A PNNL team has developed an energy- and chemical-efficient method of separating valuable critical minerals from dissolved solutions of rare earth element magnets.
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.
PNNL will engage with transmission planners and other regional partners through technical assistance and listening sessions with the goal of exploring opportunities to integrate equity into transmission planning.
The surface oxygen functionality of graphene oxide may be tuned using ultraviolet light, affecting how differently charged ions move through the material.
PNNL played host in mid-May to the Artificial Intelligence for Robust Engineering & Science workshop, an annual event that explores advances in artificial intelligence
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.