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AI Model Development for Energy Systems

Active

Grant

Response Deadline12/17/2026, 05:00:00 AM UTC

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

AI Contract Overview

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The contract involves the development of artificial intelligence models specifically designed for energy systems, including fusion energy, grid optimization, and battery materials. The primary goal is to achieve measurable improvements in these areas compared to conventional non-AI methods. This initiative reflects a focus on advancing technology to enhance energy efficiency and innovation through AI-driven solutions. Issued by the Department of Energy’s Office of Science, the contract is a subcontract opportunity under NAICS code 541715. It was posted on March 17, 2026, with a response deadline set for December 17, 2026. While specific location details for performance and points of contact are not provided, the project emphasizes cutting-edge research and development in key energy sectors, supporting the broader objective of modernizing the energy infrastructure through artificial intelligence.

General Info

Development of AI models for fusion energy, grid optimization, and battery materials by 2026 deadline.

Agency

Department Of Energy - Office Of ScienceView Agency

NAICS

541715 - Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology) View NAICS

Place of Performance

Not specified

Set-Aside

NONE

Documents

(0)

No documents available

AI Contract Breakdown

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Timeline

PostedMar 17

subcontract

Response DeadlineDec 17

Submission deadline

Response Deadline

12/17/2026, 05:00:00 AM UTCin 6 months

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Organization & Contact Information

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AgencyDepartment Of Energy - Office Of Science

ContactsNo contacts available

OfficeN/A

Organization / Agency

Department Of Energy - Office Of Science

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Office AddressN/A

ContactsNo contact information available

Full Description

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Develop AI models for energy systems such as fusion, grid optimization, and battery materials, with measurable improvement over non-AI methods.

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