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

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

PNNL chemist Christopher Anderton recently named president-elect of the Imaging Mass Spectrometry Society (IMSS). In this new position, he will help lead the merge of IMSS with a European-based society, currently underway.

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.

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.

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.

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

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

Data-driven autonomous technology to rapidly design and deliver antiviral interventions targeting SARS-CoV-2 to reduce drug discovery timeline and advance bio preparedness capabilities.

The Building and Environment journal named Drgoňa’s co-authored work one of 2022’s best papers.

Data scientist Jung Lee accepted the position of review editor for Frontiers in Computational Neuroscience after serving as a guest editor for a special issue.

Exploring why some brains are more resilient to the impact of Alzheimer’s disease could lead to improved diagnoses, treatment and prevention.

Advanced proteomic analysis tools dig deep into human blood plasma to understand the molecular nature of advanced alcoholic disease.

Scientists have taken a key step toward harnessing a form of AI known as deep reinforcement learning to protect computer networks.

A detailed snapshot of proteins by PNNL scientists marks a big step toward a diagnostic blood test for a deadly form of liver disease.

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.

Findings show method to better prepare human lung tissue for study; it represents the latest mass spectrometry-based omics advances.