Research at PNNL and the University of Texas at El Paso are addressing computational challenges of thinking beyond the list and developing bioagent-agnostic signatures to assess threats.
Data scientist at PNNL receives the Environmental and Engineering Geophysical Society and Geonics Limited Early Career Award for work with geophysical modeling and subsurface inversion codes.
PNNL computing experts Robert Rallo and Court Corley contribute their knowledge to a recent DOE report on applications of AI to energy, materials, and the power grid.
A breakthrough in electron microscopy based on deep learning can automatically visualize and identify areas of interest, helping to speed advances in materials science.
Tennessee State University received Department of Energy funding to establish an academy focused on preparing students and professionals to work in an emerging field: clean energy systems. PNNL is helping with that effort and others.
PNNL advisors joined a panel of Washington State emergency management personnel to discuss how partnerships with national laboratories are enabling science and technology solutions.
PNNL recently partnered with Amazon Web Services for AWS GameDay, a gamified learning event that challenges participants to use AWS solutions to solve real-world technical problems in a team-based setting.
Researchers at PNNL devised a new workflow for integrating life cycle analysis into building design, aided by a computational method that adapts existing software to net-zero energy, carbon-negative homes.
GUV can reduce transmission of airborne disease while reducing energy use and carbon emissions. But fulfilling that promise depends on having accurate and verifiable performance data.
The next-generation ShAPE machine has arrived at PNNL, where it will help prove the mettle of the ShAPE extrusion technique. ShAPE 2 is designed to allow researchers to produce larger, more complex extrusions.
Researchers from PNNL have been assessing installation and use of electric heat pumps in an Alaskan community that relies on fuel oil for heat. The resulting information could advance electrification in cold rural areas across the nation.
Students participating in the Public Infrastructure Security Cyber Education System program at the University of Montana recently discovered and appropriately escalated an anomaly that turned out to be a concern.
Steven Spurgeon, materials scientist supporting the National Security Directorate at PNNL, was recently named lead machine learning editor for the journal Microscopy and Microanalysis.
