Journal of Computational Intelligence in Materials Science


Journal of Computational Intelligence in Materials Science (JCIMS) provides a forum for advance in-depth understanding of the relationship between computational intelligence structure including synthesis, structure, mechanical, chemical, electronic, magnetic, and optical properties, and functions of all kinds of materials. JCIMS aims to address solutions to current engineering problems in which computational materials, artificial intelligence methods, numerical techniques, expert systems, genetic algorithms, neural networks, process system design, engineering/materials/technological design, materials databases, computer-aided materials selection/design/manufacturing, computer-integrated material processing, casting, powder metallurgy, welding, sintering, plastic deformation of the relationship between all kinds of materials.

Most Recent

A Review on Background and Applications of Machine Learning in Materials Research

Robert Ahmed and Christna Ahler, University of Akureyri, 600 Akureyri, Iceland.

Pages : 077-087

DOI : 10.53759/832X/JCIMS202301008

Published On : June 30, 2023


Machine Learning Approches for Evaluating the Properties of Materials

Nanna Ahlmann Ahm, Department of Mechatronics, University of Southern Denmark, Denmark.

Pages : 067-076

DOI : 10.53759/832X/JCIMS202301007

Published On : June 10, 2023


Automated Design Using Machine Learning in Materials Engineering - An Explicit Forecasts

Birgir Guomundsson and Gunnar Lorna, Department of Physics, Roskilde University, 4000 Roskilde, Denmark.

Pages : 056-066

DOI : 10.53759/832X/JCIMS202301006

Published On : May 06, 2023


Nano-Antibacterial Materials as an Alternative Antimicrobial Strategy

Anandakumar H, Sri Eshwar College of Engineering, Coimbatore, India.

Pages : 045-055

DOI : 10.53759/832X/JCIMS202301005

Published On : April 28, 2023