Concentrating on Chromatography

Episode 68: Peak Fitting, Deconvolution & AI in Chromatography

59 min · 6. heinä 2026
jakson Episode 68: Peak Fitting, Deconvolution & AI in Chromatography kansikuva

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Chromatography software hasn't fundamentally changed in decades — but the peaks it's trying to measure have gotten a lot harder to solve. In this episode of  @ChromatographyTalk  [https://studio.youtube.com/channel/UCU9oYSK_peqfuCrwpnv4fqA] I sit down with Ron Brown, creator of PeakFit and PeakLab, and returning guest Dr. M. Farooq Wahab, analytical chemist and research engineering scientist at the University of Texas at Arlington, to dig into the real science (and art) of peak modeling.We cover why baseline subtraction and denoising matter before you ever touch a peak model, the difference between true mathematical deconvolution and the "deconvolution" most chromatographers mean when they say it, and why mass balance is the line between a valid peak model and bad science. Ron walks through the historical roots of peak modeling going back over a century, and explains how his HVL and generalized moment models build on pioneers whose work rarely gets the recognition it deserves.We also get into resolving completely co-eluting peaks using 3D PDA/DAD data, multivariate curve resolution, and derivative-based zero-crossing methods — techniques that go well beyond what a single chromatographic dimension can tell you. And we close with a candid conversation about generative AI's growing role in analytical chemistry: where it genuinely accelerates good science, where it's eroding foundational skills in newer chemists, and why Farooq argues AI is only as useful as the prepared mind using it.In this episode:- What peak modeling actually solves that chromatography alone can't- Why baseline correction and denoising come before any modeling step- The historical origins of peak fitting, from Carl Clarison to Van der Linden- True deconvolution vs. what the field commonly (and incorrectly) calls deconvolution- Why mass balance is non-negotiable in a valid peak model- Using the F-statistic and information criteria to choose the right model complexity- Resolving fully co-eluting peaks with 3D spectral data and MCR-ALS- Generative AI's expanding role in chromatographic data processing — and its risks for early-career scientistsAbout our guests:Ronald E. Brown is a chemical engineer trained at Purdue University with 36 years of experience developing chromatography and spectroscopy peak modeling software. He is the sole developer of PeakFit and PeakLab, used by spectroscopists, chromatographers, and defense researchers worldwide. His paper on detecting outliers in nonlinear regression using the false discovery rate has been cited more than 1,950 times.Dr. M. Farooq Wahab is an analytical chemist and research engineering scientist at the University of Texas at Arlington. He earned his PhD from the University of Alberta and focuses his research on data processing, non-linear denoising, deconvolution, and generative AI applications in analytical chemistry.🎧 Listen to more episodes of Concentrating on Chromatography: https://open.spotify.com/show/1wZg67rCjoGju4yhqxI3tL?si=n9GLz9zjSCOrVfXPxFPhng🔗 Learn more about Organomation's nitrogen blowdown evaporators and sample prep instruments: https://www.organomation.com/#Chromatography #PeakFitting #AnalyticalChemistry #MassSpectrometry #Deconvolution #ChemometricsAI #HPLC #LabScience

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jakson Episode 68: Peak Fitting, Deconvolution & AI in Chromatography kansikuva

Episode 68: Peak Fitting, Deconvolution & AI in Chromatography

Chromatography software hasn't fundamentally changed in decades — but the peaks it's trying to measure have gotten a lot harder to solve. In this episode of  @ChromatographyTalk  [https://studio.youtube.com/channel/UCU9oYSK_peqfuCrwpnv4fqA] I sit down with Ron Brown, creator of PeakFit and PeakLab, and returning guest Dr. M. Farooq Wahab, analytical chemist and research engineering scientist at the University of Texas at Arlington, to dig into the real science (and art) of peak modeling.We cover why baseline subtraction and denoising matter before you ever touch a peak model, the difference between true mathematical deconvolution and the "deconvolution" most chromatographers mean when they say it, and why mass balance is the line between a valid peak model and bad science. Ron walks through the historical roots of peak modeling going back over a century, and explains how his HVL and generalized moment models build on pioneers whose work rarely gets the recognition it deserves.We also get into resolving completely co-eluting peaks using 3D PDA/DAD data, multivariate curve resolution, and derivative-based zero-crossing methods — techniques that go well beyond what a single chromatographic dimension can tell you. And we close with a candid conversation about generative AI's growing role in analytical chemistry: where it genuinely accelerates good science, where it's eroding foundational skills in newer chemists, and why Farooq argues AI is only as useful as the prepared mind using it.In this episode:- What peak modeling actually solves that chromatography alone can't- Why baseline correction and denoising come before any modeling step- The historical origins of peak fitting, from Carl Clarison to Van der Linden- True deconvolution vs. what the field commonly (and incorrectly) calls deconvolution- Why mass balance is non-negotiable in a valid peak model- Using the F-statistic and information criteria to choose the right model complexity- Resolving fully co-eluting peaks with 3D spectral data and MCR-ALS- Generative AI's expanding role in chromatographic data processing — and its risks for early-career scientistsAbout our guests:Ronald E. Brown is a chemical engineer trained at Purdue University with 36 years of experience developing chromatography and spectroscopy peak modeling software. He is the sole developer of PeakFit and PeakLab, used by spectroscopists, chromatographers, and defense researchers worldwide. His paper on detecting outliers in nonlinear regression using the false discovery rate has been cited more than 1,950 times.Dr. M. Farooq Wahab is an analytical chemist and research engineering scientist at the University of Texas at Arlington. He earned his PhD from the University of Alberta and focuses his research on data processing, non-linear denoising, deconvolution, and generative AI applications in analytical chemistry.🎧 Listen to more episodes of Concentrating on Chromatography: https://open.spotify.com/show/1wZg67rCjoGju4yhqxI3tL?si=n9GLz9zjSCOrVfXPxFPhng🔗 Learn more about Organomation's nitrogen blowdown evaporators and sample prep instruments: https://www.organomation.com/#Chromatography #PeakFitting #AnalyticalChemistry #MassSpectrometry #Deconvolution #ChemometricsAI #HPLC #LabScience

