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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Completion of lunar magma ocean solidification at 4.43 Ga

Crystallization of the lunar magma ocean yielded a chemically unique liquid residuum named KREEP. This component is expressed as a large patch on the near side of the Moon and a possible smaller patch in the northwest portion of the Moon’s South Pole-Aitken basin on the far side. Thermal models estimate that the crystallization of the lunar magma ocean (LMO) could have spanned from 10 and 200 My, while studies of radioactive decay systems have yielded inconsistent ages for the completion of LMO crystallization covering over 160 My. Here, we show that the Moon achieved >99% crystallization at 4,429 ± 76 Ma, indicating a lunar formation age of ~4,450 Ma or possibly older. Using the 176 Lu– 176 Hf decay system (t 1/2 = 37 Gy), we found that the initial 176 Hf/ 177 Hf ratios of lunar zircons with varied U–Pb ages are consistent with their crystallization from a KREEP-rich reservoir with a consistently low 176 Lu/ 177 Hf ratio of 0.0167 that emerged ~140 My after solar system formation. The previously proposed younger model age of ~4.33 Ga for the source of mare basalts (240 My after solar system formation) might reflect the timing of a large impact. Our results demonstrate that lunar magma ocean crystallization took place while the Moon was still battered by planetary embryos and planetesimals leftover from the main stage of planetary accretion. The study of Lu–Hf model ages for samples brought back from the South Pole-Aitken basin will help to assess the lateral continuity of KREEP and further understand its significance in the early history of the Moon.

Science & Technology - Other Topics↗
DOE OSTI2020

Global Techno-Economic Performance of Bifacial and Tracking Photovoltaic Systems

Although most of the current photovoltaic (PV) system installations use monofacial modules with fixed-tilt mounting structures, bifacial modules, trackers, and the combination of them are also getting more attention as potential candidates to further reduce the PV levelized cost of electricity (LCOE). This work is then the first to present a worldwide analysis on the yield potential and cost-effectiveness of PV farms composed of monofacial fixed-tilt and single/dual (1T/2T) tracker installations, as well as their bifacial counterparts. Our approach starts by estimating the irradiance reaching the front and rear surface of the modules for the different system designs (validated based on data from real PV systems and results from the literature) to estimate their energy production (row-row shading is neglected). Subsequently, the overall system cost during their 25-year lifetime is factored in, and LCOE is obtained. The results reveal that bifacial-1T installations increase energy yield by 35% and reach the lowest LCOE for the majority of the world (93.1% of the land area). Although dual axis trackers achieve the highest energy generation — especially for bifacial modules — their cost is still too high, and are therefore not as cost-effective. Sensitivity analyses based on the Monte Carlo and region sensitivity approach are performed to analyze the impact of input assumptions on the calculated LCOE. These reveal that our conclusions are robust in general but exact configuration to choose depends on specific site conditions. This investigation is not only of interest to the scientific community, but also can be used as a guide for PV installation companies and investors to determine the most suitable technology for a particular location.

14 SOLAR ENERGY↗
DOE OSTI2020

Constraining the destruction rate of K 40 in stellar nucleosynthesis through the study of the Ar 40 ( p , n ) K 40 reaction

