<p><strong>In this technical tip from </strong><span><strong>Phenomenex</strong></span><strong>, the topic of gas chromatography (GC) column trimming is addressed from a troubleshooting perspective. The key question explored is whether trimming a GC column is necessary and how it impacts chromatographic performance.</strong></p><h3><strong>Why Trim a GC Column?</strong></h3><p>Column trimming is primarily used to <strong>restore chromatographic performance</strong> by removing damaged or contaminated sections, typically located at the column inlet.</p><h5><strong>1. Baseline Bleed, Noise, Ghost Peaks, Poor Peak Shape</strong></h5><ul><li><strong>Cause:</strong> Column contamination</li><li>Removing the contaminated stationary phase at the column entrance helps restore performance.</li></ul><h5><strong>2. Elevated Baseline (Especially at High Temperature)</strong></h5><ul><li><strong>Cause:</strong> Column bleed</li><li>Degradation of the stationary phase due to <strong>oxygen exposure or thermal damage</strong> leads to increased baseline.</li></ul><h5><strong>3. Ghost Peaks (Peaks Without Injection)</strong></h5><ul><li><strong>Cause:</strong> Residual sample or contamination</li><li>Compounds trapped at the beginning of the column can appear as peaks even when no sample is injected.</li></ul><h5><strong>4. Peak Tailing (Asymmetrical Peaks)</strong></h5><ul><li><strong>Cause:</strong> Damaged or contaminated column sections</li><li>These issues result in <strong>adsorption effects or poor flow dynamics</strong>.</li></ul><h5><strong>5. Retention Time Shifts</strong></h5><ul><li><strong>Cause:</strong> Contamination or damage near the inlet</li><li>Although trimming slightly changes retention time, it can correct shifts caused by inlet-side issues.</li></ul><h5><strong>6. Baseline Noise and Spikes</strong></h5><ul><li><strong>Cause:</strong> Particulate matter or degraded stationary phase</li><li>These can lead to <strong>detector instability</strong> and random signal fluctuations.</li></ul><h5><strong>7. Baseline Drift or Wander</strong></h5><ul><li><strong>Cause:</strong> Contamination or oxidized column sections</li><li>Removing these regions stabilizes the baseline.</li></ul><h5><strong>8. Loss of Resolution or Sensitivity</strong></h5><ul><li><strong>Cause:</strong> General column degradation</li><li>Trimming removes the most exposed and damaged portions, effectively <strong>rejuvenating column performance</strong>.</li></ul><h3><strong>How to Trim a GC Column</strong></h3><p>A capillary GC column consists of:</p><ul><li><strong>Polyimide outer coating</strong> (protective layer)</li><li><strong>Fused silica tubing</strong> (fragile but flexible core)</li></ul><h3><strong>Step-by-Step Procedure</strong></h3><h5><strong>1. Scoring the Column</strong></h5><ul><li>Use a <strong>ceramic wafer</strong></li><li>Hold it at an <strong>inclined angle</strong></li><li>Score the polyimide coating <strong>perpendicular to the column</strong></li></ul><h5><strong>2. Breaking the Column</strong></h5><ul><li>Perform a <strong>quick, decisive flick</strong></li><li>This ensures a <strong>clean, square cut</strong></li></ul><h5><strong>3. Inspecting the Cut</strong></h5><p>After trimming, visually inspect the column end.</p><h3><strong>Examples of Column Cuts</strong></h3><h4><strong>Good Cut</strong></h4><ul><li>Clean, <strong>square end</strong></li><li>Ensures proper sealing and connection</li></ul><h5><strong>Bad Cuts</strong></h5><ul><li><strong>Slight Irregularity</strong><ul><li>Small imperfection at the edge</li><li>Can cause <strong>leaks</strong> and <strong>active sites</strong></li></ul></li><li><strong>Poor / Rough Cuts</strong><ul><li>Uneven or jagged edges</li><li>Lead to:<ul><li>Poor connections</li><li>Active sites</li><li>Peak tailing</li></ul></li></ul></li></ul><h2><strong>Conclusion</strong></h2><p>Trimming a GC column is a simple yet effective troubleshooting step. By removing contaminated or damaged sections—especially near the inlet—it can resolve a wide range of chromatographic issues, including baseline instability, ghost peaks, and loss of performance.</p><p>Proper cutting technique is essential to avoid introducing new problems such as leaks or active sites.</p>

