Abstract

Artificial Intelligence (AI) is a broad discipline that uses powerful algorithms to emulate important aspects of human intelligence. Provided by the Industry 4.0 revolution, AI is increasingly applied in different fields from research to production. One of these fields is Materials Science and Engineering (MSE) which studies the relationships between processing, structure, properties, and performance of materials. The application of AI to MSE has triggered the invention of new materials to satisfy the demanding requirements in myriad sectors through the years. In this context, the “MSE paradigm” emerged as a framework to define these relationships supported by the available technologies at the corresponding time. This is how Polymer Matrix Composites (PMC) were synthesized. During the last years, they have turned from a futuristic solution to a necessity due to the wide range of advantages they offer concerning other conventional materials. The present work presents a modified approach to the MSE paradigm with the application of AI algorithms. An overview of the research advances from 2003 to 2019 in each fundamental link of the proposed MSE paradigm for PMC is exhibited in an organized fashion. This article must serve engineers and scientists working at the intersection of mechanical engineering, materials science and computer science to identify trendy topics in these fields. It aims to represent a starting point for developing innovative methods and proposing new research topics in the framework of the MSE paradigm powered by AI for PMC.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.