Collaboration

Request Ticket // Limit: 1 // Tickets Available: 1

Limiting Language
Applicant institutions are limited to no more than 1 letter of intent or proposal as the lead institution.   

There is no limitation to the number of proposals 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. 

Should DOE receive submissions in excess of the applicable limits, DOE reserves the right, in its sole discretion, to request additional or clarifying information to ascertain the institution’s intended submissions.  Otherwise, DOE will consider the latest received submissions to be the institution’s intended submissions. 

• Letters of intent in excess of the limited number of submissions will be discouraged. 
• Proposals in excess of the limited number of submissions will be declined without review. 

Executive Summary
The Department of Energy (DOE) Office of Science (SC) program in Advanced Scientific Computing Research (ASCR) hereby announces interest in receiving applications to develop a concerted quantum computing verification and validation capability.  This effort should consist of interdisciplinary multi-institutional teams addressing the challenge of characterizing performance of fault-tolerant quantum computers that will accelerate scientific discovery and enable new computational workflows.  Successful efforts are expected to develop and apply a complete set of necessary tools and expertise to perform performance verification of fault tolerant quantum computers.  They should address multiple qubit technologies and be designed with enough flexibility to accommodate the rapidly evolving needs of the DOE. 

Proposed efforts should develop new and adapt existing tools for characterizing the quantum computing stack: physical hardware; quantum gates; logical quantum architecture; quantum algorithm and applications, and classical control. These teams will pave the way for the deployment of a first-of-a-kind scientifically relevant fault-tolerant quantum computing capability for the Nation, advancing DOE's mission, and ensuring America’s security, economic and scientific competitiveness, and prosperity.  Teams are encouraged to leverage the extensive scientific software, hardware, algorithms, and data resources developed under the ASCR and SC quantum-computing-related solicitations and by U.S. industry and academia.  The resulting tools, applications, and workflows may be integrated into the Genesis Mission infrastructure platform and the American Science Cloud for broad adoption by research communities. 

Proposed efforts must focus on the developing, testing, and applying algorithms, benchmarks, and software tools for real-world quantum systems.  Teams must validate their tools by demonstrating successful performance verification of the state-of-the-art quantum hardware.  Quantum hardware research and development efforts are out of scope, unless they are essential for tools development and validation.  ASCR anticipates that teams will engage in multiple quantum hardware evaluations in parallel across several qubit technologies, and the size and composition of the teams should be appropriate to meet this requirement. 

Limit: 1 // Tickets Available: 0

D. Ebert (Office of Research and Partnership)

Limiting Language
Limit on Number of Proposals per Organization: 1

The PI institution may submit only one proposal for each competition (deadline) specified in the solicitation.

Limit on Number of Proposals per PI or co-PI: 1

An individual may participate in at most one State and Regional AI Infrastructure Hubs proposal as PI, co-PI, or Senior/Key Personnel for each deadline. If an individual exceeds this limit, only the first proposal received will be accepted, and the remainder will be returned without review. This rule does not apply to advisory roles.

Program Overview
The NSF State and Regional AI Infrastructure Hubs program aims to expand access to the compute required for AI-enabled scientific discovery and to transform the research, education, and training opportunities offered by institutions of higher education. AI Infrastructure Hubs will connect researchers to new compute infrastructure that leverages contributions from state governments, research institutions, industry, and philanthropy, accelerating AI-enabled discovery across science and engineering and developing a skilled technical workforce for AI use in the scientific enterprise.

The program responds to a core tenet of Science: A New Golden Age to renew America's research and development (R&D) for changes in today's scientific enterprise, including the role of AI in laying the foundation for a new era of scientific discovery and the growing role of industry and philanthropy in funding R&D. In response, the Administration's FY28 R&D Priorities Memorandum called for investing in AI for science as a national mission and expanding the scale of, and flexible access to, advanced compute and data infrastructure that researchers now require for frontier scientific discovery.

