Predicting etch characteristics in thermal etching and atomic layer etching

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 character...

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Bibliographic Details
Main Authors DRAEGER, NERISSA SUE, GOTTSCHO, RICHARD A, LILL, THORSTEN, FISCHER, ANDREAS, BERRY III, IVAN L
Format Patent
LanguageChinese
English
Published 11.05.2023
Subjects
BASIC ELECTRIC ELEMENTS
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC SOLID STATE DEVICES NOT OTHERWISE PROVIDED FOR
ELECTRICITY
PHYSICS
SEMICONDUCTOR DEVICES
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Summary: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.
Bibliography:Application Number: TW20198114841