PNNL scientists have developed a catalyst that converts ethanol into C5+ ketones that can serve as the building blocks for everything from solvents to jet fuel.

PNNL’s new Smart Power Grid Simulator, or Smart-PGSim, combines high-performance computing and artificial intelligence to optimize power grid simulations without sacrificing accuracy.

The MIT-sponsored competition encourages community approaches to developing new solutions for analyzing graphs and sparse data; PNNL has placed a winner in each year.

PNNL researchers are contributing expertise and hydrothermal liquefaction technology to a project that intercepts harmful algal blooms from water, treats the water, and concentrates algae for transformation to biocrude.

A perspective article in the Journal of the American Chemical Society by a team of PNNL researchers shows the way forward to understand ammonia oxidation.

James A. Ang, a PNNL computing expert, was recently invited to moderate a panel in a virtual workshop focused on federally funded research and development on software for heterogeneous computing.

Infusing data science and artificial intelligence into electron microscopy could advance energy storage, quantum information science, and materials design.

NIH awarded $1.7 million to researchers from PNNL, WSU, and NREL to continue fundamental research into catalytic bias—a phenomenon in the protein environment that shifts the direction and speed of an enzyme’s catalytic reaction.

Today’s critical infrastructure systems are increasingly vulnerable to attacks that could cripple civil society, according to cybersecurity experts.

PNNL and the Georgia Institute of Technology vow to collaborate more impactfully and more often in a new MOU announced October 23, 2020.

Tracking down nefarious users is just one example of work at PNNL’s Center for Advanced Technology Evaluation, a computing proving ground supported by DOE’s Advanced Scientific Computing Research program.

PNNL has three small-scale spectroscopy devices that are speeding up the testing and analysis of candidate novel materials used in energy storage research and environmental remediation.

Pacific Northwest National Laboratory researchers used machine learning to explore the largest water clusters database, identifying—with the most accurate neural network—important information about this life-essential molecule.

Computational scientist Bo Peng attended the 2020 Heidelberg Laureate Forum in recognition of his status as an emerging leader in computational chemistry.

PNNL-University of California, Berkeley scientist cited for ‘tireless dedication to the stewardship of catalysis.’

Sharon Hammes-Schiffer, deputy director of the Center for Molecular Electrocatalysis (CME), has received awards from both the Royal Society of Chemistry and the American Chemical Society.

PNNL researchers used machine learning to develop a tool for a nonprofit to identify orthopedic implants in X-ray images to improve surgical speed and accuracy.

Pacific Northwest National Laboratory (PNNL) researchers pioneer a new tool to represent cellular response to viral infection.

The American Society for Quality (ASQ) has recognized Laboratory Fellow and Pacific Northwest National Laboratory (PNNL) Statistician Greg Piepel with the William G. Hunter Award.

PNNL team has developed and implemented a generalizable computational framework to study the resilience of the multilayered London Rail Network to the compound threat of intense flooding and a targeted cyberattack.