Funding Wizard

The Office of Science (SC) hereby announces its interest in applications to advance basic research in support of the Department of Energy’s Energy Earthshots™ initiative.[1] The Energy Earthshots drive integrated program development and execution across the Department of Energy’s basic science and energy technology offices. They are part of an all-hands-on-deck approach to provide science and technology innovations that address the tough technological challenges required to achieve our climate and economic competitiveness goals.[2],[3] The Energy Earthshots will accelerate breakthroughs towards more abundant, affordable, and reliable clean energy solutions. This FOA will support small teams to build the scientific foundations for the Energy Earthshot goals. [1] https://www.energy.gov/policy/energy-earthshots-initiative [2] U.S. Innovation to Meet 2050 Goals: Assessing Initial R&D Opportunities (2022). https://www.whitehouse.gov/wp-content/uploads/2022/11/U.S.-Innovation-t… [3] The U.S. National Blueprint for Transportation Decarbonization: A Joint Strategy to Transform Transportation (2023). https://www.energy.gov/sites/default/files/2023-01/EERE-Decarbonization…

The DOE SC programs in Fusion Energy Sciences (FES) (https://science.osti.gov/fes) and Advanced Scientific Computing Research (ASCR) (https://science.osti.gov/ascr) hereby announce their interest in receiving multi-institutional applications for the Scientific Discovery through Advanced Computing (SciDAC) Partnerships program (https://www.scidac.gov/). This FOA invites new applications for the SciDAC-5 Partnerships that enable or accelerate scientific discovery and programmatic objectives, aligned with the FES mission and the Department’s vision for fusion energy (https://www.whitehouse.gov/ostp/news-updates/2022/04/19/readout-of-the-…), through effective collaborations between fusion / plasma scientists and applied mathematicians and/or computer scientists from the SciDAC Institutes (https://www.scidac.gov/institutes.html) that fully exploit the capabilities of DOE High Performance Computing (HPC) facilities

The mission of the ASCR program is to discover, develop, and deploy computational and networking capabilities to analyze, model, simulate and predict complex phenomena for the advancement of science. Since 2015, ASCR has held a series of workshops to assess the2potential of quantum computing to advance transformative science and identify its potential impact [1-3]. A wide range of high-impact applications of quantum computing were identified in areas such as chemistry, materials, and biology as well as in computational techniques such as optimization. However, the quantum resources required to achieve a practical advantage in any area of computational science remain inadequately understood. While it is possible to make a rough estimate based on the number of logic gates needed to run a specific algorithm, details such as the physical configuration of qubits in a processor device architecture, noise mechanisms, approaches to compilation and transpilation, gate set selection and implementation, etc. can have a significant impact on whether a specific quantum computer will be able to execute a useful computation. ASCR therefore invites applications for basic research to address the following questions:1. What can fundamental physical limits on quantum processors tell us about what quantum computers can and cannot do?2. How can we use NISQ devices to move our understanding of when and how quantum computers might be useful as far forward as possible?3. How can we best assess the utility of a given (existing or hypothetical) quantum processor for advancing the frontiers of computational science?Applications may address any combination of these themes. Submitted applications should clearly identify which of the themes are addressed. Research should be backed by rigorous theory and strive to connect metrics for device performance to low-level physical parameters as well as application performance whenever possible. This program is aimed at assessing current and future quantum computers rather than developing or improving applications and algorithms.Research proposed in response to this FOA should support the growth of an active, integrated research community committed to the common goal of developing quantum computing resources for advancing scientific discovery. Students and/or other junior researchers should have ample opportunity to participate in all aspects of the project. International collaboration and personnel exchange is encouraged.[1] ASCR Report on Quantum Computing for Science Workshop, February 2015.[2] ASCR Report on Quantum Testbeds Stakeholder Workshop, February 2017.[3] Quantum Computing Testbeds Stakeholder Workshop, December, 2021.

The DOE SC program in Fusion Energy Sciences (FES) hereby announces its interest in receiving applications to advance North America’s First High Intensity Laser Research Network (LaserNetUS). The goal of this FOA is to offer support to new and existing LaserNetUS nodes that will advance the frontiers of laser science and applications, provide students and scientists with broad access to unique facilities and enabling technologies, foster collaboration among researchers and networks from around the world, and develop the workforce needed to advance high intensity laser science and Inertial Fusion Energy (IFE).

The DOE invites eligible Phase I and Phase II awardees to apply for Phase II awards (grants and cooperative agreements) (initial, second, and third) under this Funding Opportunity Announcement (FOA). Topic descriptions for this FOA can be found on the DOE SBIR/STTR web site at https://science.osti.gov/sbir/Funding-Opportunities.