Background: We present that K 40 plays a significant role in the radiogenic heating of Earth-like exoplanets, which can affect the development of a habitable environment on their surfaces. The initial amount of K 40 in the interior of these planets depends on the composition of the interstellar clouds from which they formed. Within this context, nuclear reactions that regulate the production of K 40 during stellar evolution can play a critical role. Purpose: In this study, we constrain for the first time the astrophysical reaction rate of K 40 ( n , p ) Ar 40 , which is responsible for the destruction of K 40 during stellar nucleosynthesis. We provide to the nuclear physics community high-resolution data on the cross section and angular distribution of the Ar 40 ( p , n ) K 40 reaction. These are important to various applications involving Ar 40 . The associated reaction rate of the Ar 40 ( p , n ) K 40 process addresses a reaction rate gap in the Joint Institute for Nuclear Astrophysics REACLIB database in the region of intermediate-mass isotopes. Methods: We performed differential cross-section measurements on the Ar 40 ( p , n ) K 40 reaction, for six energies in the center-of-mass system between 3.2 and 4.0 MeV and various angles between 0 ° and 135 ° . The experiment took place at the Edwards Accelerator Laboratory at Ohio University using the beam swinger target location and a standard neutron time-of-flight technique. We extracted total and partial cross sections by integrating the double differential cross sections we measured. Results: The total and partial cross sections varied with energy due to the contribution from isobaric analog states and Ericson type fluctuations. The energy-averaged neutron angular distributions were symmetrical relative to 90 ° . Based on the experimental data, local transmission coefficients were extracted and were used to calculate the astrophysical reaction rates of Ar 40 ( p , n ) K 40 and K 40 ( n , p ) Ar 40 reactions. The new rates were found to vary significantly from the theoretical rates in the REACLIB library. We implemented the new rates in network calculations to study nucleosynthesis via the slow neutron capture process, and we found that the produced abundance of K 40 is reduced by up to 10% compared to calculations with the library rates. At the same time, the above result removes a significant portion of the previous theoretical uncertainty on the K 40 yields from stellar evolution calculations. Conclusions: Our results support a destruction rate of K 40 in massive stars via the K 40 ( n , p ) Ar 40 reaction that is larger compared to previous estimates. The rate of K 40 destruction via the K 40 ( n , p ) Ar 40 reaction now has a dramatically reduced uncertainty based on our measurement. Lastly, this result directly affects the predicted stellar yields of K 40 from nucleosynthesis, which is a critical input parameter for the galactic chemical evolution models that are currently employed for the study of significant properties of exoplanets.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Challenges in simulating economic effects of climate change on global agricultural markets

Abstract Many approaches have been used to investigate climate change impacts on agriculture. However, several caveats remain in this field: (i) analyses focus only on a few major crops, (ii) large differences in yield impacts are observed between projections from site-based crops models and Global Gridded Crop Models (GGCMs), (iii) climate change impacts on livestock are rarely quantified, and (iv) several causal relations among biophysical, environmental, and socioeconomic aspects are usually not taken into account. We investigate how assumptions about these four aspects affect agricultural markets, food supply, consumer well-being, and land use at global level by deploying a large-scale socioeconomic model of the global economy with detailed representation of the agricultural sector. We find global welfare impacts several times larger when climate impacts all crops and all livestock compared to a scenario with impacts limited to major crops. At the regional level, food budget can decrease by 10 to 25% in developing countries, challenging food security. The role of land area expansion as a major source of adaptation is highlighted. Climate impacts on crop yields from site-based process crop models generate more challenging socioeconomic outcomes than those from GGCMs. We conclude that the agricultural research community should expand efforts to estimate climate impacts on many more crops and livestock. Also, careful comparison of the GGCMs and traditional site-based process crop models is needed to understand their major implications for agricultural and food markets.

Gurgel, Angelo C. (ORCID:0000000183319508)↗
DOE OSTI2023

Search for light long-lived neutral particles that decay to collimated pairs of leptons or light hadrons in $pp$ collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search for light long-lived neutral particles with masses in the O(MeV–GeV) range is presented. The analysis targets the production of long-lived dark photons in the decay of a Higgs boson produced via gluon–gluon fusion or in association with a W boson. Events that contain displaced collimated Standard Model fermions reconstructed in the calorimeter or muon spectrometer are selected in 139 fb -1 of $\sqrt{s}$ = 13 TeV $pp$ collision data collected by the ATLAS detector at the LHC. Background estimates for contributions from Standard Model processes and instrumental effects are extracted from data. The observed event yields are consistent with the expected background. Exclusion limits are reported on the production cross-section times branching fraction as a function of the mean proper decay length cτ of the dark photon, or as a function of the dark-photon mass and kinetic mixing parameter that quantifies the coupling between the Standard Model and potential hidden (dark) sectors. A Higgs boson branching fraction above 1% is excluded at 95% CL for a Higgs boson decaying into two dark photons for dark-photon mean proper decay lengths between 10 mm and 250 mm and dark photons with masses between 0.4 GeV and 2 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Situational awareness-enhancing community-level load mapping with opportunistic machine learning

