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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Second Report of the Nuclear Data Subcommittee of the Nuclear Science Advisory Committee

The central importance of the nuclear data curated by the US Nuclear Data Program (USNDP) for clean energy generation, national security, nonproliferation, medical applications, and space exploration as well as basic science was described in a prior report issued by the DOE/NSF Nuclear Science Advisory Committee subcommittee on Nuclear Data (NSAC-ND) in September 2022. In this report, we present a set of fourteen (14) recommendations that will enhance and advance DOE-NP's stewardship of nuclear data. The first three recommendations focus on the existing core USNDP capabilities, namely: 1) Support the nuclear structure evaluation workforce to improve the currency, consistency, and accessibility of the Evaluated Nuclear Structure Data File (ENSDF); 2) Enhance nuclear reaction evaluation within the USNDP in support of the Evaluated Nuclear Data File (ENDF) through expansion of the workforce and integration of high-performance computing, automation, and machine learning and; 3) Continue atomic mass evaluation in support AME and NUBASE databases. This is followed by eight (8) recommendations representing new cross-cutting initiatives involving both measurement and evaluation to address outstanding nuclear data needs. These new initiatives require a highly trained, diverse workforce that includes personnel with expertise from both inside and outside the nuclear physics community from which evaluators have traditionally been recruited. As such, many of these initiatives are accomplished via a Topical Nuclear Data Collaborations (TNDC). A TNDC is made up of domestic and international stakeholders, subject matter and nuclear data experts, and nuclear data evaluators and features a workforce development plan to ensure that nuclear data evaluators maintain currency in the relevant applications and are seen as equity partners in the endeavor. These include: 1) Establish a coordinated effort to improve evaluation and modeling in nuclear astrophysics for stellar dynamics, multi-messenger astronomy and nucleosynthesis; 2) Initiate a TNDC to develop and maintain nuclear structure evaluation beyond discrete states, including nuclear level densities, photon strength functions and photonuclear data for improved reaction modeling, and exploring nuclear structure at finite temperature; 3) Create a TNDC to perform correlated fission data evaluation, including cross sections, fragment yields, v(A), v(E n ) for nuclear energy, national security, nonproliferation and basic science; 4) From a panel of subject matter experts to establish and annually update a roster of key decay data to nurture its accelerated dissemination including both measurement and evaluation for targeted high-value nuclides for national security, nonproliferation and medical applications; 5) Comprehensive, consistent neutron-induced structure and reaction data for nuclear energy, national security, nonproliferation and planetary nuclear spectroscopy; 6) Charged-particle stopping powers for detector design, space effects and ion beam therapy; 7) High-energy reactions for space exploration and medical nuclide production, and; 8) The creation of an infrastructure for open data and data preservation for use by the entire nuclear physics community. All told, these initiatives require approximately $6.5M increase in NP support of the USNDP in fiscal year 2023 dollars and would require at least 3-5 years to carry out due to the length of time needed to recruit and train new nuclear data researchers. This relatively modest investment would help ensure that the fruits of the nuclear data research carried out by DOE-NP and its collaborators would be brought to bear to address some of the most important needs of our nation and the world. To ensure effective execution of this plan, we present an overview of recruitment, training, and retention goals for the USNDP, the centerpiece of which is a mutually agreed upon code of conduct. Finally, we identify the facility and instrumentation needed to perform the recommended experimental activities. This includes a short review of target fabrication capabilities, reactors, neutron beam, light- and heavy-stable ion, gamma-ray, high-energy and radioactive ion beam facilities. Lastly, a more complete appendix of experimental facilities previously compiled is included with new input provided for 6 facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Nuclear Physics Network Requirements Review (Final Report)

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all its laboratories and facilities in the US and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education networking community. ESnet interconnects DOE national laboratories, user facilities, and major experiments so that scientists can use remote instruments and computing resources as well as share data with collaborators, transfer large datasets, and access distributed data repositories. ESnet is specifically built to provide Between July 2023 and October 2023, ESnet and the Nuclear Physics program (NP) of the DOE SC organized an ESnet requirements review of NP-supported activities. Preparation for these events included identification of key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare formal case study documents about its relationship to the NP program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

