Researchers developed a way to precisely control dopant structures and locations in carbon-based materials.

PDX, PNNL, and Sandia National Laboratories are exploring the feasibility of hydrogen fuel for the PDX bus fleet—an idea that could have novel benefits for hazard resilience.

Researchers developed a pathway for the solution synthesis of core–crown heterostructures with controlled electronic properties.

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

Under an optical field, nanoparticle attachment in a model system heavily depends on surface roughness.

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.

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

Chromium cations better adapt to changes in oxygen stoichiometry than iron cations.

Using interfacial charge transfer to control cation charges in oxide superlattices offers insights for designing functional heterostructures.

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

Calcium carbonate mineralization occurs through a multi-step process that begins with a dense liquid phase.

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

Klickitat Valley Health's fuel cell and microgrid project boosts rural healthcare, enhancing energy resilience and sustainability for social equity.

After 20 years of contributions to the field of hydrogen safety, the Hydrogen Safety Panel launched its new mentoring program at PNNL earlier this year. Now, the program has selected its first two mentees.

A newly funded project will develop the fundamental understanding of phenomena that underpin material properties important for quantum applications.

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.

Fully identifying what controls nanocrystal assembly requires incorporating non-traditional forces into models.

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

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

The SHASTA program is doing a deep dive on subsurface hydrogen storage in underground caverns, helping to lay the foundation for a robust hydrogen economy.