<blockquote>Welcome back to the topic of protecting your GC column! If you missed <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/article/6766">part 1</a> or would like to refresh your knowledge, find further tips on GC column protection <a target="_blank" rel="noopener noreferrer" href="https://www.phenomenex.com/knowledge-center/gc-knowledge-center/protecting-your-gc-column-pt1-tech-tip-en-1025">here.</a></blockquote>Protecting your GC column and instrument components from exposure to dirty samples or contaminants is important. Non-volatile or high molecular weight components can contaminate the stationary phase, causing poor peak resolution, lower accuracy, and poor column lifetime. Cutting off the damaged portion of column tubing will often restore your column’s performance, but over time performance will degrade to a point where the column can no longer be used. If you are experiencing rapid degradation of column performance, there are several simple ways to help protect your column and increase its lifetime.<h3>Use A Liner With Wool</h3>The liner is the first line of defense for your column, and the style you choose can make a big impact in how much contamination gets onto the column. The easiest thing to do is to add a small amount of silanized glass wool to a liner, which traps the non-volatile compounds and prevents them from entering directly into the column.&nbsp;<blockquote>Caution: glass wool can also add activity for acids, bases, and pesticides. Crushing the glass wool can expose undeactivated glass and free silanols (-OH groups) even if the wool has been deactivated. This leads to increased activity, so pre-packed liners, rather than self-packed ones are highly recommended to avoid reproducibility issues.</blockquote>In addition to choosing a liner with wool, ensure that your liner (and other system consumables) are free of contaminant build-up that may form over time. Septum cores and other particulates that remain can become trapped in the wool and are sometimes difficult to spot. Regularly replace the liner (and other system consumables as needed) to reduce troubleshooting and maintenance.<h3>Bake Out Your Column</h3>The easiest way to reduce column contamination is to add a short, high temperature bake-out at the end of your standard GC method. This bake out helps remove high boiling contaminants that would otherwise remain in the column and cause damage. To bake out, the final oven temperature needs to be set high enough to ensure elution of these compounds, but not so high as to cause thermal damage. This can be done either isothermally, or more commonly, via an oven ramp until the last components elute from the column. Caution: NEVER exceed the upper temperature limits of your column. DO NOT exceed more than fifteen minutes at the upper isothermal temperature limit specified for the column.

How to Protect Your GC Column - Part 2

🎤 Presenter: Christopher Freye (Los Alamos National Laboratory)💾 <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/O_1_Freye_10783a9cf3.pdf">PDF presentation</a><h3>Abstract</h3>Two-dimensional gas chromatography (<a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?instrumentationItems=2">GC×GC</a>) when coupled with mass spectrometry (MS) especially high-resolution mass spectrometry (HRMS) provides the ideal technique to discover minute chemical changes. However, GC×GC analyses result in extremely large datasets (GBs of information) wherein the statistically significant chemical changes are buried within the background chemical matrix. To combat these issues, many chemometric techniques have been developed or applied. Recently we introduced a new chemometric technique for GC-MS termed alteration analysis (ALA) and two-dimensional correlation (2DCOR) which can be used to discover statistically significant chemical changes across a series of chromatograms and understand the relationship between the statistically relevant changes. ALA generates three sets of information, the basic alteration map (BAM) which is the magnitude of the change, the synchronous alteration map (SAM) which describes the linear change, and the asynchronous alteration map (AAM) which describes the non-linear change. 2DCOR can then be used to understand the relationship between the chemical changes but 2DCOR can also resolve the sequence of the changes. A workflow for GC×GC-MS will be demonstrated. Special attention will be given to what differentiates the GC×GC work flow from GC for both the ALA and 2DCOR.<h3>Video Transcription</h3>The presentation focuses on how advanced mathematical and chemometric methods can be used to extract meaningful information from highly complex chromatographic data, especially in multidimensional chromatography coupled with mass spectrometry (GC×GC-MS, LC-MS).<h4>Why traditional data analysis falls short</h4>Modern multidimensional chromatography generates extremely large datasets, often containing billions of data points. Visual inspection, peak tables, or classical identification-based workflows are impractical—especially when:<ul><li>Samples are highly complex (e.g. petroleum, metabolomics, high explosives)</li><li>Most compounds are unknown unknowns</li><li>The key question is not what the compounds are, but whether samples differ and how</li></ul>Program managers and decision-makers are primarily interested in detecting statistically significant changes, not exhaustive compound identification.<h4>Introduction of Alteration Analysis (ALA)</h4>To address subtle, trend-based changes across series of chromatograms, the speaker introduces Alteration Analysis (ALA), a chemometric approach adapted from spectroscopy and applied to chromatography.ALA quantitatively evaluates how individual data points change across multiple samples, allowing detection of:<ul><li>Extremely subtle trends</li><li>Overlapping peaks</li><li>Changes hidden in noise or baseline interference</li></ul>Key ALA outputs include:<ul><li>BAM (Basic Alteration Map): magnitude of change</li><li>SAM (Systematic Alteration Map): linear changes</li><li>AM (Alteration Map): nonlinear changes</li></ul>Even changes as small as 1% per sample can be detected reliably, including peaks that are heavily overlapped.<h4>Beyond detection: understanding relationships with 2D Correlation</h4>Once statistically significant changes are identified, two-dimensional correlation analysis (2D-COR) is used to understand relationships between changing compounds, including:<ul><li>Whether compounds are correlated or anti-correlated</li><li>The sequence of changes over time (which changes happen first)</li></ul>This is especially critical for degradation and aging studies, where intermediate species may appear and disappear before the final state—information that traditional methods like Fisher ratio or PCA often miss.<h4>Solving GC×GC challenges with tiling</h4>GC×GC data introduces additional challenges due to:<ul><li>Peak misalignment</li><li>Exponential data growth during correlation calculations</li></ul>The presenter explains how tile-based approaches reduce data dimensionality, overcome alignment issues, and make ALA and 2D correlation computationally feasible—even for massive GC×GC-MS datasets.<h4>Real-world application: explosive aging studies</h4>The methodology was applied to aging and decomposition of high explosives, where:<ul><li>Over 250 chemical changes were identified</li><li>Many intermediate species would have been missed using traditional comparisons</li><li>ALA combined with 2D correlation enabled reconstruction of degradation pathways</li><li>The most significant change was not necessarily the first change, a critical insight for risk assessment and stability studies</li></ul><h4>Key takeaway</h4>By combining Alteration Analysis and 2D correlation, the approach:<ul><li>Detects statistically guaranteed chemical changes</li><li>Handles subtle, overlapped, and noisy signals</li><li>Determines magnitude, type, interrelationships, and order of changes</li><li>Shifts chromatographic data analysis from identification-driven to decision-driven</li></ul>This math-driven workflow enables faster, more reliable interpretation of complex chromatographic datasets and provides actionable insights for applications such as explosive aging, pharmaceutical degradation, and complex mixture analysis.<blockquote>This text has been automatically transcribed from a video presentation using AI technology. It may contain inaccuracies and is not guaranteed to be 100% correct.</blockquote>

