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This is a record of a document published elsewhere, first published by the United States Patent and Trademark Office, as US-2026104681-A1, on 16 April 2026. OpenTechnical did not first disclose it. The identifier, hashes and timestamps below record what this library served and when, not when the material became public. View the original.

OT-2026-000000475

Reinforcement Learning System for Optimizing Selective Extraction of Lithium from Brines

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Sensors, Controls & Machine Vision › Industrial Control
Original source
US-2026104681-A1, the United States Patent and Trademark Office, 16 April 2026
Document SHA-256
2f90dc61855f7cd3fd28a1df76da283a07d69ab4361ccfae2885f92609dba780

Abstract

According to one or more embodiments, a method, computer system, and computer program product for optimizing extraction of lithium through reinforcement learning are provided. The method may include receiving measurement data from one or more sensors corresponding to a current set of operational parameters associated with a direct lithium extraction process in one or more columns. A physical simulation of the direct lithium extraction process is generated based on the received measurement data and the current set of operational parameters. A set of optimal operational parameters for the one or more columns is identified based on the generated physical simulation. The identified set of optimal operational parameters is configured to maximize extraction of lithium through the direct lithium extraction process. The current set of operational parameters is adjusted based on the identified set of optimal operational parameters.

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OpenTechnical Publication OT-2026-000000475, “Reinforcement Learning System for Optimizing Selective Extraction of Lithium from Brines,” published September 15, 2026 at 19:02:56 UTC, https://opentechnical.org/p/OT-2026-000000475.

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