Motivated by present and forthcoming challenges in the adoption and integration of distributed renewable energy, we develop a machine learning (ML) approach that builds short-fuse mappings connecting the occasionally-unobservable true load in one target community with information-rich signals collected from relatively more instrumented reference communities. Our setting is inspired by and tailored to target communities with significant unobservable behind-the-meter solar generation, where true load (a relatively well-behaved quantity of interest to grid operators) is hard to discern during daytime due to insufficient instrumentation and/or privacy reasons, but that can be related to reference communities with low unobservable distributed variable generation or with sufficient instrumentation. The developed mapping, herein realized with Support Vector Machine regression, is built using nighttime data from all communities, when their distributed generation is low or zero. Our ML algorithm opportunistically learns to correlate signals of interest and then is operationally used the next day to shed light into target community load evolution. The mapping is subsequently rebuilt, rolling its short-fuse scope perpetually forward in time. Here, we demonstrate the efficacy of our approach on nine synthetically generated topologies and associated timeseries stemming from real-world data, on which we observe cumulative error performance that yields lower than 10% and 15% daily-averaged mean absolute percentage errors in target community load estimation on more than about 75% and 90% of days, respectively, in multiple yearly evaluations that shed light on long-term performance also under seasonal and one-off effects. The proposed ML-powered methodology can offer grid operators much-improved visibility into a previously obscure space and can also serve as an additional source of information in broader, multi-modal solar disaggregation solutions.

14 SOLAR ENERGY↗
DOE OSTI2024

Automated Calibration for Rapid Optical Spectroscopy Sensor Development for Online Monitoring

An automated platform has been developed to assist researchers in the rapid development of optical spectroscopy sensors to quantify species from spectral data. This platform performs calibration and validation measurements simultaneously. Real-time, in situ monitoring of complex systems through optical spectroscopy has been shown to be a useful tool; however, building calibration models requires development time, which can be a limiting factor in the case of radiological or otherwise hazardous systems. While calibration time can be reduced through optimized design of experiments, this study approached the challenge differently through automation. The ATLAS (Automated Transient Learning for Applied Sensors) platform used pneumatic control of stock solutions to cycle flow profiles through desired calibration concentrations for multivariate model construction. Additionally, the transients between desired concentrations based on flow calculations were used as validation measurements to understand model predictive capabilities. This automated approach yielded an incredible 76% reduction in model development time and a 60% reduction in sample volume versus estimated manual sample preparation and static measurements. The ATLAS system was demonstrated on two systems: a three-lanthanide system with Pr/Nd/Ho representing a use case with significant overlap or interference between analyte signatures and an alternate system containing Pr/Nd/Ni to demonstrate a use case in which broad-band corrosion species signatures interfered with more distinct lanthanide absorbance profiles. Both systems resulted in strong model prediction performance (RMSEP < 9%). Lastly, ATLAS was demonstrated as a tool to simulate process monitoring scenarios (e.g., column separation) in which models can be further optimized to account for day-to-day changes as necessary (e.g., baseline correction). Ultimately, ATLAS offers a vital tool to rapidly screen monitoring methods, investigate sensor fusion, and explore more complex systems (i.e., larger numbers of species).

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Apparatus for measuring strength in biaxial compression

We report most measurements of compressive strength of ductile materials have involved Hopkinson–Kolsky bars or Taylor anvils placing samples in uniaxial compression. In these geometries, strain is limited by the tendency of the sample to petal, in analogy to necking in uniaxial tension. Estimation of strength for any other form of the stress tensor requires assuming a shape of the yield surface; because data exist only for uniaxial compression, these assumptions are untested. In an imploding spherical shell, compression is biaxial, the plastic strain may not be small, and the material behavior may be nonlinear as a result of work hardening and heating by plastic work. We outline a method of measuring the strengths of materials in biaxial compression, both quasistatically and dynamically, using the compression of thin spherical shells. We suggest surrounding the shell with an annulus filled with a mixture of H 2 and Cl 2 gases whose homogeneous ignition is initiated by a flash of blue and near-ultraviolet light. Less promising approaches are described in Appendixes A–C .

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Deuteron-Deuteron Elastic and Three and Four-Body Breakup Scattering Using the Faddeev-Yakubovskii Equations