Trimming a GC Column: Purpose, Symptoms, and Proper Technique

<h3><strong>We're excited to announce that </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/999"><strong>Clarity Chromatography Software</strong></a><strong> version 10.1.2 is now available!</strong></h3><p><strong>This minor update expands Clarity’s portfolio with new control modules.</strong></p><h4><strong>Newly added Instrument control modules</strong></h4><ul><li>Ecom auxiliary modules</li><li>HTA ICF control modules</li><li>Spark pump</li></ul><h4><strong>Updated Instrument control modules</strong></h4><ul><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/companies/168"><strong>Ecom</strong></a> HPLC</li><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/companies/328"><strong>Knauer</strong></a> HPLC</li><li>Spark ICF control modules</li><li>YoungIn Chromass HPLC</li></ul><blockquote><p>For a complete list of module changes, see the <a target="_blank" rel="noopener noreferrer" href="https://www.dataapex.com/version_history?product=1"><strong>Changelog</strong></a>. For more info about exciting new features directly in Clarity, explore what was introduced in the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/article/5622"><strong>Clarity 10.1 release highlights</strong></a>.</p><p>Clarity can control <strong>1000+ instruments</strong>; the <a target="_blank" rel="noopener noreferrer" href="https://www.dataapex.com/controls"><strong>list can be previewed here</strong></a>.</p></blockquote><h4><strong>Supported Instruments in Clarity (DataApex) — Quick Guide</strong></h4><p>Clarity Chromatography Software supports a wide range of chromatographs and peripherals via <strong>digital control (DD)</strong> and <strong>analog acquisition (A/D)</strong> using the <strong>Colibrick</strong> module.</p><h5><strong>Gas Chromatographs (GC)</strong></h5><p>Digital integration over LAN/RS232 (many via ICF):</p><ul><li><strong>Agilent</strong>: 5890, 6890, 7890, 8860, 8890, <strong>Intuvo 9000</strong></li><li><strong>Shimadzu</strong>: GC-2010/2014, <strong>Nexis GC-2030</strong></li><li><strong>Thermo Fisher</strong>: TRACE 1300/1310</li><li><strong>PerkinElmer</strong>: Clarus 400–690</li><li>Also supported: <strong>Dani</strong>, <strong>Ellutia</strong>, <strong>Young In Chromass</strong>, <strong>Apix</strong>, <strong>Fuli</strong>, <strong>GOW-MAC</strong> (selected models)</li></ul><blockquote><p>Note: Most Agilent 6890–8890 and Intuvo use <strong>LAN – ICF</strong>.</p></blockquote><h5><strong>HPLC Systems</strong></h5><p>Full system/module control:</p><ul><li><strong>Agilent</strong> 1100–<strong>1290 Infinity II</strong> (ICF)</li><li><strong>Shimadzu</strong> LC-10/20 and <strong>Nexera LC-40</strong></li><li><strong>PerkinElmer</strong> Flexar / NexSAR</li><li><strong>Knauer</strong> Azura / BlueShadow / Smartline</li><li><strong>Hitachi</strong> Chromaster / Primaide</li><li><strong>Young In Chromass</strong> ChroZen series</li><li><strong>Sykam</strong> S500–S600, <strong>Watrex</strong> Streamline, <strong>Hanon</strong> LC7000–7300</li></ul><h5><strong>HPLC Modules (Pumps, Detectors, Ovens, Fraction Collectors)</strong></h5><ul><li><strong>Pumps</strong>: Agilent 1100–1290 families, Knauer, Shimadzu, PerkinElmer, Sykam, SSI, Ecom</li><li><strong>Detectors</strong>: VWD/DAD(PDA)/RID/FLD/ELSD across Agilent, Shimadzu, Knauer, PerkinElmer, Young In Chromass, Ecom, etc.</li><li><strong>Column Ovens</strong>: Agilent G1316x / G7116x, Shimadzu CTO-20/30/40, Knauer CT2.1, PerkinElmer Flexar</li><li><strong>Fraction Collectors</strong>: Knauer FC 6.1, Teledyne FOXY series, Ecom ECF 2096, Waters Fraction Collector II</li></ul><h5><strong>Autosamplers</strong></h5><ul><li><strong>Agilent</strong> GC ALS (7673/7683/7693/8697), HPLC ALS modules (G1313A–G7167C)</li><li><strong>Shimadzu</strong> AOC-20 / AOC-5000+, SIL-10 / SIL-20 / <strong>SIL-40</strong> series</li><li><strong>CTC Analytics PAL</strong>, <strong>HTA</strong> autosamplers, <strong>Spark</strong> Alias/UHPLC, <strong>Knauer</strong> AS 6.1L</li><li><strong>PerkinElmer</strong> Flexar / NexSAR AS</li></ul><h5><strong>Other Devices</strong></h5><ul><li><strong>GC×GC modulators</strong> (e.g., Charles University GC×GC Modulator)</li><li><strong>Valves &amp; switch modules</strong> (Agilent, Knauer, Shimadzu, VICI-Valco)</li><li><strong>Degassers, flow monitors, managers, interfaces</strong></li><li><strong>LC-MS / GC-MS</strong>: Advion Expression CMS, Microsaic 4500 MiD, Markes BenchTOF (and others)</li><li><strong>Balances (EA extension)</strong>: Mettler Toledo, Sartorius</li></ul><h5><strong>Analog Acquisition (Colibrick)</strong></h5><p>A/D support for legacy or analog-output devices:</p><ul><li><strong>GC</strong>: Agilent 5880/4890A, Varian 3xxx/3800/3900, PerkinElmer Clarus series, Thermo TRACE, Shimadzu GC-14/9A, Scion 43x/45x/83xx/85xx, etc.