DE-FOA-0003450.000001.pdf

Department of Energy (DOE) Office of Science (SC)

Early Career Research Program (ECRP)

Notice of Funding Opportunity (NOFO) Number:

DE-FOA-0003450

NOFO Type: Amendment 000001

CFDA Number: 81.049

Amendment 000001 is issued to remove references to diversity, equity, and inclusion; to remove references to PIER plans; to update regulatory requirements from Title 2 CFR; and to update research, technology, and economic security provisions.

NOFO Issue Date: January 17, 2025 Submission Deadline for Pre-Applications:

February 18, 2025, at 5:00 PM ET A Pre-Application is required.

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

Pre-Application Response Date: March 18, 2025, at 5:00 PM ET Submission Deadline for Applications: April 22, 2025, at 11:59 PM ET

Table of Contents

I. Basic Information

Executive Summary

Funding Details

Key Facts

Key Dates

Agency Contact Information

Informational Webinar / Office Hours

Recommendation

II. Eligibility

A. Eligible Applicants

B. Cost Sharing

C. Eligible Individuals

D. Limitations on Submissions

III. Program Description

A. Purpose

B. Program Goals, Objectives, and Priorities

C. Award Contribution to Goals and Objectives

D. Performance Goals

E. Substantial Involvement

F. Program Unallowable Costs

G. Citations to Statute and Regulations

H. Program History

I. Other Information

IV. Application Contents and Format

A. Preliminary Submissions

B. Application

C. Component Pieces of the Application

D. Information that Must be Submitted After Application but Before Award

V. Submission Requirements and Deadlines

A. Address to Request Application Package

B. Unique Entity Identifier (UEI) and System for Award Management (SAM.gov)

C. Submission Instructions

D. Submission Dates and Times

VI. Application Review Information

A. Responsiveness Review

B. Review Criteria

C. Review and Selection Process

VII. Award Notices

A. Type of Award Instrument

B. Anticipated Timeline for Notice of Selection for Award Negotiation

VIII. Post-Award Requirements and Administration

A. Administrative and National Policy Requirements

B. Reporting

C. Reporting of Matters Related to Recipient Integrity and Performance (December 2015) . 102

D. Interim Conflict of Interest Policy for Financial Assistance

IX. Other Information

A. Checklist for Avoiding Common Errors

B. How-To Guides

C. Administrative and National Policy Requirements

D. Reference Material

I. Basic Information

U.S. Department of Energy (DOE) Office of Science (SC)

Executive Summary

DOE SC hereby invites applications for support under the ECRP in the following program areas:

Advanced Scientific Computing Research (ASCR); Basic Energy Sciences (BES); Biological and Environmental Research (BER); Fusion Energy Sciences (FES); High Energy Physics (HEP); Nuclear Physics (NP); Isotope Research and Development (R&D) and Production (DOE IP); and Accelerator R&D and Production (ARDAP). The purpose of this program is to support the development of individual research programs of outstanding scientists early in their careers and to stimulate research careers in the areas supported by SC.

SC’s mission is to deliver the 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 the lead Federal agency supporting fundamental scientific research for our Nation’s energy future.

SC accomplishes its mission and advances national goals by supporting:

• Science for energy, economic and national security―building a foundation of scientific and technical knowledge to spur discoveries and innovations for advancing the Department’s mission. 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.

• 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.

Funding Details Expected total available funding $136 million in current and future fiscal year funds Expected number of awards 94 Expected total dollar amount of individual awards

$875,000 for an Institution of Higher Education $2,750,000 for a DOE/NNSA National Laboratory $2,750,000 for an SC Scientific User Facility

Expected award project period 5 years

Key Facts NOFO Title Early Career Research Program (ECRP) NOFO Number DE-FOA-0003250 Announcement Type Amendment 000001 Assistance Listing 81.049 Statutory Authority The programmatic authorizing statutes are:

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

Governing 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

Key Dates

Key dates are printed on the cover of this NOFO.

Agency Contact Information

Grants.gov Customer Support

800-518-4726 (toll-free) support@Grants.gov

PAMS

Customer Support

855-818-1846 (toll-free) 301-903-9610 sc.pams-helpdesk@science.doe.gov

Technical/Scientific Program Contact

Questions regarding the specific program areas/technical requirements can be directed to the program managers/technical contacts listed for each program within the

NOFO.

