A combined experimental and computational approach showed that the hydration shell of hydroxide has a four-coordinate binding.

A combined experimental and modeling study shows that electronic interactions direct how a metal-organic framework grows.

PNNL is making waves in pursuit of a blue economy. Researchers are advancing science and technology to expand—and protect—the gifts of the sea.

A new approach broadens the reach of quantum computers to previously challenging systems.

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.

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.

With an eye on renewable, accessible, and resilient power, PNNL researchers show hyper-local microgrids are a viable option, if designed with the right mix of sources.

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.

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.

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.