Agentic workflow enables the recovery of critical materials from complex feedstocks via selective precipitation
Source abstract
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 optimization of efficient, adaptable, and scalable separations to a timeline of days, rather than months and years.
Source: openalex_inverted_index · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Recycling and Waste Management Techniques · Extraction and Separation Processes · Mineral Processing and Grinding
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Physical and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99354, USA
Physical and Computational Sciences Directorate, Pacific Northwest National Laboratory, Seattle, Washington 98109, USA
Department of Chemical Engineering, University of Washington, Seattle, Washington 98195, USA
Funding
Laboratory Directed Research and Development
References (33)
Show source-provided references
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