Discovery analysis for GCxGC trends using alteration and 2D correlation (Chris Freye, MDCW 2026)

Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 9th February 2026? Check out new documents from the field of the gas phase, especially GC and GC/MS techniques!<blockquote>👉 <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library">SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT GCMS AND RELATED TECHNIQUES</a></blockquote><blockquote>👉 Need info about different analytical techniques? Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library">LabRulezLCMS</a> or <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library">LabRulezICPMS</a> libraries.</blockquote>This week we bring you technical note by Agilent Technologies, presentation by MDCW / University of Copenhagen and application notes by Shimadzu and Thermo Fisher Scientific!<h3>1. Agilent Technologies: What Causes Spots on <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?instrumentationItems=19&amp;manufacturerItems=1&amp;search=PLOT">PLOT Columns</a>? Will It Affect the Performance of the Column?</h3><ul><li>Technical note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/te_what_causes_spots_plot_columns_affecting_performance_5994_8775en_agilent_3b7180512a.pdf">Full PDF for download</a></li></ul>Spots on porous layer open tubular (PLOT) columns are caused by small voids in the stationary phase coating inside the tube. These spots are areas where there is an uneven coating or lack of phase. It is normal to find some voids in the phase coating of PLOT columns. The stationary phase in PLOT columns is an opaque, solid, and porous material. In many Agilent PLOT columns such as the GS-Alumina phases, molecular sieves, porous polymers (Q and U), and the GS-OxyPLOT, the stationary phase is visible as a white powder. For many PLOT columns, the stationary phase fill solution is a viscous suspension of particles that are less than 10 microns in diameter. The phase is coated using a dynamic process in which a plug of fill solution is pushed through the tubing, and the plug’s speed and viscosity determines the thickness of the stationary phase layer. Once the PLOT’s stationary phase is deposited, it is held in place by electrostatic charge, chemical interactions between particles, and/or binding agents. In wall‑coated open tubular (WCOT) columns, stationary phases such as polysiloxanes or polyethylene glycols are immobilized by chemical bonding to the glass surface and cross-linking between polymer strands. Because this type of bonding and cross‑linking is not possible with PLOT phases, the result is a stationary phase layer that is both fundamentally different and inherently less stable in PLOT columns than in WCOT&nbsp;columns.<h3>2. MDCW / University of Copenhagen: One-shot tensor decomposition of full-scale GC×GC-VUV datasets for resolving petrochemical groups</h3><ul><li>Presentation</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/O_17_Schneide_67c8ff7866.pdf">Full PDF for download</a></li></ul>The presentation introduces a novel all-samples-at-once, shift-invariant tri-linear tensor decomposition approach for the analysis of full-scale <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?search=GC%C3%97GC-VUV">GC×GC-VUV</a> datasets, aimed at resolving and quantifying petrochemical groups. Traditional template-based or pixel-based methods struggle with retention-time shifts and co-eluting compounds, often requiring manual intervention and prior chemical knowledge. The proposed approach leverages the intrinsic low-rank structure of GC×GC-VUV data to enable robust, automated group-level analysis across multiple samples simultaneously.At the core of the method is a shift-invariant tri-linear model, conceptually related to PARAFAC and multivariate curve resolution, but extended using frequency-domain (FFT-based) modeling to explicitly account for chromatographic peak shifts. By decomposing the entire dataset in one step, the model provides accurate estimates of peak landscapes, VUV spectra, and relative peak areas, while remaining agnostic to retention-time variability. Importantly, the approach requires only a small number of tunable parameters, making it practical for routine use.The method was demonstrated on a case study involving 14 petrochemical gas-oil samples, including straight-run, hydrotreated, hydroconverted, coker, and light cycle oils. Extracted VUV spectra showed excellent agreement with reference spectra from a VUV spectral database, enabling confident assignment of components to chemical groups such as saturates, olefins, and mono- to poly-aromatics. Quantitative results exhibited high repeatability (RSD typically 3–9%) and strong correlation with established template-based reference methods.Overall, the work demonstrates that one-shot, shift-invariant tensor decomposition provides a powerful and scalable alternative to conventional GC×GC data-analysis strategies. By combining chemical interpretability, robustness to chromatographic shifts, and strong quantitative performance, the approach opens new opportunities for automated, high-confidence group-level analysis of complex petrochemical samples and beyond.<h3>3. Shimadzu: Py-Screener Ver. 3: Simultaneously Test for Substances Regulated Under RoHS, TSCA, and POPs</h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_01_00949_en_4754e50164.pdf">Full PDF for download</a></li></ul><h5>User Benefits</h5><ul><li>In just one analysis, <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?manufacturerItems=3&amp;search=Py-Screener">Py-Screener</a> Ver. 3 can determine levels of phthalate esters, brominated flame retardants (PBBs, PBDEs), PIP (3:1), UV-328, dechlorane plus (DP), short-chain chlorinated paraffins (SCCPs), and medium-chain chlorinated paraffins (MCCPs).&nbsp;</li><li>It can also test for SCCPs and MCCPs by electron ionization (EI) instead of negative chemical ionization (NCI).&nbsp;</li><li>PIP (3:1), UV-328, DP, and SCCPs and MCCPs can be screened without the need for corresponding reference materials.</li></ul>Countries and regulatory bodies worldwide are introducing increasingly stringent regulations on the chemical substances used in electronic devices and industrial products. The RoHS Directive and REACH regulations in the EU, the Toxic Substances Control Act (TSCA) in the USA, and the Stockholm Convention on Persistent Organic Pollutants (POPs) are also targeting an increasingly broad range of substances. Therefore, manufacturers are required to accurately identify regulated substances in their products and comply with each regulation. While Py-Screener Ver. 2 can screen for seven phthalate esters and brominated flame retardants, including substances regulated under the RoHS Directive, version 3 can also screen for PIP (3:1), which is regulated under the TSCA, as well as UV328, DP, and SCCPs and MCCPs , which are regulated under the Stockholm Convention on POPs. A list of supported substances isshown in Table 1. This article introduces the simultaneous analysis of multiple regulated substances and a case study of testing specific regulated substances in samples, using Py-Screener Ver. 3.