Machine and deep learning models for predicting high pressure density of heterocyclic thiophenic compounds based on critical properties
Crossref DOI link: https://doi.org/10.1038/s41598-025-09600-z
Published Online: 2025-07-15
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Sheikhshoaei, Amir Hossein
Khoshsima, Ali https://orcid.org/0000-0002-3210-7203
Text and Data Mining valid from 2025-07-15
Version of Record valid from 2025-07-15
Article History
Received: 28 April 2025
Accepted: 30 June 2025
First Online: 15 July 2025
Declarations
:
: The authors declare no competing interests.