Agentic workflow enables the recovery of critical materials from complex feedstocks via selective precipitation

Andrew Ritchhart; Sarah I. Allec; Pravalika Butreddy; Krista Kulesa; Qingpu Wang; Dan Thien Nguyen; Maxim Ziatdinov; Elias Nakouzi

Agentic workflow enables the recovery of critical materials from complex feedstocks via selective precipitation

Materials Science 2026-03-17 v1 Artificial Intelligence

Authors: Andrew Ritchhart , Sarah I. Allec , Pravalika Butreddy , Krista Kulesa , Qingpu Wang , Dan Thien Nguyen , Maxim Ziatdinov , Elias Nakouzi

View on arXiv ↗ PDF ↗

Abstract

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.

Keywords

critical materials selective precipitation AI agents automated instruments feedstock recovery

Cite

@article{arxiv.2603.15491,
  title  = {Agentic workflow enables the recovery of critical materials from complex feedstocks via selective precipitation},
  author = {Andrew Ritchhart and Sarah I. Allec and Pravalika Butreddy and Krista Kulesa and Qingpu Wang and Dan Thien Nguyen and Maxim Ziatdinov and Elias Nakouzi},
  journal= {arXiv preprint arXiv:2603.15491},
  year   = {2026}
}

Agentic workflow enables the recovery of critical materials from complex feedstocks via selective precipitation

Abstract

Keywords

Cite

Related papers