</li><li><strong>HPLC Detectors</strong>: Waters 2487/2489, ESA Corona, Hitachi L-series, JASCO FP/UV, Ecom LCD series, many others</li><li><strong>Elemental &amp; Amino Acid Analyzers</strong>: Carlo Erba/Costech ECS, Biochrom 20/30+</li></ul><p>If you are interested in a <strong>DEMO VERSION</strong>, contact us!</p>

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<p><strong>🎤Jessica Whitehouse</strong></p><p><strong>Haloacetic acids (HAAs) are disinfection byproducts formed when chlorine or bromine reacts with organic matter in water—and some are linked to serious health concerns. In this episode of Concentrating on Chromatography, we sit down with Jessica Whitehouse, MSc student at the University of Calgary, to discuss how she developed a GC-MS method to detect and quantify HAAs in real-world water samples.</strong></p><p>During her undergraduate research at Thompson Rivers University, Jessica tackled a major challenge faced by many academic labs: how to analyze regulated environmental contaminants without access to GC-ECD instrumentation. &nbsp;Using dispersive liquid–liquid microextraction, derivatization, and GC-MS, she built a faster, more accessible workflow—and applied it to tap water, swimming pools, and hot tubs.</p><h4><strong>In this conversation, we cover:</strong></h4><ul><li>What haloacetic acids are and why they matter</li><li>Why standard EPA methods can be difficult for smaller or teaching-focused labs</li><li>How GC-MS can be adapted for HAA analysis</li><li>The challenges of derivatization and temperature program optimization</li><li>Unexpected findings in brominated vs. chlorinated HAAs</li><li>Why pool and hot tub water can show surprisingly high HAA levels</li><li>The excitement (and frustration) of first-time method development</li><li>Advice for undergraduate and early-career analytical chemists</li></ul><p>Jessica also shares how this project led directly to her current MSc research on ozone and nanobubble water disinfection, where she’s now expanding into ion chromatography.</p><p>Whether you work in environmental analysis, chromatography, GC-MS, or are just starting your journey in analytical chemistry, this episode offers practical insight into real lab constraints, method development, and the joy of finding your first analyte peak.</p><h3><strong>Video Transcription</strong></h3><h4><span><strong>Introduction</strong></span></h4><p>Haloacetic acids (HAAs) are an important class of disinfectant byproducts formed when organic matter present in water reacts with chemical sanitizers. Because several HAAs are associated with adverse health effects, their determination remains relevant in environmental and public health analysis. This interview highlights the academic pathway and research experience of Jessica, whose undergraduate work focused on the development of a gas chromatography–mass spectrometry (GC-MS) method for the analysis of HAAs in pool and hot tub water.</p><p>Her project emerged from a combination of academic interest in analytical chemistry, practical experience with water testing, and the constraints of instrument availability in an undergraduate research setting. The resulting workflow illustrates how method adaptation, critical problem-solving, and persistence can enable meaningful analytical research even when standardized methods are not directly accessible.</p><h4><span><strong>Academic Background and Entry into Analytical Chemistry</strong></span></h4><p>Jessica completed a Bachelor of Science in Chemistry with a minor in Physics at Thompson Rivers University in British Columbia. Her interest in analytical chemistry developed during her second year of study, when coursework revealed the quantitative and detail-oriented nature of the discipline. This emphasis on numerical interpretation, precision, and method development aligned strongly with her academic strengths and motivated her to pursue analytical research.