PNNL’s Rob Howard received the 2022 Fuel Cycle and Waste Management Award from the American Nuclear Society.

The size of the alkali metal within the material influences the crystallization pathway.

Providing a perspective on the importance of integrating experimental work with theory and simulations when designing new carbon capture solvents.

PNNL scientists developed new capabilities to study materials under extreme conditions.

PNNL Materials Scientist Leo Fifield recognized for contributions to the field of nuclear instrumentation and control.

Parallel graph neural networks identify protein-ligand 3-D structural interactions to aid in protein function prediction and drug discovery.

IDREAM researchers use fast force mapping to provide insights into the boehmite interfacial solution structure.

Vanda Glezakou and Laboratory Fellow Roger Rousseau collaborated with other experts to write an American Chemical Society book chapter.

A hybrid computing approach for solving quantum chemical problems offers a practical bridge between classical and quantum computing.

Researchers achieved the complete assignment of the infrared spectrum of a hydronium-water “magic number” cluster reported in Science in 2004.

A team of researchers developed a simulation approach to identify how atomic structures can affect the phonon transport of energy and information in quantum systems near absolute zero temperatures.

Theoretical work shows that an important natural iron source can be described as a nanoscale composite of different, but experimentally indistinguishable, structures.

Fundamental research conducted at the $90-million research facility will help the nation meet its clean energy goals.

PNNL researchers are studying catalysts that are key to dealing with waste and producing sustainable energy.

Two PNNL interns are behind recent innovation in real-time testing and continuous monitoring for pH and the concentration of chemicals of interest in chemical solutions; outcomes have applicability not only to nuclear, but to industries.

Creating films with atomic precision allows researchers moving to the Energy Sciences Center to identify small, but important changes in the materials.

PNNL data scientists are refining their artificial intelligence tools with COVID-19 data to advance therapeutics and treatments for a future pandemic.

PNNL report reflects 10 years of dedication to effectively plan for the safe and uneventful removal of radioactive waste from nuclear power plants.

The U.S. Department of Energy has selected the Scalable Predictive Methods for Excitations and Correlated Phenomena project to receive funding to develop software for chemical research.

Research into practical systems for chemical energy storage will be a focus at the Energy Sciences Center.