Spectroscopy Staff

Articles by Spectroscopy Staff

Gold abstract bokeh background. real backlit dust particles with real lens flare. | Image Credit: © MrsChonthicha - stock.adobe.com

At the Winter Conference on Plasma Spectrochemistry, Alexander Gundlach-Graham of Iowa State University delivered a talk on how size distributions and measurement statistics impact single-particle inductively coupled plasma time of flight mass spectrometry (ICP-TOFMS).

DNA strand and Cancer Cell Oncology Research Concept 3D rendering | Image Credit: © catalin - stock.adobe.com

A recent study from Spain used surface-enhanced Raman spectroscopy (SERS) to study cancer cells with methylthioadenosine phosphorylase (MTAP) deletions, shedding new insights into the metabolic interactions inside the tumor microenvironment that could influence cancer aggression.

A one-inch-diameter silicon substrate coated with a conventionally deposited interference coating.| Image Credit: © Valentin Wittwer – Institut de Physique, Université de Neuchâtel, Switzerland.

Researchers from Thorlabs Crystalline Solutions, the University of Vienna, and the National Institute of Standards and Technology have achieved a revolutionary breakthrough, publishing in Nature Communications, with mid-infrared supermirrors exhibiting finesse exceeding 400,000, promising unprecedented sensitivity for applications in trace gas sensing and precision spectroscopy.

Extreme macro of polyester stable fiber on blue background | Image Credit: © Taigi - stock.adobe.com

Researchers at Kochi University and RIKEN have unveiled a new method for distinguishing individual polyester fibers in forensic investigations. Published in Spectrochimica Acta Part B: Atomic Spectroscopy, their advanced X-ray analysis refreshes how we unravel the composition of these fibers.

Messenger RNA or mRNA strand 3D rendering illustration with copy space. Genetics, science, medical research, genome replication concepts. | Image Credit: © Matthieu - stock.adobe.com

Duke University researchers, led by Joy Q. Li, revolutionize biomedical diagnostics with a multiplexed SERS-based nanosensor called inverse molecular sentinel (iMS) for micro-RNA detection, employing machine learning, particularly convolutional neural networks (CNN) and non-negative matrix factorization (NMF), to achieve higher accuracy in spectral unmixing, paving the way for more precise and efficient clinical diagnostics.