DE-FOA-0003207.pdf

DEPARTMENT OF ENERGY (DOE)

OFFICE OF SCIENCE (SC)

FY 2024 FUNDING FOR ACCELERATED, INCLUSIVE RESEARCH

(FAIR)

FUNDING OPPORTUNITY ANNOUNCEMENT (FOA) NUMBER:

DE-FOA-0003207

FOA TYPE: INITIAL

CFDA NUMBER: 81.049

FOA Issue Date: March 12, 2024 Submission Deadline for Pre-Applications: April 23, 2024 at 5:00 PM Eastern Time

A Pre-Application is required.

Pre-Applications must be submitted by an authorized institutional representative.

Pre-Application Response Date: May 28, 2024 at 11:59 PM Eastern Time Submission Deadline for Applications: July 16, 2024 at 11:59 PM Eastern Time

Table of Contents

SECTION I – FUNDING OPPORTUNITY DESCRIPTION

PROGRAM OBJECTIVE

OFFICE OF SCIENCE RESEARCH

1. ADVANCED SCIENTIFIC COMPUTING RESEARCH (ASCR)

2. BASIC ENERGY SCIENCES (BES)

3. BIOLOGICAL AND ENVIRONMENTAL RESEARCH (BER)

4. FUSION ENERGY SCIENCES (FES)

5. HIGH ENERGY PHYSICS (HEP)

6. NUCLEAR PHYSICS (NP)

7. ISOTOPE R&D AND PRODUCTION (DOE IP)

8. ACCELERATOR R&D AND PRODUCTION (ARDAP)

LIMITATION ON NUMBER OF SUBMISSIONS PER PI AND PROGRAM

TEAMING REQUIREMENTS

IDENTIFYING A DOE NATIONAL LABORATORY OR USER FACILITY PARTNER...40

ANNUAL MEETINGS

INFORMATIONAL WEBINAR

OPEN SCIENCE

SECTION II – AWARD INFORMATION

II.A. TYPE OF AWARD INSTRUMENT

II.B. ESTIMATED FUNDING

II.C. MAXIMUM AND MINIMUM AWARD SIZE

II.D. EXPECTED NUMBER OF AWARDS

II.E. ANTICIPATED AWARD SIZE

II.F. PERIOD OF PERFORMANCE

II.G. TYPE OF APPLICATION

SECTION III – ELIGIBILITY INFORMATION

III.A. ELIGIBLE APPLICANTS

III.B. COST SHARING

III.C. ELIGIBLE INDIVIDUALS

III.D. LIMITATIONS ON SUBMISSIONS

SECTION IV – APPLICATION AND SUBMISSION INFORMATION

IV.A. ADDRESS TO REQUEST APPLICATION PACKAGE

IV.B. LETTER OF INTENT (LOI) AND PRE-APPLICATION

IV.C. GRANTS.GOV APPLICATION SUBMISSION AND RECEIPT PROCEDURES

IV.D. CONTENT AND APPLICATION FORMS

IV.E. SUBMISSIONS FROM SUCCESSFUL APPLICANTS

IV.F. SUBMISSION DATES AND TIMES

SECTION V - APPLICATION REVIEW INFORMATION

V.A. CRITERIA

V.B. REVIEW AND SELECTION PROCESS

V.C. ANTICIPATED NOTICE OF SELECTION AND AWARD DATES

SECTION VI – AWARD ADMINISTRATION INFORMATION

VI.A. AWARD NOTICES

VI.B. ADMINISTRATIVE AND NATIONAL POLICY REQUIREMENTS

VI.C. REPORTING

VI.D. REPORTING OF MATTERS RELATED TO RECIPIENT INTEGRITY AND

PERFORMANCE (DECEMBER 2015)

VI.E. INTERIM CONFLICT OF INTEREST POLICY FOR FINANCIAL ASSISTANCE...71

SECTION VII - QUESTIONS/AGENCY CONTACTS

VII.A. QUESTIONS

VII.B. AGENCY CONTACTS

SECTION VIII – SUPPLEMENTARY MATERIAL

VIII.A. HOW-TO GUIDES

VIII.B. ADMINISTRATIVE AND NATIONAL POLICY REQUIREMENTS

VIII.C. REFERENCE MATERIAL

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UPDATES AND REMINDERS

RECOMMENDATION

The Department of Energy (DOE) Office of Science (SC) encourages you to register in all systems as soon as possible. You are also encouraged to submit letters of intent (LOIs), pre-applications, and applications well before the deadline.

INFORMATIONAL WEBINAR

SC plans to hold an informational webinar about this FOA on Wednesday, March 20, 2024 at 3:00 pm ET. SC also plans to hold office hours on April 9, April 17, July 2, and July 10, 2024, at 2:00 pm ET for administrative questions related to the FOA. Registration instructions and other details will be posted at https://science.osti.gov/Initiatives/FAIR/Funding-Opportunities.

Frequently asked questions (FAQ) will also be posted at https://science.osti.gov/Initiatives/FAIR.

PROMOTING INCLUSIVE AND EQUITABLE RESEARCH (PIER) PLAN

All new and renewal applications must provide a Promoting Inclusive and Equitable Research (PIER) Plan as an appendix to the project narrative. Please read the instructions in Section IV and the associated review criteria in Section V.

