Advion (Ithica, New York) announced a new award for undergraduate students, masters and PhD candidates, and post-doctoral research associates who demonstrate scientific excellence within the field of mass spectrometry.
Advion (Ithica, New York) announced a new award for undergraduate students, masters and PhD candidates, and post-doctoral research associates who demonstrate scientific excellence within the field of mass spectrometry. The award was named after Advion’s scientific co-founder, Jack Henion, professor emeritus, Cornell University, to honor his passion for the field, his strong ties with academia, and support of research excellence.
Henion commented, “I have always endeavored to attract, support and motivate the brightest and most innovative scientists to carry out applied analytical research in search of truly useful new technologies that can make a difference in the future. The purpose of this award is to motivate today’s scientists to strive for the discovery and development of the next new mass spectrometry-based analytical technology which may become as widely applicable as ion spray LC-MS became once it evolved from my Cornell laboratory. We at Advion strongly encourage and support innovation and the search for excellence in analytical technologies. We have conceived this award to honor and recognize those who truly excel in such endeavors.”
Full terms and conditions, along with the application will be posted on Advion’s website.
Best of the Week: SciX Award Interviews, Tip-Enhanced Raman Scattering
June 13th 2025Top articles published this week include an interview about aromatic–metal interactions, a tutorial article about the recent advancements in tip-enhanced Raman spectroscopy (TERS), and a news article about using shortwave and near-infrared (SWIR/NIR) spectral imaging in cultural heritage applications.
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.