United States Department of Energy (DOE)

Submit ticket request  // Limit: 3*  // Tickets Available: 1 

An entity may submit only one Concept Paper and one Full Application for each topic area of this FOA.

With this FOA, SETO aims to promote innovative solar research, technology development, and product demonstration that can substantively increase U.S. domestic manufacturing across the solar energy supply chain and expand private investment in America’s solar manufacturing sector. These investments will help accelerate the growth of the solar industry, identify emerging opportunities, and drive down costs for our domestic energy market, positioning the United States on the leading edge of solar industry advances.

Topic Area 1: Solar Research and Technology Development
Topic Area 2: Solar Technology Demonstration
Topic Area 3: Solar Permitting Software Outreach, Education, and Development

Submit ticket request  // Limit: 1 // Tickets Available: 1 

An entity may submit only one Concept Paper and one Full Application to this FOA.

This FOA seeks applications for new and/or expanded water power incubation or accelerator programs to address the commercialization needs of entrepreneurs and small businesses in marine energy and/or hydropower. The strategic goals of this FOA are to:

• Foster business creation, innovation, and competition in the water power field.
• Increase the diversity of people, perspectives, and ideas in water power.
• Ease commercialization pathways for water power entrepreneurs and small businesses to accelerate the commercialization of water power systems and solutions.

Submit ticket request  // Limit: 24* // Tickets Available: 24 

*Applicant institutions are  limited to three pre-applications and three applications for each program (ASCR, BES, BER, FES, HEP, NP, DOE IP, ARDAP).

The Office of Science (SC) seeks applications for fundamental research in fields supported by SC to build research capacity at institutions historically underrepresented in the SC portfolio, i.e. non-R1 minority serving institutions (MSIs) and non-R1 emerging research institutions (ERIs). This FOA aims to build research capacity, including infrastructure and expertise at these institutions, through mutually beneficial relationships between applicants and DOE national laboratories, SC scientific user facilities, or R1 MSI/ERIs. 

SC supports fundamental research in applied mathematics, biology, chemistry, computer science, engineering, geoscience, isotope research, materials science, fusion energy science, and physics to transform our understanding of nature and catalyze scientific discoveries that can lead to technical breakthroughs. All applications to SC should focus on hypothesis-driven basic research. SC does not support applied research, product development, or prototyping.

Submit ticket request  // Limit: 4 // Tickets Available: 4

Applicant institutions are limited to no more than four (4) pre-applications or applications as a lead institution and no more than one pre-application or application for any individual PI.

The Department of Energy (DOE) Fusion Energy Science (FES) program is embarking on a transformative initiative aimed at creating a fusion innovation ecosystem, the “Fusion Innovation Research Engine (FIRE)”, by forming virtual, centrally managed teams called “Collaboratives”, that have a collective goal of bridging FES’s basic science research programs and growing fusion industries, including the activities supported under the FES milestone-based fusion development program.

At its core, FIRE represents a departure from traditional science programs. It is structured as a framework comprised of Collaboratives with the purpose of bridging the gap between foundational science and practical application. These Collaboratives are envisioned as dynamic hubs of innovation, driving advancements in fusion energy research in collaboration with both public and private entities. FES envisions the ecosystem surrounding the Collaboratives as a facilitator for collaboration and coordination with the basic science research program and other stakeholders, creating an engine for innovation. FIRE hopes to foster synergy and alignment of goals, accelerating progress towards the realization of fusion energy as a clean, sustainable power source. Moreover, this initiative aims to create new economic opportunities, bolster US-based manufacturing and supply chains, and enable the development of technologies crucial for national security, energy security, and defense.

FES envisions FIRE Collaboratives as a collection of virtual, centrally managed teams. These teams leverage expertise, capabilities, and facilities to systematically address FS&T gaps, fostering integrated research efforts, facilitating collaboration among diverse stakeholders, and enhancing communication to accelerate progress in enabling fusion energy. The term ‘fusion ecosystem’ refers to the network of collaborative relationships, resources, and initiatives aimed at advancing fusion energy. Within this ecosystem, FIRE Collaboratives serve as a pivotal component, driving coordinated efforts to address key challenges and accelerate advancements in fusion science and technology.

Submit ticket request  // Limit: 1 // Tickets Available: 1 

Universities are permitted to submit one single application to General Scientific Infrastructure (GSI) support section of this FOA area per institution. 

The Office of Nuclear Energy (NE) mission is to advance nuclear energy science and technology to meet U.S. energy, environmental, and economic needs. NE has identified the following goals to address challenges in the nuclear energy sector, help realize the potential of advanced technology, and leverage the unique role of the government in spurring innovation:

• Keep existing U.S. nuclear reactors operating

• Deploy new nuclear reactors

• Secure and sustain our nuclear fuel cycle

• Expand international nuclear energy cooperation

Collectively, all NE-sponsored activities support the Department’s priorities to combat the climate crisis, create clean energy jobs with the free and fair chance to join a union and bargain collectively, and promote equity and environmental justice by delivering innovative clean energy technologies for nuclear energy systems.

Within Nuclear Energy University Program (NEUP), the specific goals of this Infrastructure FOA are:

• To support, maintain, or enhance the institution’s capacities to attract and teach high quality students interested in nuclear energy-related studies;

• Build the institution’s research or education capabilities; and

• Enhance the institution’s capabilities to perform R&D that is relevant to NE’s mission.

The following targeted objectives within this Infrastructure FOA will aide in achieving these goals.

(1) Upgrade and improve U.S. university nuclear research and training reactors. Upgrades for a research reactor that include the acquisition of equipment and/or instrumentation for activities related to safety, performance, control, or operational reliability. For example, equipment acquired for security/safety enhancements required by the federal/state/local regulatory agencies is permitted.