Each AI Infrastructure Hub will be organized as a flexible state or regional consortium of state and local governments, research institutions, philanthropies, and the private sector. Consortia will be responsible for all funding for new or expanded computing, data, and AI resources, whether on-premises or cloud-based. NSF will fund each Hub's consortium coordination, AI infrastructure workforce development, and faculty training and coursework development in leveraging AI for science.

Limit: 2 (one per priority outcome area)// Tickets Available: 0

Priority Outcome Areas
Priority program outcomes are (1) Water for Energy Reliability and Reservoir Resilience and (2) Energy-Water Efficiency and Industrial Success

1. Water for Energy Reliability and Reservoir Resilience
   C. Chen (Hydrology and Atmospheric Sciences)
2. Energy-Water Efficiency and Industrial Success
   A. Achilli (Chemical and Environmental Engineering)

Limiting Language
Offeror may submit multiple white papers in response to this BAA but may only submit one white paper under each priority outcome area.

Description
The primary objective of the National Science Foundation’s Energy Water Security Initiative (EWSI) is to secure American energy and national infrastructure resilience by producing measurable reductions in vulnerabilities where water scarcity threatens energy production, baseload stability, and industrial water extraction. This effort aims to accelerate deployment of technical solutions, with a priority focus on the systemic crisis within the Colorado River Basin. 

The NSF Energy Water Security Initiative seeks to develop the critical framework needed for research and development and accelerated, high-impact deployment. This initiative implements a two-phase program. Phase 1 awardees receive resources to develop consortia comprising multi-sector partnerships that can deliver on the goals of this initiative. Consortia should include regional partners and provide the collaborative infrastructure needed to accelerate development and deployment of technical capabilities. Phase 2 awardees will receive significant resources to expand the scale of projects leading to rapid completion and deployment of secure, public-domain technologies. The NAICS code for this BAA is 813920 (Professional Organization), which is a consortium focused on promoting professional research interests

 

Ticket Request Deadline -  The deadline to request a ticket for this funding opportunity was 5:00PM Monday, April 6. No additional tickets will be issued. 

Limit: 1 Phase I or Phase II Application per Focus Area (99 total) - Each PI may only submit one proposal but can be senior/key personel on an unlimited number of proposals

Topic Area 1: Reenvisioning Advanced Manufacturing and Industrial Productivity // Limit: 6 // Tickets Available: 3
Focus Area A - Agentic AI-Driven Chemical Manufacturing (BES) - OPEN
Focus Area B - AI-Driven Materials Processing (BES) - H. Kim (Civil and Architectural Engineering and Mechanics)
Focus Area C - AI-Enabled Manufacturing for Extreme Energy Systems (FES) - OPEN 
Focus Area D: Digitalization of Industrial Processes (ITO) – M. Shafae (Systems and Industrial Engineering)
Focus Area E: AI-Enabled Smart Manufacturing (AMMTO) - P. Satam (Systems and Industrial Engineering) 
Focus Area F: Energy Material Manufacturing (AFFO) - OPEN

Topic Area 2: Scaling the Biotechnology Revolution // Limit: 5 // Tickets Available: 2
Focus Area A: Biomolecular Science (BER) – T. Wheeler (Pharmacy Practice and Science)
Focus Area B: Genotype to Phenotype (BER) L. Meredith (School of Natural Resources and the Environment
Focus Area C: Predictive Engineering of Microbial Communities (BER) – M. Tfaily (Environmental Sciences) 
Focus Area D: Bio Design (BER) - OPEN
Focus Area E: AI-Enabled Biological Reaction Engineering, Bioreactor Design, Process Scale-up
and Integration (AFFO) - OPEN

Topic Area 3: Securing America’s Critical Minerals Supply // Limit: 7 // Tickets Available: 3
Focus Area A: Resource Mapping and Development (AMMPTO) – J.G. Duan (Civil and Architectural Engineering and Mechanics)
Focus Area B: AI-Enabled Materials Discovery and Engineering (AMMTO) – J.L. Bredas (Chemistry and Biochemistry)
Focus Area C: Economic Modeling and Market Analysis (ASO) - OPEN
Focus Area D: Extraction and Processing Technologies (AMMPTO, AMMTO) - N. Risso (Mining Engineering and Mineral Resources)
Focus Area E: Geological Finder/Keepers – OPEN
Focus Area F: Connections for Isolation (BES) - OPEN 
Focus Area G: Biological Pathways to CMM (BER) - Y. Song (Hydrology and Atmospheric Sciences)