Administrative Contact (questions about budgets and eligibility)

SC.Early@science.doe.gov

Informational Webinar / Office Hours

SC plans to hold an informational webinar about this NOFO. Registration instructions and other details will be posted at https://science.osti.gov/early-career and at https://science.osti.gov/grants/FOAs/Open.

Recommendation

SC encourages you to register in all systems as soon as possible. You are also encouraged to submit pre-applications and applications well before the deadline.

mailto:support@grants.gov mailto:sc.pams-helpdesk@science.doe.gov mailto:SC.Early@science.doe.gov https://science.osti.gov/early-career https://science.osti.gov/grants/FOAs/Open

II. Eligibility

A. Eligible Applicants

In accordance with 2 CFR 910.126, Competition, eligibility for award is restricted to U.S.

Institutions of Higher Education, DOE National Laboratories (listed at https://www.energy.gov/national-laboratories), and institutions operating SC Scientific User Facilities (listed at https://science.osti.gov/User-Facilities).

This eligibility restriction is intended to create an opportunity for the most promising scientists who are (a) early in their careers, (b) in positions with sufficient permanence to support independent research efforts, and (c) for investigators not at DOE-affiliated institutions, in positions that require working with the students who will become the scientific workforce of the future.

1. DOE/NNSA National Laboratories

DOE/NNSA National Laboratories are eligible to submit applications under this NOFO, but may not be proposed as subrecipients under another organization’s application. If recommended for funding as a lead applicant, funding will be provided through the DOE Field-Work Proposal System and work will be conducted under the laboratory’s contract with DOE. No administrative provisions of this NOFO will apply to the laboratory or any laboratory subcontractor. Additional instructions for securing authorization from the cognizant Contracting Officer are found in Section IX of this NOFO.

Submission of a pre-application (in PAMS) or an application (in Grants.gov) by an authorized institutional representative is a confirmation that the proposed research idea fits within the scope of SC-funded programs at the national laboratory. Proposing research that falls within this category ensures that investigators have the opportunity to belong to or join, at the laboratory’s discretion, funded research groups.

Investigators funded under this program are encouraged to charge at least 50% of their time to the award, allowing time to develop or maintain funded collaborations within the lab over the course of the award. Amounts less than 50% should be as close to 50% as possible. Making sure that investigators have potential connections with SC funded programs encourages the laboratory to actively plan to address funding transition issues that may arise when an award ends.

Applications from DOE National Laboratories should not: (a) attempt to revive previously terminated research areas within the laboratory, or (b) topically isolate investigators.

Eligibility exemptions will not be granted.

2. SC Scientific User Facilities not at a DOE/NNSA National Laboratory

Institutions operating SC Scientific User Facilities are eligible to submit applications under this NOFO. If recommended for funding as a lead applicant, funding will be provided as a financial https://www.energy.gov/national-laboratories https://science.osti.gov/User-Facilities assistance award to the non-Governmental entity operating the User Facility.

Submission of a pre-application (in PAMS) or an application (in Grants.gov) by an authorized institutional representative is a confirmation that the proposed research idea fits within the scope of SC-funded programs at the User Facility. Proposing research that falls within this category ensures that investigators have the opportunity to belong to or join, at the facility’s discretion, funded research groups.

Investigators funded under this program are encouraged to charge at least 50% of their time to the award, allowing time to develop or maintain funded collaborations within the facility over the course of the award. Amounts less than 50% should be as close to 50% as possible. Making sure that investigators have potential connections with SC funded programs encourages the facility to actively plan to address funding transition issues that may arise when an award ends.

Applications from SC Scientific User Facilities should not (a) attempt to revive previously terminated research areas within the facility or (b) topically isolate investigators.

Eligibility exemptions will not be granted.

3. Non-DOE/NNSA FFRDCs

Non-DOE/NNSA FFRDCs are neither eligible to submit applications under this NOFO nor to be proposed as subrecipients under another organization’s application.

4. Other Federal Agencies

Other Federal Agencies are neither eligible to submit applications under this NOFO nor to be proposed as subrecipients under another organization’s application.

