The DOE Early Career Research Program supports exceptional researchers during the crucial early years of their careers and helps advance scientific discovery in fundamental sciences
National Nuclear Security Administration Graduate Fellow Marc Wonders has spent the past year working with researchers exploring artificial intelligence in the national security mission space.
Research and development expertise aligns with national priorities in clean energy innovation and climate change mitigation. A workforce of 5,000 delivers scientific discovery, enables sustainable energy, and enhances national security.
With quantum chemistry, researchers led by PNNL computational scientist Simone Raugei are discovering how enzymes such as nitrogenase serve as natural catalysts that efficiently break apart molecular bonds to control energy and matter.
PNNL data scientists Svitlana Volkova and Emily Saldanha, along with former PNNL intern Pamela Bilo Thomas, will publish their research on online information spread in Nature's Scientific Reports.
Sentry-SECURE is a new communication and response platform developed by PNNL, VPI, and Microsoft Azure that rapidly and securely transfers radiological alarm data through the cloud.
Michael Henry, a senior data scientist at PNNL, has accepted a joint appointment at the Texas A&M University RELLIS Center for Applied Research and Experiential Learning.
On the looming 10th anniversary of the Fukushima disaster at the Daiichi Power Station in Japan, PNNL looks back at the science and solidarity it has shared with Fukushima and its nuclear cleanup effort.
Fifty-eight PNNL staff members were recognized as members of enterprise-wide teams that helped address challenges in national health and security through transformative science and technology solutions.
New 140,000-square-foot facility will advance fundamental chemistry and materials science for higher-performing, cost-effective catalysts and batteries, and other energy efficiency technologies.
PNNL data scientists Henry Kvinge and Ted Fujimoto presented their research on few-shot learning and reinforcement learning, respectively, at workshops during the 2021 AAAI Conference on Artificial Intelligence.