Research identifies the mechanisms through which peptoids affect ions in solution and a mineral surface, increasing the rate of carbonate crystal growth.
PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.
Sergei Kalinin honored with the David Adler Lectureship Award for contributions to materials physics through automated experimentation and ferroelectric materials work.
A switchable single-atom catalyst is activated in the presence of surface intermediates and reverts to its stable inactive form when the reaction is completed.
Ultra-thin layers of silk deposited on graphene in perfect alignment represent a key advance for the control needed in microelectronics and advanced neural network development.
PNNL researchers earned five Papers of Note, 17 Superior Papers, and one poster award for their environmental remediation, radioactive waste, and nuclear energy-related presentations.
New funding spurs a new approach to researching the effective retrieval and processing of legacy radioactive waste. Four-year focus of the IDREAM EFRC will link attosecond timescales to decades-long chemical processes.