Short Courses
25–26 DPOLY Short Course: Case Studies in Polymer Physics from the Industrial Research World
Boston, MA
www.aps.org/meetings/march/events/workshops/dpoly.cfm
12 Introduction to Inductively Coupled Plasma Atomic Emission Spectrometry
Orlando, FL
12 Side Illuminated Optical Fiber Sensor with a High Density of Sensing Points
Orlando, FL
13 Fundamentals of Particle Size Analysis with an Emphasis on Light Scattering Techniques
Orlando, FL
14–15 Basic Theory, Instrumentation and Applications of Vibrational Spectroscopy (Raman, Mid-Infrared, and Near-Infrared) in Materials Science)
Orlando, FL
24–25 Analysis and Interpretation of Mass Spectral Data
San Diego, CA
24–25 Spectroscopic Method Development: Qualitative & Quantitative Techniques
San Diego, CA
26 High-Throughput Method Development for Drug Analysis by LC–MS
San Diego, CA
26–27 Infrared Spectral Interpretation: A Systematic Approach
San Diego, CA
27 Introduction to GLP Regulations and Bioanalytical Method Validation by LC–MS-MS
San Diego, CA
27–28 NMR Spectral Interpretation and Organic Spectroscopy: A Problem-Based Learning Approach
San Diego, CA
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Rapid Sweetener Detection Achieved Through Raman Spectroscopy and Machine Learning
July 10th 2025Researchers at Heilongjiang University have developed a rapid and accurate method for detecting sweeteners in food using Raman spectroscopy combined with a Random Forest machine learning algorithm, offering a powerful tool for improving food safety.
PNNL and BaySpec Launch Compact Mass Spectrometry System for Rapid Narcotics Detection
July 8th 2025The U.S. Department of Energy’s Pacific Northwest National Laboratory’s (PNNL) VaporID, which is a newly developed portable air sampling system incorporating a miniaturized mass spectrometer (MS), can detect trace levels of fentanyl, methamphetamine, cocaine, and even explosives like TNT with great accuracy.
How Spectroscopy Drones Are Detecting Hidden Crop Threats in China’s Soybean Fields
July 8th 2025Researchers in Northeast China have demonstrated a new approach using drone-mounted multispectral imaging to monitor and predict soybean bacterial blight disease, offering a promising tool for early detection and yield protection.