Topic Area 4: Delivering Nuclear Energy that is Faster, Safer, Cheaper // Limit: 8 // Tickets Available: 8
Focus Area A - Accelerated Nuclear Power Plant Design and Licensing: Create an automated
process to enable rapid design, including safe and secure autonomous monitoring
and control of plant operations, licensing considerations, and rapid deployment of
advanced nuclear technologies using AI - OPEN
Focus Area B - Autonomous Power Plant Operations: Develop AI digital twin systems that
interpret plant operational data in real time, detect anomalies, and recommend
preemptive actions to maintain safety and operational performance - OPEN
Focus Area C: AI-Assisted Manufacturing and Construction: Support site selection, born certified
manufacturing, construction, supply chain reliability, and factory modular
production methods with AI technologies - OPEN 
Focus Area D: Autonomous Research and Development: Condense nuclear material research and
qualification timeframes using AI-driven pipelines for modeling, characterization,
evaluation, and qualification, while integrating decades of global historical
irradiation data - OPEN
Focus Area E: Accelerated Fuel Cycle Facility Design and Licensing to Secure the Domestic Fuel
Supply: Create automated processes to enable rapid design, licensing
considerations, and accelerated deployment of advanced fuel cycle technologies
using AI - OPEN
Focus Area F: AI-Assisted Site Characterization: Accelerate waste disposition site characterization
through AI Modeling - OPEN
Focus Area G: AI-Assisted End Disposition Design: Concept Design for Disposal of Used Nuclear
Fuel and Reprocessed Fuel Waste Streams - OPEN
Focus Area H: Development, Utilization and/or Adoption of AI and ML Tools to Support the
Efficient Review, Classification and Release of Legacy Documents to the Nuclear
Industry - OPEN

Topic Area 5: Accelerating Delivery of Fusion Energy // Limit: 7 // Tickets Available: 5
Focus Area A: Structural Materials (FES) - OPEN
Focus Area B: Plasma-Facing Materials (FES) - OPEN
Focus Area C: Advancing Confinement Approaches – C. Chan (Steward Observatory and Department of Astronomy)
Focus Area C: Advancing Confinement Approaches (FES) - OPEN
Focus Area D: Fuel Cycle and Tritium Processing (FES, NE) - OPEN
Focus Area E: Tritium Breeding Blankets (FES, NE) - OPEN
Focus Area F: Fusion Plant Engineering and System Integration – D. Ebert (Electrical and Computer Engineering)
Focus Area G: Plasma Science and Technology (FES) - OPEN

Topic Area 6: Transforming Nuclear Restoration and Revitalization // Limit: 3 // Tickets Available: 3
Focus Area A: EM AI R&D Roadmap Implementation (EM-3.2, ASCR, LM) - OPEN
Focus Area B: Scale-Bridging AI Foundation Model (EM-3.2, ASCR) - OPEN
Focus Area C: Treatment Process Optimization (EM-3.2, ASCR) - OPEN

Topic Area 7: Discovering Quantum Algorithms with AI // Limit: 5 // Tickets Available: 3
Focus Area A: Application-aware Error Correction (ASCR) - OPEN
Focus Area B: Computational Tools for Fault Tolerant Quantum Computational Science (ASCR) - OPEN
Focus Area C: Hybrid Quantum-Classical Optimization Algorithms (BES) - J. Chen (Electrical and Computer Engineering)
Focus Area D: Quantum Algorithms for Nonlinear Plasma Physics (FES) - OPEN
Focus Area E: Quantum Advantage for Nuclear and Hadronic Systems (NP, HEP) – P. Siwach (Physics)