(2) Obtain equipment and instrumentation that significantly improves or expands the research, instruction, training capabilities, and/or operating capabilities related to NE program missions (e.g., utilization or handling of radiological or radioactive materials). For example, this may include radiation detection and measurement equipment.

(3) Contribute to strengthening the academic community’s nuclear engineering infrastructure.

Requests should focus on individual, discrete, definable items or capabilities. An applicant must demonstrate the educational or R&D connection between requested pieces of equipment to support the NE mission. Applications made of several uncorrelated equipment requests are not of interest. A request should not duplicate existing capabilities. To review existing NE R&D capabilities in the United States, refer to the Nuclear Energy Infrastructure Database (NEID), available at https://nsuf-infrastructure.inl.gov (account login required). Information on current NE research programs can be found at NE’s website: https://energy.gov/ne.

No Applicants  // Limit: 3 // Tickets Available: 3 

Applicant institutions are limited to no more than 3 letters of intent, pre-applications, or applications as the lead institution per research area. There is no limitation to the number of applications on which an institution appears as a subrecipient or for which the institution is not the lead in a multi-institution team using collaborative applications.

The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in basic computer science and applied mathematics research in the fundamentals of Artificial Intelligence (AI) for science. Specifically, advancements in this area are sought that can enable the development of: 

• Foundation models for computational science;
• Automated scientific workflows and laboratories;
• Scientific programming and scientific-knowledge-management systems;
• Federated and privacy-preserving training for foundation and other AI models for science; and
• Energy-efficient AI algorithms and hardware for science.

No Applicants  // Limit: 5 // Tickets Available: 5 

Applicant institutions are limited to both: 

• No more than a total of five pre-applications or applications as the lead institution in a single- or multi-institutional team.
• No more than one pre-application or application for each PI at the applicant institution.

Extreme-scale science recognizes that disruptive technology changes are occurring across science applications, algorithms, computer architectures and ecosystems. Recent reports point to emerging trends and advances in high-end computing, massive datasets, visualization, and artificial intelligence on increasingly heterogeneous architectures. Significant innovation will be required in the development of effective paradigms and approaches for realizing the full potential of scientific computing from emerging technologies. Proposed research should not focus on a specific science use case, but rather on creating the body of knowledge and understanding that will inform future advances in extreme-scale science. Consequently, the funding from this FOA is not intended to incrementally extend current research in the area of the proposed project. It is expected that the proposed projects will significantly benefit from the exploration of innovative ideas or from the development of unconventional approaches.

Submit ticket request  // Limit: 2 // Tickets Available: 2

This three-phase competition will award up to $4 million to competitors to substantially increase the production and use of critical materials recovered from electronic scrap—or e-scrap. This prize encourages innovations that enhance the recovery of critical materials along the recycling value chain from end-of-life products to reintroduction. This internal competition is to determine two UT Austin candidates for Phase 1: Incubate Contest.

Phase 1 – Incubate:

Competitors will propose solutions that substantially increase the amount of recovered critical materials from e-scrap used in U.S. manufacturing. Up to 10 winners will receive $50,000 in cash and $30,000 in national laboratory analysis support.

No Applicants  // Limit: 5 // Tickets Available: 5 

Applicant institutions are limited to both: 

• No more than a total of five pre-applications or applications as the lead institution in a single- or multi-institutional team.
• No more than one pre-application or application for each PI at the applicant institution.

Extreme-scale science recognizes that disruptive technology changes are occurring across science applications, algorithms, computer architectures and ecosystems. Recent reports point to emerging trends and advances in high-end computing, massive datasets, visualization, and artificial intelligence on increasingly heterogeneous architectures. Significant innovation will be required in the development of effective paradigms and approaches for realizing the full potential of scientific computing from emerging technologies. Proposed research should not focus on a specific science use case, but rather on creating the body of knowledge and understanding that will inform future advances in extreme-scale science. Consequently, the funding from this FOA is not intended to incrementally extend current research in the area of the proposed project. It is expected that the proposed projects will significantly benefit from the exploration of innovative ideas or from the development of unconventional approaches.

 Limit: 15* // Tickets Available: 10

PO Confirmed DOE will accept 15 applications, 3 for each of the 5 research areas.

L. Xuan ( Computer science) - Research Area 2: AI Innovations for Scientific Knowledge Synthesis and Software Development
M. Chertkov (Pharmacy) - Research area 3: AI Innovations for Computational Decision Support of Complex Systems. 
R. Tandon (Electrical & Computer Engineering) // Subaward Lawrence Berkeley National Lab - Research Area 4: Federated and privacy-preserving for foundation and other AI models for science.
S. Salehi (Electrical and Computer Engineering) - Research Area 5: The Co-Design of Energy-Efficient AI Algorithms and Hardware Architectures. 
M. Krunz (Electrical & Computer Engineering) -  Research Area 5: The Co-Design of Energy-Efficient AI Algorithms and Hardware Architectures.
T. Adegbija (Electrical & Computer Engineering) -  Research Area 5: The Co-Design of Energy-Efficient AI Algorithms and Hardware Architectures.

The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in basic computer science and applied mathematics research in the fundamentals of Artificial Intelligence (AI) for science. Specifically, advancements in this area are sought that can enable the development of: 

• Foundation models for computational science;
• Automated scientific workflows and laboratories;
• Scientific programming and scientific-knowledge-management systems;
• Federated and privacy-preserving training for foundation and other AI models for science; and
• Energy-efficient AI algorithms and hardware for science.