INTERAGENCY FORMATS FOR CURRENT AND PENDING SUPPORT AND BIOGRAPHICAL SKETCHES

Interagency common instructions for preparing current and pending support and biographical sketches are being developed. The Science Experts Network Curriculum Vitae (SciENcv) system at https://www.ncbi.nlm.nih.gov/sciencv/ will be updated to support the forthcoming common instructions and formats. The fillable PDFs provided by the National Science Foundation are no longer available. When interagency common formats and instructions are promulgated, their use will be required. See https://new.nsf.gov/funding/senior-personnel-documents for more information. SC strongly encourages all researchers to use the online SciENcv system to ensure that their documents are prepared in the appropriate format with the least inconvenience.

INDIVIDUALS WHO SHOULD NOT SERVE AS MERIT REVIEWERS

Follow the updated instructions in Section VIII and consider the use of the Collaborator Template available at https://science.osti.gov/grants/Policy-and-Guidance/Agreement-Forms. Do not include this list as part of the biographical sketch.

LIVING WAGES

SC is committed to ensuring that students, trainees, and postdoctoral fellows are paid a fair and equitable wage sufficient to allow a reasonable standard of living. Applicant institutions are strongly encouraged to examine their institutional pay scales to ensure that all personnel earn a living wage. The provision of fellowships, traineeships, stipends, honoraria, subsistence allowances, and other similar payments may be allowable expenses on SC financial assistance https://science.osti.gov/Initiatives/FAIR/Funding-Opportunities https://science.osti.gov/Initiatives/FAIR https://www.ncbi.nlm.nih.gov/sciencv/ https://new.nsf.gov/funding/senior-personnel-documents https://science.osti.gov/grants/Policy-and-Guidance/Agreement-Forms ii awards, per 2 CFR 200.430, § 200.431, and § 200.466. For graduate students, SC considers a reasonable living wage to be an annual income of $45,000, excluding benefits.

SC STATEMENT OF COMMITMENT

The DOE SC is fully and unconditionally committed to fostering safe, diverse, equitable, and inclusive work, research, and funding environments that value mutual respect and personal integrity. SC is committed to advancing belonging, accessibility, justice, equity, diversity, and inclusion across the portfolio of activities we sponsor. SC’s effective stewardship and promotion of safe, accessible, diverse, and inclusive workplaces that value and celebrate the diversity of people, ideas, cultures, and educational backgrounds across the country and that foster a sense of belonging in our scientific community is foundational to delivering on our mission. We are committed to promoting people from all backgrounds, including individuals and communities that were historically underrepresented and minoritized in science, technology, engineering, and math (STEM) fields and the activities we sponsor in recognition of our responsibility to serve the public. We also recognize that harnessing a broad range of views, expertise, and experiences drives scientific and technological innovation and enables the SC community to push the frontiers of scientific knowledge for U.S. prosperity and security. Discrimination and harassment undermine SC’s ability to achieve its mission by reducing productivity, discouraging, or inhibiting talent retention and career advancement, and weakening the integrity of the SC enterprise overall. SC does not tolerate discrimination or harassment of any kind, including sexual or non-sexual harassment, bullying, intimidation, violence, threats of violence, retaliation, or other disruptive behavior at institutions receiving SC funding or other locations where activities funded by SC are carried out. All applicants and collaborators should familiarize themselves with the SC Statement of Commitment available at https://science.osti.gov/SW- DEI/SC-Statement-of-Commitment.

UPDATING YOUR PORTFOLIO ANALYSIS AND MANAGEMENT SYSTEM (PAMS) PROFILE

All applicants are encouraged to update their profiles in the PAMS website at https://pamspublic.science.energy.gov regularly, at least annually, to ensure SC has your most up to date information. The PAMS profile now requires that individuals provide responses to the demographic related fields. SC strongly encourages personnel at applicant and recipient institutions, including Principal Investigators (PIs), Co-PIs, and other Key Personnel, to provide their demographic information. By providing your demographic information, you are assisting with SC’s continued commitment to advancing diversity, equity, and inclusion in its business practices. Alternatively, for information you wish not to disclose, please select, “Do not wish to provide.” Your individual demographic information will not be shared with peer reviewers and the information in your PAMS profile is protected by the requirements established in the Federal Privacy Act of 1974. Aggregate, anonymized demographic information may be shared with confidential review committees who are charged to evaluate the quality and efficacy of SC’s business practices. For example, summary statistics of all applicants to or award selections from a particular SC FOA may be reviewed by a Committee of Visitors.

https://science.osti.gov/SW-DEI/SC-Statement-of-Commitment https://science.osti.gov/SW-DEI/SC-Statement-of-Commitment https://pamspublic.science.energy.gov/ iii

PORTABLE DOCUMENT FORMAT (PDF) GENERATION

The project narrative in an application must be one single machine-readable PDF file that contains the DOE Title Page, project narrative, all required appendices, and other attachments.

This single PDF file may not be scanned from a printed document and must be attached in Field 8 on the Grants.gov form. This must be a plain PDF file consisting of text, numbers, and images without editable fields, signatures, passwords, redactions, or other advanced features available in some PDF-compatible software. The project narrative will be read by SC staff using the full version of Adobe Acrobat: Please ensure that the narrative is readable in Acrobat. If combining multiple files into one research narrative, ensure that a PDF portfolio or binder is not created. If creating PDF files using any software other than Adobe Acrobat, please use a “Print to PDF” or equivalent process to ensure that all content is visible in the project narrative. Once a project narrative has been assembled, please submit the combined project narrative file through a “Print to PDF” or equivalent process to ensure that all content is visible in one PDF file that can be viewed in Adobe Acrobat. Review your submission to ensure that blank pages are not present.

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Checklist for Avoiding Common Errors:

Item Issue Pre-Applications - Submit your pre-application in PAMS by an authorized institutional representative.

