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:

Technology Description:

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