Smart Additive Manufacturing: Bioinspired Algorithmic - Driven Design of Composites
Nano Seminar Series
Prof. Grace X. Gu, UC Berkeley, Mechanical Engineering
2:00pm - 3:00pm
Location: 390, Hearst Memorial Mining Building
After billions of years of evolution, it comes as no surprise that biological materials are identified as invaluable sources of inspiration in the search for new materials. Bone, teeth, and spider silk are high-performing biological composites that possess impressive mechanical properties unmatched by their engineering counterparts. Many required mechanical properties in engineering practice are inherently conflicting. In contrast, natural materials can often avoid these fundamental compromises through their sophisticated hierarchical structures. Additive manufacturing, with its layer-by-layer fabrication capabilities, facilitates leveraging natural material design to create complex bioinspired architectures.
Our research focuses on emulating the simple, yet elusive, design paradigms of nature – simple in their constituent building blocks and elusive in their underlying complexity. These concepts lay the foundation for our approach to design rationally toughened composites to be used in the energy, defense, medical fields, and beyond.
In this talk, I will discuss ways we have mimicked nature’s designs using simulation, additive manufacturing, and testing to investigate how to create synthetic materials with superior mechanical properties (e.g. toughness, strength, impact resistance). Additionally, I will discuss how to further improve and adapt biological designs for engineering requirements through machine learning. In the future, this bioinspired machine learning approach will enable materials-by-design of complex architectures to tackle demanding engineering challenges.
Grace Gu just completed her PhD at MIT and joined UC Berkeley this year. She was an NDSEG Fellow and MRS medal winner, and held internships at P&G, Boeing, and ExxonMobil.
Sponsor:Berkeley Nanosciences and Nanoengineering Institute
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