PNNL played host in mid-May to the Artificial Intelligence for Robust Engineering & Science workshop, an annual event that explores advances in artificial intelligence

PNNL shared recent developments in artificial intelligence at the inaugural Special Competitive Studies Project AI for National Competitiveness Expo.

PNNL researchers review ceramic-metal composite technology for immobilizing radioactive wastes from nuclear reactors, including advanced reactors.

At the second Grid Resilience to Extreme Events Summit, a diverse range of experts gathered to tackle the biggest challenges in building a resilient grid.

Scientists at PNNL harnessing advances in deep learning, deep reinforcement learning and generative AI to change how science is conducted and achieve original scientific results and breakthroughs.

Visit featured information exchange and tours of PNNL work and facilities that relate to the work of the International Atomic Energy Agency.

IDREAM scientists capture electronic response to ionization.

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.

New research informs the development of foundational models for computational chemistry through hardware-software co-design.

The software democratizes hardware designs by enabling domain scientists to design their own accelerators.

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.

IDREAM research shows the size of cations in highly concentrated nitrite solutions affects the production of radicals.

New apps help researchers with statistical analyses of data.

New methodological approach demonstrates how to assess the economic value, including non-traditional value streams, of converting non-powered dams to hydroelectric facilities.

The Deep Vadose Zone program leads a treatability study for subsurface remediation of the Hanford Site’s Central Plateau.

PNNL is supporting the Department of Homeland Security Science and Technology Directorate's Chemical Security Analysis Center in improving capabilities to enhance detection and analysis of chemical threats.

There are many ways that researchers at PNNL bring unique perspectives to the field of distributed wind. One is the fact that PNNL's distributed wind projects are all led by women.

Wei Du will lead one of PNNL and Washington State University’s joint institutes.

A PNNL study developed a water management module for Xanthos that distinguishes between the operational characteristics of hydropower, irrigation, and flood control reservoirs.

The physics-informed machine learning optimization framework is now PNNL’s most popular open-source repository on GitHub.