The first direct molecular-scale evidence of the temperature-driven transformation of the coordination environment of ytterbium at geologically relevant conditions.

Three research teams led by PNNL organizers achieve journal publications following the Mathematics Research Communities program.

PNNL showcased its expertise in AI, machine learning, and related domains at the International Conference on Machine Learning.

PNNL researchers continue to deliver high-quality, high-impact research on radioactive waste and nuclear materials management, earning “Papers of Note” and “Superior Paper” awards.

PNNL researchers showcased subsurface sampling and remediation expertise at the 2025 Federal Remediation Technologies Roundtable.

Expanding the nation’s largest wind power plant time series database; helping grid planners navigate a resilient energy future with better data.

Brown University professor and PNNL joint appointee was honored for his exceptional work in applied mathematics.

PNNL researchers have published their paper, “Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data,” in the Journal of Proteome Research.

The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.

Jeff Burghardt is the chair of the technical program for the 59th US Rock Mechanics/Geomechanics Symposium of the American Rock Mechanics Association.

Formal mathematics both reveals what’s inside the black box of AI algorithms and pushes the boundary of what’s possible within math as a discipline.

Researchers can now quantify uncertainty in trained AI models aimed at solving difficult chemistry, biology and materials science problems.

Researchers have created an algorithm that slashes the calculations necessary to prepare and customize data for quantum computing.

Scientists are exploring how web search engine technology might also keep the lights on, the water running and the trains moving.

RemPlex and IAEA convene international leaders to tackle recruitment and retention in complex environmental cleanup efforts.

Led by interns from multiple DOE programs, a newly expanded dataset allows researchers to use easy-to-obtain measurements to determine the elemental composition of a promising carbon storage mineral.

Federal environmental permitting process to be fast-tracked with AI-powered tools and cloud-supported data analysis.

A new database allows researchers to connect lattice parameters and composition in olivine.

New methodology can evaluate the potential for carbon storage and critical mineral recovery in undercharacterized geological settings.

Calculating quantum chemistry quickly allows scientists to refine their understanding of complex chemical systems.