Six PNNL projects were selected as part of the Department of Energy’s Funding for Accelerated, Inclusive Research.

At the Nonproliferation, Counterproliferation, and Disarmament Science Gordon Research Conference, researchers from PNNL shared research and scientific approaches for countering diverse threats.

Brown University Applied Mathematics and Engineering Professor George Karniadakis has driven solutions for science and engineering problems for over ten years with a joint appointment at PNNL.

The Rapid Assessment of Platform Technologies to Expedite Response project aims to prepare against future pandemics.

PNNL researchers present challenges and opportunities for fusing graph neural networks with deep reinforcement learning.

PNNL recently joined the Department of Homeland Security for two technical meetings exploring national security research spanning the threat realm, from chemical and biological attacks to adversarial artificial intelligence.

ACMD staff contributed to 30 years of atmospheric data collection for the Department of Energy’s Atmospheric Radiation Measurement user facility.

Purvine shares how research-collaboration workshops focused for women in data science create a sense of inclusion, empowerment, and networking.

Unveiling diverse scenarios and implications for water resource management in a rapidly changing world.

The papers were featured in the security and quantum sessions at the 2023 International Symposium on Computer Architecture.

PNNL researchers are helping to better define the need for grid energy storage in future clean energy scenarios, as well as working to improve technologies for storing renewable energy so it's available when and where it's needed.

Using a combination of satellite data and modeling to study the temperatures and humidity people might feel in urban areas, researchers have pinpointed who in the U.S. is most vulnerable to heat stress.

Computational chemistry libraries from NWChem, NWChemEX, SPEC, and more are now available on Azure Quantum Elements.

Quantifying the long-term destination of anthropogenic emissions and robustness of global carbon sinks.

New study identifies crucial factors for more accurate hydrological predictions in the Community Land Model version 5.

Groundwater modeling of irrigation return flow dynamics is important for improving estimates of water availability.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

PNNL and The University of Texas at El Paso expand their premier partnership to include the Cyber Halo Innovation Research Program.

To overcome high-performance computing bottlenecks, a research team at PNNL proposed using graph theory, a mathematical field that explores relationships and connections between a number, or cluster, of points in a space.

Researchers have knitted together three large databases of information to help cybersecurity experts detect and prevent attacks.