Artificial Intelligence in Material Engineering: A review on
applications of AI in Material Engineering
- URL: http://arxiv.org/abs/2209.11234v3
- Date: Thu, 27 Apr 2023 13:16:13 GMT
- Title: Artificial Intelligence in Material Engineering: A review on
applications of AI in Material Engineering
- Authors: Lipichanda Goswami, Manoj Deka and Mohendra Roy
- Abstract summary: High-performance computing has made it possible to test deep learning (DL) models with significant parameters.
generative adversarial networks (GANs) have facilitated the generation of chemical compositions of inorganic materials.
The use of AI to analyze the results from existing analytical instruments is also discussed.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The role of artificial intelligence (AI) in material science and engineering
(MSE) is becoming increasingly important as AI technology advances. The
development of high-performance computing has made it possible to test deep
learning (DL) models with significant parameters, providing an opportunity to
overcome the limitation of traditional computational methods, such as density
functional theory (DFT), in property prediction. Machine learning (ML)-based
methods are faster and more accurate than DFT-based methods. Furthermore, the
generative adversarial networks (GANs) have facilitated the generation of
chemical compositions of inorganic materials without using crystal structure
information. These developments have significantly impacted material
engineering (ME) and research. Some of the latest developments in AI in ME
herein are reviewed. First, the development of AI in the critical areas of ME,
such as in material processing, the study of structure and material property,
and measuring the performance of materials in various aspects, is discussed.
Then, the significant methods of AI and their uses in MSE, such as graph neural
network, generative models, transfer of learning, etc. are discussed. The use
of AI to analyze the results from existing analytical instruments is also
discussed. Finally, AI's advantages, disadvantages, and future in ME are
discussed.
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