eprintid: 20623
rev_number: 3
eprint_status: archive
userid: 1
dir: disk0/00/02/06/23
datestamp: 2026-07-21 06:28:47
lastmod: 2026-07-21 06:28:47
status_changed: 2026-07-21 06:28:47
type: article
metadata_visibility: show
creators_name: Alakbari, Fahd Saeed
creators_name: Mahmood, Syed Mohammad
creators_name: Bamumen, Salem Saleh
creators_name: Tsegab, Haylay
creators_name: Hagar, Haithm Salah
creators_name: Babikir, Ismailalwali
creators_name: Darkwah-Owusu, Victor
title: New and Highly Accurate Static Young�s Modulus Model Using Machine Learning Techniques
ispublished: pub
note: Cited by: 1; All Open Access; Gold Open Access; Green Open Access
date: 2024
publisher: American Chemical Society
official_url: https://www.scopus.com/pages/publications/85204530688?origin=resultslist
id_number: 10.1021/acsomega.4c04930
full_text_status: none
publication: ACS Omega
refereed: TRUE
issn: 24701343
citation:   Alakbari, Fahd Saeed and Mahmood, Syed Mohammad and Bamumen, Salem Saleh and Tsegab, Haylay and Hagar, Haithm Salah and Babikir, Ismailalwali and Darkwah-Owusu, Victor  (2024) New and Highly Accurate Static Young�s Modulus Model Using Machine Learning Techniques.  ACS Omega.   ISSN 24701343