Energy gap estimation of zinc sulfide metal chalcogenide nanostructure semiconductor using genetically hybridized support vector regression

Journal article

Open access

Peer reviewed

AIP advances, Vol.11(11), pp.115222-115222-11

01/11/2021

Files and links (1)

url

https://doi.org/10.1063/5.0069749View

Published (Version of record) Open

1 Record Views

Title: Energy gap estimation of zinc sulfide metal chalcogenide nanostructure semiconductor using genetically hybridized support vector regression
Creators - without role: Nahier Aldhafferi - Imam Abdulrahman Bin Faisal University
Publication Details: AIP advances, Vol.11(11), pp.115222-115222-11
Identifiers: 9916105508331
Academic Unit: Imam Abdulrahman Bin Faisal University
Language: English
Resource Type: Journal article