Notes for applicants of all types:

Eligibility is restricted to the above entities due to the requirement for an applicant institution to have already made a career commitment to individuals as exemplified by putting them on the tenure track or in a permanent position at a national laboratory or an SC Scientific User Facility.

Non-tenure-track positions and fellowships lack the expected permanence required by the ECRP.

Outside of DOE/NNSA National Laboratories and SC Scientific User Facilities, tenure track faculty positions at academic institutions involve a long standing growth and evaluation process committed to by the institution. Achieving tenure is a uniquely academic pursuit: No equivalent positions exist in industry or non-profit organizations.

This NOFO seeks to support basic research to advance understanding rather than to address commercial opportunities. Applications that propose research related to current commercial activity or current customer needs may be declined without merit review.

Applications that are submitted by applicants that have not submitted a required pre-application may be declined without further review.

B. Cost Sharing

Cost sharing for basic and fundamental research is not required pursuant to an exclusion from the requirements of Section 988 of the Energy Policy Act of 2005.

Cost sharing is not required of DOE/NNSA National Laboratories or their subcontractors at any tier. DOE/NNSA National Laboratories may impose cost-sharing requirements on their contractors subject to their policies and procedures.

Cost sharing will not be considered as a factor during merit review or award selection.

C. Eligible Individuals

Individuals with the skills, knowledge, and resources necessary to carry out the proposed research as a Principal Investigator (PI) are invited to work with their organizations to develop an application. Individuals from underrepresented groups as well as individuals with disabilities are always encouraged to apply.

SC does not require that individuals be U.S. citizens or permanent residents to be proposed as a PI or in any other role under an award, but all personnel working or proposed to work under an award must have the legal right to perform such work in the jurisdiction where the work will be performed.

There can be no co-PIs. Applications including co-PIs may be declined without review.

PIs who have received awards previously under the SC ECRP are not eligible. PIs of early career awards funded by other agencies or entities are eligible, but the proposed research must have a scope different from that already funded by the other organization.

No more than 10 years can have passed between the year the PI’s Ph.D. was awarded and the calendar year in which this NOFO is released. For the present competition, those who received doctorates on or after January 1, 2014, are eligible. If a PI has multiple doctorates, the discipline of the one they have earned within the 10-year eligibility window must be relevant to the proposed research. To address special circumstances and challenges due to the COVID-19 pandemic, during FY2023 and FY2024 SC extended the PI eligibility window for the competition from 10 to 12 years for all applicants. In line with the expectation described in last year’s ECRP NOFO (DE-FOA-0003176), SC reverted to the original 10-year PI eligibility window in this year’s competition.

Extensions to eligibility will be considered for individuals who have had a major life event requiring an extended absence (three months or longer) from the workplace, including but not limited to active military service, an absence due to personal disability, or an absence covered by the Family and Medical Leave Act. Requests for extended eligibility must be made by including in the pre-application a letter signed by the dean, research vice president, laboratory division director, or equivalent official stating that the proposed PI will have, as of the application deadline, no more than 10 years of full-time professional work experience in positions requiring a Ph.D. in the field in which the application will be submitted. The request for an eligibility extension will be evaluated as part of the pre-application assessment.

PIs from Institutions of Higher Education, DOE National Laboratories, and SC Scientific User Facilities must adhere to the respective eligibility standards below.

The eligibility requirements improve the quality of applications submitted and encourages those who are strong candidates to submit applications to the program.

1. PIs from Institution of Higher Education

The PI must be an untenured Assistant Professor on the tenure track or an untenured Associate Professor on the tenure track at a U.S. academic institution where the application is originating from and as of the deadline for the application. The PI must be employed in the eligible position as of the closing date for this NOFO. If a PI has multiple doctorates, the discipline of the one they have earned within the 10-year eligibility window should be relevant to the proposed research.

2. PIs from DOE/NNSA National Laboratories

The PI must be a full-time, permanent, non-postdoctoral national laboratory employee as of the deadline for the application. If a PI has multiple doctorates, the discipline of the one they have earned within the 10-year eligibility window should be relevant to the proposed research.

3. PIs from SC Scientific User Facilities not at a DOE/NNSA National Laboratory

The PI must be a full-time, permanent, non-postdoctoral user facility employee as of the deadline for the application. If a PI has multiple doctorates, the discipline of the one they have earned within the 10-year eligibility window should be relevant to the proposed research.

