USA Rare Earth, Pasqal and Riven Test Quantum Machine Learning for Rare Earth Separation

Insider Brief

• USA Rare Earth, Pasqal and Riven Systems have partnered to explore quantum machine learning for discovering molecules that could improve rare earth separation processes.
• Riven’s automated laboratory will generate experimental data on extractant selectivity, while Pasqal will benchmark quantum machine learning models against classical models using data from the lab.
• The project will focus on USA Rare Earth’s planned feedstocks, including material from the Round Top mine, mixed rare earth carbonates and recycled magnet-manufacturing swarf.

PRESS RELEASE — USA Rare Earth (Nasdaq: USAR), a rare earth, critical minerals and advanced materials company, Pasqal (Nasdaq: PSQL), a global leader in neutral-atom quantum computing and Riven Systems, a specialist in AI for industrial chemistry, today announced a strategic partnership to develop next-generation separation technology for the rare earth value chain. Using quantum machine learning, the project aims to identify new separation molecules that bind more effectively to rare earths than existing alternatives, enabling smaller, lower-cost, less energy-intensive processing facilities.

The collaboration brings together U.S. and French expertise in two strategically important sectors: critical minerals and quantum computing. Together, the companies aim to explore technologies that could help support a more secure, efficient and competitive Western rare earth supply chain.