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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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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Comparisons of triple-differential cross sections for quasielastic-like $ν_μ$-hydrocarbon interactions using $\langle E_ν\rangle \sim$ 3~GeV versus $\sim$ 6~GeV beams in MINERvA

Neutrino charged-current quasielastic-like scattering, a reaction category extensively used in neutrino oscillation measurements, receives contributions from single nucleon knockout processes, multinucleon processes, and inelastic scattering with subsequent rescattering or absorption in the nucleus to produce only nucleons in the final state. In this article, comparisons are presented of the same measurement in two different wideband neutrino beams: one beam peaks near 3 GeV with few neutrinos above 6 GeV; the other peaks near 6 GeV with few neutrinos above 10 GeV. Comparisons of differential cross sections in muon and proton kinematics for these two exposures probe deviations from free-neutron scattering that arise from the processes involving the nuclear medium, and provide a test of neutrino interaction models used to infer neutrino energies in oscillation experiments. Discrepancies are observed between the data and predictions that point to overestimates of the final state interactions of both protons and charged pions in quasielastic-like events.

Ruterbories, D. [Rochester U.]↗
DOE OSTI2026

Robust Interpretation of Electrochemical Impedance Spectra Using Numerical Complex Analysis

Electrochemical Impedance Spectroscopy (EIS) is a noninvasive technique widely used for understanding charge transfer and charge transport processes in electrochemical systems and devices. Standard approaches for the interpretation of EIS data involve starting with a hypothetical circuit model for the physical processes in the device based on experience/intuition and then fitting the EIS data to this circuit model. This work explores a mathematical approach for extracting key characteristic features from EIS data by relying on fundamental principles of complex analysis. These characteristic features can suggest the presence of inductors and constant phase elements (nonideal capacitors) from impedance data and enable us to answer questions about the identifiability and nonuniqueness of equivalent circuit models. In certain scenarios such as models with only resistors and capacitors, we are able to enumerate all possible families of circuit models. Finally, we apply the mathematical framework presented here to real-world electrochemical systems and highlight results using impedance measurements from a lithium-ion battery coin cell.

charge transfer↗
DOE OSTI2020

Evaluation of Changes to the MTR Fuel Dissolution Flowsheet to Increase the Number of L-Bundles Charged to a Dissolver

Material Test Reactor (MTR) fuels are dissolved in the H-Canyon facility using a Hg-catalyzed, HNO₃ dissolution flowsheet. The flowsheet is based on experimental work in which laboratory-scale experiments were used to provide bounding values for both offgas and H₂ generation rates. The generation of H₂ gas, primarily from the dissolution of Al, is controlled by limiting the surface area exposed to the solution. The number of L-Bundles charged and their submergence level defines the exposed surface area which is directly proportional to the H₂ generation rate. For the MTR fuel dissolution flowsheet, the maximum number of L-Bundles which can be charged to a dissolver was specified as a function of the Al concentration in the solution and the submergence level of the bundle. The MTR fuels are currently dissolved in the 6.1D dissolver. To reach the desired terminal Al concentration, a total of 12 L-Bundles of fuel are dissolved per batch. Depending on the submergence level being used in the dissolver, the 12 bundles are dissolved in three charges of four bundles per charge or in a sequence of three, four, and five bundles. However, if six L-Bundles could be dissolved in the initial charge, a dissolver batch could be completed in two dissolutions instead of three. To assess the feasibility of dissolving six bundles in the first charge, the Savannah River National Laboratory evaluated changes to the MTR flowsheet which increase the number of bundles which can be charged to a dissolver. Since the development of the existing MTR fuel dissolution flowsheet, improved offgas measurement methods have been developed to more accurately calculate the offgas composition and generation rate during laboratory-scale dissolutions. In the first part of this study, improvements in the calibration model for the Raman spectrometer (used for offgas characterization) and a more effective data smoothing routine were applied to existing data. The uncertainty in the offgas composition data used to define the MTR fuel dissolution flowsheet were subsequently re-evaluated which resulted in an approximate 50% reduction in the uncertainty of the H₂ gas concentration measurements. The reduced uncertainty was used in new calculations to define the maximum number of L-Bundles which can be charged to either the 6.1D or 6.4D dissolver as a function of the Al concentration. With the reduced uncertainty in the H₂ concentration measurements, a flowsheet was defined which supported initially charging 6 bundles to a dissolver. This flowsheet is based on the use of 0.002 M Hg, an L-Bundle immersion depth of 54 in., an air sparge/purge flowrate of 40 scfm, an iodine reactor operating temperature of 200 °C, and not exceeding 60% of the H₂ LFL in the dissolver offgas. In the second phase of this study, calculations were performed to assess the impact of changing various operating parameters to increase the number of L-Bundles charged to an H-Canyon dissolver. Applying the improved offgas measurement techniques including the reduced uncertainty in the H₂ concentration measurements to the existing data, the number of bundles of MTR fuel which can be charged to either the 6.1D or 6.4D dissolver were calculated based on varying the bundle immersion depth (44-60 in.), air sparge/purge flowrate (40-60 scfm), iodine reactor operating temperature (150-200 °C), and the percentage of the H₂ LFL which must not be exceeded (60-76%). Qualitatively, the percentage of the LFL had the largest influence on the maximum number of bundles which can be charged to a dissolver followed by the air sparge/purge flowrate, L-Bundle immersion depth, and the iodine reactor operating temperature. During the evaluation of each variable, the other variables were held at the baseline flowsheet conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Mixing effects on spectroscopy and partonic observables of heavy mesons with logarithmic confining potential in a light-front quark model

