Amine functionalized graphene oxide yields laminates with an enhanced capacity to adsorb rare earth elements, improved water transport, and greater stability for effective membrane-based separation of critical minerals.

Chiral nanotubes facilitate the direction-specific diffusion of carbon dioxide to be faster than nitrogen gas.

A research team from Pacific Northwest National Laboratory used machine reasoning to schedule scientific workflows while guaranteeing quality of service (QoS).

Replacing commercial acid with acidic waste enables researchers to improve nickel extraction efficiency, lower projected costs, and improve process economics.

Studying a series of rare earth element compounds revealed differences in their magnetic behavior that will be leveraged for separations.

Localized gradients in magnetic fields have long-range effects on the concentration of rare earth ions in solution, facilitating field-driven extraction of critical minerals.

The Scientific Discovery through Advanced Computing institute will focus on making scientific machine learning accessible to domain scientists.

This achievement earned DIMPLES a Best Paper award at the ACM International Conference on Supercomputing 2025.

Nanoscale domains of magnetically susceptible critical materials encounter enhanced magnetic interactions under external magnetic fields, providing a promising new avenue for separations.

The size of graphene oxide sheets affects the ability of assembled membranes and adsorbents to separate rare earth elements.

A PNNL team has developed an energy- and chemical-efficient method of separating valuable critical minerals from dissolved solutions of rare earth element magnets.

Surface manganese mining from nodules in South Dakota is now possible with a new scalable selective precipitation process.

Cobalt substitution for magnesium in a model mafic mineral dramatically slows reaction with carbon dioxide to form a cobalt-doped carbonate.

Precipitation with sodium hydroxide in a flow-gel device enables the rapid extraction of magnesium from seawater in a new scalable process.

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.

The atomic-level distribution of nickel and cobalt in forsterite depends on the concentration of the different elements.

The surface oxygen functionality of graphene oxide may be tuned using ultraviolet light, affecting how differently charged ions move through the material.

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

PNNL played host in mid-May to the Artificial Intelligence for Robust Engineering & Science workshop, an annual event that explores advances in artificial intelligence

PNNL shared recent developments in artificial intelligence at the inaugural Special Competitive Studies Project AI for National Competitiveness Expo.