Tutorial 8. Graphs and Networks for Complex Materials II: Biomimetic/Biological Materials, Machine Learning, and Intelligent Materials

ANCILLARYEVENT · MAR-8T · ID: MAR-8T

This is the second of a set of tutorials that detail the applications of graph theory and network science and across materials science and biology. Emerging from graph theory, network science has profoundly influenced diverse fields—from physics to biology and social sciences—by revealing deep connections between complexity of structures, their functions and dynamics. Graph-based structural descriptors replacing crystal order parameter for complex materials combining order and disorder, provide a rapidly expanding toolbox for the study of complex structured materials in soft matter physics, where complex structures offer previously inaccessible functionalities, exemplified by biological and biomimetic materials.

A growing frontier in soft matter physics applies graph- and network-based approaches to investigate the properties, functionalities, and self-assembly mechanisms of multiple functional materials essential for sustainability and other challenges facing humankind. This tutorial, building upon the fundamental concepts and tools introduced in the first tutorial, will offer practical examples where network science explains essential features of biological materials, as well as the intersection between graph theory and network science descriptions of materials with artificial intelligence (AI) and machine learning (ML). In the biological domain, we will discuss complexity and functionality of vascular and neuronal systems, demonstrating can deepen our understanding of complex biological structures processes and inform biomedical advances. By fostering cross-disciplinary insights and leveraging AI/ML advancements, this tutorial will illuminate how these technologies could reshape materials science, enabling rapid design seamlessly integrated with manufacturing of materials with exceptional properties. Frontiers in the design of intelligent materials and structures capable of information processing will be addressed as well. 

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