Using the variational principle, we systematically investigate the mass spectra and wave functions of both 1⁢𝑆 and 2⁢𝑆 state heavy pseudoscalar (𝑃) and vector (𝑉) mesons within the light-front quark model. This approach incorporates a Coulomb plus logarithmic confinement potential to accurately describe the constituent quark and antiquark dynamics. Additionally, spin hyperfine interactions are introduced perturbatively to compute the masses of pseudoscalar and vector mesons. The present analyses of the 1⁢𝑆 and 2⁢𝑆 states require the consideration of mixing between them to account for empirical constraints. These constraints include the mass gap Δ⁢𝑀 𝑃 >Δ⁢𝑀 𝑉 , where Δ⁢𝑀 𝑃⁡(𝑉) =𝑀$^{2⁢𝑆}_{𝑃⁡(𝑉)}$−𝑀$^{1⁢𝑆}_{𝑃⁡(𝑉)}$ and the hierarchy of the decay constants 𝑓 1⁢𝑆 >𝑓 2⁢𝑆 . We find the optimal value of the mixing angle to be 𝜃 =1⁢8°, significantly enhancing the consistency between our spectroscopic predictions and the experimental data compiled by the Particle Data Group. Furthermore, based on the predicted mass, the newly observed resonance 𝐵 𝐽⁡ (5840) could be assigned as a 2 1⁢ 𝑆 0 state in the 𝐵 meson family. The study also reports various pertinent observables, including twist-two distribution amplitudes, electromagnetic form factors, charge radii, 𝜉 moments, and transition form factors that are found to be consistent with both available lattice simulations and experimental data. In addition, our predicted branching ratios for the channels of 𝐵 + →𝜏 + ⁢𝜈 𝜏 as well as rare decays of 𝐵 0 and 𝐵$^0_𝑠$ appear in accordance with experimental data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Influence of Rare-Earth Ion Radius on Metal–Metal Charge Transfer in Trinuclear Mixed-Valent Complexes