- Do not submit your pre-application in Grants.gov.

- Do not attach your pre-application to the SF- 424 Research and Related (R&R) form.

- Follow the instructions in Section IV for the preparation of a pre-application.

Include:

- Title page

- Objective and Technical Approach

- Letter of Collaboration

- List of Individuals who Should not Serve as Merit Reviews (upload a separate .xls file as an “Additional Attachment” in

PAMS)

Applications Submitted in Grants.gov. Do not submit applications in PAMS or FedConnect.

Grants.gov Submission Ensure that applications are submitted under the correct Opportunity Number.

Standard Form (SF)-424 Research and Related (R&R):

- Attach nothing to field 20

- Attach nothing to field 21

SF-424 Research and Related Other Project Information form:

- Attach the abstract to field 7

- Attach the project narrative, with all appendices, to field 8

- Attach nothing to field 9

- Attach nothing to field 10

- Attach nothing to field 11

- Attach the list of individuals who should not serve as merit reviewers (Collaborator Template) to field 12

- Do not attach other files to field 12

- NOTE: Files attached to field 12 will not be shared with merit reviewers.

Page Limits Strictly followed throughout application, including particular attention to:

- Project narrative and appendices v

Item Issue

- Biographical sketches

- Data Management Plans (DMPs)

- Promoting Inclusive and Equitable

Research (PIER) Plan

- Letter(s) of Collaboration or Access

Personally Identifiable Information None present in the application Project Narrative Composed of one PDF file including all appendices (bibliography, facilities, equipment, DMP, PIER)

Project Summary / Abstract Name of PI, PI’s institutional affiliation(s), Co-Investigator(s), Co-Investigator’s institutional affiliation(s)

DOE Title Page Follow instructions closely Budget Use current negotiated indirect cost and fringe benefit rates Budget Justification (attached to budget) Justify all requested costs Biographical Sketches Follow page limits strictly and do not include list of collaborators. Attach the biographical sketch to the Senior/Key Person Profile (Expanded) Form.

Current and Pending Support Ensure complete listing of all activities, regardless of source of funding. Attach the current and pending support to the Senior/Key Person Profile (Expanded) Form.

List of Individuals who Should not Serve as Merit Reviews

Attach to field 12 of the SF-424 Research and Related Other Project Information form.

Data Management Plans (DMP) - If referring to an experiment’s DMP, describe the relationship to the proposed research.

- Include a DMP even if no experimental data is expected.

Promoting Inclusive and Equitable Research (PIER) Plan

PIER Plans are required for new and renewal applications.

Section I – FUNDING OPPORTUNITY DESCRIPTION

GENERAL INQUIRIES ABOUT THIS FOA SHOULD BE DIRECTED TO:

Technical Contacts:

Questions regarding the specific program areas/technical requirements can be directed to the technical contacts listed within the FOA.

Administrative Contact:

Questions about budgets, eligibility, and similar topics should be directed to sc.fair@science.doe.gov.

STATUTORY AUTHORITY

Section 646 of Public Law 95-91, U.S. Department of Energy Organization Act Section 901, et seq. of Public Law 109-58, Energy Policy Act of 2005

APPLICABLE REGULATIONS

Uniform Administrative Requirements, Cost Principles, and Audit Requirements for Federal Awards, codified at 2 CFR 200 U.S. Department of Energy Financial Assistance Rules, codified at 2 CFR 910 U.S. Department of Energy, Office of Science Financial Assistance Program Rule, codified at 10

CFR 605

SUMMARY

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)1,2 and non-R1 emerging research institutions (ERIs).3 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. A list of institutions and their

1 The Carnegie Classification of Institutions of Higher Education can be found at https://carnegieclassifications.acenet.edu. A list of institutions with very high research activity (R1 institutions) is available at https://carnegieclassifications.acenet.edu/institutions/?basic2021__du%5B%5D=15.

2 MSI designations are based on the Department of Education eligibility matrix (https://www2.ed.gov/about/offices/list/ope/idues/eligibility.html). Eligible MSIs are listed as Asian American and Native American Pacific Islander Serving Institutions (AANAPISIs), Alaska Native and Native Hawaiian Serving Institutions (AANHs), Hispanic Serving Institutions (HSIs), Native American Serving Non-Tribal Institutions (NASNTI), Predominantly Black Institutions (PBIs), Historically Black Colleges and Universities (HBCUs), and Tribally Controlled Colleges and Universities (TCCUs). For the purposes of this FOA, institutions marked in the eligibility matrix as either being eligible to receive funding or as receiving funding will be considered an MSI.

3 Emerging research institution was defined in the CHIPS and Science Act of 2022. Federal research expenditures are based on the National Science Foundation’s Higher Education Research and Development Survey: Fiscal Year 2021 (https://ncses.nsf.gov/surveys/higher-education-research-development/2021).

mailto:sc.fair@science.doe.gov https://carnegieclassifications.acenet.edu/ https://carnegieclassifications.acenet.edu/institutions/?basic2021__du%5B%5D=15 https://www2.ed.gov/about/offices/list/ope/idues/eligibility.html https://ncses.nsf.gov/surveys/higher-education-research-development/2021 designations is provided at https://science.osti.gov/grants/Applicant-and-Awardee- Resources/Institution-Designations.

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.