</p><p>Her specific interest in water chemistry originated even earlier through practical work in a pool and hot tub store, where she became familiar with routine water testing and the chemical factors influencing water quality. This early exposure led naturally into undergraduate research under the supervision of Dr. Sharon Brewer, whose expertise in water analysis provided an ideal foundation for the project.</p><h4><span><strong>Haloacetic Acids as Disinfectant Byproducts</strong></span></h4><p>Haloacetic acids are a subset of disinfectant byproducts generated when sanitizing agents react with natural organic matter in water. In treated recreational water systems such as pools and hot tubs, disinfectants are essential for microbial control, yet they can also lead to formation of unwanted chemical byproducts. Because some HAAs are considered potentially harmful, their occurrence and concentration warrant analytical attention.</p><p>In this study, both chlorinated and brominated HAAs were of interest. Although the tested water systems were primarily sanitized using chlorine-based products, the occurrence of brominated HAAs emerged as a notable and somewhat unexpected finding.</p><h4><span><strong>Analytical Challenges and Method Selection</strong></span></h4><p>A major challenge in the project was the lack of access to the instrumentation required for the standard EPA-based method initially considered for HAA analysis. The available protocol depended on GC-ECD instrumentation, which was not accessible at the university. This limitation required the development of an alternative strategy based on the instruments available locally.</p><p>GC-MS was selected as the most practical analytical platform. To support this approach, Jessica identified a literature source describing a similar method that could be adapted to her research aims. In parallel, dispersive liquid–liquid microextraction was introduced into the workflow as a means of sample preparation, providing valuable methodological experience beyond the standard undergraduate laboratory curriculum.</p><p>This adaptation illustrates a common reality in academic research: analytical methodology is often shaped not only by ideal regulatory procedures, but also by local instrument access, scheduling limitations, and the practical needs of the researcher.</p><h4><span><strong>Need for Derivatization in GC-MS Analysis</strong></span></h4><p>A central analytical issue was that HAAs are inherently nonvolatile, which makes them poorly suited to direct GC analysis. To enable gas chromatographic separation, derivatization was required to convert the analytes into more volatile derivatives with more favorable boiling characteristics.</p><p>In this method, derivatization with octanol was employed. This modification improved volatility and also generated larger fragments, which aided mass spectral interpretation by making the analyte fragmentation patterns easier to distinguish. Thus, derivatization served both chromatographic and mass spectrometric purposes.</p><h4><span><strong>Optimization of the GC Temperature Program</strong></span></h4><p>Considerable effort was devoted to optimization of the GC temperature program. The main difficulty did not arise solely from the analytes themselves, but from the derivatization reagent. Octanol produced a broad and persistent chromatographic feature, including a significant shoulder extending into later retention times. This complicated separation and increased pressure to keep the method sufficiently short for routine sample throughput.</p><p>Among the analytes, monochloroacetic acid proved especially problematic. Because it differed only subtly in structure and produced overlapping behavior relative to the octanol-derived background, its signal was difficult to isolate confidently. Although chlorine-containing fragments could be observed, precise assignment remained challenging. This difficulty underscores how small structural differences and matrix-related interferences can complicate quantitative GC-MS workflows.