We report the synthesis and characterization of a highly conjugated bisferrocenyl pyrrolediimine ligand, Fc 2 PyrDIH (1), and its trinuclear complexes with rare earth ions—(Fc 2 PyrDI)M(N(TMS) 2 ) 2 (2-M, M = Sc, Y, Lu, La). Crystal structures, NMR spectra, and UV/Vis-NIR data are presented. The latter are in good agreement with DFT calculations, illuminating the impact of the rare earth ionic radius on NIR charge transfer excitations. For [2-Sc] + , the charge transfer is at 11500 cm -1 , while for [2-Y] + only a d-d transition at 8000 cm -1 is observed. Lu has an ionic radius in between Sc and Y, and the [2-Lu] + complex exhibits both transitions. From TDDFT analysis we assign the 11500 cm -1 transition as a mixture of MLCT and MMCT, rather than pure metal-to-metal CT, because it has significant ligand character. Typically, the ferrocenes have high rotational freedom in bis-ferrocenyl mixed valent complexes. However, in the present (Fc 2 PyrDI)M(N(TMS) 2 ) 2 complexes, ligand-ligand repulsions lock the rotational freedom, so that rare earth ionic radius-dependent geometric differences increasingly influence orbital overlap as the ionic radius falls. The Marcus-Hush coupling constant HAB trends as: [2-Sc] + >[2-Lu] + >[2-Y] +

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Search for a light charged Higgs boson in the H$^\pm$ $\to $ cs channel in proton-proton collisions at $\sqrt{s} =$ 13 TeV

A search is conducted for a low-mass charged Higgs boson produced in a top quark decay and subsequently decaying into a charm and a strange quark. The data sample was recorded in proton-proton collisions at s=13 TeV by the CMS experiment at the LHC and corresponds to an integrated luminosity of 35.9 fb-1. The search is performed in the process of top quark pair production, where one top quark decays to a bottom quark and a charged Higgs boson and the other to a bottom quark and a W boson. With the W boson decaying to a charged lepton (electron or muon) and a neutrino, the final state comprises an isolated lepton, missing transverse momentum, and at least four jets, of which two are tagged as b jets. To enhance the search sensitivity, one of the jets originating from the charged Higgs boson is required to satisfy a charm tagging selection. No significant excess beyond standard model predictions is found in the dijet invariant mass distribution. An upper limit in the range 1.68%–0.25% is set on the branching fraction of the top quark decay to the charged Higgs boson and bottom quark for a charged Higgs boson mass between 80 and 160 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

High temperature stability and transport characteristics of hydrogen in alumina via multiscale computation

Here, the impact of hydrogen charge states on the stability and transport characteristics of hydrogen interstitials in alumina polymorphs is evaluated by multiscale computational methods including density functional theory (DFT), ab initio molecular dynamics (AIMD) and machine learned force fields. Thermodynamic calculations show that the protonic H i +1 interstitial is the most stable defect species for most values of the electronic bandgap in both and amorphous alumina (Al 2 O 3 ). Further, active learned Gaussian approximation potentials (GAP) were developed using AIMD data to study temperature dependent long time proton diffusion in alumina. Diffusivity calculations from GAP-MD simulations are found to be comparable with of the AIMD data, while being ~340 times faster and scalable to larger systems. Comparisons with diffusivity values for other interstitial charge states (H i 0 and H i -1 ) and published experimental literature indicate that H i +1 diffusion is the likely mechanism of hydrogen transport. A good agreement is obtained between H i +1 diffusivity calculated in α-Al 2 O 3 from DFT: 5.05 10 -3 exp(-0.81 eV/k B /T) cm 2 /s and reported experiment: 9.7X10 -4 exp(-0.83 eV/k B /T) cm 2 /s. Computationally and experimentally calculated energy barriers (0.81 and 0.83 eV respectively) only differ by 2.5%. Similarly, the pre-exponential diffusion coefficients only differ by 0.5 orders of magnitude. Moreover, the diffusivity of H i +1 in amorphous Al 2 O 3 in the 1000–2000 K range is calculated to be 2.53X10 -2 exp(-0.89 eV/k B /T), just one order of magnitude higher than the corresponding value in α-Al 2 O 3 . This suggests that local structural disorder does not significantly affect the energy landscape and diffusion behavior of H i +1 in Al 2 O 3 . Overall, these results show promise for the application of alumina polymorphs as hydrogen permeation barriers.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Dynamic In‐Plane Heterogeneous and Inverted Response of Graphite to Fast Charging and Discharging Conditions in Lithium‐Ion Pouch Cells