D. Limitations on Submissions

While there is no limit on the number of pre-applications from a DOE/NNSA national laboratory or an SC Scientific User Facility in a given year, each laboratory or user facility is responsible for ensuring that the research ideas submitted in its pre-applications fit within the scope of SC-funded programs at the national laboratory or the user facility.

LIMITATIONS ON PI

Only one application on behalf of a PI may be submitted in any given SC ECRP competition. A PI may not submit an application in more than three SC ECRP competitions.

Submission of multiple distinct pre-applications on behalf of a PI is allowed in any given SC ECRP competition, but only one application may be encouraged. The same pre-application should not be submitted multiple times in any given SC ECRP competition: a pre-application is assigned to the program manager best aligned with the proposed work.

Participation in the competition is defined as submission of a full application that completed the review/decision process. In rare cases, it is necessary to withdraw an application; an application withdrawn prior to it being officially declined will not count as a submission. Likewise, an application declined without merit review by the DOE SC will not count as a submission.

Letters of recommendation and department chair letters are not allowed. Applications that include recommendation or department chair letters will be subject to elimination from consideration during DOE’s initial review.

III. Program Description

A. Purpose

The DOE SC hereby invites applications for support under the ECRP in the following program areas: Advanced Scientific Computing Research (ASCR); Basic Energy Sciences (BES);

Biological and Environmental Research (BER); Fusion Energy Sciences (FES); High Energy Physics (HEP); Nuclear Physics (NP); Isotope Research and Development (R&D) and Production (DOE IP); and Accelerator R&D and Production (ARDAP). The purpose of this program is to support the development of individual research programs of outstanding scientists early in their careers and to stimulate research careers in the areas supported by SC.

SUPPLEMENTARY INFORMATION

B. Program Goals, Objectives, and Priorities

The Office of Science’s (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 (U.S.). SC is the Nation’s largest Federal sponsor of basic research in the physical sciences and the lead Federal agency supporting fundamental scientific research for our Nation’s energy future.

• Science for energy, economic and national security―building a foundation of scientific and technical knowledge to spur discoveries and innovations for advancing the Department’s mission. 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.

• 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.

SC is an established leader of the U.S. scientific discovery and innovation enterprise. Over the decades, SC investments and accomplishments in basic research and enabling research capabilities have provided the foundations for new technologies, businesses, and industries, making significant contributions to our nation’s economy, national security, and quality of life

ECRP opportunities exist in the following SC research programs. Additional details about each program, websites, and technical points of contact are provided in the materials that follow.

Advanced Scientific Computing Research (ASCR)

(1) Multiscale Mathematics for the Modeling and Simulation of Complex Systems

(2) Scalable Scientific Machine Learning, Data Analysis, and Reduction

(3) Systems

(4) Data Management, Visualization, and Analytics

(5) Quantum Computing

(6) Quantum Networking

(7) Emerging Computing Technologies

Basic Energy Sciences (BES)

(1) Materials Chemistry

(2) Biomolecular Materials

(3) Synthesis and Processing Science

(4) Experimental Condensed Matter Physics

(5) Theoretical Condensed Matter Physics

(6) Physical Behavior of Materials

(7) Mechanical Behavior and Radiation Effects

(8) Quantum Information Science in Materials Sciences and Engineering (QIS-MSE)

(9) X-ray Scattering

(10) Neutron Scattering

(11) Electron and Scanning Probe Microscopies

(12) Atomic, Molecular, and Optical Sciences (AMOS)

(13) Gas Phase Chemical Physics (GPCP)

(14) Computational and Theoretical Chemistry

(15) Condensed Phase and Interfacial Molecular Science (CPIMS)

(16) Quantum Information Science Research in Chemical Sciences, Geosciences, and Biosciences (QIS-CSGB)

(17) Catalysis Science

(18) Separation Science (SEP)

(19) Heavy Element Chemistry (HEC)

(20) Geosciences (GEO)

(21) Solar Photochemistry

(22) Photosynthetic Systems

(23) Physical Biosciences

(24) Accelerator and Detector Research

(25) Instrumentation and Technique Development for BES User Facilities

Biological and Environmental Research (BER)

(1) Systems biology and biosystems design of bioenergy-relevant microbes to enable production of next-generation biofuels, bioproducts, and biomaterials

