Humankind has long studied natural systems to understand their complexity and to find motivation and inspiration for improving knowledge and design capabilities for a number of varied applications. These concepts are summarized in a term that has been used as the main keyword in many important research areas: biomimicry. Among all research fields, materials science has been, perhaps, the most influenced by nature. This chapter delivers the basic concepts of hierarchical structures and their universal/diverse features in order to present the most influential natural materials and compounds and their employment in synthetic made-up composites for tissue engineering and industrial applications. Later, we also show how artificial intelligence and machine learning algorithms have contributed to improve the characterization and design of natural and bio-inspired materials, optimizing the computational tools and overcoming the limitations of traditional approaches. We conclude with a deliberation to discuss future opportunities in the field.

Biomimicry for natural and synthetic composites and use of machine learning in hierarchical design

Libonati, Flavia;
2022-01-01

Abstract

Humankind has long studied natural systems to understand their complexity and to find motivation and inspiration for improving knowledge and design capabilities for a number of varied applications. These concepts are summarized in a term that has been used as the main keyword in many important research areas: biomimicry. Among all research fields, materials science has been, perhaps, the most influenced by nature. This chapter delivers the basic concepts of hierarchical structures and their universal/diverse features in order to present the most influential natural materials and compounds and their employment in synthetic made-up composites for tissue engineering and industrial applications. Later, we also show how artificial intelligence and machine learning algorithms have contributed to improve the characterization and design of natural and bio-inspired materials, optimizing the computational tools and overcoming the limitations of traditional approaches. We conclude with a deliberation to discuss future opportunities in the field.
2022
9780128210536
9780128210543
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1101496
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