The deuteron-deuteron elastic and three and four-body breakup scattering cross section have been calculated using the Faddeev-Yakubovskii (FY) chain-of-partition momentum-space equations. In this calculation the initial two-cluster potential is split into separable and non-separable components, and the effective potential is reduced to elastic two-body and three and four-body breakup open-channels and a closed-channel many-body contribution. The closed-channel contribution is determined by minimizing a variational bound. The Coulomb interaction was included by expanding the initial and final Coulomb states in a Coulomb-Sturmian basis. The three sets of chain-of-partition integral equations were solved for the elastic and three and four-body breakup scattering amplitudes. The calculations were performed for the S = 2 spin/L = 0 angular-momentum state. The elastic and double-breakup calculations were performed for energies up to E = 5.48 MeV, while the single-breakup calculations were performed for energies up to E = 4.17 MeV. In the case of elastic scattering, the calculated scattering length of 5 a dd = 7.8 ± 0.3 fm is in good agreement with a FY cluster reduction calculation. The calculated phase shift is smaller than that predicted by the resonating group model and this difference is believed to be due to the differences in the potential and calculation methods. The breakup cross sections were calculated as a function of initial deuteron momentum and fragmented-deuteron momentum. Here, the d+d → d+n+p cross sections were compared with neutron yield measurements and, while the measurements also included the L > 0 components, the general features were consistent. Estimates of the calculational uncertainties/bias are provided.

42 ENGINEERING↗
DOE OSTI2022

Robust and scalable uncertainty estimation with conformal prediction for machine-learned interatomic potentials

Abstract Uncertainty quantification (UQ) is important to machine learning (ML) force fields to assess the level of confidence during prediction, as ML models are not inherently physical and can therefore yield catastrophically incorrect predictions. Established a-posteriori UQ methods, including ensemble methods, the dropout method, the delta method, and various heuristic distance metrics, have limitations such as being computationally challenging for large models due to model re-training. In addition, the uncertainty estimates are often not rigorously calibrated. In this work, we propose combining the distribution-free UQ method, known as conformal prediction (CP), with the distances in the neural network’s latent space to estimate the uncertainty of energies predicted by neural network force fields. We evaluate this method (CP+latent) along with other UQ methods on two essential aspects, calibration, and sharpness, and find this method to be both calibrated and sharp under the assumption of independent and identically-distributed (i.i.d.) data. We show that the method is relatively insensitive to hyperparameters selected, and test the limitations of the method when the i.i.d. assumption is violated. Finally, we demonstrate that this method can be readily applied to trained neural network force fields with traditional and graph neural network architectures to obtain estimates of uncertainty with low computational costs on a training dataset of 1 million images to showcase its scalability and portability. Incorporating the CP method with latent distances offers a calibrated, sharp and efficient strategy to estimate the uncertainty of neural network force fields. In addition, the CP approach can also function as a promising strategy for calibrating uncertainty estimated by other approaches.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Analysis and modeling of tungsten emission and net erosion in the DIII-D divertor using updated atomic data

Tungsten (W) is one of the leading candidate materials for plasma-facing components. However, its main drawback is its high radiative efficiency; if W penetrates the plasma, it can lead to core degradation or even collapse. Since eroded tungsten tends to ionize in the sheath and redeposit promptly, the net erosion flux that escapes prompt redeposition can differ significantly from the gross erosion. This work presents a modeling framework to estimate net erosion and photon emission from W coatings exposed to the lower divertor of DIII-D using the DiMES material exposure probe. The approach couples RustBCA for sputtering yields with a Monte Carlo transport code (LPTMC) that models redeposition and W emission. Computation is carried out with new atomic data, based on R-matrix and Mons calculations, leading to lower ionization probabilities and a twofold increase in net erosion estimates compared to calculations done with OPEN-ADAS atomic data. The model results are benchmarked against experimental measurements, showing quantitative agreement for erosion, although the trends in W emission are reproduced only qualitatively. The model is also used to assess whether W II emission can serve as a direct measurement of the net erosion of W in the lower divertor of DIII-D. Simulations show that this is not valid if the electron pressure is above ~120 Pa or if the toroidal length of the eroded material is smaller than the parallel-to-B distance traveled by impurity ions before steady-state conditions are reached. Finally, simulations suggest that when W is sputtered by carbon ions with high impact energies (≳300 eV) in DIII-D, W net erosion scales with W gross erosion and can be numerically approximated using W I flux alone as input.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Heavy-Duty Vehicle Air Drag Coefficient Estimation: From an Algebraic Perspective