</p><h4><span><strong>Method Performance and Practical Advantages</strong></span></h4><p>Although the adapted GC-MS method was developed out of necessity, it also provided practical advantages over the more standardized workflow that had initially been considered. In particular, the derivatization step in the adapted approach required only approximately 10 minutes, whereas the more conventional procedure involved a water bath step lasting around two hours. In addition, the adapted workflow offered shorter overall preparation and analysis timing, allowing batches of samples to be prepared and placed on the autosampler within a normal working schedule.</p><p>From a practical research perspective, this translated into substantially improved laboratory efficiency. The ability to complete derivatization quickly and begin automated sample analysis without extensive delays made the workflow more manageable and better suited to the demands of an undergraduate project.</p><h4><span><strong>Unexpected Findings: Brominated HAAs in Chlorine-Sanitized Systems</strong></span></h4><p>One of the more surprising outcomes of the study was the predominance of brominated HAAs, despite the fact that the investigated pools and hot tubs were sanitized using chlorine-based treatments. Four of the systems relied on sodium chloride electrolysis to generate chlorine species, while others used chlorine-containing puck formulations commonly applied in recreational water treatment.</p><p>Given these conditions, higher levels of chlorinated HAAs might have been expected. Instead, the results suggested a greater abundance of brominated HAAs. A plausible explanation is the presence of bromine-containing impurities in commercial pool and hot tub chemicals. Although such impurities may occur at relatively low levels, they can still influence disinfectant byproduct formation. The observation highlights the importance of considering the full chemical composition of treatment products, not merely their primary declared active ingredients.</p><h4><span><strong>Value of Practical Industry Experience</strong></span></h4><p>Jessica’s prior work in the pool and hot tub industry provided an unusually strong contextual advantage for the project. Because the samples originated from store clients, she had access to detailed information about the chemicals used in each system, including safety data sheets and knowledge of treatment timing. This background significantly strengthened interpretation of the analytical results by linking measured byproducts to known product usage patterns.</p><p>Such integration of practical field knowledge with laboratory analysis represents an important strength in applied environmental chemistry, particularly when studying real-world water systems rather than idealized laboratory samples.</p><h4><span><strong>Scientific Development and Early Research Motivation</strong></span></h4><p>An especially valuable element of the project was the role it played in building research confidence. Jessica described the first successful identification of an analyte peak as a memorable turning point, reflecting the emotional significance of early experimental success in scientific training. In analytical chemistry, where method optimization often involves repeated setbacks and ambiguous data, such moments can be critical in sustaining motivation and reinforcing scientific identity.</p><p>This experience also informed her advice to early-stage researchers: unfavorable or unexpected outcomes still constitute valid results. Negative or imperfect findings remain analytically meaningful and contribute to scientific understanding, provided they are interpreted carefully.</p><h4><span><strong>Connection to Current Research</strong></span></h4><p>Jessica is now working at the University of Calgary on a different project focused on ozone and nanobubble disinfection. Although the analytical platform and immediate research questions have changed, the conceptual connection to her earlier work remains clear. Her experience with disinfectant byproducts and water chemistry directly supported her transition into this new role and helped position her as a strong candidate for research in water treatment-related systems.