Federal Bid

Last Updated on 02 Oct 2019 at 4 AM
Location Unknown

GEMINA FOA

Solicitation ID DE-FOA-0002174
Posted Date 02 Oct 2019 at 4 AM
Archive Date Not Specified
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Contracting Office Not Specified
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Location United states
Point Of Contact Not Available
Generating Electricity Managed by Intelligent Nuclear Assets(GEMINA) Agency Overview: The Advanced Research Projects Agency – Energy (ARPA-E), an organization within the Department of Energy (DOE), is chartered by Congress in the America COMPETES Act of 2007 (P.L. 110-69), as amended by the America COMPETES Reauthorization Act of 2010 (P.L. 111-358) to: “(A) to enhance the economic and energy security of the United States through the development of energy technologies that result in— (i) reductions of imports of energy from foreign sources; (ii) reductions of energy-related emissions, including greenhouse gases; and (iii) improvement in the energy efficiency of all economic sectors; and (B) to ensure that the United States maintains a technological lead in developing and deploying advanced energy technologies.” ARPA-E issues this Funding Opportunity Announcement (FOA) under the programmatic authorizing statute codified at 42 U.S.C. § 16538. The FOA and any awards made under this FOA are subject to 2 C.F.R. Part 200 as amended by 2 C.F.R. Part 910. ARPA-E funds research on and the development of high-potential, high-impact energy technologies that are too early for private-sector investment. The agency focuses on technologies that can be meaningfully advanced with a modest investment over a defined period of time in order to catalyze the translation from scientific discovery to early-stage technology. For the latest news and information about ARPA-E, its programs and the research projects currently supported, see: http://arpa-e.energy.gov/. Program Overview: The aim of this ARPA-E program is to make a transformational change to the current state-of-the-art and improve advanced reactor (AR) designs with operations and maintenance (O&M) in mind. Advances in autonomous, efficient, and low-cost systems O&M are occurring in many industrial sectors, largely powered by artificial intelligence (AI), advanced data analytics, distributed computing, powe
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