Writing in the journal Nature Chemistry, PNNL materials scientists Jim De Yoreo and Benjamin Legg provides context to new work showing how single atoms organize into clusters that seed crystal growth
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.
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.
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.
First-ever measurements provide evidence that supercooled water exists in two distinct structures that co-exist and vary in proportion dependent on temperature.
In a new review, PNNL researchers outline how to convert stranded biomass to sustainable fuel using electrochemical reduction reactions in mini-refineries powered by renewable energy.
The PNNL-developed VOLTTRON™ software platform’s advancement has benefited from a community-driven approach. The technology has been used in buildings nationwide, including most recently on a university campus.
Making sure there’s enough electricity at the lowest price is a critical endeavor undertaken daily by electricity market operators. Now, there’s an approach that provides more timely and accurate information to make day-ahead decisions.
PNNL scientists have created a tool called WatchOwl to collect more than 4 million tweets per day related to the COVID-19 pandemic. The tool analyzes tweets related to interventions like social distancing and movement restrictions.
