July 2nd 2025
Researchers from Shanghai Jiao Tong University are harnessing artificial intelligence to elevate surface-enhanced Raman spectroscopy (SERS) for highly sensitive, multiplexed biomedical analysis, enabling faster diagnostics, imaging, and personalized treatments.
Combining AI and NIR Spectroscopy to Predict Resistant Starch (RS) Content in Rice
June 24th 2025A new study published in the journal Food Chemistry by lead authors Qian Zhao and Jun Huang from Zhejiang University of Science and Technology unveil a new data-driven framework for predicting resistant starch content in rice
New Spectroscopy Methods Target Counterfeit Oral Medication Syrups
June 23rd 2025Researchers at Georgia College and Purdue University have developed a fast, low-cost method using Raman and UV–visible spectroscopy combined with chemometric modeling to accurately screen and quantify active ingredients in over-the-counter oral syrups, helping to fight counterfeit medications.
Short Tutorial: Complex-Valued Chemometrics for Composition Analysis
June 16th 2025In this tutorial, Thomas G. Mayerhöfer and Jürgen Popp introduce complex-valued chemometrics as a more physically grounded alternative to traditional intensity-based spectroscopy measurement methods. By incorporating both the real and imaginary parts of the complex refractive index of a sample, this approach preserves phase information and improves linearity with sample analyte concentration. The result is more robust and interpretable multivariate models, especially in systems affected by nonlinear effects or strong solvent and analyte interactions.
Hyperspectral Imaging for Walnut Quality Assessment and Shelf-Life Classification
June 12th 2025Researchers from Hebei University and Hebei University of Engineering have developed a hyperspectral imaging method combined with data fusion and machine learning to accurately and non-destructively assess walnut quality and classify storage periods.
AI-Powered Near-Infrared Imaging Remotely Identifies Explosives
June 11th 2025Chinese researchers have developed a powerful new method using near-infrared (NIR) hyperspectral imaging combined with a convolutional neural network (CNN) to identify hazardous explosive materials, like trinitrotoluene (TNT) and ammonium nitrate, from a distance, even when concealed by clothing or packaging.
New NIR/Raman Remote Imaging Reveals Hidden Salt Damage in Historic Fort
June 10th 2025Researchers have developed an analytical method combining remote near-infrared and Raman spectroscopy with machine learning to noninvasively map moisture and salt damage in historic buildings, offering critical insight into ongoing structural deterioration.
New Machine Learning Model Distinguishes Recycled PET with 10% Accuracy Threshold
June 9th 2025Researchers from Jinan University and Guangzhou Customs Technology Center have developed a cost-effective UV-vis spectroscopy and machine learning method to accurately identify recycled PET content as low as 10%, advancing sustainable packaging and circular economy efforts.
Harnessing Near-Infrared Spectroscopy and Machine Learning to Detect Microplastics in Chicken Feed
June 5th 2025Researchers from Tianjin Agricultural University, Nankai University, and Zhejiang A&F University have developed a highly accurate method using near-infrared spectroscopy and machine learning to rapidly detect and classify microplastics in chicken feed.
AI-Powered Raman Spectroscopy Signals New Era for Drug Development and Disease Diagnosis
June 4th 2025A recent review in the Journal of Pharmaceutical Analysis highlights how AI, particularly deep learning, is revolutionizing Raman spectroscopy by enhancing its accuracy, efficiency, and applications in drug development, quality control, and clinical diagnostics.
Bruce R. Kowalski: The Maverick Mind Behind Chemometrics
June 2nd 2025In this Icons of Spectroscopy article, Executive Editor Jerome Workman Jr. delves into the life and impact of Bruce Kowalski, an analytical chemist whose major contributions to chemometrics helped establish the field of applying advanced quantitative and qualitative mathematics to extract meaningful chemical information from complex datasets. Kowalski’s visionary approach to chemical data analysis, education, and software development has transformed the landscape of modern analytical chemistry for academia and industry.
Machine Learning Accelerates Clinical Progress of SERS Technology
May 22nd 2025A new review in TrAC Trends in Analytical Chemistry by Alfred Chin Yen Tay and Liang Wang highlights how machine learning (ML) is transforming surface-enhanced Raman spectroscopy (SERS) into a powerful, clinically viable tool for rapid and accurate medical diagnostics.
