PNNL researchers combined deep operator networks with spectral methods to efficiently and accurately solve complex equations.

Data-driven autonomous technology to rapidly design and deliver antiviral interventions targeting SARS-CoV-2 to reduce drug discovery timeline and advance bio preparedness capabilities.

The Building and Environment journal named Drgoňa’s co-authored work one of 2022’s best papers.

Report for the Oregon Public Utility Commission highlights innovations and best practices for resilience and utility planning could be helpful to other states as well.

Data scientist Jung Lee accepted the position of review editor for Frontiers in Computational Neuroscience after serving as a guest editor for a special issue.

Scientists have taken a key step toward harnessing a form of AI known as deep reinforcement learning to protect computer networks.

A new sodium battery technology shows promise for helping integrate renewable energy into the electric grid. The battery uses Earth-abundant raw materials such as aluminum and sodium.

The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.

The Public Infrastructure Security Cyber Education System is a university-community-nonprofit collaboration changing cyber education and cybersecurity.

Zhenyu (Henry) Huang acts as guest editor in an upcoming special issue on “Climate Change Mitigation and Adaptation in Power and Energy Systems." The special edition is published by Elsevier.

PNNL mathematician Aaron Luttman contributed to the organizing committee for workshop exploring robust machine learning and artificial intelligence systems for the U.S. Army.

Researchers developed a machine learning model that can analyze chemical reactions as they happen in an electron microscope.

PNNL scientists Daniel Gaspar and Wei Wang were among nine scientists featured in journal article recognizing 2021-2022 ACS award honorees.

PNNL and Georgia Tech launch a joint institute focused on accelerating security for the critical infrastructure community.

Steven Spurgeon’s research is featured in the cover of the MRS Bulletin along with his team’s invited perspective on the future of machine learning for electron and scanning probe microscopy.

As leaders in AI and machine learning, PNNL experts are sharing their latest findings at the 36th annual Neural Information Processing Systems (NeurIPS) Conference, Nov. 28–Dec. 9, 2022.

PNNL gathered researchers from eight national laboratories plus the U.S. Department of Energy (DOE) to share ideas and build synergy at the Energy Equity and Environmental Justice Summit.

PNNL researchers use machine learning and data analytics to assist with detection of nuclear proliferation and nuclear material trafficking.

Scientists at PNNL are working to better prepare authorities, emergency responders, communities and the grid in the face of increasingly extreme hurricanes.

Scientists are pioneering approaches in the branch of artificial intelligence known as machine learning to design and train computer software programs that guide the development of new manufacturing processes.