SUPPLEMENTARY INFORMATION

Program Objective

FAIR is focused on building research capacity at academic institutions that have been historically underrepresented in the SC portfolio. Capacity building is interpreted broadly to include both personnel expertise and infrastructure and is expected to be durable, contributing over time toward sustained research strength at the lead institution. Because collaboration is critical to SC research, relationship building through the partnership is considered a key component of the FAIR program. All applications must be submitted on behalf of a lead institution and include a single partnering team member. The lead institution must be a non-R1 MSI or a non-R1 ERI and the partner must be either a DOE National Laboratory (https://www.energy.gov/national-laboratories), an SC Scientific User Facility (https://science.osti.gov/User-Facilities), or an R1 MSI/ERI.

Applications may include costs for infrastructure such as lab equipment, instrumentation, and computing resources that support the proposed research. Applications may also include funds directed toward building relationships, for example for travel by the PI, key personnel, and students to the partner institution, conferences, or scientific meetings. Applications do not need to be at or near the award ceiling. Equal budgets for each year of the award are not required; for example, the first year of the award could include one-time costs for equipment purchases.

In addition to FAIR, SC also administers the Reaching a New Energy Sciences Workforce (RENEW) initiative. The primary differences between the two initiatives are the goals of each.

Training is the primary goal for RENEW, and applications to RENEW must include training activities beyond conduct of research. Whereas training is not the primary goal of FAIR which supports fundamental research to build research capacity, including infrastructure and expertise, at institutions historically underrepresented in the SC portfolio. However, research supported by FAIR may include support for students or postdoctoral researchers. Applicants may apply to one or both funding opportunities. However, the same application is unlikely to be relevant to both solicitations.

Office of Science Research

The SC mission is to deliver scientific discoveries and major scientific tools to transform our understanding of nature and advance the energy, economic and national security of the United States. SC is the Nation’s largest Federal sponsor of basic research in the physical sciences and https://science.osti.gov/grants/Applicant-and-Awardee-Resources/Institution-Designations https://science.osti.gov/grants/Applicant-and-Awardee-Resources/Institution-Designations https://www.energy.gov/national-laboratories https://science.osti.gov/User-Facilities the lead Federal agency supporting fundamental scientific research for our Nation’s energy future.

SC accomplishes its mission and advances national goals by supporting:

• The frontiers of science—exploring nature’s mysteries from the study of fundamental subatomic particles, atoms, and molecules that are the building blocks of the materials of our universe and everything in it to the DNA, proteins, and cells that are the building blocks of life. Each of the programs in SC supports research probing the most fundamental disciplinary questions.

• The 21st Century tools of science—providing the Nation’s researchers with 28 state-of-the-art national scientific user facilities, the most advanced tools of modern science, propelling the U.S. to the forefront of science, technology development and deployment through innovation.

• Science for energy and the environment―building the knowledge foundation to spur discoveries and innovations for advancing the Department’s mission in energy and environment. SC supports a wide range of funding modalities, from single principal investigators to large team-based activities, to engage in fundamental research on energy production, conversion, storage, transmission, and use, and on our understanding of the earth systems.

SC manages its research portfolio through eight scientific programs. The following program descriptions, websites, and technical points of contact are offered to provide more in-depth information on scientific and technical areas of interest to SC:

1. Advanced Scientific Computing Research (ASCR)

(a) Applied Mathematics

(b) Computer Science

(c) Advanced Computing Technologies

2. Basic Energy Sciences (BES)

(a) Scattering and Instrumentation Sciences Research

(b) Condensed Matter and Materials Physics Research

(c) Materials Discovery, Design, and Synthesis Research

(d) Fundamental Interactions Research

(e) Chemical Transformations Research

(f) Photochemistry and Biochemistry Research

3. Biological and Environmental Research (BER)

(a) Biological Systems Science

(b) Earth and Environmental Systems Sciences

4. Fusion Energy Sciences (FES)

(a) Burning Plasma Science: Foundations—Advanced Tokamak

(b) Enabling Research and Development

(c) Burning Plasma Science: Foundations—Spherical Tokamak

(d) Burning Plasma Science: Foundations—Theory & Simulation

(e) Burning Plasma Science: Long Pulse—Tokamak

(f) Burning Plasma Science: Long Pulse—Stellarator

(g) Burning Plasma Science: Long Pulse—Materials

(h) Burning Plasma Science: Long Pulse—Fusion Nuclear Science

(i) Discovery Plasma Science: Plasma Science and Technology

(j) Discovery Plasma Science: Measurement Innovation

5. High Energy Physics (HEP)

(a) Experimental Research at the Energy Frontier in High Energy Physics

(b) Experimental Research at the Intensity Frontier in High Energy Physics

(c) Experimental Research at the Cosmic Frontier in High Energy Physics

(d) Theoretical Research in High Energy Physics

(e) Computational Research in High Energy Physics

(f) Accelerator Science and Technology Research and Development in High Energy Physics

(g) Detector Research and Development in High Energy Physics

(h) Quantum Information Science for High Energy Physics Research

6. Nuclear Physics (NP)

(a) Medium Energy Nuclear Physics

(b) Heavy Ion Nuclear Physics

(c) Nuclear Structure and Nuclear Astrophysics

(d) Fundamental Symmetries

(e) Nuclear Theory

(f) Nuclear Data

(g) Nuclear Physics Computing

(h) Accelerator Research and Development for Current and Future Nuclear Physics Facilities

(i) R&D in Quantum Information Science (QIS)

7. Isotope R&D and Production (DOE IP)

(a) Isotope Production Research

(b) Isotope Processing, Purification, Separation, and Radiochemical Synthesis

(c) Biological Tracers and Imaging

(d) Isotopic Enrichment Technology

8. Accelerator R&D and Production (ARDAP)

Program Descriptions

1. Advanced Scientific Computing Research (ASCR) Program Website: https://science.osti.gov/ascr

ASCR’s mission is to advance applied mathematics and computer science; deliver the most advanced computational scientific applications in partnership with disciplinary science; advance https://science.osti.gov/ascr computing and networking capabilities; and develop future generations of computing hardware and software tools for science and engineering, in partnership with the research community, including U.S. industry. The ASCR program gives the science and technology community, including U.S. industry, access to world-class supercomputers and the tools to use them for science and engineering. ASCR accomplishes this by developing and maintaining world-class computing and network facilities for science; and advancing research in applied mathematics, computer science, and advanced networking.