Solutions for improving fast charging of lithium‐ion batteries have largely focused on alleviating through‐plane lithiation gradients while little is understood about in‐plane heterogeneities and how to resolve them. Herein, high‐speed synchrotron X‐ray diffraction (XRD) resolves graphite lithiation spatially and temporally during 6 C charging and 2 C discharging. At every point during operation, considerable differences in the state of lithiation across the pouch cell are present. Some regions are more responsive to operation than others, reaching full lithiation early during charge and full delithiation during discharge. Other regions within the cell never fully delithiate during discharge, despite a prolonged voltage hold at 2.8 V. Using time‐resolved XRD data, the calculated local current density (mA cm −2 ) at the graphite surface shows an unexpected occurrence of local inverted current densities where regions of graphite are observed to delithiate during charging and lithiate during discharging. A pseudo‐3D model is developed for the graphite electrode with spatially varying microstructural tortuosity to show how microstructural heterogeneity could influence spatial charge dynamics. The model could not predict the complex in‐plane charge behavior observed within the cell. Consequently physics‐based charging protocols based on homogeneous electrode assumptions may underestimate the local variations in charge dynamics and occurrence of lithium plating.

25 ENERGY STORAGE↗
DOE OSTI2024

A Computational Review of Privacy-Preserving Mechanisms for the Smart Grid

Smart grid technologies have rapidly become one of the largest and most comprehensive sources of data for the modern utility. For the most part, data streams are seen as an essential tool that enable utilities to carry their day-to-day business operations, but they also create the need for efficient and secure data management strategies. In the context of the smart grid, ensuring data privacy is becoming an increasing concern due to a combination of factors that range from shifts in operational paradigms and rapid technology evolution to changes in legislation. Furthermore, researchers have highlighted the risks associated with improperly protected energy records. For example, energy consumption data from homes could be used to infer the behaviors and habits of home occupants through activity recognition or user profiling (Fan, 2017), which may lead to unfair service pricing, targeted advertising, or other personal security violations. Similarly, Electric Vehicles’ (EVs) charging metadata could be used to reveal private information about the owner such as their payment methods, preferred charging stations, and other locational and timing information that could be used to reconstruct the vehicle owner’s behaviors. The privacy of user data, even when used for statistical analysis or machine learning training processes, also needs to be carefully considered, as an individual’s private traits may still be vulnerable if their inclusion/exclusion greatly impacts the result or could be linked to a public dataset through cross-reference. The breach of user privacy also has severe impacts for organizations that store, transmit, or work on the data in the form of diminishing the public’s trust in them while potentially incurring legal consequences (e.g., fines and suspensions under the European Union General Data Protection Regulation, Health Insurance Portability and Accountability Act, etc.). Because of these risks, several privacy-preserving mechanisms are available to help organizations comply with privacy legislations and prevent the unauthorized and malicious use of user data. In light of these concerns, this report focuses on performing a computational review of privacy-preserving mechanisms that have received a significant amount of interest in literature. It specifically focuses on 1) homomorphic encryption, 2) zero-knowledge proofs, 3) differential privacy, and 4) federated learning. It is worth noting that although many of the methods presented in this document rely on cryptographic primitives, their intent is not to provide perfect secrecy, but rather to enable users to maintain privacy, and thus they shall not be compared or equated to other constructs that are aimed to address cybersecurity constructs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Progress toward differential cross-section measurements of coherent charged-pion production in charged-current muon neutrino interactions on argon with SBND

