Graph neural network force field computational algorithms for molecular dynamics computer simulations
US11817184B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 16, 2019 |
| Grant date | Nov 14, 2023 |
| Priority date | — |
| Expiry date | Jul 25, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16C20/70
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computational method simulating the motion of elements within a multi-element system using a graph neural network (GNN). The method includes converting a molecular dynamics snapshot of the elements into a directed graph comprised of nodes and edges. The method further includes the step of initially embedding the nodes and the edges to obtain initially embedded nodes and edges. The method also includes updating the initially embedded nodes and edges by passing a first message from a first edge to a first node using a first message function and passing a second message from the first node to the first edge using a second message function to obtain updated embedded nodes and edges, and predicting a force vector for one or more elements based on the updated embedded edges and a unit vector pointing from the first node to a second node or the second node to the first node.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.