Machine learning techniques are accelerating the development of stronger alloys for power plants, which will yield efficiency, cost, and decarbonization benefits.

PNNL’s energy-efficient dehumidifier may reduce energy consumption by up to 50% in residential A/C systems and increase the range of electric vehicles by up to 75%. The system has been licensed to Montana Technologies.

Stanford-bound aspiring scientist gained valuable national laboratory research experiences through the Community College Internship program at PNNL.

PNNL materials scientist Dongsheng Li looks forward to using a co-located collection of advanced research equipment in the new Energy Sciences Center.

Modeling study suggests vigorous ventilation can cause spike in viral concentrations

Research shows that previous drought and flooding conditions strongly influence soil respiration and carbon composition.

New quantum chemistry pipeline can help predict the effects of bioengineering.

PNNL’s Framework for Assessment of Complex Environmental Tradeoffs helps navigate and evaluate competing environmental, economic, and social impacts.

Research shows that erosional nutrient fluxes linked to extreme rains may complicate efforts to reduce nutrient enrichment in the Gulf of Mexico.

PNNL’s infrared pulsed heating technique reveals supercooled water’s weird behavior; opens door to other fluid studies at new Energy Sciences Center.

New research aids the design of more efficient water purification technologies.

A research project that brings together mathematicians and atmospheric scientists has developed into a deep collaboration for improving atmospheric models.

U.S. Secretary of Energy Jennifer M. Granholm virtually visits PNNL, one of several national lab visits she is conducting.

High-throughput biochemical assays targeting a vital viral protein identified one molecule out of more than 13,000 with promising antiviral activity against SARS-CoV-2.

New research shows that a warmer ocean strengthens the North Pacific westerly jet stream, steering more storms toward California.

Spectroscopic experiments reveal significant variations in the electronic structures of actinide tetrafluorides despite their nearly identical crystal structures.

The multi-year project funded by DOE’s High Energy Physics program will focus on using machine learning to prevent power outages.

PhD student wins Gold Award at Materials Research Society Spring 2021 meeting.

Researchers found that using deep neural networks can significantly enhance the resolution of observations from weather radars.

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