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Mapping influences of AI for selected domains in material science and engineering: A systematic literature metadata analysis for research areas of high-entropy alloy and recycled aggregate concrete
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School of Engineering |
Bachelor's thesis
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en
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37
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This thesis applied methods and techniques mainly from the large-scale literature metadata analysis onto small-scale datasets with the aim of evaluating the influence of AI in specific research areas within material science and engineering field. These small-scale evaluations are done for the first time to reveal hidden patterns within the selected research areas. To conduct the analyses, a framework incorporating relevant research questions, quantitative indicators, and selected bodies of literature is established. Several quantitative indicators are selected based on literature review, and original materials for the studies are downloaded from Scopus based on certain search criteria. Multiple results are recorded and plotted based on the calculated values of quantitative indicators and random sampling process. Although the consistencies and reliabilities of them are not always guaranteed, some yield stable outcomes. Within the coverage of the sampled articles, the conducted analyses indicate that the impact of AI varies across different research area regarding knowledge extent, citation distribution, and methodological choice.