</p><p>She also expressed interest in expanding her analytical expertise through ion chromatography, which will play a role in her current work. This transition reflects the broader development of an environmental analytical chemist whose work continues to center on water quality, disinfection chemistry, and the analytical tools needed to investigate both.</p><h4><span><strong>Public Health Relevance</strong></span></h4><p>A notable practical implication of the project concerns recreational water safety. Jessica emphasized that pool and hot tub water should not be ingested, a recommendation already widely understood in general terms but further reinforced by her findings. In at least one case, HAA concentrations were reported at levels far above the federal drinking water regulation threshold. While such regulations are designed for potable water rather than recreational water, the comparison nevertheless illustrates the extent to which disinfectant byproducts may accumulate in these environments.</p><p>She also noted that several HAAs are classified as probable human carcinogens, with prolonged exposure linked to serious health concerns. Although occasional accidental ingestion is not equivalent to chronic exposure, the findings reinforce the importance of appropriate hygiene, safe water maintenance practices, and awareness of chemical byproduct formation in recreational systems.</p><h4><span><strong>Conclusion</strong></span></h4><p>This research demonstrates how meaningful analytical chemistry can emerge from a combination of scientific curiosity, practical constraints, and strong mentorship. By adapting a GC-MS workflow for the determination of haloacetic acids in pool and hot tub water, Jessica developed a method that was both workable within local instrument limitations and efficient enough to offer practical benefits over more conventional procedures.</p><p>Beyond the analytical results themselves, the project highlights several broader themes: the value of undergraduate research, the importance of flexibility in method development, the benefit of practical contextual knowledge, and the relevance of environmental analytical chemistry to real-world public health questions. It also shows how early research experiences can shape a long-term scientific trajectory, leading from undergraduate investigation to continued work in water chemistry and disinfection science.</p><blockquote><p><strong>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.</strong></p></blockquote><blockquote><h4><strong>Concentrating on Chromatography Podcast</strong></h4><p>Dive into the frontiers of chromatography, mass spectrometry, and sample preparation with host David Oliva. Each episode features candid conversations with leading researchers, industry innovators, and passionate scientists who are shaping the future of analytical chemistry. From decoding PFAS detection challenges to exploring the latest in AI-assisted liquid chromatography, this show uncovers practical workflows, sustainability breakthroughs, and the real-world impact of separation science. Whether you’re a chromatographer, lab professional, or researcher you'll discover inspiring content!</p><p>You can find <strong>Concentrating on Chromatography Podcast </strong>in podcast apps:</p><ul><li><a target="_blank" rel="noopener noreferrer" href="https://open.spotify.com/show/1wZg67rCjoGju4yhqxI3tL"><strong>Spotify</strong></a></li><li><a target="_blank" rel="noopener noreferrer" href="https://podcasts.apple.com/tz/podcast/concentrating-on-chromatography/id1788429185"><strong>Apple podcast</strong></a></li><li><a target="_blank" rel="noopener noreferrer" href="https://podscan.fm/podcasts/concentrating-on-chromatography"><strong>podscan</strong></a></li></ul><p>and on <a target="_blank" rel="noopener noreferrer" href="https://www.youtube.com/@ChromatographyTalk/videos"><strong>YouTube channel</strong></a></p></blockquote>

Detecting Haloacetic Acids in Water with GC-MS

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Mestrelab Mnova ElViS software

By integrating Mnova ElViS into your analytical workflows, you can enhance the efficiency and accuracy of your spectroscopic data analysis across a wide range of techniques.

