Innovation in Materials: Key Steps for Algorithm Selection in Predicting Mechanical Characteristics through Machine Learning

The central importance of materials in society and their relationship with various properties is highlighted. The growing relevance of artificial intelligence (AI), especially machine learning (ML) and deep learning algorithms, in mechanical engineering and materials science is emphasized. The ability of AI to predict features and create innovative materials is highlighted. Furthermore, the crucial steps for applying ML in materials innovation are described, from data collection and cleaning to algorithm selection and optimization, emphasizing the importance of understanding the nature of data and model validation. Finally, a comprehensive overview of the integration of AI and ML in materials research is provided, highlighting their fundamental role in the optimization and prediction of mechanical properties.