Artificial Intelligence Reinventing Materials Engineering: A Bibliometric Review

Author:

Vergara Diego1ORCID,Lampropoulos Georgios23ORCID,Fernández-Arias Pablo1ORCID,Antón-Sancho Álvaro1ORCID

Affiliation:

1. Technology, Instruction and Design in Engineering and Education Research Group (TiDEE.rg), Catholic University of Ávila, C/Canteros s/n, 05005 Ávila, Spain

2. Department of Applied Informatics, University of Macedonia, 54636 Thessaloniki, Greece

3. Department of Education, University of Nicosia, 1700 Nicosia, Cyprus

Abstract

The use of artificial intelligence (AI) is revolutionizing many professions and research fields. Thus, the present study focuses on the implications that AI is having on research in materials science and engineering (MSE). To this end, a bibliometric review has been conducted to analyze the advances that AI is generating in MSE. Although expectations for AI advances in the field of MSE are high, the results of this study indicate that we are still at a preliminary stage of development. It is worth highlighting that despite the progress made, the potential of AI in MSE has not been fully exploited and numerous challenges remain to be overcome to achieve effective and widespread implementation. It should be noted that the subarea “Materials structure, processing, and properties” is the one that currently presents the largest number of research works linked to AI. It appears that the United States and China are currently the countries with the greatest involvement in the use of AI in the field of MSE. The emerging themes and thematic map of the topic are revealed, and future research directions are provided.

Publisher

MDPI AG

Reference29 articles.

1. (2024, June 02). Materials Research Society—2021 MRS Fall Meeting & Exhibit. Available online: https://www.mrs.org/past-fall-meetings/2021-mrs-fall-meeting.

2. The bibliometric analysis of scholarly production: How great is the impact?;Ellegaard;Scientometrics,2015

3. Which academic search systems are suitable for systematic reviews or meta-analyses? Evaluating retrieval qualities of google scholar, PubMed, and 26 other resources;Gusenbauer;Res. Synth. Methods,2020

4. How to conduct a bibliometric analysis: An overview and guidelines;Donthu;J. Bus. Res.,2021

5. Bibliometrix: An r-tool for comprehensive science mapping analysis;Aria;J. Informetr.,2017

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