Eric Hoppe, senior scientist, was selected a 2019 American Chemical Society (ACS) fellow. Eric is being recognized for his contributions to analytical chemistry measurements and three decades of volunteer service to the ACS community.
Researchers at PNNL have developed a model that predicts outcomes from the algae hydrothermal liquefaction process in a way that mirrors commercial reality much more closely than previous analyses.
Researchers at PNNL have introduced an alternative method using a molecular-based pump that could potentially use a quarter less energy than the age-old mechanical pump.
His research is dedicated to the development of experimental tools and expertise critical for controlled synthesis and characterization of complex oxides, and gaining deep understanding of structure-composition-function relationships.
Yong Wang, a PNNL laboratory fellow, has received the 2019 Catalysis and Reaction Engineering Practice Award from the American Institute of Chemical Engineers.
Editors of the journal Emission Control Science and Technology deemed “Coating Distribution in a Commercial SCR Filter” Best Paper in 2018. The authors include PNNL's Mark Stewart, Carl Justin Kamp, Feng Gao, Yilin Wang, and Mark Engelhard.
Patricia Huestis, a collaborator in the Interfacial Dynamics in Radioactive Environments and Materials (IDREAM) Energy Frontier Research Center, has been awarded the DOE Office of Science Graduate Student Research (SCGSR) award.
Frannie Smith, a chemist specializing in nuclear waste management and disposal, was recognized as a "Notable Woman in STEM" for 2019 by the nonprofit Washington STEM program.
PNNL’s Johannes Lercher was one of 148 researchers recognized at the annual conference of the National Academy of Inventors, held April 10-11, 2019 in Houston, Texas. Lercher recently achieved NAI fellow status, a highly selective honor.
Researchers at PNNL and their collaborators have made a significant improvement to a catalyst that is more rugged and can reduce tailpipe pollution at lower temperatures than existing methods.
Several years ago, a relatively new catalyst for vehicle emission control began showing failure. A team at PNNL found that this seemingly suicidal catalyst wasn’t actually self-destructing but was the victim of an external assailant.
Scientists created a fast-track tutorial that equips a neural network to tackle drug discovery and other applications where there's a shortage of precisely labeled chemical data.
