A new AI model developed at PNNL can identify patterns in electron microscope images of materials without requiring human intervention, allowing for more accurate and consistent materials science.
The nation is closer to its offshore wind energy goals than ever before, but better wind forecasting is still needed. To address this challenge, PNNL and collaborators are charting a new course with help from novel technology.
Identifying how curvature affects the doping and hydrogen binding energies of carbon-based materials provides a framework for designing hydrogen storage materials.
A simple gel-based system separates metals ions from a model solution of dissolved battery electrodes without the need for specialty chemicals, membranes, or toxic solvents.
The convergence of artificial intelligence, cloud, and high-performance computing to accelerate scientific discovery is the focus of a multi-year collaboration between Microsoft and PNNL.
PNNL had a significant presence at October’s North American Wind Energy Academy/WindTech 2023 Conference in Denver, Colorado. Thirteen PNNL wind experts participated in various capacities.
A newly developed, highly conductive copper wire could find applications in the electric grid, as well as in homes and businesses. The finding defies what's been thought about how metals conduct electricity.