The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jun. 02, 2026

Filed:

Jul. 08, 2020
Applicant:

Shenzhen Jingtai Technology Co., Ltd., Guangdong, CN;

Inventors:

Hongrui Lin, Guangdong, CN;

Mingjun Yang, Guangdong, CN;

Chunwang Peng, Guangdong, CN;

Chunan Wu, Guangdong, CN;

Jian MA, Guangdong, CN;

Shuhao Wen, Guangdong, CN;

Lipeng Lai, Guangdong, CN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16C 10/00 (2019.01); G16C 20/70 (2019.01);
U.S. Cl.
CPC ...
G16C 10/00 (2019.02); G16C 20/70 (2019.02);
Abstract

The present invention provides a molecular force field multi-objective fitting algorithm library and the workflow, including: FFOptlterator as the main module for input and output and force field parameter training iteration; EnergyCalculator module used for MM energy and energy derivatives calculation for the required value of each iteration in the optimization algorithm; the PropertyEstimator module used for the thermodynamic property calculation based on the MD simulation. Wherein, when initializing the FFOptlterator and EnergyCalculator objects, the user specifies the training force field parameters, adjustable parameter ranges, system setting arguments, and MD simulation parameters. The invention is suitable for the related applications of molecular force field training and verification, and implement the framework for different training targets, the prediction of different molecular physical properties, the compatibility and conversion of force field parameters in different formats, integration of multi-objective optimization, result analysis and graphing, etc.


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