John A. Reffner has been named the recipient of the 2015 Gold Medal Award from the New York section of the Society for Applied Spectroscopy. The award was presented to him at the 2015 Eastern Analytical Symposium in Somerset, New Jersey, on November 16.
John A. Reffner has been named the recipient of the 2015 Gold Medal Award from the New York section of the Society for Applied Spectroscopy. The award was presented to him at the 2015 Eastern Analytical Symposium in Somerset, New Jersey, on November 16.
Reffner is currently a professor of forensic science at John Jay College in New York, New York, which is part of the City University of New York (CUNY) system. His scientific interests are focused on uniting microscopy with spectroscopy and applying novel technologies to advancing materials and forensic science.
Jay pioneered the development of infrared microspectrometers, accessories, and innovative applications infrared microprobe technology. Reffner’s scientific accomplishments are recognized by his receiving numerous awards, including the American Academy of Forensic Sciences’ Paul L. Kirk Award (2004), the New York Microscopical Society’s Abbe Memorial Award (2002), the Georgia Microscopical Society’s Honorary Achievement Award (2002), the Coblentz Society’s Williams-Wright Award (2000), and the Illinois State Microscopical Society’s Emile M. Chamot Award (1993). In 2011, Dr. Reffner was named a Fellow of the Society of Applied Spectroscopy.
Reffner has authored more than 80 papers and four book chapters, and holds 10 patents. He served as a consultant to the Connecticut State Police for over 25 years, and testified as an expert witness in criminal, civil, and patent litigations.
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March 11th 2025A research team from Jiangsu University has developed a Raman spectroscopy-based method to detect aflatoxin B1 (AFB1) in peanuts with improved accuracy and efficiency. By employing a two-step hybrid strategy integrating backward interval partial least squares (BiPLS) and variable combination population analysis (VCPA), the new model significantly enhances the precision of AFB1 detection, providing a more reliable approach for food safety monitoring.
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