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Meeting 2023 TMS Annual Meeting & Exhibition
Symposium Nix Award and Lecture Symposium: Learning from Nature – From Insight to Sustainable Innovation
Presentation Title Deep Learning from Nature and Machines for Engineered and Biological Materials
Author(s) Subra Suresh
On-Site Speaker (Planned) Subra Suresh
Abstract Scope Rapid advances in computing and machine learning, along with developments in materials processing that mimic unique features and characteristics found in natural systems, offer unprecedented opportunities to design and deploy a new generation of engineered and biological materials. We demonstrate specific examples of materials design, analysis, or characterization using machine learning and biomimetics from the vantage point of three different disciplines: materials science, plant science, and biomedical science. The examples chosen here cover a spectrum of topics that include: modulating the bandgap of natural and engineered materials for applications in microelectronics, optoelectronics and energy systems; characterization of material properties at multiple length scales using multi-fidelity approaches in machine learning; design of new classes of plant-based materials with unique properties for environmental sustainability, soft robotics and flexible electronics; and machine-learning approaches combined with microfluidics and computational simulations to assess, monitor and guide clinical outcomes in such diseases as diabetic retinopathy.
Proceedings Inclusion? Planned: None Selected


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Bioinspired Designs for Micro-object Releasing
Deep Learning from Nature and Machines for Engineered and Biological Materials

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