di Vacri’s expertise in low-background detection earned her a place on the Executive Board of the Coordinating Panel for Advanced Detectors.

In the search for rare physics events, extremely pure materials are essential. A partnership between PNNL and Ultramet has led to tungsten with low contamination from other elements.

Staff at PNNL recently traveled to Cyprus to facilitate a multilateral workshop on chemical forensics investigations hosted by the U.S. Department of State, Office of Weapons of Mass Destruction Terrorism.

PNNL welcomed United Kingdom researcher for a six-week hands-on research exchange to develop nuclear forensic techniques.

Capstone engineering projects deliver equipment to improve accuracy of chemistry lab elutions and enhance training to safeguard critical infrastructure.

Spatial proteomics enables researchers to link protein measurements to features in the image of a tissue sample, which are lost using standard approaches.

Researchers designed ultra-low radiation cables to reduce background noise for highly sensitive neutrino and dark matter detectors.

Scientists are studying tiny subatomic particles that pass through humans and possess clues about the origins of the universe.

PNNL’s Richard Saldanha will lead a new project to benchmark and validate models of cosmic ray exposure

PNNL is honoring its postdoctoral researchers as part of the fourteenth annual National Postdoc Appreciation Week with seven profiles of postdocs from around the Laboratory.

Glenn Fugate was selected to serve on the American Chemical Society's Science Committee.

Neutrino mass, a crucial piece of many unresolved physics puzzles, may one day be revealed through a novel measurement system that has just proven its mettle: Cyclotron Radiation Emission Spectroscopy.

New PNNL research makes it easier to differentiate between chemical and nuclear explosions.

New research findings published in Science Advances (November 2022), help explain the progression of Alzheimer-related dementia in each patient. The findings outline a biological classification system that predicts disease severity.

PNNL researchers use machine learning and data analytics to assist with detection of nuclear proliferation and nuclear material trafficking.

PNNL research, featured on the cover of two science journals, describes advancements in using Raman spectrometry for Hanford Site nuclear waste remediation.

PNNL chemist Ying Zhu was honored as one of the top 40 researchers under the age of 40 in analytical science by The Analytical Scientist.

PNNL experts in nuclear forensics helped lead laboratories around the world through a rigorous test involving nuclear materials.

IDREAM researchers assess the potential of photon-in/photon-out XFEL techniques to explore early time reaction steps and ultimately improve nuclear waste processing strategies.

The nested nanoPOTS chip is the next generation of technology developed at PNNL to prepare single cells for proteomics.