Coherent charged pion production in charged-current muon neutrino–nucleus interactions provides a clean experimental signature and enables an excellent estimate of the neutrino energy, making it particularly valuable for neutrino flux constraints and oscillation analyses in future long-baseline experiments. Despite its importance, theoretical modeling of this process remains challenging, especially in the low-energy region below 1 GeV and its dependence on the nuclear target. The Short-Baseline Near Detector (SBND) offers a unique opportunity to study coherent charged pion production using neutrinos in the few-hundred-MeV energy range from the Booster Neutrino Beam (BNB) interacting with an argon target (A = 40), with unprecedented statistics expected to yield approximately three thousand signal events in SBND’s BNB data with 3.5 x 10^20 protons on target. This analysis aims to achieve the first differential cross-section measurement of charged-current coherent charged pion production on argon, as well as the first measurement of this process using BNB neutrinos.

Oh, Sungbin [Fermilab]↗
DOE OSTI2022

Simulating single-particle dynamics in magnetized plasmas: The RMF code

The RMF (Rotating Magnetic Field) code is designed to calculate the motion of a charged particle in a given electromagnetic field. It integrates Hamilton’s equations in cylindrical coordinates using an adaptive predictor-corrector double-precision variable-coefficient ordinary differential equation solver for speed and accuracy. RMF has multiple capabilities for the field. Particle motion is initialized by specifying the position and velocity vectors. Here, the six-dimensional state vector and derived quantities are saved as functions of time. A post-processing graphics code, XDRAW, is used on the stored output to plot up to 12 windows of any two quantities using different colors to denote successive time intervals. Multiple cases of RMF may be run in parallel and perform data mining on the results. Recent features are a synthetic diagnostic for simulating the observations of charge-exchange-neutral energy distributions and RF grids to explore a Fermi acceleration parallel to static magnetic fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Real-Time event reconstruction for Nuclear Physics Experiments using Artificial Intelligence

Charged track reconstruction is a critical task in nuclear physics experiments, enabling the identification and analysis of particles produced in high-energy collisions. Machine learning (ML) has emerged as a powerful tool for this purpose, addressing the challenges posed by complex detector geometries, high event multiplicities, and noisy data. Traditional methods rely on pattern recognition algorithms like the Kalman filter, but ML techniques, such as neural networks, graph neural networks (GNNs), and recurrent neural networks (RNNs), offer improved accuracy and scalability. By learning from simulated and real detector data, ML models can identify and classify tracks, predict trajectories, and handle ambiguities caused by overlapping or missing hits. Moreover, ML-based approaches can process data in near-real-time, enhancing the efficiency of experiments at large-scale facilities like the Large Hadron Collider (LHC) and Jefferson Lab (JLAB). As detector technologies and computational resources evolve, ML-driven charged track reconstruction continues to push the boundaries of precision and discovery in nuclear physics. In these proceedings, we highlight advancements in charged track identification leveraging Artificial Intelligence within the CLAS12 detector, achieving a notable enhancement in experimental statistics compared to traditional methods. Additionally, we showcase real-time event reconstruction capabilities, including the inference of charged particle properties, such as momentum, direction, and species identification, at speeds matching data acquisition rates. These innovations enable the extraction of physics observables directly from the experiment in real-time.

