Practical decontamination of industrial wastewater depends on energy-efficient separations. This study explored using ionic liquids as part of the process, enabling efficient electrochemical separation from aqueous solutions.

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

A novel electrode functionalization strategy enables efficient removal of toxic heavy metals from wastewater.

A new review describes the insights that may be gained into important electrochemical processes using ion soft landing.

Research from PNNL and the University of Washington demonstrates the extension of the MBE for periodic systems and its use to decompose the lattice energies of different ice polymorphs.

Combining peptoids and carbon nanotube porins creates a new class of stable membranes with potential applications in separations science.

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.

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

PNNL researchers created a model that helps materials scientists not only predict what is, but what could be.

Providing a perspective on the importance of integrating experimental work with theory and simulations when designing new carbon capture solvents.

Ionic liquids bound to thin layers of graphene oxide produces more selective and efficient multi-layer membranes for water filtration.

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

Surface characterization allows researchers to explore the compatibility between different solvent-membrane combinations.

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

PNNL researchers developed a way to produce accurate simulations of complex physical systems using renormalized approximations across multiple scales

Hypergraphs can more faithfully identify important genes in complex immune responses.

The web-based tool, called PLATIPUS, is publicly available and interacts with publications available in the CovidScholar database.

Seeking a deeper understanding of when, where, and why large wildfires occur using explainable artificial intelligence.

New mathematical tools developed at PNNL hold promise to transform the way we operate and defend complex cyber-physical systems, such as the power grid.

Predictive models indicate cells regulate enzyme activity to maintain liquid center.