A combined experimental and computational approach showed that the hydration shell of hydroxide has a four-coordinate binding.

A combined experimental and modeling study shows that electronic interactions direct how a metal-organic framework grows.

PNNL researchers combined deep operator networks with spectral methods to efficiently and accurately solve complex equations.

A new approach broadens the reach of quantum computers to previously challenging systems.

To thwart pathogens, researchers in the epidemiology field of infectious disease (ID) prediction are continuously trying to forecast when, where, and how an ID event will occur.

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

PNNL joint appointee Auroop Ganguly uses data science to study the impacts of climate change.

A new web-based tool provides easy-to-understand progress metrics and other data about groundwater cleanup sites overseen by the DOE Office of Environmental Management.

Lauren Charles joins the CABI One Health Editorial Board as an associate editor.

SEA-CROGS is one of four Mathematical Multifaceted Integrated Capability Centers selected for support by the Department of Energy.

New research makes molecular-level calculations of water faster and easier.

James Ang, John Feo, and Marco Minutoli organized a high performance computing workshop at the prestigious ISC High Performance 2022 conference.

PNNL researchers teamed up with SambaNova to enhance artificial intelligence for scientific computing.

TransMED analyzes patient data from similar diseases across multiple sources to understand COVID-19 patient outcome risk factors.

Business, industry, and government careers were a focus of the PNNL-led Mathematics Research Communities conference.

The size of the alkali metal within the material influences the crystallization pathway.

Providing a perspective on the importance of integrating experimental work with theory and simulations when designing new carbon capture solvents.

Parallel graph neural networks identify protein-ligand 3-D structural interactions to aid in protein function prediction and drug discovery.

PNNL dual appointee Nathan Kutz is one of 26 mathematicians and computer scientists to be selected this year.

PNNL experts perform fundamental climate science work at multiple scales to understand impacts on energy, water, food, and infrastructure systems.