Invention Grant
- Patent Title: Generating control settings for a chemical reactor
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Application No.: US16444565Application Date: 2019-06-18
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Publication No.: US11520310B2Publication Date: 2022-12-06
- Inventor: Dmitry Zubarev , Victoria A. Piunova , Nathaniel H. Park , James L. Hedrick , Sarath Swaminathan
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Amin, Turocy & Watson, LLP
- Main IPC: G05B19/4155
- IPC: G05B19/4155 ; G06N20/00 ; G05B13/02

Abstract:
Techniques regarding autonomously controlling one or more chemical reactors using generative machine learning models are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a model component that can build a generative machine learning model based on training data regarding a past chemical reactor operation. The generative machine learning model can generate a recommended chemical reactor control setting for experimental discovery of a polymer.
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