Topic Area 8: Realizing Quantum Systems for Discovery // Limit: 4 // Tickets Available: 2
Focus Area A: AI for Quantum Systems Design - OPEN
Focus Area B: AI for Control of Quantum System (HEP, NP) - OPEN
Focus Area C: AI for Quantum Imaging and Sensing (HEP, NP) – D. Soh (Wyant College of Optical Sciences) 
Focus Area D: AI for Quantum Computing and Networking (ASCR) – N. Rengaswamy (Electrical and Computer Engineering)

Topic Area 9: Recentering Microelectronics in America // Limit: 10 // Tickets Available 4
Focus Area A: Angstrom (sub-1-nm) Scale Microelectronics Manufacturing (AMMTO) - OPEN
Focus Area B: Materials and Architectures for Non-von Neuman Computing Devices (BES) – X. Yan (Materials Science and Engineering)
Focus Area C: AI-Driven Architecture Design (ASCR) – J. Dass (Electrical and Computer Engineering)
Focus Area D: 3D Non-Volatile Compute-In-Memory Technology (ASCR) – S. Salehi (Electrical and Computer Engineering) 
Focus Area E: Physics-Based Circuit Design, Simulation, and Emulation (ASCR) – H. Yang (Electrical and Computer Engineering)
Focus Area F: Microelectronics in Harsh Environments (HEP) - J. Roveda (Electrical and Computer Engineering)
Focus Area G: Plasma-Enabled Microelectronics Manufacturing (FES) -OPEN
Focus Area H: Power Electronics and Communication Networks (ASCR) - OPEN
Focus Area I: Low-temperature Electronics for Sensors and Computation (ASCR, HEP) – M. Hassan (Physics)
Focus Area J: Transform Neuromorphic Computing Connectivity, Communication, and System
Hardware Integration (ASCR) - OPEN

Topic Area 10: Securing U.S. Leadership in Data Centers // Limit: 2 // Tickets Available: 2
Focus Area A: Data Center Load Flexibility (ITO) - OPEN
Focus Area B: Data Center Thermal Management (ITO) - OPEN

Topic Area 11: Achieving AI-Driven Autonomous Laboratories // Limit: 5 // Tickets Available: 2
Focus Area A: Advanced Robotics for Dynamic Laboratory Environments (ASCR) - S. He (Electrical and Computer Engineering)
Focus Area B: AIOps - AI for Network Operations (ASCR) - OPEN
Focus Area C: AI-Accelerated Science: Correlation to Understanding (BES) - A. Black (Information Science)
Focus Area D: AI-Enabled Diagnostics and Remote Handling (FES) - B. Liu (Electrical and Computer Engineering)
Focus Area E: Accelerate the design and prototyping of neuromorphic computing circuit primitives for robotic embodied physical artificial intelligence (ASCR) - OPEN

Topic Area 12: Designing Materials with Predictable Functionality // Limit: 7 // Tickets Available: 4
Focus Area A: Functional to Quantum Materials (BES) - OPEN
Focus Area B: Structural Materials (BES, FES, AMMTO) - M. Latypov (Materials Science and Engineering) 
Focus Area C: Biomolecular Materials (BES) - OPEN
Focus Area D: Plasma-Facing Materials (FES) - OPEN
Focus Area E: Targetry by Design (IRP) - The RFA was updated to remove this topic/focus area on 4/10/2026/.
Focus Area F: AI-Enabled Materials Discovery, Development, and Qualification (AMMTO) - M. Beidaghi (Aerospace and Mechanical Engineering)
Focus Area G: Electrochemical Energy Conversion Catalyst Discovery and Scale up (AFFO) - Z. Yan (Chemistry and Biochemistry)

Topic Area 13: Enhancing Particle Accelerators for Discovery // Limit: 2 // Tickets Available: 2
Focus Area A: AI-driven Accelerator Facilities (BES, HEP, IRP, NP) - OPEN
Focus Area B: Integration of Digital Twins for Fusion Systems and Actuators (FES) - OPEN

Topic Area 14: Unifying Physics from Quarks to the Cosmos // Limit: 3 // Tickets Available: 1
Focus Area A: Foundation Models of Particle Interactions and Cosmic Physics – S. Pandey (Astronomy and Steward Observatory)
Focus Area B: AI Accelerated DUNE Science (HEP) - OPEN 
Focus Area C: Expedited Discovery from High Complexity and Petabyte-Scale Datasets (HEP, NP) - T. Eifler (Astronomy and Steward Observatory) 

