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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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35 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Proposed Lunar Measurements of r-Process Radioisotopes to Distinguish the Origin of Deep-sea 244 Pu

Abstract 244 Pu has recently been discovered in deep-sea deposits spanning the past 10 Myr, a period that includes two 60 Fe pulses from nearby supernovae. 244 Pu is among the heaviest r -process products, and we consider whether it was created in supernovae, which is disfavored by nucleosynthesis simulations, or in an earlier kilonova event that seeded the nearby interstellar medium with 244 Pu that was subsequently swept up by the supernova debris. We discuss how these possibilities can be probed by measuring 244 Pu and other r -process radioisotopes such as 129 I and 182 Hf, both in lunar regolith samples returned to Earth by missions such as Chang’e and Artemis, and in deep-sea deposits.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Future Advances in Photon-Based Neutrino Detectors: A SNOWMASS White Paper

We discuss here new, enabling technologies for future photon-based neutrino detectors. These technologies touch nearly every aspect of such detectors: new scintillating materials, new methods of loading isotopes, new photon sensors and collectors, new approaches to simulation and analysis, and new front-end electronics and DAQ ideas. Of particular interest are technologies that enable broad physics programs in hybrid Cherenkov/scintillation detectors, such as slow fluors, water-based liquid scintillator, and spectral sorting of photons. Several new large-scale detector ideas are also discussed, including hybrid detectors like Theia, ArTEMIS, and generic slow-fluor detectors, as well as the very different SLIPs and LiquidO approaches to instrumenting photon-based detectors. A program of demonstrators for future detectors, including ANNIE, Eos, and NuDOT are also discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

PplD is a de-N-acetylase of the cell wall linkage unit of streptococcal rhamnopolysaccharides

The cell wall of the human bacterial pathogen Group A Streptococcus (GAS) consists of peptidoglycan decorated with the Lancefield group A carbohydrate (GAC). GAC is a promising target for the development of GAS vaccines. In this study, employing chemical, compositional, and NMR methods, we show that GAC is attached to peptidoglycan via glucosamine 1-phosphate. This structural feature makes the GAC-peptidoglycan linkage highly sensitive to cleavage by nitrous acid and resistant to mild acid conditions. Using this characteristic of the GAS cell wall, we identify PplD as a protein required for deacetylation of linkage N-acetylglucosamine (GlcNAc). X-ray structural analysis indicates that PplD performs catalysis via a modified acid/base mechanism. Genetic surveys in silico together with functional analysis indicate that PplD homologs deacetylate the polysaccharide linkage in many streptococcal species. We further demonstrate that introduction of positive charges to the cell wall by GlcNAc deacetylation protects GAS against host cationic antimicrobial proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Extreme shape coexistence observed in 70 Co

The shape of the atomic nucleus is a property that underpins our understanding of nuclear systems, impacts the limits of nuclear existence, and enables probes of physics beyond the Standard Model. Nuclei can adopt a variety of shapes, including spheres, axially deformed spheroids, and pear shapes. In some regions of the nuclear chart where a spherical nucleus would naively be expected, deformed nuclear states can result from the collective action of constituent protons and neutrons. In a small subset of nuclei both spherical and deformed nuclear states have been experimentally observed, a phenomenon termed shape coexistence. We present spectroscopic evidence for the coexistence of J π = 1 + spherical and deformed states in 70 Co, separated by less than 275 keV. This close degeneracy of levels with the same J π and different shapes demonstrates an extreme example of shape coexistence resulting from the interplay of independent particle motion and collective behavior in highly unstable nuclear systems and identifies the Co isotopes as a transition point between deformed ground states observed in the Cr isotopes and spherical configurations observed in the closed-shell Ni isotopes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

RNAcentral 2021: secondary structure integration, improved sequence search and new member databases

RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences that provides a single access point to 44 RNA resources and >18 million ncRNA sequences from a wide range of organisms and RNA types. RNAcentral now also includes secondary (2D) structure information for >13 million sequences, making RNAcentral the world’s largest RNA 2D structure database. The 2D diagrams are displayed using R2DT, a new 2D structure visualization method that uses consistent, reproducible and recognizable layouts for related RNAs. The sequence similarity search has been updated with a faster interface featuring facets for filtering search results by RNA type, organism, source database or any keyword. This sequence search tool is available as a reusable web component, and has been integrated into several RNAcentral member databases, including Rfam, miRBase and snoDB. To allow for a more fine-grained assignment of RNA types and subtypes, all RNAcentral sequences have been annotated with Sequence Ontology terms. The RNAcentral database continues to grow and provide a central data resource for the RNA community. RNAcentral is freely available at https://rnacentral.org.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Indirect measurement of the 90 Sr ⁢(𝑛, 𝛾)⁢ 91 Sr reaction cross section and the implications for astrophysical Zr production

