For 30 years, Spectroscopy has provided its readers with valuable content, advice, troubleshooting tips, and insight to many areas of materials analysis. Our mission statement says
For 30 years, Spectroscopy has provided its readers with valuable content, advice, troubleshooting tips, and insight to many areas of materials analysis. Our mission statement says
Spectroscopy's mission is to enhance productivity, efficiency, and the overall value of spectroscopic instruments and methods as a practical analytical technology across a variety of fields. Scientists, technicians, and laboratory managers gain proficiency and competitive advantage for the real-world issues they face through unbiased, peer-reviewed technical articles, trusted troubleshooting advice, and best-practice application solutions.
I believe we have lived up to that mission statement very well during the past three decades, but it would not have been possible without the invaluable work of our columnists, peer-reviewed authors, editorial advisory board, advertisers, and, of course, the editorial and sales staff at Spectroscopy-both past and present. In honor of our 30th anniversary celebration this month, I would like to say thank you to everyone that has contributed to Spectroscopy over the years. I'd also like to extend a thank you to our readers, who always push us to do better and provide the best content to meet their specific needs.
Our magazine is a staple in the spectroscopic community because of the hard work and dedication of our staff and contributors. Below you will find photos of the terrific and hard-working staff at Spectroscopy. Please feel free to say hello to us at conferences and industry events.
Thank you again to everyone who has been a part of this publication. Here's to the next 30 years!
Michael J. Tessalone
Science Group Publisher
mtessalone@advanstar.com
Michael J. Tessalone
Advancing Near-Infrared Spectroscopy and Machine Learning for Personalized Medicine
February 12th 2025Researchers have developed a novel approach to improve the accuracy of near-infrared spectroscopy (NIRS or NIR) in quantifying highly porous, patient-specific drug formulations. By combining machine learning with advanced Raman imaging, the study enhances the precision of non-destructive pharmaceutical analysis, paving the way for better personalized medicine.
New Method for Detecting Fentanyl in Human Nails Using ATR FT-IR and Machine Learning
February 11th 2025Researchers have successfully demonstrated that human nails can serve as a reliable biological matrix for detecting fentanyl use. By combining attenuated total reflectance-Fourier transform infrared (ATR FT-IR) spectroscopy with machine learning, the study achieved over 80% accuracy in distinguishing fentanyl users from non-users. These findings highlight a promising, noninvasive method for toxicological and forensic analysis.