Under Secretary for Science and Innovation at the Department of Energy Geri Richmond visited PNNL.

Irradiated boehmite nanoplatelets form smaller aggregates and have a rougher surface than non-irradiated platelets.

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

Led by PNNL, the new Cathode-Electrolyte Interphase Consortium has been launched, involving 10 national laboratories and 10 universities.

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.

Vrabie co-organized the 2022 Workshop on Artificial Intelligence for Isotope R&D and Production for the Department of Energy Isotope Program.

Variations in burn severity are a key control on the chemical constituents of dissolved organic matter delivered to streams within a single burn perimeter.

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

PNNL’s Sameera Horawalavithana joins the journals IEEE Transactions on Artificial Intelligence and Humanities and Social Sciences Communications.

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

A new nano-optical bioimaging technology in development at PNNL enables researchers to watch climate-bellwether microbes exchange metabolites and other essential signals.

Xantheas was one of four professors in 2021/2022 to be selected by the Göttingen Academy of Sciences and Humanities for this award.

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

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

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

Combining peptoids and carbon nanotube porins creates a new class of stable membranes with potential applications in separations science.

Machine learning models help identify important environmental properties that influence how often extreme rain events occur with critical intensity and duration.

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.