Predicting etch characteristics in thermal etching and atomic layer etching
US11520953B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 3, 2018 |
| Grant date | Dec 6, 2022 |
| Priority date | — |
| Expiry date | Sep 9, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Etch in a thermal etch reaction is predicted using a machine learning model. Chemical characteristics of an etch process and associated energies in one or more reaction pathways of a given thermal etch reaction are identified using a quantum mechanical simulation. Labels indicative of etch characteristics may be associated with the chemical characteristics and associated energies of the given thermal etch reaction. The machine learning model can be trained using chemical characteristics and associated energies as independent variables and labels as dependent variables across many different etch reactions of different types. When chemical characteristics and associated energies for a new thermal etch reaction are provided as inputs in the machine learning model, the machine learning model can accurately predict etch characteristics of the new thermal etch reaction as outputs.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.