<h4>Analysis Process</h4>Py-Screener Ver. 3 can determine levels of phthalate esters and brominated flame retardants contained in products in accordance with the international analytical standards IEC62321-8 and IEC62321-3-3. It can also test for specific regulated substances (Table 1) under the same conditions and in the same analysis. In this test, background intensity and instrument sensitivity (S/N) were verified before analyzing samples. These parameters are prescribed by IEC62321-8 to ensure the accuracy of the methods used. Background intensity and instrument sensitivity were determined using a reference material (PN: 225-31003- 91) *1 that consisted of a plastic sheet that was spiked with seven phthalate esters. The results met the criteria for both parameters.The testing workflow is shown in Fig. 1. Before testing samples, calibration curves were prepared by analyzing the 1000 mg/kg phthalate ester reference material and polypropylene spiked with brominated flame retardants (ERM-EC591). A hole puncher was used to punch out two discs at a time of the phthalate ester reference material, and a cutter was used to obtain pieces of the other materials. Each material was weighed in a sample cup for analysis. During the analysis of samples, phthalate esters and some of the regulated brominated flame retardants were quantitated using a one-point calibration curve. The remaining brominated flame retardants and specific regulated substances were quantitated using the correction factor database*2 that is included with Py-Screener Ver. 3.<h4>Conclusion</h4>Py-Screener Ver. 3 successfully determined in samples the concentrations of the regulated substances PIP (3:1), UV-328, DP, and SCCPs and MCCPs. Normally, SCCP and MCCP levels are tested using NCI, but Py-Screener Ver. 3 uses EI. This enables it to test for not only SCCPs and MCCPs but also phthalate esters, brominated flame retardants, and other regulated substances in just one analysis. In addition, by using the relative correction factors linked to DEHP in the phthalate ester reference material, the levels of these regulated substances were determined without the need for the corresponding reference materials. Py-Screener Ver. 3 can also create a screening program that addresses substance restrictions under the RoHS Directive, the US TSCA, and the POPs Convention.<h3>4. Thermo Fisher Scientific: Improving low carbon steel production in specialty steel processes</h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/prima_pro_process_mass_spectrometer_an1626_7fc840235f.pdf">Full PDF for download</a></li></ul>World crude steel production reached 1,691 million tonnes in 2017, up by 5.3% compared to 2016.1 While much of this capacity is still produced in primary steel processes such as basic oxygen furnaces and electric arc furnaces, the need for refined steel with greater durability and resistance to heat and corrosion has led to the increased use of vacuum degassing processes, such as VOD and RH, in secondary steel production. These processes are able to achieve ultra-low levels of residual carbon, while at the same time retaining desired levels of other alloy materials. If these processes are to achieve the required level of steel product quality, they need fast, continuous gas analysis of the furnace exhaust gas. Without accurate information on the composition of the gas leaving the furnace, any variations in the decarburization process are only detected after the event, resulting in the production of out-of-specification steel.<h4>Advantages of mass spectrometry&nbsp;</h4>Traditional Non-Dispersive Infra-Red (NDIR) analyzers are used in many conventional steelmaking processes to measure CO and CO2 , but they can only sample at atmospheric pressure. In vacuum steelmaking the process pressure changes dramatically, typically from atmospheric pressure down to less than 1 mbar, over the 20-30 minutes of the melt. So NDIR analyzers have to sample some distance downstream from the process. Analytical data is updated several minutes after the gas leaves the melt and the control system is forced to operate on historic rather than real-time data.&nbsp;Paramagnetic analyzers can be used to measure O2 , while thermal conductivity analyzers can be used to measure H2 . These analyzers also suffer from slow response, while the need to operate three different types of analyzers adds to the plant maintenance burden. Moreover, the three analyzers cannot analyze inert gases, so N2 is calculated by difference, a result that suffers from the sum of the errors of the three analytical techniques.&nbsp;Mass spectrometry operates at high vacuum so it is ideal for monitoring vacuum processes. It is also able to monitor all seven components in Table 1 in seconds rather than minutes, ensuring the plant control model is frequently updated with accurate compositional data.<h4>Precision of analysis&nbsp;</h4>At the heart of the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?manufacturerItems=2&amp;search=Prima+PRO+Mass+Spectrometer">Thermo Scientific™ Prima PRO Mass Spectrometer</a> (MS) is a magnetic sector analyzer which offers unrivalled precision and accuracy compared with other mass spectrometers. Thermo Fisher Scientific manufactures both quadrupole and magnetic sector mass spectrometers; over thirty years of industrial experience have shown the magnetic sector based analyzer offers the best performance for industrial on-line gas analysis.&nbsp;Key advantages of magnetic sector analyzers include improved precision, accuracy, long intervals between calibrations, and resistance to contamination. Typically, analytical precision is between 2 and 10 times better than a quadrupole analyzer, depending on the gases analyzed and complexity of the mixture.&nbsp;A unique feature of the Prima PRO magnet is that it is laminated. Its analysis times are similar to a quadrupole analyzer, offering the unique combination of rapid analysis and high stability. This allows the rapid and extremely stable analysis of an unlimited number of user-defined gases. The scanning magnetic sector is controlled with 24-bit precision using a magnetic flux measuring device for extremely stable mass alignment.&nbsp;The ion source is an enclosed type for high sensitivity, minimum background interference, and maximum contamination resistance. This is a high-energy (1000 eV) analyzer that offers extremely rugged performance in the presence of gases and vapors that have the potential for contaminating the analyzer. Typical performance specifications for the Prima PRO MS are shown in Table 1. Analytical performance is demonstrated by analyzing the calibration bottle over 1 hour following calibration, with an analysis time of just 6 seconds. Standard deviations measured on the calibration cylinder will be equal to or better than the stated values.