Topic Area 15: Predicting U.S. Water for Energy // Limit: 3 // Tickets Available: 1 
Focus Area A: Cloud Microphysics and Atmospheric Turbulence – X. Dong (Hydrology and Atmospheric Sciences)
Focus Area B: Water and Energy (BER) - A. Bennett (Hydrology and Atmospheric Sciences)
Focus Area C: Weeks to Years Prediction (BER) - OPEN

Topic Area 16: Scaling the Grid to Power the American Economy // Limit: 3 // Tickets Available: 1 
Focus Area A: Grid Modeling and Analysis (OE, CMEI-IESO, SC-ASCR) – M. Chertkov (Mathematics)
Focus Area B: Grid Operations Optimization (OE, CMEI-IESO, SC-ASCR) - OPEN
Focus Area C: Uncertainty Quantification (SC-BER, SC-ASCR, OE, CMEI-IESO) – R. Tandon (Electrical and Computer Engineering)

Topic Area 17: Unleashing Subsurface Strategic Energy Assets // Limit: 3 // Tickets Available: 2
Focus Area A: Chemical and Hydrologic Transport in Subsurface – S. Saleska (Biosphere 2)
Focus Area B: Evolution of Fractures in the Upper Crust (BES) - OPEN
Focus Area C: Control of Subsurface Fractures (HGEO) - OPEN

Topic Area 18: HPC Code Curation, Translation, and Development for Accelerated Scientific Discoveries  // Limit: 7 // Tickets Available: 7
Focus Area A: AI-Driven Code Porting and Optimization (ASCR) - OPEN
Focus Area B: Automated Scientific Problem-to-Code Generation (ASCR) - OPEN 
Focus Area C: Neuro-Symbolic Agents for Code Development (ASCR) - OPEN
Focus Area D: Performance Prediction and Feedback Loops (ASCR) - OPEN
Focus Area E: Trustworthy AI for Scientific Software (ASCR) - OPEN
Focus Area F: Multi-Modal Data Integration for Code Intelligence (ASCR) - OPEN
Focus Area G: Partnerships for HPC AI Advancement (ASCR, AMMTO) - OPEN

Topic Area 19: AI for Scientific Reasoning // Limit: 3 // Tickets Available: 1
Focus Area A: Trustworthy Mathematical and Symbolic Reasoning (ASCR) – E. Blanco (Computer Science)
Focus Area B: Hypothesis Generation from Multi-Modal Data (ASCR) - A. Zabludoff (Astronomy and Steward Observatory)
Focus Area C: Composable and Modular Foundation Models (ASCR) - OPEN

Topic Area 20: Cybersecurity for AI-Driven Science Workflows // Limit: 3 // Tickets Available: 0
Focus Area A: AI for Adversarial Robustness and Resilience– M. Krunz (Electrical and Computer Engineering)
Focus Area B: Data Provenance and Integrity Verification (ASCR) – D. Alharthi (College of Information Science) 
Focus Area C: Real-Time Attack Detection and Mitigation for AI Models (ASCR) – M. Li (Electrical and Computer Engineering)

Topic Area 21: Artificial Intelligence in Fluid Flow for Energy Components and Technologies // Limit: 3 // Tickets Available: 1
Focus Area A: Physics-Informed AI for Complex Flow Modeling – K. Kratter (Astronomy and Steward Observatory)
Focus Area B: AI-Driven Design and Control for Performance and Durability (IESO, ASCR) - OPEN
Focus Area C: Data-Driven Operational Intelligence and System Resilience (IESO) – L. Zhang (Civil and Architectural Engineering and Mechanics)

Limiting Language
Applicant institutions are limited to no more than one application as the lead institution per focus area for Phase I and Phase II applications combined. Phase II applications must list a primary focus area but will have the option to list secondary focus areas. The primary focus area will be used for determining limitations on institutional submissions.