V-INT: Automated Vulnerability Intelligence and Risk Assessment

The project team, including the University of Arkansas (UA) as the lead, the University of Arkansas at Little Rock (UALR), Network Perception (NP), and Bastazo, has successfully researched, developed, and demonstrated the V-INT toolset, and also integrated it into the commercial products of NP (i.e., NP-View) and Bastazo (i.e., Spartan). The end product is a cybersecurity software tool for energy utilities that can automatically assess the risks of software vulnerabilities in an organization’s assets considering the organization’s firewall policies. It allows security operators to identify the small portion of vulnerabilities that poses true threats to their system (i.e., those that are not protected by firewall policies) and prioritize the mitigation of these vulnerabilities to minimize risks. It also allows security operators to identify the vulnerability-induced attack paths under their organization’s firewall policy, providing effective decision supports for mitigating potential attacks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Neptunium mononitride as a target material for Pu-238 production

Deep space exploration requires specialized sources for both thermal and power applications. Radioactive decay heat of plutonium-238 (238Pu) provides these sources in the form of radioisotope thermoelectric generators (RTGs). The 238 Pu is produced via neutron capture reaction involving neptunium-237 ( 237 Np) target material. Continual optimization of 237 Np target materials and evaluation of potential alternative targets for production of 238 Pu RTGs are advantageous for meeting ongoing space power system resource requirements. Current production of 238 Pu for RTGs for the United States space program utilizes neptunium dioxide ( 237 NpO 2 ) targets; however, the use of neptunium mononitride ( 237 NpN) presents an opportunity to increase the mass of 237 Np per target compared to the dioxide form, as well as increase the thermal conductivity of the target. To assess the viability of a 237 NpN target material, the material chemistry must be thoroughly evaluated, including synthesis methods and dissolution and reprocessing schemes. This review presents a summary of synthesis pathways for 237 NpN based on published literature on actinide mononitrides. Specific literature on 237 NpN is limited, necessitating evaluation of other actinide systems to gather parallels. This suggests a need for additional experimental studies on 237 NpN. A particular limitation in the existing literature is a lack of information on the differences in material characteristics, such as morphology, particle size, and trace chemical impurities, as a function of synthesis method. These parameters may affect subsequent reactor performance or dissolution of irradiated targets. The evaluation of existing literature is presented with a focus on the efficacy of 237 NpN targets for 238 Pu production.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Sustainable Valorization of CO2 through Nuclear Power-to-X Pathways

Some of the issues concerning energy security and climate change can be addressed by employing nuclear power (NP) to supply the energy required for the conversion of carbon dioxide (CO2) into chemicals, products, and materials. Nuclear energy represents a neutral carbon source that can be generated sustainably, reliably, and consistently. Nuclear power plants (NPPs) could supply energy in the form of heat, electricity, and ionizing radiation to drive CO2 chemical reactions underpinning NP-to-X type of pathways. CO2 conversion processes are either commercially available or emerging technologies at different developmental maturity stages. This work reviews the published literature (articles and patents) that reports R&D results and the understanding and development of chemical reactions and processes, as well as the efforts in integrating NPPs and chemical processes (CPs). As will be made evident, a new industrial era for the manufacturing of decarbonized chemicals, products, and materials will be possible by developing and implementing new (more energy- and carbon-efficient) processes responding to the NP-to-X pathways. This new decarbonizing platform not only contributes to achieving net zero goals but also broadens the NPP product beyond electricity.

08 HYDROGEN↗
DOE OSTI2020

Nuclear reactor assemblies, nuclear reactor target assemblies, and nuclear reactor methods

Reactor target assemblies are provided that can include a housing defining a perimeter of at least one volume and Np or Am spheres within the one volume. Reactor assemblies are provided that can include a reactor vessel and a bundle of target assemblies within the reactor vessel, at least one of the target assemblies comprising a housing defining a volume with Np or Am spheres being within the volume. Irradiation methods are also provided that can include irradiating Np or Am spheres within a nuclear reactor, then removing the irradiated spheres from the reactor and treating the irradiated spheres.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Extending Power of Nature from Binary Problems to Real-Valued Graph Learning in Real World

Nature performs complex computations constantly at clearly lower cost and higher performance than digital computers. It is crucial to understand how to harness the unique computational power of nature in Machine Learning (ML). In the past decade, besides the development of Neural Networks (NNs), the community has also relentlessly explored nature-powered ML paradigms. Although most of them are still predominantly theoretical, a new practical paradigm enabled by the recent advent of CMOS-compatible room-temperature nature-based computers has emerged. By harnessing the nature's power of entropy increase, this paradigm can solve binary learning problems delivering immense speedup and energy savings compared with NNs, while maintaining comparable accuracy. Regrettably, its values to the real world are highly constrained by its binary nature. A clear pathway to its extension to real-valued problems remains elusive. This paper aims to unleash this pathway by proposing a novel end-to-end Nature-Powered Graph Learning (NP-GL) framework. Specifically, through a three-dimensional co-design, NP-GL can leverage the nature's power of entropy increase to efficiently solve real-valued graph learning problems. Experimental results across 4 real-world applications with 6 datasets demonstrate that NP-GL delivers, on average, 6970X speedup and 10^5x energy consumption reduction with comparable or even higher accuracy than Graph Neural Networks (GNNs).

