Research in the Energy Sciences Center explores how heat changes in chemical reactions, paving the way for more efficient fuels and processes.

Purvine shares how research-collaboration workshops focused for women in data science create a sense of inclusion, empowerment, and networking.

Highly precise and controllable single-atom catalysts are affected by reaction conditions, which can alter the bonding around the atoms and the activity.

Chemical Engineer Yong Wang explains the influence and opportunity for joint appointments. Wang maintains one of the longest joint appointment tenures at PNNL.

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

PNNL scientists investigate the promising properties of a common, Earth-abundant salt.

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.

To overcome high-performance computing bottlenecks, a research team at PNNL proposed using graph theory, a mathematical field that explores relationships and connections between a number, or cluster, of points in a space.

Researchers have knitted together three large databases of information to help cybersecurity experts detect and prevent attacks.

Water affects the intermediates present on the surface of a metal oxide catalyst during ketonization.

Brian Milbrath, a physicist at Pacific Northwest National Laboratory (PNNL), was selected as a new Task Leader for the PrepCom’s Working Group B.

Research.com ranked PNNL joint appointee George Karniadakis as one of the top mathematicians in the world.

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

PNNL-developed catalytic process and catalyst to upgrade ethanol to sustainable aviation fuel wins American Chemical Society award.

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.

Artificial intelligence may help humans and computers work together to monitor materials that could be used to make weapons.

Newly developed models can help rapidly optimize systems to meet the need for rapidly deployable commercial carbon capture.

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