crossrefNext MaterialsCited by 0

Machine learning and AI-driven digital twins in manufacturing of advanced metal alloys and compounds: A review

Mohsen Soori, Behrooz Arezoo

Related papers

crossrefNext Materials2026-07-01Cited by 1

A review on bearing fault diagnosis methods with emphasis on machine learning and deep learning applications

Prachi Dixit, Pawan Pingle, Adinath Funde, Kedarnath Chaudhary, Vikas Kanake

semantic_scholarNext Materials

An explainable machine learning framework for predicting the compressive strength of sustainable metakaolin mortars

View free PDFSource page

semantic_scholarNext Materials

Ensemble machine learning models for predicting mechanical properties of epoxy-based nanocomposites

O. Pastukh, Andrii Buketov, O. Totosko, Vitaliy Sotsenko, E. Appazov, Yuriy Petrov, et al.

View free PDFSource page

semantic_scholarNext Materials

A numerical investigation of carbon conversion using a random pore model in gasification process for selected carbonaceous feedstocks, kinetics studies, artificial intelligence and machine learning applications

View free PDFSource page

semantic_scholarNext Materials

Effect of tensile testing parameters on the mechanical performance of Poulsenia Armata fiber cloth: Experimental analysis and machine learning modeling

Germán Omar Barrionuevo, Wilson Navas-Pinto, Xavier Sánchez-Sánchez, M. Zylberberg, D. Cree

View free PDFSource page

semantic_scholarNext Materials

Predictive modelling of surface and wetting behaviour in diamond-reinforced zinc coatings using machine learning

S. Awasthi, Lokesh Kumar, Ashish Goyal

View free PDFSource page