><li><strong>MS system: </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/554"><strong>Xevo TQ Absolute</strong></a></li></ul><h4><strong>Conclusion&nbsp;</strong></h4><p>The updated EU Drinking Water and Water Framework Directives provide the regulatory framework for effective monitoring and management of water quality and include provisions for emerging contaminants. Ensuring compliance with these regulations and comprehensive coverage for an ever increasing analyte lists requires versatile, robust analytical methods and high performance LC/MS/MS systems. The direct-injection method investigated in this work is effective at detection of a wide range of PPCPs and pesticides at trace levels suitable for monitoring multiple water types for the presence of compound classes known or suspected to pose risks to human and environmental health. It further provides more rapid turn around time and greener operation than methods that rely upon high volumes of solvent and extensive sample preparation. Method performance was assessed using criteria described in ISO 21253–2:2019. The calibration characteristics, linearity, and residuals were excellent over the concentration range studied. Accuracy and precision were evaluated at three matrix QC levels with six replicate spikes and found to provide excellent performance for 154 analytes in tap and bottled water and 74 analytes in surface water matrix.</p>

News from LabRulezLCMS Library - Week 43, 2025

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News from LabRulezLCMS Library - Week 43, 2025

News from LabRulezGCMS Library - Week 43, 2025

Webinars LabRulezICPMS Week 43/2025

Webinars LabRulezLCMS Week 43/2025

Webinars LabRulezGCMS Week 43/2025

Mechanochemical-Aging Synthesis of Bismuth Oxide Nanosheets for Photocatalysis

Lab-on-a-Scalpel: Medical Tool Incorporating a Disposable Fully 3D-Printed Electrochemical Cell Promoting Drop-Volume Chemical Analysis in the Operating Theater

Mapping Metabolomic Relationships of Hop Cultivars in an Ancestral Lineage Context

News from LabRulezICPMS Library - Week 42, 2025

News from LabRulezLCMS Library - Week 42, 2025

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