The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in basic research to explore potentially high-impact approaches in scientific computing and extreme-scale science. SUPPLEMENTARY INFORMATION 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, scientific machine learning, artificial intelligence (AI) on increasingly heterogeneous architectures, including neuromorphic and quantum systems. 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 strictly 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. DOE is committed to promoting the diversity of investigators and institutions it supports, as indicated by the ongoing use of program policy factors (see Section V) in making selections of awards. To strengthen this commitment, DOE encourages applications that are led by, or include partners from Established Program to Stimulate Competitive Research (EPSCoR)[1] states, that are underrepresented in the ASCR portfolio[2] and applications led by individuals from groups historically underrepresented in STEM. RESEARCH OPPORTUNITIES Exploratory Research for Extreme-Scale Science (EXPRESS) opportunities exist for the following research topics: A) Modeling Future Supercomputing Systems B) Programming Techniques for Computational Physical Systems C) Quantum Algorithms across Models [1] https://beta.nsf.gov/funding/initiatives/epscor/state-websites [2] Information about SC awards can be found in the Public Award Search at https://pamspublic.science.energy.gov/WebPAMSExternal/Interface/Awards/…

The DOE SC program in Nuclear Physics (NP) and the DOE National Nuclear Security Administration (NNSA) Office of Defense Nuclear Nonproliferation Research and Development (NA-22) hereby announce their interest in receiving applications to the Nuclear Data InterAgency Working Group / Research program for research projects intended to answer nuclear data questions of interest to the research communities supported by those programs and offices.

The DOE SC program in Basic Energy Sciences (BES) hereby announces its interest in receiving new applications for Energy Innovation Hub projects pursuing multi-investigator, cross-disciplinary fundamental research to address emerging new directions as well as long-standing challenges for the next generation of rechargeable batteries and related electrochemical energy storage technologies. Electrochemical energy storage is typically viewed as the bidirectional interconversion of electricity and chemical potential energy using electrochemistry for the purpose of storing electrical energy for later use, with lithium (Li)-ion and lead acid batteries being representative of the current generation of electrochemical energy storage. Discovery and scientific exploration of new battery chemistries, materials, and architectures for energy storage are encouraged. Research on electrolyzer/fuel cell combinations using hydrogen or hydrocarbons as the chemical storage media are supported elsewhere within DOE programs and are specifically excluded from this FOA. Regardless of materials and electrochemical processes involved, the focus must be on fundamental scientific concepts and understanding for the next generation of batteries and electrochemical energy storage.The proposed fundamental electrochemical energy storage research should impact a broad range of topics, including decarbonization of transportation and incorporation of clean energy into the electricity grid, especially for long duration energy storage (LDES). Two recent DOE-wide activities involving batteries and related electrochemical energy storage are the Energy Storage Grand Challenge and the Long Duration Storage Energy EarthshotTM. Electrochemical energy storage technology has the potential to accelerate full decarbonization of the electric grid, and the Long Duration Storage Shot establishes a target to reduce the cost of grid-scale energy storage by 90% for systems that deliver 10+ hours of duration within the decade. More broadly the Energy Storage Grand Challenge provides a programmatic framework that supports the vision to develop and domestically manufacture energy storage technologies, including batteries and other electrochemical energy storage, that can meet all U.S. market demands by 2030. Given the foundational role of basic scientific research in providing the needed technology options to support these critical goals, Energy Innovation Hub investments in scientific discovery and exploration to advance the fundamental understanding of electrochemical energy storage processes, materials, and systems are needed. Progress in the fundamental science topics described in the 2017 Basic Research Needs for Next Generation Electrochemical Energy Storage Workshop will drive innovation in batteries and advance development of new and effective energy storage technologies needed for a decarbonized economy by 2050.

The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in research applications to explore potentially high-impact approaches in the development and use of scientific machine learning (SciML) and artificial intelligence (AI) in the predictive modeling, simulation and analysis of complex systems and processes.High-performance computational models, simulations, algorithms, data from experiments and observations, and automation are being used to accelerate scientific discovery and innovation. Recent workshops, report, and strategic plans across the DOE have highlighted the research, development, and use of artificial intelligence and machine learning for science, energy, and security. Relevant domains include materials, environmental, and life sciences; high-energy, nuclear, and plasma physics; and the DOE Energy Earthshots Initiative, for examples. A 2018 Basic Research Needs workshop and report on scientific machine learning (SciML) and AI identified six Priority Research Directions (PRDs) for the development of the broad foundations and research capabilities needed to address such DOE mission priorities. The first three PRDs for foundational research are a set of themes common to all SciML approaches and correspond to the need for domain-awareness, interpretability, and robustness and scalability, respectively. Of the other three PRDs for capability research, PRD #5 (Machine Learning-Enhanced Modeling and Simulation) and uncertainty quantification are the subject of this FOA.DOE is committed to promoting the diversity of investigators and institutions it supports, as indicated by the ongoing use of program policy factors (see Section V) in making selections of awards. To strengthen this commitment, DOE encourages applications that are led by, or include partners from Established Program to Stimulate Competitive Research (EPSCoR) states, that are underrepresented in the ASCR portfolio and applications led by individuals from groups historically underrepresented in STEM.

The DOE SC program in Fusion Energy Sciences (FES) hereby announces its interest in receiving new applications from U.S. researchers to carry out frontier plasma science research on one or more of the FES General Plasma Science (GPS) Program supported collaborative research facilities (CRFs). These include the Big Red Ball (BRB) and Madison Symmetric Torus (MST) experiments at the Wisconsin Plasma Physics Laboratory (WiPPL) at the University of Wisconsin – Madison, the Large Plasma Device (LAPD) in the Basic Plasma Science Facility (BaPSF) at the University of California – Los Angeles, the DIII-D Frontier Science Campaign at General Atomics, the Magnetized Dusty Plasma Experiment (MDPX) at the Magnetized Plasma Research Laboratory (MPRL) at Auburn University, and the low-temperature Plasma Research Facility (PRF) at Sandia National Laboratories and Princeton Collaborative Research Facility (PCRF) at the Princeton Plasma Physics Laboratory.