New Deep Learning AI Tool Decodes Minerals with Raman Spectroscopy
May 21st 2025Researchers have developed a powerful deep learning model that automates the identification of minerals using Raman spectroscopy, offering faster, more accurate results even in complex geological samples. By integrating attention mechanisms and explainable AI tools, the system boosts trust and performance in field-based mineral analysis.
Whey Protein Fraud: How Portable NIR Spectroscopy and AI Can Combat This Issue
May 20th 2025Researchers from Tsinghua and Hainan Universities have developed a portable, non-destructive method using NIR spectroscopy, hyperspectral imaging, and machine learning to accurately assess the quality and detect adulteration in whey protein supplements.
AI and Infrared Light Team Up to Advance Soil Carbon Monitoring
May 19th 2025A team of international researchers has developed a faster, more accurate method to analyze soil carbon fractions using mid-infrared spectroscopy and deep learning. Their approach preserves the chemical balance of soil organic carbon components, paving the way for improved climate models and sustainable land management.
Analyzing the Protein Secondary Structure in Tissue Specimens
May 19th 2025In the first part of this three-part interview, Ayanjeet Ghosh of the University of Alabama and Rohit Bhargava of the University of Illinois Urbana-Champaign discuss their interest in using discrete frequency infrared (IR) imaging to analyze protein secondary structures.
Exploring Data Transforms in Chemometrics
May 14th 2025Our “Chemometrics in Spectroscopy” column highlights the methodology that is used in order to apply chemometric methods to data. Integrating chemometrics with spectroscopy allows scientists to understand solutions to their problems when they encounter surprising results. Recently, columnists Howard Mark and Jerome Workman, Jr., wrote a series of articles about data transforms in chemometric calibrations. In this listicle, we profile all pieces in this series and invite you to learn more about applying chemometric models to continuous spectral data.
Wearable fNIRS Sensor Tracks Cognitive Fatigue in Real Time
May 7th 2025Researchers have developed a wireless, wearable brain-monitoring device using functional near-infrared spectroscopy (fNIRS) to detect cognitive fatigue in real time. The miniaturized system enables mobile brain activity tracking, with potential applications in driving, military, and high-stress work environments.
Real-Time Health Monitoring Using Smart Wearable Spectroscopy Sensors With AI
May 6th 2025A newly published review in the journal Advanced Materials explores how intelligent wearable sensors, powered by smart materials and machine learning, are changing healthcare into a decentralized, personalized, and predictive modeling system. An international team of researchers highlights emerging technologies that promise earlier diagnosis, improved therapy, and continuous health monitoring—anytime, anywhere.
AI and Satellite Spectroscopy Team Up to Monitor Urban River Pollution in China
April 30th 2025A study from Chinese researchers demonstrates how combining satellite imagery, land use data, and machine learning can improve pollution monitoring in fast-changing urban rivers. The study focuses on non-optically active pollutants in the Weihe River Basin and showcases promising results for remote, data-driven water quality assessments.
How Satellite-Based Spectroscopy is Transforming Inland Water Quality Monitoring
Published: April 29th 2025 | Updated: April 29th 2025New research highlights how remote satellite sensing technologies are changing the way scientists monitor inland water quality, offering powerful tools for tracking pollutants, analyzing ecological health, and supporting environmental policies across the globe.
Introduction to Satellite and Aerial Spectral Imaging Systems
April 28th 2025Modern remote sensing technologies have evolved from coarse-resolution multispectral sensors like MODIS and MERIS to high-resolution, multi-band systems such as Sentinel-2 MSI, Landsat OLI, and UAV-mounted spectrometers. These advancements provide greater spectral and spatial detail, enabling precise monitoring of environmental, agricultural, and land-use dynamics.
Best of the Week: AI and IoT for Pollution Monitoring, High Speed Laser MS
April 25th 2025Top articles published this week include a preview of our upcoming content series for National Space Day, a news story about air quality monitoring, and an announcement from Metrohm about their new Midwest office.
LIBS Illuminates the Hidden Health Risks of Indoor Welding and Soldering
April 23rd 2025A new dual-spectroscopy approach reveals real-time pollution threats in indoor workspaces. Chinese researchers have pioneered the use of laser-induced breakdown spectroscopy (LIBS) and aerosol mass spectrometry to uncover and monitor harmful heavy metal and dust emissions from soldering and welding in real-time. These complementary tools offer a fast, accurate means to evaluate air quality threats in industrial and indoor environments—where people spend most of their time.