Summer internship programs with partnering colleges provide pathways for students to explore careers in science, technology, engineering, and math.

PNNL energy storage experts express need for continued investment in developing and deploying long-duration energy storage.

PNNL researchers present challenges and opportunities for fusing graph neural networks with deep reinforcement learning.

Computational chemistry libraries from NWChem, NWChemEX, SPEC, and more are now available on Azure Quantum Elements.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

Research from PNNL and the University of Washington demonstrates the extension of the MBE for periodic systems and its use to decompose the lattice energies of different ice polymorphs.

Advances in understanding the nature of the chemical bond are featured in this special issue of The Journal of Chemical Physics.

Deep learning helps make predictions on the effects of the El Niño-Southern Oscillation on river flows more accurate.

PNNL welcomes new joint appointments to expand the research productivity and scientific impact of both PNNL and the university partners, broadening the base of expertise at each institution and helping to build interdisciplinary teams.

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

Report for the Oregon Public Utility Commission highlights innovations and best practices for resilience and utility planning could be helpful to other states as well.

The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

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.

Launching a premier partnership, PNNL and the University of Texas El Paso (UTEP) signed a memorandum of agreement on UTEP’s campus on October 6.

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.

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

New research from PNNL results in faster and more accurate variational quantum algorithm training.