News from LabRulezGCMS Library - Week 07, 2026

Article

Application

Academy

Video

Presentation

The Multidimensional Chromatography (MDC) Workshop draws experts in this exciting field to share and discuss their research.

The Multidimensional Chromatography Workshop

Everything from the world of analytical chemistry in one place. We connect people in solving their problems. At Labrulez you will find all the necessary information easily, quickly and clearly. Stop searching and start finding.

LabRulez

Phenomenex is a global technology leader committed to developing novel analytical chemistry solutions that solve the separation and purification challenges of researchers in industrial, government and academic laboratories.

Phenomenex

Agilent Technologies

Thermo Fisher Scientific

Frontier Lab

Wiley

VWR/Avantor

The installation and care of your GC column is of the utmost importance. Whether you are new to the practice of gas chromatography, or would like a refresher, join us as we discuss proper column installation and handling for all Agilent GCs, including the Agilent Intuvo 9000 GC. We will also address the common modes of column degradation and some of the misconceptions that people have concerning column degradation. Lastly, we will discuss ways that you can protect and maintain your column performance and extend its lifetime while minimizing instrument downtime.
<blockquote>
Presenter: Alex Ucci (Application Engineer, Agilent Technologies, Inc.)
</blockquote>
<blockquote>
In his current position at Agilent, Alex provides application assistance and technical support for sample preparation products as well as GC and LC consumables. Before he joined Agilent in 2014, Alex was a graduate student at the Pennsylvania State University researching the morphology and surface properties of aerosol particles using a wide variety of analytical techniques. He has an MS degree in chemistry.
</blockquote>
<blockquote>
Presenter: Ryan Birney (Application Engineer, Agilent Technologies, Inc.)
</blockquote>
<blockquote>
In Ryan’s current role at Agilent, he provides application assistance and technical support for GC and Spectroscopy. He has been supporting Agilent in technical and sales roles for the past seven years. Ryan came to Agilent from industry, and has an BS degree in Biochemistry.
</blockquote>

Agilent Technologies: Tips and Tricks: Best Practices for Column Installation and Care of GC Columns

Tips and Tricks: Best Practices for Column Installation and Care of GC Columns

Whether you are new to the practice of GC, or would like a refresher, join us as we discuss proper column installation and handling for all Agilent GCs.

Tips and Tricks: GC Column Installation and Care

In this application, we will review a fast, easy and reliable analysis method of THCA and CBDA decarboxylation in cannabis oil and flower samples by infrared spectroscopy.
<blockquote>
Presenter: Rogelio García Juárez (Application Scientist, Agilent Technologies, Inc.)
</blockquote>
<blockquote>
Rogelio García has a Bachelor’s degree in Pharmaceutical Chemistry from the University National of Mexico and a Master´s degree in Environmental Engineering from the National Polytechnic Institute. He worked in environmental laboratories in the development of methods and applications in water, soil, and air and method design for the pharmaceutical and food industry. He also worked in the implementation of quality management systems in laboratories to obtain accreditation in the 17025 standard, validation process, and analysis of the uncertainty of the method. In 2015, he joined Agilent Technologies as an Application Scientist for Molecular Spectroscopy in UV-Vis, FTIR, and Raman techniques, at Agilent México and Latin America.
</blockquote>

Agilent Technologies: Cannabinoid analysis by FTIR

Cannabinoid analysis by FTIR

Fast, easy and reliable analysis method of THCA and CBDA decarboxylation in cannabis oil and flower samples by infrared spectroscopy.

Dear Orbitrap users,
We are pleased to invite you to our Autumn 2023 version of virtual activities to support our Compound Discoverer (CD) software users.
The workshops are designed to bring beginners up-to-speed with best practices as well as allow advanced users to interact with software experts and enquire how to get the most out of their data. Additionally, two dedicated sessions specialized in Metabolite/drug metabolite Identification (Met ID) and Gas Chromatography Mass Spectrometry (GCMS) data analysis will follow.
The content is delivered through online workshops, 2-3 hours each, via MS-Teams. The workshops feature live exercises on pre-distributed data, discussion of CD features, parameters, and optimized settings. The sessions are hands-on and highly interactive, so get the best experience by having CD 3.3 SP2 up and running. <a href="https://www.thermofisher.com/cz/en/home/industrial/mass-spectrometry/liquid-chromatography-mass-spectrometry-lc-ms/lc-ms-software/multi-omics-data-analysis/compound-discoverer-software.html">Click HERE</a> to download a free 60-day trial version of the latest Compound Discoverer software release.
The sessions allow ample time for the participants to get their CD-related questions answered in real time. The workshops will be taught in English, but participants can use MS Team`s instant subtitles in their preferred language.
<h5>Specialized data processing:</h5>
<ul>
<li>Met ID: Wednesday 4th October: 10.00 - 13.30 CEST (Berlin time)</li>
<li>GCMS: Thursday 18th October: 10.00 - 13.30 CEST (Berlin time)</li>
</ul>

Thermo Scientific: Compound Discoverer software workshops (Specialized data processing: Met ID)

Compound Discoverer software workshops (Specialized data processing: Met ID)

The workshops are designed to bring beginners up-to-speed with best practices as well as allow advanced users to interact with software experts.

