Grants / Department of Energy / Office of Science

DE-FOA-0002474: Data Science to Advance Chemical and Materials Sciences

Closed Closed June 8, 2021 Opportunity DE-FOA-0002474 ☆ Save

This grant is closed. A newer notice from the same program is open now: Genesis Mission Graduate Fellowship Pilot (DE-FOA-0003673). Status: Closes January 12, 2027 (66 days left). It is in our archive of Office of Science notices from 2021.

• Award ceiling$1.2 million
• Award floor$400,000
• Total funding$21.0 million
• Cost sharingNot required
• Funding typeGrant

Key dates

Who can apply

This opportunity was open to any type of organization.

• Unrestricted (i.e., open to any type of entity above), subject to any clarification in text field entitled "Additional Information on Eligibility"

More grants for nonprofits, colleges and universities, state and local governments, tribes, small businesses, businesses, individuals.

Is this a realistic fit?

• Past Office of Science Financial Assistance Program awards averaged $1.2 million; this notice allows up to $1.2 million per award.
• Most of the program's money (69% over five years) went to colleges and universities.
• No cost sharing or match is required.

What the grant funds

The DOE SC program in Basic Energy Sciences (BES) announces its interest in receiving new applications from teams of investigators expanding the integration of data science methods with BES research disciplines, to accelerate scientific discovery and overcome difficult challenges in these fields. This FOA is focused on new applications that will take advantage of the rapid growth of data science, including artificial intelligence (AI) and machine learning (ML) methodologies. The FOA will support teams of investigators for synergistic computational, experimental, and theoretical research covered by the research areas in the BES divisions of Chemical Sciences, Geosciences, and Biosciences (CSGB) and Materials Sciences and Engineering (MSE). The focus of the proposed research must be on science-based, data-driven approaches enabling solutions for fundamental basic energy sciences challenges not possible otherwise. The goal of the application should be to integrate novel data science, uncertainty quantification, and other AI and ML approaches with domain sciences to uniquely advance the understanding of fundamental properties and processes relevant to chemical and materials systems, and achieve predictability of functions and behavior under dynamic conditions.

Category: Science and Technology and other Research and Development.

Applying now

This notice no longer takes applications. Apply under the newer notice, DE-FOA-0003673, which is open now.

The notice on Grants.gov keeps its full text and attachments, which is useful for planning a resubmission.