Invention Grant
- Patent Title: Neural network force field computational algorithms for molecular dynamics computer simulations
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Application No.: US16202890Application Date: 2018-11-28
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Publication No.: US11455439B2Publication Date: 2022-09-27
- Inventor: Jonathan Mailoa , Mordechai Kornbluth , Georgy Samsonidze , Boris Kozinsky , Nathan Craig
- Applicant: Robert Bosch GmbH
- Applicant Address: DE Stuttgart
- Assignee: Robert Bosch GmbH
- Current Assignee: Robert Bosch GmbH
- Current Assignee Address: DE Stuttgart
- Agency: Brooks Kushman P.C.
- Main IPC: G06F30/20
- IPC: G06F30/20 ; G06N3/04 ; G06N10/00

Abstract:
A computational method for simulating the motion of elements within a multi-element system using a neural network force field (NNFF). The method includes receiving a combination of a number of rotationally-invariant features and a number of rotationally-covariant features of a local environment of the multi-element system; and predicting a force vector for each element within the multi-element system based on the combination of the number of rotationally-invariant features, the number of rotationally-covariant features, and the NNFF, to obtain a simulated motion of the elements within the multi-element system.
Public/Granted literature
- US20200167439A1 Neural Network Force Field Computational Algorithms For Molecular Dynamics Computer Simulations Public/Granted day:2020-05-28
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