Genesis Mission awards to PNNL will advance scientific discovery, next-generation energy systems and advanced manufacturing, among others.

PNNL researchers demonstrate high-purity production of two essential gases to ensure a U.S. domestic feedstock for advanced quantum computing.

PNNL convenes leaders from the Department of Energy, national laboratories, computing industry and academia for a two-day workshop to advance quantum computing for computational chemistry.

Researchers at PNNL have developed an interpretable, lightweight AI model that can easily predict weld microstructure features using only basic machine sensor inputs.

An international research team deployed AI-powered computing to solve important chemical structures for energy applications using NVIDIA hardware.

A suite of new modeling methods gives researchers better tools to predict molecular behavior inside cavities.

PNNL has developed a next-generation electrical resistivity tomography system for DOE that uses E4D software and AI-enhanced modeling to produce real-time subsurface images that help guide environmental remediation decisions.

PNNL set to create a practical path for near-term hybrid classical-quantum computers with NVIDIA accelerated computing.

PNNL’s Center for the Remediation of Complex Sites inducted leaders Director David Peeler, Deputy Director Carolyn Pearce, Operations Director Christian Johnson, and advisors with multidisciplinary subsurface research expertise.

A recent article highlighted a PNNL report focused on post-quantum cryptography and electric vehicle charging infrastructure.

Darío Gil, DOE's Undersecretary for Science, makes his inaugural visit to PNNL.

An approach combining multiple theories increases the accuracy of quantum-based simulations without increasing computational demands.

As Laboratory Director Steve Ashby pens his last monthly column, he highlights PNNL’s accomplishments with pride and gratitude.

Quantum computing promises leaps in chemistry and materials science, and PNNL is preparing to realize its potential with a collaborative approach.

PNNL researchers received an award from the Materials, Metals & Materials Society (TMS) for a publication on friction riveting.

Neural networks techniques enable the efficient capture of electron correlation effects in reduced-dimensionality spaces.

In the search for rare physics events, extremely pure materials are essential. A partnership between PNNL and Ultramet has led to tungsten with low contamination from other elements.

Erik Lentz and Christian Boutan will research quantum information science-enabled discoveries in high energy physics with these awards.

Developing a new scheme to more efficiently solve quantum chemistry problems.

Researchers have created an algorithm that slashes the calculations necessary to prepare and customize data for quantum computing.