Materials for a Sustainable Energy Future

September 9 - December 13, 2013

Overview

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A secure and sustainable energy future that is not based on a fossil-fuel based infrastructure requires the design of new materials for efficient energy conversion, transport, and storage. Indeed, materials development is a rate limiting step in many potential new energy conversion strategies, impacting the efficiency of photovoltaic solar cells, the storage capacity and power density of batteries for automobile applications, the synthesis of liquid fuels, and the catalysis and durability of energy conversion in fuel cells.

A key bottle-neck in this historic transition is the wide range of length scales present in the morphology and time scales in the transport phenomena. Serious progress in the development of new materials requires predicative modeling which surmounts the particle-continuum divide. Recent developments in macro-micro modeling, incorporating machine and manifold learning, combined with new classes of continuum models and increases in computational resources, provide a new framework with which to develop a fundamental understanding of complex materials; it is becoming possible to design new materials from first principles.

Creating interactions between people with different expertise and a common goal will facilitate breakthroughs in predictive materials design. This program will bring together researchers from mathematics, physics, materials science, engineering, chemistry, biology, computer sciences, and other sciences with the goal to understand the mathematical structure of continuum models governing material properties as well as the electronic, atomic, and molecular structure of such new materials.

This program is part of the Initiative “Mathematics of Planet Earth” which is an international endeavor involving a wide range of partners and activities.Mathematics of Planet Earth

Organizing Committee

Martin Bazant (Massachusetts Institute of Technology)
Giulia Galli (University of California, Davis (UC Davis))
Graeme Henkelman (University of Texas at Austin)
Keith Promislow (Michigan State University)
Matthias Scheffler (Fritz-Haber-Institut der Max-Planck-Gesellschaft)