PNNL’s Andrea Mengual co-chaired a working group that produced Building Performance Standards: A Technical Resource Guide. PNNL’s Kim Cheslak, Bing Liu, and Jian Zhang contributed to the effort.
Claudia Tebaldi, a PNNL Earth scientist, has been named a Fellow of the American Geophysical Union. Tebaldi and others will be recognized at AGU23 in December.
The results of this study are consistent with the idea that the stress of chronic salinity exposure changes tree leaf shape and function, weakening their physiology and setting in motion processes that lead to death.
Scientists developed a process (or pipeline) that combined molecular probes—a specific chemical that binds to microbes carrying out a particular function—with a method that isolated these cells from their complex community.
In a new paper, researchers point to three major efforts where the biggest climate mitigation gains stand to be realized: ramping up carbon dioxide removal, reigning in non-carbon dioxide emissions and halting deforestation.
Scientists screen for nanobodies that recognize wild type and mutant functional proteins to develop a framework to disrupt protein interactions that can cause disease.
Rechargeable battery performance could be improved by a new understanding of how batteries work at the molecular level. Researchers at PNNL upend what's known about how rechargeable batteries function.
High fidelity simulations enabled by high-performance computing will allow for unprecedented predictive power of molecular level processes that are not amenable to experimental measurement.
PNNL is honoring its postdoctoral researchers as part of the fourteenth annual National Postdoc Appreciation Week with seven profiles of postdocs from around the Laboratory.
A new discovery by PNNL researchers has illuminated a previously unknown key mechanism that could inform the development of new, more effective catalysts for abating NOx emissions from combustion-engines burning diesel or low carbon fuel.
The diversity and function of organic matter in rivers at a large scale are influenced by factors, such as the types of vegetation covering the land, the energy characteristics, and the breakdown potential of the molecules.
Scientists at PNNL were awarded nearly $12 million to better understand pathogens, how they spread, and how to prepare the nation against future outbreaks.
Scientists can now generate a protein database directly from proteomics data gathered from a specific soil sample using a digital tool and deep learning computer model called Kaiko.
PNNL data scientist in the Biological Sciences Division won the 2023 JSM Data Challenge Expo. The award-winning analysis focused on the ability to identify crime patterns by correlating them with historical events and trends.