Lu honored for "elucidating design principles of artificial metalloproteins to gain novel and deeper insights into the structure and function of natural systems."
The project received an Innovative and Novel Computational Impact on Theory and Experiment (INCITE) award, a highly competitive U.S. Department of Energy Office of Science program.
A new report outlines future research paths that are needed for airlines to reduce carbon emissions and notes that the only way to achieve emission reduction goals is with Sustainable Aviation Fuels.
Researchers at Pacific Northwest National Laboratory (PNNL) are closer to understanding how iron may pave the way for sequestration of technetium-99 contaminants in the subsurface.
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.
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.
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.
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.
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.