When a heavy-duty vehicle (HDV) operates at the nominal highway speed, over two-thirds of its total resistive force comes from the air drag, contributing to more than half of its fuel consumption. One effective countermeasure to reduce the fuel consumption of HDVs is platooning, which employs connectivity and automated driving technologies to link two or more HDVs in convoy. Platooning allows HDVs to drive closer together and yields improved fuel economy and less CO2 emission thanks to the reduced air drag. Maximizing the energy benefits of an HDV platoon requires quantifying the drag interaction between vehicles. In practice, modeling the drag reduction in a platoon boils down to identifying the relationship between the air drag coefficient C d and the inter-vehicle distance d. Existing approaches to identify C d (d) include vehicle field tests, wind tunnel experiments, and computational fluid dynamics simulation, which can howbeit be time-consuming and cost prohibitive. In contrast, this paper proposes an algebraic approach, which relies on onboard-measurable variables, to estimate the air drag coefficient of an HDV in a platoon. Its algebraic nature avoids the classical persistence of excitation condition for parameter identification and can yield the identified parameter almost instantaneously. Simulation results demonstrate its effectiveness and the improved estimation speed over a recursive least squares identifier.

Wang, Zejiang↗
DOE OSTI2025

Multiplicity-dependent inclusive J/ ψ production at forward rapidity in pp collisions at $\sqrt{s}$ = 13 TeV

This paper presents a study of the inclusive forward J/ψ yield as a function of forward charged-particle multiplicity in pp collisions at $\sqrt{s}$ = 13 TeV using data collected by the ALICE experiment at the CERN LHC. The results are presented in terms of relative J/ψ yields and relative charged-particle multiplicities with respect to these quantities obtained in inelastic collisions having at least one charged particle in the pseudorapidity range |η| < 1. The J/ψ mesons are reconstructed via their decay into μ + μ − pairs in the forward rapidity region (2.5 < y < 4). The relative multiplicity is estimated in the forward pseudorapidity range which overlaps with the J/ψ rapidity region. The results show a steeper-than-linear increase of the J/ψ yields versus the multiplicity. They are compared with previous measurements and theoretical model calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Harnessing plant‐based platform for low‐cost cellulosic sugar recovery from bioenergy crops

The price of pure cellulase enzyme for the recovery of fermentable cellulosic sugars is one of the major challenges that limit the commercialization of second-generation biofuels and bio-based products. This work shows a means to greatly reduce the cost of cellulases. The abundant capacity of plants to synthesize and hyperaccumulate transgenic proteins in their plastids has been demonstrated for two gene constructs using either NPT II or Tet C to regulate the expression of bacterial cellulase Cel6A. Previously, the expression of Cel6A to 20–35% of total soluble leaf protein in tobacco was shown in two consecutive field trials. Moving forward, the key challenge was the extraction of active enzymes from the transgenic tobacco leaves hyperaccumulating bacterial cellulases in a cost-effective manner. The study showed that unpurified crude extracts of NPT II and Tet C transgenic tobacco leaves recovered ~23% and ~29% w/w cellulosic sugars from energycane bagasse, respectively. A supplementation of as low as 25% of purified commercial cellulase improved the glucose recovery by 2.9 times (~85% w/w) compared to 100% crude extract, which is comparable to the glucose recovery obtained by commercial cellulases, thereby suggesting a reduced requirement of commercial cellulases leading to a cost reduction of 75% for biorefineries. Assuming a stable 40% cellulase yield in total soluble protein under field conditions and multiple harvests (one to three) a year, the study estimates that the potential cost for saccharification of 1 t of lignocellulosic biomass can be reduced to 67–200 USD by using crude leaf extracts of transgenic tobacco.

biofuel↗
DOE OSTI2020

Implications from Monitoring Gopher Tortoises at Two Spatial Scales

A problem that conservation biologists face is how to monitor species, given both resource limitations and the inherent challenges of assessing long-term demographic processes. We assessed gopher tortoise (Gopherus polyphemus) abundance at a landscape scale and at the scale of 3 local populations within the Conecuh National Forest (CNF).USA between 1991 and 2017. Landscape-level data were collected 26 from line transect distance sampling arranged uniformly across the CNF and collected during a single season (2011); data for local populations were generated from long-term mark-recapture of individuals at three sites selected based on prior knowledge of high density at each. At a landscape scale, we estimated 5,242 (95% CI = 3,538-7,768) tortoises occurred across the approximately 34,000-ha forest, yielding a density of 0.14-0.32 tortoises/ ha. These low densities across the landscape suggest that, on average, management activities across the property have not allowed tortoise populations to retain social structure needed for long-term persistence. The three local populations, however, contained 25-60 individuals and densities of 1.9–6.9 tortoises/ha. Over the study period, populations at two sites were stable and the third experienced significant population growth. Mean annual survival of individuals was 0.89 and invariant across size classes. Altogether, line transect distance sampling is important for assessing landscape-scale abundance of tortoises but may fail to detect local clusters of high-density sites important for population persistence. Our mark-recapture efforts at the local scale revealed that small populations on these high-density sites can exhibit long-term stability or growth even though they do not meet current established criteria for viability. Improved models that incorporate immigration and emigration and better reflect dynamics of peripheral populations would assist in determining how such populations best contribute to species recovery and regional conservation targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Study of the connected four-point correlation function of galaxies from the DESI Data Release 1 luminous red galaxy sample

