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

PNNL welcomes six Department of Energy Office of Science Graduate Student Research awardees from across the nation.

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.

Department of Energy Office of Electricity Assistant Secretary Gene Rodrigues makes his first visit to PNNL.

A new policy database containing energy equity-related actions could serve as a useful starting point for state policymakers and stakeholders who want to enact similar energy equity measures or adapt policies to their local circumstances.

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.

Cesar Moriel from University of Texas at El Paso will be interning at the PNNL over the summer as part of the Energy Environment Diversity Internship Program.

PNNL researchers design liquid-based porous electrolyte that could transport lithium ions more easily between electrodes, improving battery efficiency.

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 Model Selection Platform compares more than 60 energy storage modeling, valuation, and simulation tools developed by DOE’s national laboratories.

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.

Harnessing the sea for decarbonized energy is the focus of a new collaboration between PNNL and the University of Guam.

PNNL researchers are moving energy research forward through collaborative projects with universities across the United States.

Tailoring hydrogen-based energy storage solutions to specific real-world applications.

PNNL gathered researchers from eight national laboratories plus the U.S. Department of Energy (DOE) to share ideas and build synergy at the Energy Equity and Environmental Justice Summit.