Gavalian, Gagik (ORCID:0000000267385457)↗
DOE OSTI2024

Proceedings for the Workshop on Applied Nuclear Data Activities 2024

The Workshop for Applied Nuclear Data Activities (WANDA) is designed to increase communication among nuclear data (ND) users in multidisciplinary federal programs, ND producers, ND funders, and other ND experts. It also presents an opportunity to cross-pollinate ideas as well as introduce ND gaps identified by federal programs to ND experts and ND capabilities to the various federal ND users. WANDA 2024 included five technical sessions, three of which focused on Fusion Energy Sciences (FES)—FES Fusion Neutronics, FES Tritium Production, and FES Material Damage—and two stand-alone sessions—Isotopes and Targetry for Nuclear Data and Uncertainty Quantification. The FES sessions successfully brought new voices to the WANDA discussions, expanding the application space in which nuclear data are critical. FES programs need accurate nuclear data with realistic uncertainty quantification to properly estimate, for example, shielding, activation, tritium production, helium production, structural material integrity, and superconducting magnet operation. This includes a variety of projectile (neutrons, photons, charged particles) and target atoms. One of the action items common to all the FES sessions was a need to perform sensitivity studies to identify the prioritization of nuclear data needs. The Isotopes and Targetry session highlighted the many capabilities available to produce high-quality targets for nuclear data measurements, including 3D printing with spherical powders, combustion synthesis coupled with spin coating & electrospraying, inkjet printing, and isotopic doping. These new methods open doors for more accurate measurement, but it was also stressed that sample characterization following any method of fabrication is of the highest importance to accurately interpret nuclear data measurement results that used that sample. The Uncertainty Quantification (UQ) session was broken into two categories: nuclear data uncertainty quantification and the use of that uncertainty quantification. Thematic to the UQ session was the loss of information when going from nuclear data measurement, to evaluation, to evaluated file, and finally to neutron transport calculations. Current evaluated ND libraries typically only contain covariances, which assume that the probability distributions are Gaussian. Beyond being a simplified assumption for many evaluations, this can lead to negative values on many observables when attempting to sample the covariance. The covariance format, however, is very efficient in that a simple set of linear equations can transform uncertainty from parameters or cross sections to the application of interest. Focused collaboration is needed between nuclear data evaluators and nuclear data users to ensure that needs are being met.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Accelerating the Structure Exploration of Diverse Bi–Pt Nanoclusters via Physics‐Informed Machine Learning Potential and Particle Swarm Optimization

Bimetallic Bi–Pt nanoclusters exhibit diverse structural motifs, including core-shell, Janus, and mixed alloy configurations, due to the unique bonding characteristics between Bi and Pt atoms. Using density functional theory refinements from ChIMES physically machine-learned potential and CALYPSO particle swarm optimization global searches, 34 Bi20-Pt20 nanoclusters are systematically classified. The results reveal that Bi atoms predominantly occupy surface sites, driven by charge transfer effects. Cohesive energy trends alone prove insufficient for structure differentiation, necessitating a data-driven approach employing principal component analysis and K-means clustering. Furthermore, vibrational, electronic, and infrared spectral analyses provide additional insights into structure-property relationships. The findings offer an original framework for the automated classification and analysis of bimetallic nanoclusters, enhancing the understanding of their stability and functional properties.

bimetallic nanoparticles↗
DOE OSTI2020

Search for electroweak production of a vector-like T quark using fully hadronic final states

A search is performed for electroweak production of a vector-like top quark partner T of charge 2/3 in association with a top or bottom quark, using proton-proton collision data at $\sqrt{s} =$ 13 TeV collected by the CMS experiment at the LHC in 2016. The data sample corresponds to an integrated luminosity of 35.9 fb$^{-1}$. The search targets T quarks over a wide range of masses and fractional widths, decaying to a top quark and either a Higgs boson or a Z boson in fully hadronic final states. The search is performed using two experimentally distinct signatures that depend on whether or not each quark from the decays of the top quark, Higgs boson, or Z boson produces an individual resolved jet. Jet substructure, b tagging, and kinematic variables are used to identify the top quark and boson jets, and also to suppress the standard model backgrounds. The data are found to be consistent with the expected backgrounds. Upper limits at 95% confidence level are set on the cross sections for T quark-mediated production of tHQq, tZQq, and their sum, where Q is the associated top or bottom heavy quark and q is another associated quark. The limits are given for each search signature for various T quark widths up to 30% of the T quark mass, and are between 2 pb and 20 fb for T quark masses in the range 0.6-2.6 TeV. These results are significantly more sensitive than prior searches for electroweak single production of T$\to$tH and represent the first constraints on T$\to$tZ using hadronic decays of the Z boson with this production mode.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Search for supersymmetry in final states with two oppositely charged same-flavor leptons and missing transverse momentum in proton-proton collisions at $\sqrt{s} =$ 13 TeV