Compound Discoverer software (data processing: Met ID)

The use of sample preparation to provide enhanced performance is reviewed for the analysis of biological fluids.
The comprehensive investigation into different sample preparation techniques will determine the effect on recovery, matrix effects and matrix removal. It is shown that the use of protein precipitation can provide robust data, however some of the underlying information demonstrates that this approach may not always be suitable. Data will be presented which demonstrates the effect of changing the sample preparation technique on the retention of phospholipids and the impact that this can have on detection robustness. Finally, the impact of sample preparation will be investigated with real samples provided from an endangered species. This part of the presentation will investigate the use of solvent extraction in an approach to determine key biomarkers that will ultimately be applied to optimising captive environments to lower stress levels.
<blockquote>
Presenter: Tony Edge (R&amp;D Manager, Avantor Sciences)
</blockquote>
<blockquote>
Tony Edge is R&amp;D Manager at Avantor Sciences, heading a team of specialist scientists in manufacturing and developing next generation stationary phases for HPLC. He has worked in both manufacturing and also industry, having periods of employment at LGC and also AstraZeneca as well as ThermoFisherScientific and latterly Agilent Technologies. In 2008, he was fortunate enough to be awarded the Desty memorial lecture for his contributions to innovating separation science, and in the same year also won a clinical excellence award from AstraZeneca. He is currently the President of the UK chromatographic Society and also the chair of the permenent scientific committee for the ISC, as well as being the chair for the next ISC which is due to be held in Liverpool in 2024.
</blockquote>

Avantor: Understanding the importance of sample preparation for the analysis of biological samples

Understanding the importance of sample preparation for the analysis of biological samples

Understanding the importance of sample preparation for the analysis of biological samples.

Sample preparation for the analysis of biological samples

Comparing MS spectra to libraries of reference spectra is one of the most widely used and successful methodologies in the identification of unknown mass spectra. Using this approach, access to an expansive, quality dataset is critical to achieving reliable results.
In this session we will introduce the latest release of the Wiley Registry® / NIST Mass Spectral Library 2023, which combines the power of two trusted MS spectral libraries to provide comprehensive compound coverage and ensure identification across multiple use cases and a wide variety of analytes.
In this session, we will also demonstrate through a series of live examples how this library can be used to successfully identify unknown spectra.
<blockquote>
Presenter: Dr. Nadia Laschuk
</blockquote>
<blockquote>
Dr. Nadia Laschuk is a Product Manager for Wiley Science Solutions, for which she manages new products and databases while supporting existing KnowItAll capabilities. Nadia previously completed her PhD in Materials Science from Ontario Tech University, where she performed research applying a wide array of instrumental techniques to analyze metal-organic coordination compounds. Nadia has since pursued cheminformatics and software, joining Wiley in 2022.
</blockquote>

Wiley: Increase the Likelihood of MS Identification with the Wiley Registry / NIST Library

Increase the Likelihood of MS Identification with the Wiley Registry / NIST Library

The latest release of the Wiley Registry® / NIST Mass Spectral Library 2023, which combines the power of two trusted MS spectral libraries.

MS Identification with the Wiley Registry / NIST Library

Seeing everything, and as low as possible, with GC and MS is a function of selectivity and sensitivity: get as much as you can on column, and as best as you can, don&#39;t favor one set of compounds over another.
At some point a one microliter injection of a sample fails this criteria; what next? Concentration!
We will focus on how to concentrate analytes introduced via liquid, headspace, SPME, thermal desorption, and more, all using the latest advancements in a Peltier cooled, valveless, and simple to understand dynamic focusing system for your GC.
<blockquote>
Presenter: Kurt Thaxton (International Product Manager, Gerstel)
</blockquote>
<blockquote>
Kurt Thaxton is an International Product Manager for GERSTEL, a German manufacturer of thermal desorption, pyrolysis, and other means of sample preparation and sample introduction for GC- and LC-MS.
</blockquote>
<blockquote>
For over twenty years, Kurt has been a user of thermal desorption and pyrolysis as a research scientist at International Paper and later as a Product Specialist for Varian Inc. Later Kurt became involved in both the commercial and technical aspects of these techniques at Markes International and now GERSTEL.
</blockquote>
<blockquote>
Kurt also serves actively in different capacities at SAE, ASTM, AIHA, and ISO. Kurt has an M.S. in Analytical Chemistry from The Ohio State University where he focused on using mass spectrometry to solve analytical problems; MS remains a central interest and focus of Kurt&#39;s work today.
</blockquote>

Agilent Technologies: New Advances in Pre-Concentration for GC-MS: Seeing More and Lower

New Advances in Pre-Concentration for GC-MS: Seeing More and Lower

How to concentrate analytes introduced via liquid, headspace, SPME, thermal desorption, and more, all using the latest advancements in a Peltier.