6. heinä 202659 min
jakson Episode 67: Is Your Lab Sitting on a Data Goldmine? AI, Deep Learning, & Mass Spectrometry with mzio kansikuva

Episode 67: Is Your Lab Sitting on a Data Goldmine? AI, Deep Learning, & Mass Spectrometry with mzio

Welcome back to another episode of Concentrating on Chromatography! In this episode of  @ChromatographyTalk  [https://studio.youtube.com/channel/UCU9oYSK_peqfuCrwpnv4fqA] host David Oliva sits down with Dr. Ansgar Korf, CEO and Co-Founder of mzio GmbH, to explore how their vendor-agnostic platform is fundamentally changing how researchers and industrial users extract value from complex mass spectrometry data.Historically rooted in the open-source academic community as mzmine, Bremen-based mzio has evolved into a powerhouse for multimodal data analysis—spanning LC-MS, GC-MS, ion mobility MS, and MS-imaging. Ansgar pulls back the curtain on how laboratories can break free from proprietary vendor software stacks to streamline workflows across mixed-instrument fleets.We dive deep into their massive announcements from ASMS 2026, including FAIR-MS—an AI-powered initiative utilizing deep learning embeddings to automatically search and match new measurements against archived, historical data sets. We also break down the LIMMIC calibration project, their new small molecule and lipidomics dashboards, and how AI agents will shape the next 5 years of automated, real-time MS data acquisition.Whether you are an industry veteran or an early-career chemist, this episode is packed with insights on avoiding the "black box" of automated analysis while unleashing the true power of your lab's data.Mass Spectrometry, Chromatography, mzio, mzmine, FAIR-MS, LIMMIC, Lipidomics, Metabolomics, Open-Source Science, Analytical Chemistry, AI in Chemistry, Deep Learning, LC-MS, GC-MS, PFAS Analysis, Vendor-Agnostic Software, ASMS 2026

29. kesä 202635 min
jakson Episode 66: Why Sustainable Labs Save Money: James Connelly, CEO of My Green Lab kansikuva

Episode 66: Why Sustainable Labs Save Money: James Connelly, CEO of My Green Lab

Can sustainability actually make laboratories more efficient—and more profitable?In this episode of Concentrating on Chromatography,  @Organomation  [https://studio.youtube.com/channel/UC_VaXQ_xrx4881G8Fo4dxDg] General Manager David Oliva sits down with James Connelly, CEO of My Green Lab, to discuss how a grassroots movement founded by scientists evolved into the leading global organization for laboratory sustainability.James explains why sustainability is no longer just a "nice-to-have" initiative, how major pharmaceutical companies and funding organizations are driving change, and why laboratory suppliers and instrument manufacturers are becoming increasingly important in helping scientists achieve their environmental goals.Topics include:🔬 How My Green Lab grew from an academic movement into a global standard💰 Why sustainable laboratories often deliver significant financial ROI🏭 The changing role of laboratory equipment manufacturers and suppliers📊 What Scope 1, Scope 2, and Scope 3 emissions actually mean♻️ The ACT Eco Label and sustainable product design⚡ Renewable energy, recycled materials, and resilient supply chains🤖 AI-powered predictive maintenance and smart laboratory technologies🗑️ Emerging innovations in laboratory waste management🌎 Why sustainability is becoming a business imperative across life sciences🎓 The My Green Lab Ambassador and Accredited Professional programsWhether you're an analytical chemist, laboratory manager, instrument manufacturer, or simply interested in the future of scientific research, this episode provides practical insights into how sustainability is transforming laboratories around the world. Subscribe to  @ChromatographyTalk  [https://studio.youtube.com/channel/UCU9oYSK_peqfuCrwpnv4fqA] for more conversations with leaders in chromatography, mass spectrometry, sample preparation, and analytical science.#Sustainability #GreenLab #MyGreenLab #LaboratoryScience #Chromatography #MassSpectrometry #AnalyticalChemistry #LifeSciences #ESG #SciencePodcast

