NAVER LABS Europe seminars are open to the public. This seminar is virtual and requires registration
Date: 12th April 2022, 5:00 pm (CEST)
The Open Catalyst Project: using AI to help address climate change.
Abstract: The Open Catalyst Project’s goal is to use AI to model and discover new catalysts for use in renewable energy storage and other applications to help in addressing climate change. As we increase our reliance on renewable energy sources such as wind and solar, which produce intermittent power, storage is needed to transfer power from times of peak generation to peak demand. This may require the storage of power for hours, days, or even months. One solution that offers the potential of scaling to nation-sized grids is the conversion of renewable energy to other fuels, such as hydrogen. To be widely adopted, this process requires cost-effective solutions to running chemical reactions.
An open challenge is finding low-cost catalysts to drive these reactions at high rates. Through the use of quantum mechanical simulations (density functional theory), new catalyst structures can be tested and evaluated. Unfortunately, the high computational cost of these simulations limits the number of structures that may be tested. The use of AI or machine learning may provide a method to efficiently approximate these calculations, leading to new approaches in finding effective catalysts.
In this talk, I describe the Open Catalyst Project, current progress, and why this is such a challenging and interesting machine learning problem. The Open Catalyst Project is a collaborative research effort between Facebook AI Research (FAIR) and Carnegie Mellon University’s (CMU) Department of Chemical Engineering.
About the speaker: Larry Zitnick is a research director at Meta AI Research. He is currently focused on scientific applications of AI and machine learning, such as the discovery of new catalysts for renewable energy applications. Previously, his research in computer vision covered many areas such as the FastMRI project to speed up the acquisition of MRIs, and the COCO and VQA datasets to benchmark object detection and visual language tasks. He developed the PhotoDNA technology used by Microsoft, Facebook, Google, and various law enforcement agencies to combat illegal imagery on the web. Before joining FAIR (now Meta AI Research), he was a principal researcher at Microsoft Research. He received the PhD degree in robotics from Carnegie Mellon University.