The computing resources and high-speed networks required to meet the scientific needs of the future exceed the state-of- the-art by a significant margin. Furthermore, the algorithms, software tools, the software libraries and the distributed software environments needed to accelerate scientific discovery through modeling and simulation are beyond the realm of commercial interest. To establish and maintain DOE’s modeling and simulation leadership in scientific areas that are important to its mission, ASCR operates Leadership Computing facilities, a high-performance production computing center, and a high-speed network, and implements a broad base research portfolio to solve complex problems on computational resources that are on a trajectory to reach well beyond hundreds and thousands of petaflops within a few years.

Proposed research under ASCR for the FY 2024 Funding for Accelerated, Inclusive Research (FAIR) FOA must be responsive to one of the specific subprograms below:

(a) Applied Mathematics

This subprogram supports basic research leading to fundamental mathematical advances and computational breakthroughs across DOE and SC missions. Applied Mathematics efforts span a range of research in scalable high-performance solvers, adaptive multiscale mathematical models, and coupled scientific data analysis, statistical methodologies, and algorithms. These research developments are the foundation for enabling predictive models, simulations, and analysis of DOE-relevant science and engineering applications. The specific topic areas of interest are:

(i) Extreme-Scale Algorithms for Scientific Computing Technical Contact: Steven Lee, Steven.Lee@science.doe.gov

The scientific computing research community faces a broad array of challenges in the development of high-performance algorithms and solvers for emerging computing architectures.

Because algorithms, solvers, and decision support methods can dominate the overall execution time of computational and data science applications, research in developing efficient, robust, resilient, and portable techniques is essential for scientific advances over the next decade.

Research areas of interest include novel approaches for addressing grand challenges such as:

• High computational and communication complexity and the development of efficient algorithms,

• Better algorithm scalability for low-power, high-performance computing,

• Reduced ill-conditioning and sensitivity for inverse problems, and

• Improved algorithm reliability and robustness to noise mailto:Steven.Lee@science.doe.gov

These challenges should be addressed in the context of future architectures where extreme parallelism, data placement and movement, resilience, and extreme heterogeneity may be significant considerations. The ASCR workshop report on “Randomized Algorithms for Scientific Computing” includes the types of algorithms and research directions that are in scope for this topic area.

Topics and research areas that are out of scope for sub-topic (1) include:

• Pre-applications that do not address one or more of the four grand challenges described above.

• Pre-applications and applications that do not address research for creating a body of knowledge and understanding that will inform future advances in extreme-scale science;

• Pre-applications that do not clearly articulate the main scientific motivations and barriers to progress, the technical basis for overcoming those barriers, and the key insights or novel approaches for addressing the scientific and technical challenges; and

• Research in cryptography or quantum computing algorithms.

(ii) Scalable Scientific Data Analysis and Reduction Technical Contact: William Spotz, William.Spotz@science.doe.gov

The incorporation of increasingly massive data sets in scientific computing is a growing challenge for the scientific community. This topic area seeks rigorous and innovative mathematical and computationally efficient approaches that address the use of such data sets, relevant to the DOE mission, in three ways: (1) machine learning algorithms in accordance with priority research directions outlined in the Report on Basic Research Needs for Scientific Machine Learning: Core Technologies for Artificial Intelligence; (2) analyzing and extracting information and insight from large-scale data, especially the integration of observational data, experimental data, simulations and/or models using new statistical methodologies; and (3) the reduction of data consistent with the core research topics presented in the Workshop Brochure on Data Reduction for Science.

Topics and research areas that are out of scope for sub-topic (2) include:

• Pre-applications and applications that do not address any of the three specified scenarios detailed above.

• Research and development that requires or assumes that the bulk of the data are all in one place, rather than widely distributed geographically.

• Use of machine learning algorithms to address a specific problem; proposed research should advance the mathematics of machine learning, not apply machine learning.

• Use of data reduction algorithms to address a specific problem; proposed research should advance the mathematics of data reduction, not apply data reduction.

(iii) Multiscale Mathematics for the Modeling and Simulation of Complex Systems Technical Contact: William Spotz, William.Spotz@science.doe.gov

Innovative mathematics research is needed to improve the fidelity and predictability of continuous and/or distributed complex systems that accurately capture the physics and/or mailto:William.Spotz@science.doe.gov mailto:William.Spotz@science.doe.gov subcomponent interactions across vastly different time and length scales. This topic area is focused on the challenges of accurately coupling different multi-physics systems, the rigorous development of hybrid or hierarchical mathematical models that incorporate machine learning or reduced order models, and other approaches that bring together multiple facets of more realistic, predictive modeling and simulation.

Topics and research areas that are out of scope for sub-topic (3) include: pre-applications and applications that do not address innovation in coupling or multifaceted mathematical models.

Overall, the topics and research areas that are out of scope for Applied Mathematics include:

• Approaches for specific scientific or engineering problems that are not applicable to a broader class of problems,

• Approaches with a primary emphasis on tailoring, or the implementation of, existing numerical methods for specific scientific problems,

• Computational implementation or frameworks for scientific or engineering problems that are primarily based on specific programming models or architecture,

• Research that results in incremental improvements to the existing state of practice.

