Context-Aware Learning for Inverse Design in Photovoltaics

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Program:
DIFFERENTIATE
Award:
$1,979,995
Location:
Ames, Iowa
Status:
ALUMNI
Project Term:
04/08/2020 - 05/31/2022
Website:

Critical Need:

The DIFFERENTIATE program seeks to leverage the emerging artificial intelligence (AI) revolution to help resolve the energy and environmental challenges of our time. The program aims to speed energy innovation by incorporating machine learning (ML) into the energy technology development process. A core part of AI, ML is the study of computer algorithms that improve automatically through experience. This approach is expected to facilitate a rapid transition to lower-carbon-footprint energy sources and systems. To organize the proposed efforts, the program uses a simplified engineering design process framework to conceptualize several ML tools that could help engineers execute and solve these problems in a manner that dramatically accelerates the pace of energy innovation.

Project Innovation + Advantages:

Iowa State University will develop novel machine learning tools to accelerate the inverse design of new microstructures in photovoltaics. The team will create a new deep generative model called bi-directional inverse design networks to combat challenges in real-world inverse design problems. The proposed inverse design tools, if successful, will produce novel, manufacturable material microstructures with improved electromagnetic properties relative to existing technology for better, more efficient solar energy.

Potential Impact:

DIFFERENTIATE aims to enhance the productivity of energy engineers in helping them to develop next-generation energy technologies. If successful, DIFFERENTIATE will yield the following benefits in ARPA-E mission areas:

Security:

Seek U.S. technological competitive advantage by leading the development of machine-learning enhanced engineering design tools.

Environment:

Use these tools to solve our most challenging energy and environmental problems by facilitating an economically attractive transition to lower carbon-footprint energy sources and systems.

Economy:

Reap the economic productivity benefits associated with the commercial adoption of the resulting higher-value energy technologies and associated products.

Contact

ARPA-E Program Director:
Dr. David Tew
Project Contact:
Prof. Baskar Ganapathysubramian
Press and General Inquiries Email:
ARPA-E-Comms@hq.doe.gov
Project Contact Email:
baskarg@iastate.edu

Partners

National Renewable Energy Laboratory

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Release Date:
04/05/2019