- 专利标题: Science-driven automated experiments
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申请号: US18324343申请日: 2023-05-26
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公开(公告)号: US11982684B1公开(公告)日: 2024-05-14
- 发明人: Maxim A. Ziatdinov , Kevin Roccapriore , Yongtao Liu , Kyle P. Kelley , Rama K. Vasudevan , Jacob D. Hinkle , Sergei V. Kalinin
- 申请人: UT-Battelle, LLC
- 申请人地址: US TN Oak Ridge
- 专利权人: UT-Battelle, LLC
- 当前专利权人: UT-Battelle, LLC
- 当前专利权人地址: US TN Oak Ridge
- 代理机构: Scully, Scott, Murphy & Presser, P.C.
- 主分类号: G01Q60/10
- IPC分类号: G01Q60/10 ; G02B21/10
摘要:
Systems, methods and programs are provided for automated science experiments which use a model with learnt model parameters to define points for physical-characteristic measurements once the model is trained. The systems, methods and programs use active learning which enables describing a relationship between local features of sample-surface structure shown in image patches and determined representations of physical-characteristic measurements.
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