New Advances in Pre-Concentration for GC-MS

Two years have passed since we hosted our first microplastics symposium.
Since then, the microplastic landscape has witnessed significant developments—the impending release of the first ISO standard and ongoing advancements in SOPs. We are pleased that we can bring you together with experts in our field.
This digital conference aims to explore various crucial topics related to the analysis of microplastics, covering areas such as sampling, sample preparation, analysis, and evaluation.
<h3>Highlights – Why you should attend</h3>
<h5>Stay updated on microplastic analysis</h5>
Gain insight into the latest advancements and challenges in microplastic analysis. This seminar covers essential aspects such as sampling, sample preparation, and analysis techniques like spectroscopy (ICP-MS) and chromatography (pyr/TED-GC/MS). 
<h5>Explore diverse applications</h5>
Discover the wide range of applications beyond microplastic analysis that can be addressed with a QCL-based IR imaging system like the LDIR 8700. Get an overview of its potential in areas such as materials, bio, and pharmaceuticals.
<h5>Take part in a live demo</h5>
Witness a live demonstration of an automatic microplastic analysis workflow. Experience firsthand how these techniques and technologies come together to address real-world challenges. Engage with Agilent experts who will answer any questions you may have.
<h5>Showcase your expertise</h5>
Actively participate by presenting your work and contributions in techniques like TED-GC/MS, pyr-GC/MS, and ICP-MS, which are crucial for microplastic analysis. Alternatively, highlight your knowledge of the versatile LDIR 8700 system, showcasing its applications in pharmaceuticals, material analysis, or bio sectors.
<h3>Agenda</h3>
<h5>09:00 Welcome Introduction &amp; Video of Geoff Winkett , Agilent Technologies</h5>
<h5>9:10 The World of Microplastics Up to Date an Overview</h5>
<ul>
<li>Andreas Kerstan (Agilent Technologies)</li>
</ul>
<h5>09:30 Hot news on Agilent LDIR, new developments, and future perspective</h5>
<ul>
<li>Wesam Alwan , Darren Robey (Agilent Technologies)</li>
</ul>
<h5>09:50 Release of Plastic Additives and Microplastic Particles from Different Consumer Products into Water under Accelerated UV Weathering Conditions</h5>
<ul>
<li>Lars Hildebrandt (Scientist, Helmholtz Zentrum Hereon)</li>
</ul>
Photodegradation of plastic products is known to accelerate weathering and the resulting release of chemical additives and particles to the environment, however these processes are complex. Here, eight different plastic consumer products were leached in double distilled water under exposure to strong ultraviolet (UV) light for ten days, and the chemical composition of the leachates was compared to their respective dark controls. The leachates and plastic particles were investigated with a wide battery of chemical analytical tools to broadly characterize the underlying processes and possible hazards. These covered (a) metal(loid) analysis, (b) microplastic analysis, (c) analysis of &gt;70 organic target analytes and (d) nontargeted screening of the extracts.
<h5>10:10 Identification of Polymers Using Machine Learning</h5>
<ul>
<li>Xin Tian (Scientific Researcher, KWR NL)</li>
</ul>
Microplastics and other polymers are found in the environment. For this reason, it is important to have reliable methods to identify them. Methods used to detect nano- and microplastics in the environment include Fourier-transform infrared (FTIR) spectroscopy, Raman spectroscopy, laser-directed infrared (LDIR) spectroscopy and thermogravimetric analysis (TGA)/pyrolysis. These measurement techniques can provide a lot of information, but sometimes require a database with a lot of high-quality data to compare measurement results. Machine learning (especially classification models) can help improve data processing and accuracy.
Recent research has looked at how machine learning can help improve the accuracy of identification with infrared spectroscopy. Different computer models were tested and examined to see if the accuracy increases and if it does not require an unreasonable amount of computing power and time. This research focused on finding an effective method for identifying polymers in the environment based on their mid-infrared spectroscopic signals.
Polymers are identified by infrared spectroscopy by comparing their spectra with spectra in a database/library. This works well for new polymers, which are clean and barely degraded. Since polymers from the environment are actually degraded, comparing their infrared spectra with spectra in the library is difficult. This is because the spectra in the library often have large deviations from the spectra of the measured polymers. Increasing the number of spectra in the library is not possible because the number of spectra of environmentally degraded polymers is almost infinite. The study therefore looked at whether the problem of small data sets can be addressed using machine learning. The research presents a data enrichment technique to generate spectra of degraded polymers from single spectra of a limited number of samples. Four models were tested using these spectra to identify polymers. The study shows that all the models achieve high success rates, thereby facilitating the identification of polymers from environmental samples. Moreover, the research shows that it is not necessarily the most advanced computer model (particularly deep neural network models) that yields the best results.
<h5>10:30 From the River to the Sea: Microplastics in Sediments of the Thames River</h5>
<ul>
<li>Friederike Strock (Postdoc, German Federal Institute of Hydrology)</li>
</ul>
Microplastics have been investigated for over 45 years especially in the marine environment, but only in the past years research has started to focus on freshwater environments. In the frame of the H2020 LABPLAS project, sediments along the course of the Thames river in its freshwater and estuarune part were studied in order to better understand the sources, transport, distribution and impacts of plastic pollution and to detect the amount of plastics transport via the rivers into the sea.
In the frame of the project, a winter and a summer campaign were conducted 2022 and samples taken from 6 sites within the study area. Sediment samples were taken with a Van Veen grabber from the edge of the river, wet sieved into different compartments (10 100 µm, 100 1000 µm, &gt;1000 µm), density separated and the organic matter digested. The plastics from the sediments were characterized with a Laser Direct Infrared (LDIR). The preliminary results reveal that microplastics are present in all samples. The amount of particles varies significantly between the sampling sites showing the importance of industrial emissions and cities.
<h5>10:50 Good Laboratory Practices to Characterize Microplastics Using Quantum-Cascade Laser Reflectance Absorbance Spectrometry</h5>
<ul>
<li>Jose Manuel Andrade Garda (Professor Analytical Chemistry, University of A Corunna)</li>
</ul>