<h4><strong>Visualize, process, analyze and report various electronic and vibrational spectroscopic techniques</strong></h4><p>Carry out the analysis of various optical spectroscopy data including ultraviolet and visible (UV/Vis), near and mid infrared (NIR/MIR), Raman, fluorescence, and other spectroscopic methods operating in the whole region of wavelength from 100 nm to 100 µm.</p><h4><strong data-start="641" data-end="654">Benefits:</strong></h4><ul><li>Spectroscopic processing and analysis of ultraviolet and visible (UV/Vis), near and mid infrared (NIR/MIR), Raman, fluorescence methods.</li><li>Vendor and Operating System agnostic, supports most data file formats.</li><li>Wide range of processing functions, including a dynamic processing template.</li><li>Manual and automatic peak picking analysis.</li><li>Data Analysis of stacked/arrayed spectra.&nbsp;</li></ul><h4><strong>Features:</strong></h4><h5><strong data-start="1039" data-end="1108">PLS-Based Baseline Correction Tool (IarPLS)</strong></h5><p>To improve the processing of electronic and vibrational spectroscopy data, Mnova 15 introduces an enhanced PLS-based baseline correction tool, IarPLS (penalized-least-squares based). It now features an automatic button to compute the near-optimal asymmetry parameter.&nbsp;</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_EI_Vis_PLS_Based_Baseline_Correction_Tool_Iar_PLS_f3180f6927.webp" alt="Mestrelab Research: Mnova EIVis - PLS-Based Baseline Correction Tool (IarPLS)." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Research_Mnova_EI_Vis_PLS_Based_Baseline_Correction_Tool_Iar_PLS_f3180f6927.webp 245w," sizes="100vw" width="1500" height="845"></p><h5><strong>Normalization Processing Modes</strong></h5><p>Three Normalization Processing modes, namely Largest Peak, Integral and Vector Length are available in Mnova 15. These three features aim to simplify the baseline correction process, streamline your workflow, and provide a rapid method for normalizing data to address quantitative issues.&nbsp;</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_EI_Vis_Normalization_Processing_Modes_675cb7c407.webp" alt="Mestrelab Research: Mnova EIVis - Normalization Processing Modes" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Research_Mnova_EI_Vis_Normalization_Processing_Modes_675cb7c407.webp 245w," sizes="100vw" width="1500" height="844"></p><h5><strong>Electronic and Vibrational Spectroscopies supported file formats</strong></h5><p>Mnova ElViS supports the most frequently used data file formats for these analytical techniques, including import and export of single and multi-column matrix-like spectra (i.e., ASCII XY and XYY, as .txt or .csv files). Supported formats include SPC (Galactic), JCAMP-DX, OPUS (Bruker), SPA and SPG (Omnic), Perkin Elmer's .sp files, and ASCII (XY and XYY).</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_EI_Vis_Electronic_and_Vibrational_Spectroscopies_supported_file_formats_bb6afc3eab.webp" alt="Mestrelab Research: Mnova EIVis - Electronic and Vibrational Spectroscopies supported file formats" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Research_Mnova_EI_Vis_Electronic_and_Vibrational_Spectroscopies_supported_file_formats_bb6afc3eab.webp 245w," sizes="100vw" width="1500" height="910"></p><h5><strong>Manual &amp; automatic spectral analysis</strong></h5><p>Mnova ElViS provides both manual and automatic peak picking, offering flexibility and convenience in your spectral analysis. It also features advanced tools for the analysis of stacked or arrayed spectra, ensuring thorough data evaluation and interpretation for all your spectral needs.&nbsp;</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_EI_Vis_Manual_and_automatic_spectral_analysis_e24a19a151.webp" alt="Mestrelab Research: Mnova EIVis - Manual &amp; automatic spectral analysis" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Research_Mnova_EI_Vis_Manual_and_automatic_spectral_analysis_e24a19a151.webp 240w," sizes="100vw" width="940" height="611"></p><h5><strong>Main processing features</strong></h5><p>Mnova ElViS comes with a range of useful processing features, including Multiplicative Scatter Correction, Probabilistic Quotient Normalization, Baseline correction (both automatic IarPLS and tailored Multipoint Baseline Correction), several smoothing techniques (such as Savitzky-Golay, Nonlocal Means, Exponential), normalization and Standard Normal Variate (SNV), derivatives, and units conversion between absorbance and transmittance.<br><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Mnova_EI_Vis_Main_processing_features_bc6eb64b99.webp" alt="Mestrelab Research: Mnova EIVis - Main processing features" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Mestrelab_Research_Mnova_EI_Vis_Main_processing_features_bc6eb64b99.webp 245w," sizes="100vw" width="1074" height="581"></p>

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