The first direct molecular-scale evidence of the temperature-driven transformation of the coordination environment of ytterbium at geologically relevant conditions.

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

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.

A new database allows researchers to connect lattice parameters and composition in olivine.

New methodology can evaluate the potential for carbon storage and critical mineral recovery in undercharacterized geological settings.

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.

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

A review article examines a decade of work on the atom-scale process of turning carbon dioxide into stable minerals.

Biochemical preservation and mineral association retain carbon in grassland soils, resulting in consistent molecular composition across ecosystems.

Across the United States, water moving between the river and riverbed sediments does not overcome localized processes that govern organic matter chemistry.

A new study shows how organic molecules respond to global change varies according to functional traits and ecological processes.

A novel combination of temperature and four-dimensional geophysical sensors revealed otherwise unseeable hydrologic dynamics below riverbed sediments.

PNNL researchers developed a hybrid quantum-classical approach for coupled-cluster Green’s function theory that maintains accuracy while cutting computational costs.

ICON science is a Department of Energy-developed framework to enhance scientific outcomes via more intentional design of research efforts across all domains of science.

New data analysis approach gives researchers deeper understanding of microbial ecology and evolution.

Quantum simulators help navigate noise on GPU-based HPC systems.

PNNL researchers utilized the Peeters-Devreese-Soldatov formulation to improve the accuracy of calculations for quantum chemistry.

Improving predictability of water quality and nutrient cycling in large river systems.