Important note for encourage and discourage decisions: Pre-applications must clearly articulate the main scientific motivations and barriers to progress, the technical basis for overcoming those barriers, and the key insights or novel approaches for addressing the scientific and technical challenges. The lack of such details is sufficient for discouragement of the proposed research.

References:

(1) Workshop report on Randomized Algorithms for Scientific Computing (RASC), https://doi.org/10.2172/1807223

(2) Data Reduction for Science, https://doi.org/10.2172/1770192

(3) Basic Research Needs for Scientific Machine Learning: Core Technologies for Artificial

Intelligence, https://doi.org/10.2172/1478744

(4) Opportunities and Challenges from Artificial Intelligence and Machine Learning for the

Advancement of Science, Technology, and the Office of Science Missions -https://doi.org/10.2172/1734848

(5) AI for Science: Report on the Department of Energy (DOE) Town Halls on Artificial Intelligence (AI) for Science - https://doi.org/10.2172/1604756

(6) 2018 Basic Research Needs Workshop on Extreme Heterogeneity, https://doi.org/10.2172/1473756

(7) Report on Applied Mathematics Research for Exascale Computing, https://doi.org/10.2172/1149042

(8) DOE Workshop Report on Multiphysics Simulations https://science.osti.gov/- /media/ascr/pdf/programdocuments/docs/MultiPhysics-Simulations-Report.pdf

(9) Report on the Extreme Scale Solvers Workshop, https://science.osti.gov/- /media/ascr/pdf/program- documents/docs/reportExtremeScaleSolvers2012.pdf

(10) Report on A Multifaceted Mathematical Approach for Complex Systems https://science.osti.gov/-/media/ascr/pdf/program-documents/docs/Multifaceted_Mathematical_Approach_for_Complex_Systems.pdf https://doi.org/10.2172/1807223 https://doi.org/10.2172/1770192 https://doi.org/10.2172/1478744 https://doi.org/10.2172/1734848 https://doi.org/10.2172/1604756 https://doi.org/10.2172/1473756 https://doi.org/10.2172/1149042 https://science.osti.gov/-/media/ascr/pdf/programdocuments/docs/MultiPhysics-Simulations-https://science.osti.gov/-/media/ascr/pdf/programdocuments/docs/MultiPhysics-Simulations-https://science.osti.gov/-/media/ascr/pdf/programdocuments/docs/MultiPhysics-Simulations-Report.pdf https://science.osti.gov/-/media/ascr/pdf/program-documents/docs/reportExtremeScaleSolvers2012.pdf https://science.osti.gov/-/media/ascr/pdf/program-documents/docs/reportExtremeScaleSolvers2012.pdf https://science.osti.gov/-/media/ascr/pdf/program-documents/docs/reportExtremeScaleSolvers2012.pdf https://science.osti.gov/-/media/ascr/pdf/program-documents/docs/Multifaceted_Mathematical_Approach_for_Complex_Systems.pdf https://science.osti.gov/-/media/ascr/pdf/program-documents/docs/Multifaceted_Mathematical_Approach_for_Complex_Systems.pdf

(b) Computer Science

This subprogram supports research that enables computing and networking at extreme scales and the understanding of extreme scale and complex data from both simulations and experiments. It aims to make high performance scientific computers and networks highly productive and efficient to solve scientific challenges while attempting to reduce domain science application complexity as much as possible.

Topics of interest for this FOA are focused on the following key core computer science research areas:

(i) Systems Technical Contact: Hal Finkel, Hal.Finkel@science.doe.gov

a. Programming Models and Environments: Innovative programming models for developing applications on next-generation platforms, exploiting unprecedented parallelism, heterogeneity of memory systems (e.g. Non-Uniform Memory Access [NUMA], non-coherent shared memory, high-bandwidth memory [HBM], scratchpads, and heterogeneity of processing (e.g., Graphics Processing Units [GPUs], Field- Programmable Gate Arrays [FPGAs], Coarse-Grained Reconfigurable Architectures [CGRAs], other types of accelerators, big-small cores, processing in memory, and near memory, etc.), with particular emphasis on making it easier to program at scale. All phases of the software-development cycle are relevant, including but not limited to, design, implementation, verification, optimization, and integration. Particularly welcome are methods that infuse artificial intelligence/machine learning into the programming environment.

b. Operating and Runtime Systems: System software that provides intelligent, adaptive resource management and support for highly parallel software and workflow-management systems, and that facilitates effective and efficient use of heterogeneous computing technologies, including diverse execution models, processors, accelerators, memory, and storage systems. Target workloads include modeling and simulation, data analysis, and the processing of large-scale, streaming data from experiments.

c. Performance Portability and Co-design: Methods that support performance portability, which provides the ability to efficiently use diverse kinds of hardware platforms with minimal changes to the application source code, and/or hardware/software co-design, which is a method for designing and/or adapting both hardware and software design as part of a holistic process. These methods include automated and semi-automated refinements from high-level specification of an application and/or hardware design to low-level code, optimized when compiled and/or, for software, at runtime, to different HPC platforms. The focus is on enabling performance portability of, and/or the design of future hardware for, applications developed for extreme-scale computing and beyond.