There is no limitation to the number of applications for which the institution is not the lead in a multi-institution team using collaborative applications.

The PI on an application may also be listed as a senior or key personnel on an unlimited number of separate submissions but can be the lead PI on only one application.  However, the PI on an awarded Phase I award may submit a Phase II proposal as part of the FY27 go/no-go decision process.  

The full RFA is linked here. 

Executive Summary 
The DOE Office of Science (SC), Office of Critical Minerals and Energy Innovation (CMEI), Office of Environmental Management (EM), Office of Nuclear Energy (NE), Office of Electricity (OE), and Hydrocarbons and Geothermal Office (HGEO) hereby announce interest in receiving applications from interdisciplinary teams addressing the Genesis Mission National Science and Technology Challenges to accelerate scientific discovery and research and development (R&D) workflows using novel artificial intelligence (AI) models and frameworks. By achieving AI advantage, these teams will advance the DOE's mission and ensure America’s security and prosperity by addressing energy, environmental, and nuclear challenges through science and technology. Teams are encouraged to leverage the extensive scientific and data resources of the DOE/National Nuclear Security Administration (NNSA), the National Laboratories, U.S. industry, and academia. The resulting AI models and workflows, if successful, may be integrated into the American Science Cloud. 

DOE is soliciting new FY26 Phase I small team and Phase II large team applications in the following topic areas: advanced manufacturing, biotechnology, critical materials, nuclear fission, nuclear fusion, quantum information science, semiconductors and microelectronics, discovery science, and energy (see specific focus areas in Section III Program Descriptions). 

In addition, this RFA will remain available to allow the recipients of FY26 Phase I awards to apply for larger team Phase II awards. In a few weeks, DOE plans to amend the RFA to clarify the LOI and application guidelines for FY26 Phase II awards. In FY27, DOE plans to amend the RFA or to issue an alternative funding opportunity to update the topic and focus areas to allow a second competition of Phase I small team applications and Phase II large team applications. 

Additional applications for Phase I and Phase II may be submitted after the corresponding deadline listed on the cover of this RFA, however, DOE reserves the right to decline such applications without review.

No Applicants // Limit: 1 // Tickets Available: 1

Limiting Language
An institution may submit only one application in response to this RFP.  

Background
The first heart transplant was performed in 1967, one of the most extraordinary feats of modern medicine. The system that supports it, however, has failed to evolve significantly since then, with none of the astonishing novel therapies we see being developed in other areas of medicine. Despite decades of innovation in almost all the other cardiovascular spheres, heart transplant care remains fragmented, inequitable, and frustratingly stagnant. Patients face ongoing cardiac rejection with imprecise methods to detect the immunologic process, potentially toxic immunosuppressive regimens which have not been updated substantially for two decades, and inconsistent outcomes—especially among Black recipients and pediatric populations. Data are siloed, research is underfunded, and quality improvement is virtually nonexistent. The majority of clinical practice guideline recommendations are driven by consensus rather than an evolving catalog of evidence. 

There is no unified national data infrastructure that can support retrospective and prospective research, no standardized quality improvement framework, and no coordinated research agenda to address these challenges. In short, we are crawling in one of the most high-stakes areas of healthcare. 

The American Heart Association is launching a bold, multi-phase initiative to transform heart transplantation care across the United States, a transformation in treatment built on three pillars: 

• A Global Heart Transplant Data Infrastructure In collaboration with key transplant organizations, the American Heart Association will manage a comprehensive heart transplant database, designed not as a static registry, but as a dynamic, harmonized data platform to drive research, quality improvement, and policy change.
• A Research Network for Breakthrough Science We are now recruiting from leading institutions to launch a research network focused on rejection detection, remote monitoring, viral load surveillance, and innovative, safer therapies. This network will be the sandbox for high-impact studies, including planning grants for clinical trials in immune tolerance, and chronic rejection.
• A Quality Improvement Infrastructure Modeled after our Get With The Guidelines® success, we will build a scalable Quality Improvement (QI) framework to standardize transplant care, reduce disparities, and improve long-term outcomes. This will drive system-wide change.