The nowadays broad societal interest in microplastic pollution demands urgent responses and actions. For these be possible politicians must set rules which, in turn, are not possible at all without sound scientific data. Unfortunately, there is a general feeling that the experimental results obtained so far are not still fully comparable and, further, that the monitoring field where hundreds or samples are taken is not being fully considered. Scientific studies and future regulations depend critically on a reliable identification of the polymers (if any) that constitute the suspicious particles under study. Out of the various analytical techniques to characterize them a novel one based on reflectance-absorbance spectrometry, commercialized as LDIR, outstands. It uses a tuneablemid-IR quantum cascade laser (QCL) to imaging a reflective microscopy slide or a metal-coated filter in a remarkable small timeframe. This communication is meant to present best practice guides to overcome some obstacles/difficulties in routine measurements, and open a path for field monitoring; among them: the adequacy of the spectral range, the variation of the peak&#39;s intensities with the size of the particles; the speed of the analysis as a function of the instrumental setup; the criterion to identify unknown spectra (a tiered approach is finally suggested); and how to differentiate fibers and fragments semiautomatically. Also, an empirical dependence of the depth of penetration of the QCL laser in common plastic particles is approached first time.
<h5>11:10 Chemical Characterization of Microplastics using Pyrolysis-Gas Chromatography-Mass Spectrometry (Py-GC-MS)</h5>
<ul>
<li>Soledad Muniategui-Lorenzo (Pull Professor of Analytical Chemistry, University of A Corunna)</li>
</ul>
The implementation of monitoring programs for Microplastics requires reliable and standardisedmethods. Fourier Transform Infrared (FTIR) and Raman spectroscopy techniques are the most commonly used for Microplastics analysis. However, thermal analytical techniques are currently gaining popularity. This presentation focuses on the potential of mass-based thermal analytical techniques, in particular, Pyrolysis coupled with Gas Chromatography-Mass Spectrometry (Py-GC-MS), for the accurate qualitative and quantitative analysis of microplastics in environmental matrices. It outlines some advantages and good laboratory practices of this approach, the importance of method normalisation, and how it can provide detailed information on polymers and plastic additives.
<h5>11:20 Analysis of Fibrous Microplastics Using Laser Direct Infrared Imaging</h5>
<ul>
<li>Monique Greiner (Research Associate, Hohenstein Laboratories)</li>
</ul>
In the research field of microplastics the identification of their source is important in order to develop strategies to minimize the pollution. A major percentage of microplastics originates from textiles. One pathway into the environment are washing procedures because the textiles release fibers during the process. Therefore our aim was to find a fast and easy way to identify fibers. In our presentation we want to give insights in our approach to the analysis of fibrous microplastics with the LDIR 8700. We will talk about our strategies, the results we achieved and difficulties we faced.
<h5>11:40 Looking beyond the Polymer: Using Thermal Desorption GC MS to expand our understanding of Microplastics</h5>
<ul>
<li>Jan Peter Mayser (Market Specialist, Markes International)</li>
</ul>
Detecting and analysingmicroplastics in the environment is challenging. The method must be able to detect and distinguish between a large variety of polymers. Additives, such as hardeners, flame retardants and preservatives, used during the manufacturing process and other compounds, that can adhere to the surfaces of microplastics from their environment, can affect their toxicity assessment. These additives could be used to link the microplastics found in the environment to their original use or potentially even back to the manufacturer.
In this study, various salts were sampled and filtered and analyzed for their microplastic content. TD–GC–MS was used to identify and measure which concentration of the plastic PS, PET, PVC and Nylon 6 had been incorporated into the crystalline structure of the salt during evaporation. By using direct desorption and backflushing technology, a large sample size could be easily isolated from the lab environment during analysis while ensuring a large range of volatile organic compounds (VOCs) including the marker compounds for four polymers could be trapped and analyzed.
The VOC-profile of the microplastics not only gave information about the polymer and its concentration within the sample, but further information about the toxicity could be extracted. This enabled the determination and tentative identification of additional compounds in the samples, such as dimethyl ether, acrolein and cyclopentane. These are used in the process of manufacturing plastics, so could assist with identifying the source of the plastics. For the four analysed polymers distinct marker compounds could be identified and calibration curves determined for each polymer. In all of the real-world salt samples microplastics were identified, highlighting the ubiquitous nature of the microplastic contamination.
This further information about the origin of the polymer, as well as the origin of the microplastic particles can be gathered by investigating the full VOC-profile obtained by TD-GC-MS. This allows both additional polymer information and particle source characterization.
<h5>12:00 Tiny Problems</h5>
<ul>
<li>Roxana Sühring (Assistant Professor in Analytical Environmental Chemistry, Toronto Metropolitan University)</li>
</ul>
Microplastics have been on the front page of newspapers, a dominant topic for environmental research (and funding), and a recent focus for regulatory action across the globe. Their potential impacts have been classed as a planetary boundary threat and new studies are published daily, reporting microplastics virtually anywhere on the planet. But despite numerous publications, there are still a lot of open questions on how to effectively and reproducibly characterize microplastics. How can microplastic characterization be automized? What is the impact of additives or weathering on the characterization accuracy?
In this presentation I will provide an overview and the first results of a research collaboration between Agilent technologies and the Emerging contaminants lab at Toronto Metropolitan University that works on addressing some of these questions. Our research aims to create a versatile microplastic library using weathered and new plastics commonly found in the environment. This library will additionally be used as a training set for developing automated particle characterization for the LDIR.
<h5>12:20 Identification of Microplastic Particles in Soil Using LDIR</h5>
<ul>
<li>Martine Graf, PhD (Student &amp; Senior Technician, Bangor University)</li>
</ul>
The use of agricultural plastic has become increasingly concerning in an environmental setting in recent years; in Europe alone, an estimated 2.5 million tones of plastic mulch films are used each year. The use of mulch films for crop production has been promoted by governments worldwide due to its many benefits, however the removal of these films from the soil can be difficult due to their poor mechanical strength and fragmentation, and barriers such as poor incentives for farmers and underdeveloped infrastructure for collection and disposal. The latter often leading to the films being discarded or incinerated along field margins, or ploughed back into the fields, leading to an accumulation of plastic legacy in soil. To evaluate the microplastic pollution levels in agricultural soils, we are i ) conducting a global soil survey in all partner countries; ii) assessing the degradation and fragmentation of conventional and biodegradable plastic mulch films in soil, and measuring the resulting microplastic production rate; and iii) measure the degradation and movement of microplastic in soil after repeated application. Microplastics are extracted from soil using targeted methods for different polymer types, and analysed using fluorescent microscopy, FTIR spectroscopy, and LDIR spectroscopy.
<h5>12:40 Wrap up and open discussion</h5>