artificial intelligence↗
DOE OSTI2025

Charged Lepton Flavour Violations searches with muons: present and future

Charged-lepton flavor violation (cLFV) is one of the most powerful probes for New Physics (NP). Since lepton flavor conservation is an accidental symmetry in the Standard Model (SM), it is naturally violated in many NP models, with contributions at the level of the current experimental sensitivities. Moreover, the negligible SM contributions would make the observation of cLFV unambiguous evidence of NP. It makes these searches extremely sensitive and, at the same time, extremely pure. Thanks to the intense muon beams currently available, their intriguing upgrade programs, and the progress in the detection techniques, cLFV muon processes are the golden channels in this field. Experimental programs to search for $\mu^+ \to e^+ \gamma$, $\mu^+ \to e^+ e^+ e^-$ and the $\mu \to e$ conversion in the nuclear field are currently ongoing. We review the current status and the strategic plans for future searches. This document is an update of the prior cLFV submission to the 2018 European Strategy for Particle Physics (ESPP); the earlier submission should be consulted for more experimental details.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

A Data Deposition Platform for Sharing Nuclear Magnetic Resonance Data

Nuclear magnetic resonance (NMR) data are rarely deposited in open databases, leading to loss of critical scientific knowledge. Existing data reporting methods (images, tables, lists of values) contain less information than raw data, and are poorly standardized. Together, these issues limit FAIR (findable, accessible, interoperable, reusable) access to these data, which in turn creates barriers for compound dereplication and the development of new data-driven discovery tools. Existing NMR databases are either not designed for natural products data, or employ complex deposition interfaces that disincentivize deposition. Journals, including the Journal of Natural Products (JNP), are now requiring data submission as part of the publication process, creating the need for a streamlined, user-friendly mechanism to deposit and distribute NMR data. Recently, our team reported the development of the Natural Products Magnetic Resonance Database (NP-MRD; www.np-mrd.org). Here in this paper we present a new data deposition platform for the NP-MRD project that is designed to enable users to deposit NMR data for published or submitted manuscripts in under five minutes. This platform includes a suite of automated data extraction and standardization tools, together with a simple-to-use web-based interface and detailed error reporting to simplify the data deposition process and is available at www.np-mrd.org/submissions.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Materials Data on NpAsS by Materials Project

NpAsS is Matlockite structured and crystallizes in the tetragonal P4/nmm space group. The structure is three-dimensional. Np5+ is bonded in a 5-coordinate geometry to four equivalent As3- and five equivalent S2- atoms. All Np–As bond lengths are 3.07 Å. There are four shorter (2.79 Å) and one longer (2.80 Å) Np–S bond lengths. As3- is bonded to four equivalent Np5+ and four equivalent As3- atoms to form distorted AsNp4As4 hexagonal bipyramids that share corners with four equivalent AsNp4As4 hexagonal bipyramids, corners with twelve equivalent SNp5 square pyramids, edges with four equivalent AsNp4As4 hexagonal bipyramids, edges with four equivalent SNp5 square pyramids, and faces with four equivalent AsNp4As4 hexagonal bipyramids. All As–As bond lengths are 2.73 Å. S2- is bonded to five equivalent Np5+ atoms to form distorted SNp5 square pyramids that share corners with twelve equivalent AsNp4As4 hexagonal bipyramids, corners with four equivalent SNp5 square pyramids, edges with four equivalent AsNp4As4 hexagonal bipyramids, and edges with eight equivalent SNp5 square pyramids.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on NpPO4F by Materials Project

NpPO4F crystallizes in the orthorhombic Pnma space group. The structure is three-dimensional. Np4+ is bonded in a 6-coordinate geometry to six O2- and two equivalent F1- atoms. There are a spread of Np–O bond distances ranging from 2.23–2.65 Å. Both Np–F bond lengths are 2.29 Å. P5+ is bonded in a tetrahedral geometry to four O2- atoms. There is two shorter (1.53 Å) and two longer (1.57 Å) P–O bond length. There are three inequivalent O2- sites. In the first O2- site, O2- is bonded in a distorted bent 150 degrees geometry to one Np4+ and one P5+ atom. In the second O2- site, O2- is bonded in a 2-coordinate geometry to two equivalent Np4+ and one P5+ atom. In the third O2- site, O2- is bonded in a distorted bent 150 degrees geometry to one Np4+ and one P5+ atom. F1- is bonded in a distorted bent 150 degrees geometry to two equivalent Np4+ atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on NpSi by Materials Project