22. kesä 202633 min
jakson Episode 65: Why Scientists Need to Tell Their Story | Funding, Visibility & Industry Impact kansikuva

Episode 65: Why Scientists Need to Tell Their Story | Funding, Visibility & Industry Impact

Why should analytical chemists, chromatographers, and researchers care about science communication? Is publishing papers enough? How can scientists increase their visibility without spending hours on social media?In this episode of  @ChromatographyTalk  [https://studio.youtube.com/channel/UCU9oYSK_peqfuCrwpnv4fqA] , David is joined by Lisa Jones and Johnnie Aycock, co-hosts of  @TheNoonShow100.1  [https://studio.youtube.com/channel/UC0Eem9w82ZhQowMauATSakg] and creators of the upcoming BrightPath program on Alabama Public Radio. Together, they explore why communicating science matters—not just for public understanding, but for research funding, industry partnerships, talent development, and the future of innovation itself.From translating complex ideas with simple analogies to building relationships beyond the laboratory, this conversation offers practical advice for scientists who want their work to have a greater impact.In this episode:🔬 Why scientists need to tell their story beyond journal publications🎙️ How researchers can communicate complex science to non-scientists💡 Why visibility matters for funding, collaboration, and career opportunities🏭 Bridging the gap between academia and industry🤝 The importance of partnerships and advocacy for research📢 Practical first steps for chemists who want to promote their work🧪 Why conferences alone aren't enough to reach broader audiences🎓 How science communication can inspire the next generation of scientists🌎 The role of research in economic development and global competitiveness🎧 The vision behind BrightPath and bringing science stories to the publicMemorable topics discussed:Explaining chromatography through the analogy of making coffeeWhy researchers should "lead with why it matters"Lessons learned from interviewing scientists across AlabamaThe connection between research, workforce development, and economic growthHow communication can influence public support for scienceWhy showing up and building relationships often matters more than perfectionFeatured GuestsLisa JonesFormer University of Alabama Department of Chemistry & Biochemistry staff member (27 years)Co-host of The Noon ShowScience communication advocate and STEM enthusiastJohnnie AycockFormer President & CEO of the West Alabama Chamber of CommerceEconomic development leaderCo-host of The Noon Show🎙️ Concentrating on Chromatography explores chromatography, mass spectrometry, sample preparation, and the people advancing analytical science.If you enjoy conversations about analytical chemistry, LC-MS, GC-MS, sample preparation, and scientific careers, subscribe for future episodes featuring researchers, industry leaders, and innovators from around the world.#Chromatography #AnalyticalChemistry #MassSpectrometry #ScienceCommunication #STEM #Research #LCMS #GCMS #Chemistry #SciencePodcast #Scientists #AcademicResearch #Innovation #Spectroscopy #CareersInScience #ConcentratingOnChromatography

15. kesä 202653 min
jakson Episode 64: The Chemistry of Human Decomposition: GC×GC, Body Farms, and Forensic Science kansikuva

Episode 64: The Chemistry of Human Decomposition: GC×GC, Body Farms, and Forensic Science

In this episode of  @ChromatographyTalk  [https://studio.youtube.com/channel/UCU9oYSK_peqfuCrwpnv4fqA] David sits down with Dr. Darshil Patel, Assistant Professor of Forensic Science at the University of North Dakota, to discuss his remarkable journey from dentistry in India to becoming a leading researcher in forensic chemistry across Australia, Canada, and the United States.Dr. Patel shares how his work at human taphonomic facilities—commonly known as "body farms"—has helped advance our understanding of human decomposition and the volatile compounds released during the postmortem process. Using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS), his research aims to improve human remains detection, cadaver dog training, and the development of future electronic sensing technologies.Topics discussed include:🔬 How a dentist became a forensic scientist🌏 Working in Australia, Canada, and the United States⚰️ What human taphonomic facilities ("body farms") really do🧪 The chemistry of human decomposition📈 Why GC×GC-TOFMS excels at analyzing complex VOC mixtures🐕 How chromatography can improve cadaver dog training🤖 The future of electronic noses and human remains detection🏔️ Challenges posed by geography and environmental conditions🏫 Building a new forensic chemistry laboratory at the University of North Dakota🔍 The future of forensic chromatographyWhether you're interested in forensic science, chromatography, mass spectrometry, or the chemistry behind real-world investigations, this episode offers a fascinating look into one of the most unique applications of analytical chemistry.#ForensicScience #GCxGC #MassSpectrometry #Chromatography #Forensics #GCMS #TOFMS #AnalyticalChemistry #HumanDecomposition #VOCs #UniversityOfNorthDakota #CadaverDogs #BodyFarm #SeparationScience

9. kesä 202635 min