Agilent Technologies: Agilent Microplastics Virtual Symposium 2023

Agilent Microplastics Virtual Symposium 2023

Explore various crucial topics related to the analysis of microplastics, covering areas such as sampling, sample preparation, analysis, and evaluation.

Do you face difficulty in selecting the most appropriate GC column for your analysis? Are you always wondering which column will work best for your application or if the existing column will work for your application or not?
In this webinar, we will discuss:
<ul>
<li>Things to consider while choosing GC Columns
</li>
<li>GC Column types
</li>
<li>Stationary Phase Polymers
</li>
<li>Low Bleed Phases
</li>
<li>Ultra Inert columns
</li>
<li>Suitable columns for Critical Applications
</li>
</ul>
Join us in this live webinar to discuss on various aspects of GC column selection.
<blockquote>
Presenter: Sunil B Lakhmapure (Technical Support Specialist, Agilent Technologies)
</blockquote>
<blockquote>
Sunil holds 19 year plus experience in the analytical field with major exposure to LC/GC with Single Quad, Triple Quad and high resolution (QToF) mass spectroscopy. Started career in Pharma R&amp;D as a scientist with hands on experience on high end instruments like LC/MS, XRD &amp; NMR. Developed &amp; published application notes using Chromatographic techniques on real world samples/issues at various levels.
</blockquote>

Agilent Technologies: Practical Advice on GC Column Selection

Practical Advice on GC Column Selection

Do you have a new GC column to install? Do you often wonder about the nuances of GC column installation and how to get your new column up and running? Do you often wonder for how long you should condition the column and at what temperature?
In this webinar, we will discuss:
<ul>
<li>Column construction
</li>
<li>Column Unboxing
</li>
<li>Column Installation
</li>
<li>Leak and Installation Check
</li>
<li>Preventive measures for better column life 
</li>
<li>Corrective measures in case you run into a problem
</li>
</ul>
Join us in this webinar to understand a hassle-free GC column installation and how to take care of your GC column.
<blockquote>
Presenter: Dr. Rajni Mujoo (Technical Support Specialist, Chemistries &amp; Supplies Division, Agilent Technologies)
</blockquote>
<blockquote>
Dr. Rajni is working with us as Technical Support Specialist in Chemistries and Supplies Division at Agilent Technologies since 2011. She has a Ph.D degree in Food Science from CFTRI, Mysore and Post Doctorate from Department Of Food Science, Michigan State University. She also has four International Presentations &amp; 13 publications in reputed National &amp; International journals to her credit. Rajni has a total work experience of 16 yrs spread across research and Sales building expertise in different Instrument techniques.
</blockquote>

Agilent Technologies: Best Practices for GC Column Installation and Care

Best Practices for GC Column Installation and Care

Understand a hassle-free GC column installation and how to take care of your GC column.

Thermal desorption and pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS) is a well-established and proven analytical method for materials characterization.
In combination with GC-MS, thermal desorption is used to identify additives and contaminants, and pyrolysis is a key tool for identifying involatile materials such as polymers, lacquers, paints, adhesives, plastics, and synthetic fibers.
This webinar will explain the basics of Py-GC-MS and how it can be applied to applications such as quality control, troubleshooting, and deformulation using applications of the Frontier Lab micro-furnace Multi-Shot Pyrolyzer combined with JEOL single quadrupole and high-resolution time-of-flight GC-MS systems
Attendees of this webinar will learn:
<ul>
<li>How pyrolysis GC-MS is used to identify polymers, additives, and contaminants.
</li>
<li>how hard and soft ionization methods provide complementary information.
</li>
<li>about software tools and interpretation libraries for analysis
</li>
</ul>
<blockquote>
Presenter: Rojin Belganeh
</blockquote>
<blockquote>
Rojin Belganeh is the Technical Director at Frontier Laboratories Americas. As a former user of Frontier products with more than ten years of experience in analytical instrumentation, Rojin is passionate about creating awareness about Frontier technology and providing technical support to users. Rojin graduated from the University of Houston with a Bachelor of Science in Chemistry. She started her profession as an analytical chemist working with various analytical instruments, such as Pyrolysis GCMS, TGA, FTIR, and X-Rays for material characterization, polymer identification, and contamination analysis. She also holds an MBA degree concentrating in strategic marketing.
</blockquote>
<blockquote>
Presenter: Robert “Chip” Cody
</blockquote>
<blockquote>
Chip Cody has worked at JEOL USA, Inc. in Peabody, MA for the past 34 years and is currently Principal Scientist. Dr. Cody is responsible for developing the trapped-ion tandem-in-time MS/MS and MSn techniques, laser-desorption in a trapped ion mass spectrometer, Electron Impact Excitation of Ions from Organics (EIEIO), and is a coinventor of the DART ion source. He has consulted with NASA on the Mars 2020 Rover project, served as Vice-President for Arrangements for the American Society of Mass Spectrometry (ASMS), was awarded the 2011 Anachem Award and a 2012 Purdue University Distinguished Alumni Award, and is currently on the Editorial Board for the ASMS journal and a member of the ASMS History Committee.
</blockquote>
<blockquote>
Presenter: Bryan Katzenmeyer
</blockquote>
<blockquote>
Bryan Katzenmeyer has over 15 years of experience specializing in mass spectrometry and separation techniques for characterizing materials, polymers, monomers, and small molecules. He obtained his Ph.D. in polymer/analytical chemistry at The University of Akron under Distinguished Professor Chrys Wesdemiotis and his M.S. and B.S. in chemistry at the University of Wisconsin-Madison and Penn State, respectively. Bryan joined JEOL USA, Inc. in 2023, where he currently manages business development for mass spectrometry with an emphasis on the polymer and chemical industrial markets.
</blockquote>

JEOL - Thermal Desorption and Pyrolysis-GC-MS for Deformulation and Material Characterization

Thermal Desorption and Pyrolysis-GC-MS for Deformulation and Material Characterization

Basics of Py-GC-MS and how it can be applied to applications such as quality control, troubleshooting, and deformulation.