Frontiers of biological material intelligence

Abstract

Biological materials exhibit a form of intelligence that enables them to sense, adapt, and self-optimize in response to their environments. Unlike synthetic materials, which are often designed for singular, static functions, natural material systems integrate sensing, memory, and feedback directly into their architectures. As industries face increasing demands for resilience, sustainability, and efficiency, the development of intelligent materials has become a promising step toward the future of material innovation. Advances in artificial intelligence and machine learning, along with mathematical frameworks spanning graph theory and category theory, provide powerful tools to uncover the underlying design principles of intelligent biological materials. Simultaneously, digital fabrication methods, including additive manufacturing and biofabrication, allow the scalable realization of adaptive material systems. As the integration of deep biological insight, computational modeling, and advanced fabrication continues to evolve, it sets the stage for a profound shift in how we conceive, create, and deploy materials. Advancing this convergence will accelerate the development of intelligent systems that are capable of autonomous adaptation, long-term resilience, and embedded functionality across scales and environments.