We present a measurement of the non-Gaussian four-point correlation function (4PCF) from the DESI DR1 luminous red galaxy (LRG) sample. For the gravitationally induced parity-even 4PCF, we detect a signal with a significance of 14.7⁢𝜎 using our fiducial setup. We assess the robustness of this detection through a series of validation tests, including auto and cross-correlation analyses, sky partitioning across multiple patch combinations, and variations in radial scale cuts. Due to the low completeness of the sample, we find that differences in fiber assignment implementation schemes can significantly impact estimation of the covariance and introduce biases in the data vector. After correcting for these effects, all tests yield consistent results. This is one of the first measurements of the connected 4PCF on the DESI LRG sample; the good agreement between the simulation and the data implies that the amplitude of the density fluctuation inferred from the connected 4PCF is consistent with the Planck Λ⁢ CDM cosmology. The methodology and diagnostic framework established in this work provide a foundation for interpreting parity-odd 4PCF.

Cosmology↗
DOE OSTI2020

Shell-model studies of the astrophysical r p -process reactions S 34 ( p , γ ) Cl 35 and Cl 34 g , m ( p , γ ) Ar 35

Background: Dust grains condensed in the outflows of presolar classical novae should have been present in the protosolar nebula. Candidates for such presolar nova grains have been found in primitive meteorites and can in principle be identified by their isotopic ratios, but the ratios predicted by state-of-the-art one-dimensional hydrodynamic models are uncertain due to nuclear-physics uncertainties. Purpose: To theoretically calculate the thermonuclear rates and uncertainties of the S 34 ( p , γ ) Cl 35 and Cl 34 g , m ( p , γ ) Ar 35 reactions and investigate their impacts on the predicted 34 S/ 32 S isotopic ratio for presolar nova grains. Method: A shell-model approach in a (0 +1 ) ℏ ω model space was used to calculate the properties of resonances in the 34 S(p ,γ ) 35 Cl and 34 g,m Cl (p ,γ ) 35 Ar reactions and their thermonuclear rates. Uncertainties were estimated using a Monte Carlo method. The implications of these rates and their uncertainties on sulfur isotopic nova yields were investigated using a postprocessing nucleosynthesis code. The rates for transitions from the ground state of 34 Cl as well as from the isomeric first excited state of 34 Cl were explicitly calculated. Results: At energies in the resonance region near the proton-emission threshold, many negative-parity states appear. Energies, spectroscopic factors, and proton-decay widths are reported. The resulting thermonuclear rates are compared with previous determinations. Conclusions: The shell-model calculations alone are sufficient to constrain the variation of the 34 S/ 32 S ratios to within about 30%. Uncertainties associated with other reactions must also be considered, but in general we find that the 34 S/ 32 S ratios are not a robust diagnostic to clearly identify presolar grains made from nova ejecta.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Rigorous constraints on three-nucleon forces in chiral effective field theory from fast and accurate calculations of few-body observables

We explore the constraints on the three-nucleon force (3NF) of chiral effective field theory (χ EFT) that are provided by bound-state observables in the A = 3 and A = 4 sectors. Our statistically rigorous analysis incorporates experimental error, computational method uncertainty, and the uncertainty due to truncation of the χ EFT expansion at next-to-next-to-leading order. A consistent solution for the 3 H binding energy, the 4 He binding energy and radius, and the 3 H β-decay rate can only be obtained if χ EFT truncation errors are included in the analysis. Here, the β-decay rate is the only one of these that yields a nondegenerate constraint on the 3NF low-energy constants, which makes it crucial for the parameter estimation. We use eigenvector continuation for fast and accurate emulation of no-core shell model calculations of the few-nucleon observables. This facilitates sampling of the posterior probability distribution, allowing us to also determine the distributions of the parameters that quantify the truncation error. We find a χ EFT expansion parameter of Q = 0.33 ± 0.06 for these observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