Agentic workflow enables the recovery of critical materials from complex feedstocks via selective precipitation
This addresses the need for efficient and scalable separations in resource recovery, though it appears incremental as it builds on existing multi-agent and automation concepts.
The paper tackles the problem of recovering critical materials from complex feedstocks like produced water and magnet leachates, achieving selective precipitation with simple chemicals and accelerating development timelines from months/years to days.
We present a multi-agentic workflow for critical materials recovery that deploys a series of AI agents and automated instruments to recover critical materials from produced water and magnet leachates. This approach achieves selective precipitation from real-world feedstocks using simple chemicals, accelerating the development of efficient, adaptable, and scalable separations to a timeline of days, rather than months and years.