At a conference featuring the most advanced computing hardware and software, ML in its various guises was on full display and highlighted by Nathan Baker’s featured invited presentation.
Global climate change is often at the forefront of national and international discussions and controversies, yet many details of the specific contributing factors are poorly understood.
In the third year of the DISCOVR Consortium project, the consortium team has identified an algal strain that progressed successfully through multiple evaluation phases.
Scientists at PNNL are bringing artificial intelligence into the quest to see whether computers can help humans sift through a sea of experimental data.
A new Co-Optima report describes an assessment of 400 biofuel-derived samples and identifies the top ten candidates for blending with petroleum fuel to improve boosted spark ignition engine efficiency.
More than 350 people from scientific institutions, education and the private sector gathered at the PNNL campus July 30 for the IEEE Women in Engineering International Leadership Summit.
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.
Network Collapse, a virtual reality science, technology, engineering, and mathematics (STEM) app developed by PNNL researchers, has won a Gold Award from the 2019 International Serious Play Award.
PNNL scientists have taken one of the most in-depth looks ever at the riot of protein activity that underlies colon cancer and have identified potential new molecular targets to try to stop the disease.
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.
PNNL leads a consortium to help find the best algae strains for biofuels and bioproducts to reduce the cost of producing bioenergy from algae feedstocks.
Researchers at PNNL are developing a new class of acoustically active nanomaterials designed to improve the high-resolution tracking of exploratory fluids injected into the subsurface. These could improve subsurface geophysical monitoring.
"It's sort of like using infrared goggles to see heat signatures in the dark, except this is underground." PNNL and CHPRC implemented a state-of-the-art approach to monitor the process of remediating residual uranium at Hanford's 300 Area.