(2) Understanding and predicting processes regulating methane (CH4) and nitrous oxide (N2O) fluxes from terrestrial ecosystems

Fusion Energy Sciences (FES)

(1) Advanced and Long Pulse Tokamak Research

(2) Spherical Tokamak Research

(3) Stellarator Research in Magnetic Fusion Energy Sciences

(4) Magnetic Fusion Energy Science Theory and Simulation

(5) Measurement Innovation

(6) Inertial Fusion Energy (IFE)

(7) General Plasma Science Experiment and Theory

(8) Fusion Nuclear Science and Enabling R&D Programs for Fusion

(9) Materials Research for Fusion

(10) Artificial Intelligence and Machine Learning for Fusion Energy Sciences

High Energy Physics (HEP)

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

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

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

(4) Theoretical Research in High Energy Physics

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

(6) Detector Research and Development in High Energy Physics

(7) Computational Research in High Energy Physics

(8) Quantum Information Science in High Energy Physics (HEP-QIS)

Nuclear Physics (NP)

(1) Medium Energy Nuclear Physics

(2) Heavy Ion Nuclear Physics

(3) Nuclear Structure and Nuclear Astrophysics

(4) Fundamental Symmetries

(5) Nuclear Theory

(6) Nuclear Theory Computing

(7) Nuclear Data

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

(9) NP - Quantum Information Science (QIS)

Isotope R&D and Production (DOE IP)

(1) Targetry and Isotope Production Research

(2) Nuclear and Radiochemical Separation, Purification, and Radiochemical Synthesis

(3) Biological Tracers, Imaging and Therapeutics

(4) Isotopic Enrichment Technology

Accelerator R&D and Production (ARDAP) Accelerator R&D and Production

Advanced Scientific Computing Research (ASCR) Program Website: https://www.energy.gov/science/ascr/advanced-scientific-computing-research or 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 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.

https://www.energy.gov/science/ascr/advanced-scientific-computing-research https://www.energy.gov/science/ascr/advanced-scientific-computing-research https://science.osti.gov/ascr

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 ECRP must be responsive to one of the specific topic areas below. 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.

Applied Mathematics

This program 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, 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.

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, and

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

The specific topic areas of interest are:

(1) Multiscale Mathematics for the Modeling and Simulation of Complex Systems Technical Contact: Steven Lee, Steven.Lee@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 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 scientific machine learning or reduced order models, and other approaches that bring together multiple facets of more realistic, predictive modeling and simulation [1, 2] and [3, see PRD #5]. A recent National Academies report includes the type of basic research challenges and needs for interactive, data-mailto:Steven.Lee@science.doe.gov driven, computational modeling and simulation [4]. Topics and research areas that are out of scope include:

• Pre-applications and applications that do not address problems that span time and length scales of multiple orders of magnitude,

• Pre-applications and applications that do not address innovation in coupling or multifaceted mathematical models.

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

Rigorous mathematical and computationally efficient approaches are needed for analyzing and extracting information and insight from large-scale data relevant to the DOE missions. Data- Intensive Scientific Machine Learning is Priority Research Direction (PRD) #4 from the 2019 workshop report [3]. The 2021 workshop report on Data Reduction in Science identifies the research and development challenges in that area [5]. This overall topic area is specifically focused on the research and development of scientific machine learning and data reduction in two different scenarios: Models and analysis 1) for large-scale distributed data sets that occurs without moving the data (static), and 2) in real-time, streaming environments (dynamic).

Rigorous mathematical and computationally efficient approaches are needed for analyzing and extracting information and insight from large-scale data relevant to the DOE missions. The principal focus of this topic area is algorithms and techniques that can improve data analysis or reliably reduce the volume of scientific data by finding signals, patterns, or structure under such challenges as high-dimensionality, noise, or uncertainty. Research areas of interest include novel approaches that address PRDs from two recent ASCR workshop reports:

PRD #4 from the Scientific Machine Learning workshop [3]:

4. Data-intensive scientific machine learning for automated scientific inference and data analysis.

PRDs #1-4 from the Data Reduction for Science workshop [5]:

1. Effective algorithms and tools that can be trusted by scientists for accuracy and efficiency,

2. Progressive reduction algorithms that enable data to be prioritized for efficient streaming,

3. Algorithms which can preserve information in features and quantities of interest with quantified uncertainty, and

4. Reduction techniques that map to new architectures and use cases.

Research areas that are out of scope for this topic include:

• Approaches that do not advance data analysis or any of the PRDs listed above,

• Approaches that apply scientific machine learning to a new application, rather than advancing fundamental mathematical aspects of scientific machine learning.

