The AI-Driven Transformation in New Materials Manufacturing and the Development of Intelligent Sports

The advancement of materials science has had a profound, even revolutionary, impact on sports. Materials are used in the sports field, equipment, and sportswear, each with distinct functionality and safety requirements. Additionally, diverse sport-related data require physical devices for collection, analysis, and storage, which can be crucial in athlete selection, performance assessment, strategy planning, and training optimization. Artificial intelligence, with its strong cognitive abilities, learning capacity, large-scale data processing, and adaptability, can effectively enhance efficiency, reduce errors, and lower costs. The integration of advanced materials and artificial intelligence (AI) has significantly enhanced the efficiency and precision of research and development in sports-related technologies, while also facilitating the innovation of training methodologies through intelligent data analytics. This convergence has initiated a transformative phase in the digitalization of the sports industry. Anchored in both theoretical analysis and practical implementation, this study seeks to construct a systematic cognitive framework that elucidates the interrelationship between material science and AI technologies. The aim is to assist sports professionals in understanding and leveraging this technological shift to support strategic decision-making and to foster sustainable, high-quality development within the field.

Authors

Institutions

Publication Details

Journal
Applied Sciences
Published
2025-05-19
DOI
https://doi.org/10.3390/app15105667
Citations
7
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
3.62

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The AI-Driven Transformation in New Materials Manufacturing and the Development of Intelligent Sports

Fang Wang, Jun Li, Shenhao Jiang
7 citations
Applied Sciences
Machine Learning in Materials Science
3.62
article

The AI-Driven Transformation in New Materials Manufacturing and the Development of Intelligent Sports

Fang Wang, Jun Li, Shenhao Jiang
article en
7 citations

Abstract

The advancement of materials science has had a profound, even revolutionary, impact on sports. Materials are used in the sports field, equipment, and sportswear, each with distinct functionality and safety requirements. Additionally, diverse sport-related data require physical devices for collection, analysis, and storage, which can be crucial in athlete selection, performance assessment, strategy planning, and training optimization. Artificial intelligence, with its strong cognitive abilities, learning capacity, large-scale data processing, and adaptability, can effectively enhance efficiency, reduce errors, and lower costs. The integration of advanced materials and artificial intelligence (AI) has significantly enhanced the efficiency and precision of research and development in sports-related technologies, while also facilitating the innovation of training methodologies through intelligent data analytics. This convergence has initiated a transformative phase in the digitalization of the sports industry. Anchored in both theoretical analysis and practical implementation, this study seeks to construct a systematic cognitive framework that elucidates the interrelationship between material science and AI technologies. The aim is to assist sports professionals in understanding and leveraging this technological shift to support strategic decision-making and to foster sustainable, high-quality development within the field.

Applied SciencesVol. 15(10)
Chongqing University (CN)
Ministry of Education, India
Openalex Percentile: Top 7%
Machine Learning in Materials Science
3.62
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.