Artificial intelligence-based Modeling Mechanisms for Material Analysis and Discovery

Main Article Content

Do Hyeun Kim


Artificial intelligence-based materials application is one of the hot topics in the field of materials science. Materials are widely used in the space industry, cutting tools, thermal and electrical insulators, and refractory materials. The conventional experiments and statistical approaches usually require more resources and time. Thus, the need for Artificial intelligence applications in the simulation and exploration of novel materials is increasing. Recently, AI has been applied to materials for improving efficiency and prediction accuracy; however, there are many limitations due to the lack of benchmark datasets, advanced pre-processing mechanisms, prediction modelling mechanisms, and simulation tools in the materials literature. Thus it is challenging to identify optimal learning models, including algorithm selection, the architecture of models, data processing, and simulation mechanisms. In this paper, we attempt to review experimental and computational data-based AI mechanisms. Furthermore, the current research status is analyzed for using artificial intelligence techniques in material simulation tools and discovering new materials. Finally, we present research issues of AI-based application realization in materials science.

Article Details

How to Cite
Imran, & Kim, D. H. (2022). Artificial intelligence-based Modeling Mechanisms for Material Analysis and Discovery. Journal of Intelligent Pervasive and Soft Computing, 1(01), 10–15. Retrieved from
Computer Science and Multidisciplinary research
Author Biographies

Imran, Engineering Department, Jeju National University, Jeju-si 63243, Korea.

Imran obtained his Ph.D. from the computer engineering department at Jeju National University, the Republic of Korea. He worked as a researcher with MCL and JNU Big Data lab. Currently, He is an assistant professor at the department of biomedical engineering of Gachon University, South Korea. His working interests include software development, IT convergence solutions, and entrepreneurship. His research mainly focuses on interdisciplinary scientific applications based on the Internet of Things, Machine learning, Data science, and BlockChain.

Do Hyeun Kim, Engineering Department, Jeju National University, Jeju-si 63243, Korea.

Do Hyeun Kim received the B.S. degree in electronics engineering and the M.S. and Ph.D. degrees in information telecommunication from Kyungpook National University, South Korea, in 1988, 1990, and 2000, respectively. He was with the Agency of Defense Development (ADD), from 1990 to 1995. Since 2004, he has been with Jeju National University, South Korea, where he is currently a Professor with the Department of Computer Engineering. From 2008 to 2009, he was a Visiting Researcher with the Queensland University of Technology, Australia. His research interests include sensor networks, M2M/IOT, energy optimization and prediction, intelligent service, and mobile computing.


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