Important note regarding topic areas: The ASCR Applied Mathematics program now rotates its topic areas, competing two of three topics every year. If this is your last year of eligibility and your topic area best matches with Extreme-Scale Algorithms for Scientific Computing, as described in previous ECRP funding opportunities, please contact Steven Lee, Steven.Lee@science.doe.gov.

mailto:William.Spotz@science.doe.gov mailto:Steven.Lee@science.doe.gov

Important note on the encouragement of competitive research: For each Applied Mathematics topic area, the exact number of encouraged applications will depend on the availability of appropriated funds, and ASCR anticipates an award rate of at least ten percent.

See Section IV for details regarding the pre-application submission and review process.

References:

1. Report on A Multifaceted Mathematical Approach for Complex Systems https://www.osti.gov/biblio/1093585/

2. DOE Workshop Report on Multiphysics Simulations https://science.osti.gov/-

/media/ascr/pdf/programdocuments/docs/MultiPhysics-Simulations-Report.pdf

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

Intelligence, https://www.osti.gov/servlets/purl/1478744/

4. National Academies of Sciences, Engineering, and Medicine. 2024. Foundational Research

Gaps and Future Directions for Digital Twins. Washington, DC: The National Academies Press. https://www.nationalacademies.org/our-work/foundational-research-gaps-and-future-directions-for-digital-twins

5. Workshop report on Data Reduction for Science, https://doi.org/10.2172/1770192

Computer Science

This program 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 NOFO are focused on the following key core computer science research areas:

(3) Systems Technical Contact: Hal Finkel, Hal.Finkel@science.doe.gov, Kalyan Perumalla, Kalyan.Perumalla@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.

https://www.osti.gov/biblio/1093585/ https://science.osti.gov/-/media/ascr/pdf/programdocuments/docs/MultiPhysics-Simulations-Report.pdf https://science.osti.gov/-/media/ascr/pdf/programdocuments/docs/MultiPhysics-Simulations-Report.pdf https://www.osti.gov/servlets/purl/1478744/ https://www.nationalacademies.org/our-work/foundational-research-gaps-and-future-directions-for-digital-twins https://www.nationalacademies.org/our-work/foundational-research-gaps-and-future-directions-for-digital-twins https://doi.org/10.2172/1770192 mailto:Hal.Finkel@science.doe.gov mailto:Kalyan.Perumalla@science.doe.gov

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.

d. Memory-Aware Systems: Advances in memory technologies are creating new opportunities and challenges where it is unclear how to best introduce or abstract memory awareness and composition. Memory is evolving in highly asymmetric and distributed directions, with new industry standards greatly expanding memory sharing and capacities to much larger sizes, largely in backward-compatible system architectures. Research is needed to uncover new possibilities for solving larger scientific computing problems with such highly asymmetric and distributed memory architectures. Innovations in algorithms, software interfaces, programming languages and models are needed to also effectively exploit new processing-in-memory architectures that are emerging as a relatively newer paradigm for scientific computing. Memory safety needs to be revisited in new research aimed at a more fundamental level of programming languages, runtimes, and operating systems, considering the multi-developer and shared nature of modern scientific programming eco-systems. The smoothening of the spectrum from volatile to non-volatile memories needs to be investigated for revisiting out-of-core algorithms to expand the limits of scientific computing. On-the-fly compression and decompression needs investigation for increasing the problem sizes without detriment to performance. The intersection of machine learning with memory systems opens the potential for new solutions, including smarter ML-informed cache prefetching and replacement policies potentially customizable for specific scientific applications via signatures and other mechanisms.

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.