Applications are not restricted to a single Systems topic above and may span all of them, provided the scope of work remains appropriate for the program.

mailto:Hal.Finkel@science.doe.gov

(ii) Data Management, Visualization, and Analytics Technical Contact: Margaret Lentz, Margaret.Lentz@science.doe.gov

a. Data Management approaches for managing and analyzing large and complex data

(multidimensional, multimodal, etc.) from scientific experiments and simulations are of interest as highlighted recent ASCR Workshop on the Management and Storage of Scientific Data, building on the outcomes of prior community activities, including Storage Systems and I/O: Organizing, Storing, and Accessing Data for Scientific Discovery and the Office of Science Roundtable on Data for AI. Areas of interest include:

• Innovative interfaces and management methods that allow for flexible, high-performance access to large data sets, potentially federated across different kinds of memory, edge devices, and repositories, capturing and management relevant usage statistics, provenance, and other metadata.

• Innovative methods to design scientific-data-management services for state-of-the-art storage and networking devices, including those providing computational capabilities.

b. Analytic Methods and Environments includes approaches to improve visual exploration and understanding of petabyte to exabyte multi-scale, multi-physics scientific data sets from simulations and/or experimental platforms; to support efficient analysis of data across federated resources; to support interactivity with simulation and/or real-time steering of experiments, including remote interactions; and to help answer scientifically relevant questions from the data about, for example, uncertainty, sensitivity analysis, causality, and the debugging of codes and methods. As appropriate, applicants are encouraged to consider evaluation methods for new visualization tools and techniques resulting from the proposed research. These areas highlighted in the recent ASCR Workshop on Visualization for Scientific Discovery, Decision-Making, and Communication. Areas of interest include:

• Advancing Theory and Techniques for Visualization to Support the Analysis and Understanding of Complex Scientific Data

• Introducing Interoperable and Adaptable Visualization to Support Diverse Scientific Workflows Across All Scales

• Harnessing Technology Innovations to Accelerate Science through Visualization

• Developing Intelligent Approaches for Adaptive, Context-Aware Visualization of

Scientific Data and AI

The primary focus of the proposed work for either topic A or B must be on innovative computer- science techniques, which may include explainable machine learning and AI techniques to help address the aforementioned areas of data management, visualization, and analytics.

Topics that are out of scope for the Computer Science subprogram include:

• Pre-applications and applications that do not address the specific Computer Science topics described above.

• Pre-applications and applications that do not explain/describe their relevance to current mailto:Margaret.Lentz@science.doe.gov and future high performance computing platforms and/or data-centric science as well as their relevance to the mission of SC and ASCR.

• Pre-applications and applications that focus primarily on the development or application of data-reduction techniques (see Applied Mathematics Topic on Scientific Machine Learning, Data Analysis and Reduction).

• Pre-applications and applications that are primarily focused on the mathematics of AI (see Applied Mathematics Topic on Scientific Machine Learning, Data Analysis and Reduction).

• Pre-applications and applications with primary emphasis on computer hardware design, fabrication, or integration; materials science; and computing devices and/or device/circuit design and/or manufacturing.

• Research primarily focused on advancing discipline-specific research or capabilities without also proposing a generalization of this research to other SC priority mission areas.

• Research primarily focused on advancing Virtual Reality and Augmented Reality technologies.

• Research focused on the World Wide Web and/or Internet.

• Research that is only applicable to hand-held, tablets, laptops, portable, desktop, embedded or cloud computing.

• Research focused on quantum computing.

References:

(1) DOE Workshop report: Reimagining Codesign. https://www.osti.gov/biblio/1822199/

(2) DOE Workshop report: The Management and Storage of Scientific Data. United

States, 2023. https://www.osti.gov/biblio/1845707/

(3) DOE Workshop report: Management, Analysis and Visualization of Experimental and

Observational Data: The Convergence of Data and Computing https://www.osti.gov/biblio/1440647

(4) DOE Workshop report: Crosscut Report: Exascale Requirements Reviews, March 2017.

https://science.osti.gov/~/media/ascr/pdf/programdocuments/docs/2018/DOE- ExascaleReport- CrossCut.pdf

(5) DOE Workshop report: Storage Systems and Input/Output: Organizing, Storing, and Accessing Data for Scientific Discovery. https://www.osti.gov/biblio/1491994/

(6) DOE Workshop report: Data and Models: A Framework for Advancing AI in Science https://www.osti.gov/biblio/1579323

(7) DOE Workshop brochure: Visualization for Scientific Discovery, Decision-Making, and Communication. https://www.osti.gov/biblio/1845708

(c) Advanced Computing Technologies (ACT)

This subprogram supports quantum computing and networking efforts and Research and Evaluation Prototypes (REP). The REP activity addresses the challenges of next generation computing systems. By actively partnering with the research community, including industry and Federal agencies, on the development of technologies that enable next-generation machines, ASCR ensures that commercially available architectures serve the needs of the scientific community. The REP activity also prepares researchers to effectively use future generation of scientific computers, including novel technologies, and seeks to reduce risk for future major https://www.osti.gov/biblio/1822199/ https://www.osti.gov/biblio/1440647 https://science.osti.gov/%7E/media/ascr/pdf/programdocuments/docs/2018/DOE-ExascaleReport-CrossCut.pdf https://science.osti.gov/%7E/media/ascr/pdf/programdocuments/docs/2018/DOE-ExascaleReport-CrossCut.pdf https://science.osti.gov/%7E/media/ascr/pdf/programdocuments/docs/2018/DOE-ExascaleReport-CrossCut.pdf https://www.osti.gov/biblio/1491994/ https://www.osti.gov/biblio/1579323 https://www.osti.gov/biblio/1845708 procurements. The specific topic areas of interest are:

(i) Quantum Computing and Networking Technical Contact: Marco Fornari, Marco.Fornari@science.doe.gov

• Research to evaluate the suitability of specific quantum computing hardware architectures or devices for science applications, including resource estimates for quantum computing applications of interest to SC.