NpSi crystallizes in the orthorhombic Cmcm space group. The structure is three-dimensional. there are two inequivalent Np4+ sites. In the first Np4+ site, Np4+ is bonded to six equivalent Si4- atoms to form distorted edge-sharing NpSi6 pentagonal pyramids. There are two shorter (2.90 Å) and four longer (2.93 Å) Np–Si bond lengths. In the second Np4+ site, Np4+ is bonded in a 8-coordinate geometry to eight equivalent Si4- atoms. There are four shorter (2.95 Å) and four longer (3.07 Å) Np–Si bond lengths. Si4- is bonded in a 9-coordinate geometry to seven Np4+ and two equivalent Si4- atoms. There are one shorter (2.43 Å) and one longer (2.45 Å) Si–Si bond lengths.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on NpAsSe by Materials Project

NpAsSe is Matlockite structured and crystallizes in the tetragonal P4/nmm space group. The structure is three-dimensional. Np5+ is bonded in a 9-coordinate geometry to four equivalent As3- and five equivalent Se2- atoms. All Np–As bond lengths are 3.06 Å. There are four shorter (2.91 Å) and one longer (3.02 Å) Np–Se bond lengths. As3- is bonded in a 8-coordinate geometry to four equivalent Np5+ and four equivalent As3- atoms. All As–As bond lengths are 2.81 Å. Se2- is bonded to five equivalent Np5+ atoms to form a mixture of distorted edge and corner-sharing SeNp5 trigonal bipyramids.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on NpTeAs by Materials Project

NpAsTe is Matlockite structured and crystallizes in the tetragonal P4/nmm space group. The structure is three-dimensional. Np5+ is bonded in a 9-coordinate geometry to four equivalent As3- and five equivalent Te2- atoms. All Np–As bond lengths are 3.02 Å. There are four shorter (3.10 Å) and one longer (3.38 Å) Np–Te bond lengths. As3- is bonded in a 8-coordinate geometry to four equivalent Np5+ and four equivalent As3- atoms. All As–As bond lengths are 2.92 Å. Te2- is bonded in a 5-coordinate geometry to five equivalent Np5+ atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Cs3Np(Cl2O)2 by Materials Project

Cs3NpO2Cl4 crystallizes in the monoclinic C2/c space group. The structure is three-dimensional. there are two inequivalent Cs1+ sites. In the first Cs1+ site, Cs1+ is bonded in a 8-coordinate geometry to two equivalent O2- and six Cl1- atoms. There are one shorter (3.22 Å) and one longer (3.23 Å) Cs–O bond lengths. There are a spread of Cs–Cl bond distances ranging from 3.56–3.90 Å. In the second Cs1+ site, Cs1+ is bonded in a 8-coordinate geometry to two equivalent O2- and six Cl1- atoms. Both Cs–O bond lengths are 3.12 Å. There are a spread of Cs–Cl bond distances ranging from 3.50–3.99 Å. Np5+ is bonded in a distorted linear geometry to two equivalent O2- and four Cl1- atoms. Both Np–O bond lengths are 1.85 Å. All Np–Cl bond lengths are 2.78 Å. O2- is bonded in a distorted single-bond geometry to three Cs1+ and one Np5+ atom. There are two inequivalent Cl1- sites. In the first Cl1- site, Cl1- is bonded in a 5-coordinate geometry to four Cs1+ and one Np5+ atom. In the second Cl1- site, Cl1- is bonded in a 1-coordinate geometry to five Cs1+ and one Np5+ atom.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Np2S3 by Materials Project

Np2S3 is Stibnite structured and crystallizes in the orthorhombic Pnma space group. The structure is three-dimensional. there are two inequivalent Np3+ sites. In the first Np3+ site, Np3+ is bonded to seven S2- atoms to form a mixture of distorted corner and edge-sharing NpS7 pentagonal bipyramids. There are a spread of Np–S bond distances ranging from 2.73–2.79 Å. In the second Np3+ site, Np3+ is bonded in a 7-coordinate geometry to eight S2- atoms. There are a spread of Np–S bond distances ranging from 2.80–3.28 Å. There are three inequivalent S2- sites. In the first S2- site, S2- is bonded to five Np3+ atoms to form a mixture of distorted corner and edge-sharing SNp5 square pyramids. In the second S2- site, S2- is bonded to five Np3+ atoms to form a mixture of distorted corner and edge-sharing SNp5 square pyramids. In the third S2- site, S2- is bonded in a 4-coordinate geometry to five Np3+ atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on NpF4 by Materials Project