(4) 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:

mailto:Margaret.Lentz@science.doe.gov

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 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 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 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

(5) Quantum Computing Technical Contact: Marco Fornari, Marco.Fornari@science.doe.gov, Kalyan Perumalla, Kalyan.Perumalla@science.doe.gov

Research to develop modules of end-to-end software toolchains aimed to program and control quantum computing systems at scale. Possible topics include modeling of realistic noise, computing and programming models, algorithms, and compilation. Methods should seek to understand, quantify, and reduce the impact of errors introduced via device imperfections and in low levels of the software stack. Research should be backed by rigorous theory and should connect metrics for device performance to low-level physical parameters as well as application performance where possible and as appropriate.

Topics that are out of scope include:

• Pre-applications and applications that do not address the specific topics described above,

• Development of new candidate physical qubit systems and improvements to physical qubits,

• Quantum networking,

• Quantum key distribution,

• Cryptography and cryptanalysis,

• Research solely relevant to large-scale, high-fidelity, fault-tolerant quantum machines,

• Projects that are duplicative of or competitive with industry.

https://www.osti.gov/biblio/1822199/ https://www.osti.gov/biblio/1845707/ 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 mailto:Marco.Fornari@science.doe.gov

References:

1. “Report for the ASCR Workshop on Basic Research Needs in Quantum Computing and

Networking,” https://doi.org/10.2172/2001045, July 2023.

(6) Quantum Networking Technical Contact: Kalyan Perumalla, Kalyan.Perumalla@science.doe.gov, Marco Fornari, Marco.Fornari@science.doe.gov

This topic involves innovative research in the area of quantum networking to advance our understanding of utility and new applications of quantum networking concepts, systems, and protocols. Research is needed to ascertain the specific ways by which quantum networking applies in scientific discovery, including, but not limited to, distribution of quantum information from sensors, quantum networking in support of distributed quantum computing, networking for scalability of quantum computing systems, and blind/cloud quantum computing. Networking can span heterogeneous systems or homogeneous systems (such as all-photonic). In scope is research in computer-scientific aspects of applications of entanglement distribution networks; design and analysis of networked quantum computing and distributed quantum programming models, and associated complexity analyses to uncover and establish limits of feasibility, scalability, and efficiency; demonstration of rigorously quantifiable utility of end-to-end networked quantum systems; theory and protocols for next-generation quantum networks.

Topics that are out of scope include:

• Pre-applications and applications that do not address the specific topics described above,

• Quantum hardware and testbeds,

• Quantum computing,

• Quantum key distribution,

• Cryptography and cryptanalysis.

References

1. “Report for the ASCR Workshop on Basic Research Needs in Quantum Computing and

Networking,” https://doi.org/10.2172/2001045, July 2023

Advanced Computing Technologies

This activity supports Quantum efforts and Research and Evaluation Prototypes (REP). The Research and Evaluation Prototypes (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 procurements.

https://doi.org/10.2172/2001045 mailto:Marco.Fornari@science.doe.gov https://doi.org/10.2172/2001045

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

Neuromorphic Computing: Specific to analog microelectronic fabrication, modeling, and characterization of scalable neuromorphic computing circuits for generalizable computing architecture applications emphasizing analog approaches, leading edge CMOS integrated with emerging devices (for example, memristors, memcapacitors, spintronic, magnetic, or ionic devices only). Applications must address state-of-the-art and propose to investigate basic research approaches beyond the state-of-the-art. In addition, pre-applications and applications must clearly articulate a neuroscience-based justification and rationale to the proposed research approach.

Topics that are out of scope include:

• Pre-applications and applications that do not address the specific topics described above,

• Pre-applications and applications that do not explain/describe their relevance to current and future high performance computing platforms and/or research-centric science as well as their relevance to the mission of SC and ASCR;

• Pre-applications and applications that do not effectively explain/describe their neuroscience-based justification which must also be focused, integrated, and relevant to the proposed research and descriptive beyond simply saying neurons and synapses or represented by an artistic diagram or caricature;

• Pre-applications and applications with primary emphasis on materials science, device research, fluidics, sensors, cross-bar arrays, digital, mix-signal, or that do not propose fabrication; research ideas that do not propose fabrication and integration of analog emerging devices and analog CMOS.

• Any proposed emerging device (for example, memristor, memcapacitor, meminductor, spintronic, magnetic, or ionic device) must be already fully fabricated, characterized, and information about it readily available in the open published scientific literature; therefore, research in the pursue of new devices based on new materials science will be declined without review.

• 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 focused on reservoir computing; hyperdimensional computing;…