Aclara Resources, Stanford to pioneer AI-driven HREE research

Aclara Resources announced a strategic collaboration between its U.S.-based subsidiary Aclara Technologies and Stanford University to accelerate the development of artificial intelligence (AI) innovations aimed at securing a resilient and sustainable supply chain for heavy rare earth elements (HREE). 

The agreement establishes the foundation for a strong academic and technological alliance, leveraging advanced AI solutions to optimize the HREE supply chain from the ground up, starting with exploration and continuing through processing and supply chain integration.

“This partnership with Stanford’s Mineral-X  [initiative] reinforces our commitment to innovation and leadership in the global rare earth supply chain,” said Ramón Barúa, Aclara CEO. “By embedding Aclara into Silicon Valley’s innovation ecosystem and combining our expertise in heavy rare earths with Mineral-X’s advanced AI technologies, we aim to jointly develop smarter, cleaner, and more secure solutions that strengthen the resilience of alternative supply chains.”

Key objectives of the collaboration include: 

  • Joint development of AI-powered predictive models to better understand and target REE mineralization in regolith and ionic clays.
  • Academic and technical exchange between researchers, students and professionals.
  • Innovation opportunities in sustainable exploration, traceability and responsible development of REE supply chains.
  • Co-authorship of scientific publications and joint management of intellectual property related to AI applications in exploration.
  • Roadmap for a long-term strategic alliance, including future R&D initiatives and pilot projects.

Stanford’s Mineral-X is a leading research initiative focused on transforming the critical minerals´ supply chain through advanced technologies, particularly AI, decision science, and data science. It has served as the launchpad for some of the world’s most successful mining AI startups and is at the forefront of integrating machine learning, geosciences and sustainability.

Source: Aclara Resources

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