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.
In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.
Research at PNNL and the University of Texas at El Paso are addressing computational challenges of thinking beyond the list and developing bioagent-agnostic signatures to assess threats.
Spatial proteomics enables researchers to link protein measurements to features in the image of a tissue sample, which are lost using standard approaches.
A combined experimental and theoretical study identified multiple interactions that affect the performance of redox-active metal oxides for potential electrochemical separation and quantum computing applications.
Microbes that were previously frozen in soils are becoming more active. This study demonstrates the diverse RNA viral communities found in thawed permafrost.
PNNL researchers developed a hybrid quantum-classical approach for coupled-cluster Green’s function theory that maintains accuracy while cutting computational costs.
