AI-Enabled Design and Additive Manufacturing of Mechanical Materials: Methods and Future Directions
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Keywords
mechanical metamaterials, artificial intelligence, additive manufacturing, topology optimization
Abstract
This review provides a comprehensive overview of recent advancements in the development of mechanical metamaterials through the synergistic integration of artificial intelligence (AI) and additive manufacturing (AM). By combining computational design strategies with high-precision fabrication techniques, researchers can rapidly identify optimized microstructures and translate them into functional prototypes. This approach accelerates the exploration of multifunctional and adaptive metamaterials, enabling properties that are difficult to achieve with conventional materials. This paper highlights key methodologies for AI-assisted design and AM-based fabrication, examines their capabilities and limitations, and outlines workflows that bridge theoretical modeling and practical implementation. Emerging trends, including self-adaptive metamaterials and application-specific architectures, are discussed to provide guidance for future research. Overall, this review emphasizes how AI and AM collectively transform the landscape of mechanical metamaterial design, offering pathways toward faster innovation, enhanced performance, and real-world applicability.
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