Here, the intermediate neutron-capture process (𝑖 process) has gained notable traction within the past decade as a way to describe stellar abundance observations which cannot be explained by the slow and rapid neutron-capture processes. Despite the general success of 𝑖-process models, many open questions remain. Among the observations, Zr stands out, as its elemental abundance is difficult to replicate with available 𝑖-process models, while the reactions that affect its production through the 𝑖 process are close enough to stability to study experimentally. Here, we present the experimental constraint of the nuclear level density and 𝛾-strength function (𝛾 SF) of 91 Sr using the 𝛽-Oslo method, which were then input into the TALYS Hauser-Feshbach code to produce the first experimental constraint of the 90 Sr ⁢(𝑛, 𝛾)⁢ 91 Sr capture reaction. This constraint was used alongside that of 92 Sr ⁢(𝑛, 𝛾)⁢ 93 Sr for a reduction in the uncertainty of [Y/Zr] production in the 𝑖-process relevant environmental neutron density of 10 13.5 and 10 14.5 neutrons/cm 3 .

Physics - Nuclear physics and radiation physics↗
DOE OSTI2024

First study of the $^{139}\text{Ba}(n,y)^{140}\text{Ba}$ reaction to constrain the conditions for the astrophysical $\mathcal{i}$ process

New astronomical observations point to a nucleosynthesis picture that goes beyond what was accepted until recently. The intermediate “i” process was proposed as a plausible scenario to explain some of the unusual abundance patterns observed in metal-poor stars. The most important nuclear physics properties entering i-process calculations are the neutron-capture cross sections and they are almost exclusively not known experimentally. In this report we provide the first experimental constraints on the 139 Ba(n,γ) 140 Ba reaction rate, which is the dominant source of uncertainty for the production of lanthanum, a key indicator of i-process conditions. This is an important step towards identifying the exact astrophysical site of stars carrying the i-process signature.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

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

Accurate, reliable nuclear data is essential for the success of Federal missions such as nonproliferation, nuclear forensics, homeland security, national defense, space exploration, clean energy generation, and scientific research. Data access is also key to innovative commercial developments such as new medicines, automated industrial controls, energy exploration, energy security, nuclear reactor design, and isotope production. The United States Nuclear Data Program (USNDP) is the domestic custodian of nuclear data. In its April 2022 meeting, the DOE/NSF Nuclear Science Advisory Committee was charged with preparing two reports on nuclear data. In this first report, we review recent accomplishments of the USNDP and discuss complementary and collaborative international efforts. Detailed descriptions of nuclear data needs for basic science, nonproliferation, national security, nuclear energy together with medical and space applications are also presented. Lastly, a set of specific cross-cutting nuclear data needs with relevance for multiple applications areas are also identified for further discussion in a follow-on report planned for release at the end of January 2023.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
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 OSTI2025

Maximizing Free Energy Gain

Maximizing the amount of work harvested from an environment is important for a wide variety of biological and technological processes, from energy-harvesting processes such as photosynthesis to energy storage systems such as fuels and batteries. Here, we consider the maximization of free energy—and by extension, the maximum extractable work—that can be gained by a classical or quantum system that undergoes driving by its environment. We consider how the free energy gain depends on the initial state of the system while also accounting for the cost of preparing the system. We provide simple necessary and sufficient conditions for increasing the gain of free energy by varying the initial state. We also derive simple formulae that relate the free energy gained using the optimal initial state rather than another suboptimal initial state. Finally, we demonstrate that the problem of finding the optimal initial state may have two distinct regimes, one easy and one difficult, depending on the temperatures used for preparation and work extraction. We illustrate our results on a simple model of an information engine.

Physics↗
DOE OSTI2020

Apparatus and method for determining state of change (SOC) and state of health (SOH) of electrical cells

Systems and methods for prediction of state of charge (SOH), state of health (SOC) and other characteristics of batteries using acoustic signals, includes determining acoustic data at two or more states of charge and determining a reduced acoustic data set representative of the acoustic data at the two or more states of charge. The reduced acoustic data set includes time of flight (TOF) shift, total signal amplitude, or other data points related to the states of charge. Machine learning models use at least the reduced acoustic dataset in conjunction with non-acoustic data such as voltage and temperature for predicting the characteristics of any other independent battery.

25 ENERGY STORAGE↗
DOE OSTI2023

Apparatus and method for determining state of change (SOC) and state of health (SOH) of electrical cells

Systems and methods for prediction of state of charge (SOH), state of health (SOC) and other characteristics of batteries using acoustic signals, includes determining acoustic data at two or more states of charge and determining a reduced acoustic data set representative of the acoustic data at the two or more states of charge. The reduced acoustic data set includes time of flight (TOF) shift, total signal amplitude, or other data points related to the states of charge. Machine learning models use at least the reduced acoustic dataset in conjunction with non-acoustic data such as voltage and temperature for predicting the characteristics of any other independent battery.

Steingart, Daniel Artemis↗