• Theoretical methods and software tools to assess the performance of real-world quantum processors, facilitate device-specific optimization of individual operations ranging from state preparation and measurement through gate implementation and compilation, suppress noise, mitigate crosstalk, control errors, and maintain optimally high-fidelity operations in the absence of formal error correction.

• Proof-of-concept demonstrations of technology required for distributing quantum entanglement in a multi-node network.

• Theoretical explorations of possible applications of a quantum network for advancing scientific research.

(ii) Emerging Computing Technical Contact: Robinson Pino, Robinson.Pino@science.doe.gov

• Neuromorphic Computing: Research and development of biological and computational neuroscience-inspired computing software tools and techniques as well as energy-efficient hardware. The aim is to create computing environments that will help accelerate artificial intelligence for scientific research while advancing the development of neuromorphic approaches to computation.

• Advanced Wireless: Research and development approaches to reinvent the digital continuum linking the wireless edge to advanced high-performance computing and data centers, and effectively integrate data collection from advanced wireless scientific sensors or edge computing devices through enhanced or new computational software tools that can provide end-to-end services such as data movement, analysis, integrity, and performance optimization.

• Microelectronics: Research and development approaches leveraging microelectronic technologies, leading edge devices, application specific architectures, advanced packaging, algorithms, and the software tools required to design, simulate, and prototype emerging computing systems.

Topics that are out of scope for the Advanced Computing Technologies subprogram include:

• Research that does not address the specific ACT topics described above;

• Development of application-specific techniques to use quantum computers or application-specific quantum algorithms that do not generalize to multiple scientific domains;

• Development of new candidate qubit systems or improvements to physical qubits;

• Development of integrated circuits for quantum computing;

• Cryptography and cryptanalysis;

• Quantum Key Distribution and other security-focused approaches to quantum communication;

• Error correction codes and implementation of error correction codes for quantum computers;

mailto:marco.fornari@science.doe.gov and

• Research solely relevant to large-scale, high-fidelity, fault-tolerant quantum computers; and

• Projects that are duplicative of or competitive with industry.

2. Basic Energy Sciences (BES) Program Website: https://science.osti.gov/bes/

The mission of the Basic Energy Sciences (BES) program is to support fundamental research to understand, predict, and ultimately control matter and energy at the electronic, atomic, and molecular levels. BES research provides the foundations to develop new energy technologies, to mitigate the climate and environmental impacts of energy generation/use, and to support DOE missions in energy, environment, and national security. The portfolio supports fundamental research in Materials Sciences and Engineering (MSE) and Chemical Sciences, Geosciences, and Biosciences (CSGB). BES accomplishes its mission through excellence in scientific discovery in the energy sciences, and through stewardship of world-class scientific user facilities that enable cutting-edge research and development.

The research disciplines that BES supports—condensed matter and materials physics, chemistry, geosciences, and aspects of biosciences—touch virtually every important aspect of energy resources, production, conversion, transmission, storage, efficiency, and waste mitigation, providing a knowledge base for achieving a secure and sustainable clean energy future. The Basic Energy Sciences Advisory Committee (BESAC) report, “A Remarkable Return on Investment in Fundamental Research“ provides key examples of major technological, commercial, and national security impacts, including clean energy technologies, directly traceable to BES-supported basic research.

Subprograms Technical Contact: BES-FAIR.FOA@science.doe.gov Program Manager to select when submitting a pre-application: Viviane Schwartz

The BES program funds research in the following subprograms. Proposed research must be responsive to one of the core research areas in one of the following six subprograms:

(a) Scattering and Instrumentation Sciences Research

Advancing science using new tools and techniques to characterize materials structure and dynamics across multiple length and time scales, including ultrafast science, and to correlate this data with materials performance under real world and extreme conditions. Core research areas include x-ray scattering, neutron scattering, electron and scanning probe microscopies, and accelerator and detector research.

(b) Condensed Matter and Materials Physics Research

Understanding the foundations of material functionality and behavior including electronic, thermal, optical, and mechanical properties; the impact of extreme environments; and materials whose properties arise from the effects of quantum mechanics. Core research areas include https://science.osti.gov/bes/ https://science.osti.gov/bes/ https://science.osti.gov/bes/mse https://science.osti.gov/bes/csgb https://science.osti.gov/bes/csgb https://science.osti.gov/%7E/media/bes/pdf/BESat40/BES_at_40.pdf https://science.osti.gov/%7E/media/bes/pdf/BESat40/BES_at_40.pdf mailto:BES-FAIR.FOA@science.doe.gov https://science.osti.gov/bes/mse/Research-Areas/Scattering-and-Instrumentation-Sciences https://science.osti.gov/bes/mse/Research-Areas/X-Ray-Scattering https://science.osti.gov/bes/mse/Research-Areas/Neutron-Scattering https://science.osti.gov/bes/mse/Research-Areas/Electron-and-Scanning-Probe-Microscopies https://science.osti.gov/bes/suf/Accelerator-and-Detector-Research https://science.osti.gov/bes/mse/Research-Areas/Condensed-Matter-and-Materials-Physics experimental condensed matter physics, theoretical condensed matter physics, physical behavior of materials, mechanical behavior and radiation effects, and quantum information science.

(c) Materials Discovery, Design, and Synthesis Research

Developing the knowledge base and synthesis strategies to design and…