Topic: Deep Generative Models Automated Crystalline Materials Inverse Design
Speaker: Dr. Zhenpeng Yao from Harvard and University of Toronto
We’re very pleased to host Dr. Zhenpeng Yao from Harvard and University of Toronto this week to present his work on "Deep Generative Models Automated Crystalline Materials Inverse Design".
Abstract
Many aspects of renewable energy, from its generation (e.g., high-efficiency photovoltaic cells) and storage (e.g., large-capacity battery electrodes) to its utilization (e.g., lightweight alloys), are profoundly associated with materials discovery. Energy materials, like battery electrodes, generally function in a complex chemical environment involving various processes. The design of better energy materials, therefore, requires a comprehensive understanding of the material behaviors upon operation. Traditionally, the discovery of new materials with targeted properties involves a large number of experimental trials, while these efforts are far from adequate considering the well-recognized near-infinite chemical space. The efficient investigation of the unexplored chemical space calls for automated techniques with smart navigation. In this talk, I will first give an overview of how simulations, cheminformatics, deep generative models, and robotics have been accelerating the materials design process. Followingly, I will demonstrate the realization of the generative design of reticular frameworks (e.g., MOFs and COFs) using a supramolecular variational autoencoder empowered automated nanoporous materials discovery platform.
Biography
Dr. Zhenpeng Yao is a postdoctoral research associate of Chemistry and Computer Science at Harvard and the University of Toronto. Zhenpeng received his B.Sc. and M.Sc. in Mechanical Engineering from the Huazhong University of Science and Technology in 2008 and Shanghai Jiao Tong University in 2012. Zhenpeng obtained his Ph.D. in Materials Science and Engineering from Northwestern University in 2018. Then Zhenpeng joined Harvard University as a postdoc fellow till now. Zhenpeng’s research interests cover advanced battery electrodes and electrolytes, solid-state conductors, 2D materials, reticular chemistry, cheminformatics, deep generative model-based materials inverse design.
Very much looking forward to the seminar – hope to see you all on Wednesday: (SGT) 9am, Wed, 3 Mar! https://mit.zoom.us/j/96231985116
Warmest regards, @Siyu Tian (Isaac) @kedar @Tonio
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