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.

From developing new energy storage materials to revealing patterns of Earth’s complex systems, studies led by PNNL researchers are recognized for their innovation and influence.

Shear Assisted Processing and Extrusion (ShAPE) imparts significantly more deformation compared to conventional extrusion. The latest ShAPE system at PNNL, ShAPEshifter, is a purpose-built machine designed for maximum configurability.

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.

Ampcera has an exclusive licensing agreement with PNNL to commercially develop and license a new battery material for applications such as vehicles and personal electronics.

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

Pacific Northwest National Laboratory researchers developed a new theoretical method for studying highly correlated systems.

Nineteen PNNL-affiliated researchers have been named to Clarivate’s 2024 list of the world's most highly cited researchers.

In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.

A new approach validates quantum algorithms for low-energy nuclear physics applications

A new quantum algorithm speeds up simulations of coupled oscillator dynamics.

In a new approach, quantum flow algorithms are used to simulate many-body systems on quantum computers and effectively describe chemical processes.

A combined experimental and theoretical study identified multiple interactions that affect the performance of redox-active metal oxides for potential electrochemical separation and quantum computing applications.

The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.

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

HiSVSIM enables large-scale quantum simulations through graph partitioning.

New research shows that compressing quantum circuits decreases noise and increases the accuracy of quantum calculations.