NpF4 crystallizes in the monoclinic C2/c space group. The structure is three-dimensional. there are two inequivalent Np4+ sites. In the first Np4+ site, Np4+ is bonded in a 8-coordinate geometry to eight F1- atoms. There are a spread of Np–F bond distances ranging from 2.26–2.35 Å. In the second Np4+ site, Np4+ is bonded in a 8-coordinate geometry to eight F1- atoms. There are a spread of Np–F bond distances ranging from 2.24–2.31 Å. There are seven inequivalent F1- sites. In the first F1- site, F1- is bonded in a distorted bent 150 degrees geometry to two equivalent Np4+ atoms. In the second F1- site, F1- is bonded in a distorted bent 150 degrees geometry to two Np4+ atoms. In the third F1- site, F1- is bonded in a distorted linear geometry to two Np4+ atoms. In the fourth F1- site, F1- is bonded in a distorted bent 150 degrees geometry to two Np4+ atoms. In the fifth F1- site, F1- is bonded in a distorted linear geometry to two equivalent Np4+ atoms. In the sixth F1- site, F1- is bonded in a bent 150 degrees geometry to two Np4+ atoms. In the seventh F1- site, F1- is bonded in a linear geometry to two equivalent Np4+ atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on NpAgSeO5 by Materials Project

NpAgSeO5 crystallizes in the triclinic P-1 space group. The structure is three-dimensional. there are two inequivalent Np5+ sites. In the first Np5+ site, Np5+ is bonded to seven O2- atoms to form distorted corner-sharing NpO7 pentagonal bipyramids. There are a spread of Np–O bond distances ranging from 1.88–2.54 Å. In the second Np5+ site, Np5+ is bonded to seven O2- atoms to form distorted corner-sharing NpO7 pentagonal bipyramids. There are a spread of Np–O bond distances ranging from 1.89–2.48 Å. There are two inequivalent Ag1+ sites. In the first Ag1+ site, Ag1+ is bonded in a 5-coordinate geometry to five O2- atoms. There are a spread of Ag–O bond distances ranging from 2.38–2.76 Å. In the second Ag1+ site, Ag1+ is bonded in a 6-coordinate geometry to eight O2- atoms. There are a spread of Ag–O bond distances ranging from 2.37–3.11 Å. There are two inequivalent Se4+ sites. In the first Se4+ site, Se4+ is bonded in a trigonal non-coplanar geometry to three O2- atoms. There are a spread of Se–O bond distances ranging from 1.71–1.76 Å. In the second Se4+ site, Se4+ is bonded in a distorted trigonal non-coplanar geometry to three O2- atoms. There are a spread of Se–O bond distances ranging from 1.73–1.76 Å. There are ten inequivalent O2- sites. In the first O2- site, O2- is bonded in a 1-coordinate geometry to two Np5+ atoms. In the second O2- site, O2- is bonded in a distorted rectangular see-saw-like geometry to one Np5+, two Ag1+, and one Se4+ atom. In the third O2- site, O2- is bonded in a 3-coordinate geometry to one Np5+, two Ag1+, and one Se4+ atom. In the fourth O2- site, O2- is bonded in a distorted single-bond geometry to two Np5+ and one Ag1+ atom. In the fifth O2- site, O2- is bonded in a 4-coordinate geometry to one Np5+, two equivalent Ag1+, and one Se4+ atom. In the sixth O2- site, O2- is bonded in a bent 120 degrees geometry to one Np5+ and one Se4+ atom. In the seventh O2- site, O2- is bonded in a 1-coordinate geometry to two Np5+ and one Ag1+ atom. In the eighth O2- site, O2- is bonded in a 1-coordinate geometry to one Np5+, two Ag1+, and one Se4+ atom. In the ninth O2- site, O2- is bonded in a 1-coordinate geometry to one Np5+, three Ag1+, and one Se4+ atom. In the tenth O2- site, O2- is bonded in a distorted bent 150 degrees geometry to two Np5+ atoms.

36 MATERIALS SCIENCE↗