A search for phenomena beyond the standard model in final states with two oppositely charged same-flavor leptons and missing transverse momentum is presented. The search uses a data sample of proton-proton collisions at $ \sqrt{s} $ = 13 TeV, corresponding to an integrated luminosity of 137 fb$^{−1}$, collected by the CMS experiment at the LHC. Three potential signatures of physics beyond the standard model are explored: an excess of events with a lepton pair, whose invariant mass is consistent with the Z boson mass; a kinematic edge in the invariant mass distribution of the lepton pair; and the nonresonant production of two leptons. The observed event yields are consistent with those expected from standard model backgrounds. The results of the first search allow the exclusion of gluino masses up to 1870 GeV, as well as chargino (neutralino) masses up to 750 (800) GeV, while those of the searches for the other two signatures allow the exclusion of light-flavor (bottom) squark masses up to 1800 (1600) GeV and slepton masses up to 700 GeV, respectively, at 95% confidence level within certain supersymmetry scenarios.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Simulating low-energy neutrino interactions with MARLEY

Monte Carlo event generators are a critical tool for the interpretation of data obtained by neutrino experiments. Several modern event generators are available which are well-suited to the GeV energy scale used in studies of accelerator neutrinos. However, theoretical modeling differences make their immediate application to lower energies difficult. In this paper, I present a new event generator, MARLEY, which is designed to better address the simulation needs of the low-energy (tens of MeV and below) neutrino community. The code is written in C++14 with an optional interface to the popular ROOT data analysis framework. The current release of MARLEY (version 1.2.0) emphasizes simulations of the reaction 40 Ar ( ν e , e − ) 40 K ⁎ but is extensible to other channels with suitable user input. This paper provides detailed documentation of MARLEY's implementation and usage, including guidance on how generated events may be analyzed and how MARLEY may be interfaced with external codes such as Geant4. Further information about MARLEY is available on the official website at http://www.marleygen.org. Program title:MARLEY 1.2.0 CPC Library link to program files:https://doi.org/10.17632/4v7zxnc8j3.1 Developer's respository link:http://github.com/MARLEY-MC/marley Code Ocean capsule:https://codeocean.com/capsule/9868179 Licensing provisions: GNU General Public License 3.0 Programming language: C++14 External routines/libraries used: GNU Scientific Library [1,2] (required), ROOT [3,4] (optional) Nature of problem: Simulation of neutrino-nucleus scattering events at energies of tens-of-MeV and below Solution method: Initial two-to-two scattering kinematics are sampled using the allowed approximation differential cross section and tables of precomputed nuclear matrix elements. Subsequent de-excitations of the remnant nucleus are simulated using a Monte Carlo implementation of the Hauser-Feshbach statistical model and tabulated γ-ray decay schemes for discrete nuclear levels. Additional comments including restrictions and unusual features: Input data are provided with the code that are suitable for producing simulations of the charged-current reaction 40 Ar ( ν e , e − ) 40 K ⁎ , coherent elastic neutrino-nucleus scattering on spin-zero target nuclei, and neutrino-electron elastic scattering on any atomic target. Preparation of new reaction input files (whose format is documented in Appendix B) would enable other reaction channels and nuclear targets to be handled by the existing code framework. Although there is no maximum neutrino energy enforced by the code itself, realistic neutrino-nucleus scattering events may be generated up to roughly 50 MeV. Above this energy, the effects of forbidden nuclear transitions, which are neglected in the current treatment of the cross sections (see section 2.1), become increasingly important.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Enhanced physics-constrained deep neural networks for modeling vanadium redox flow battery

Numerical simulation has become indispensable in advancing cost-effective process optimization and control of flow batteries. We propose an enhanced version of the physics-constrained deep neural network (PCDNN) approach to provide high-accuracy voltage predictions in the vanadium redox flow batteries (VRFBs). The purpose of the PCDNN approach is to enforce the physics-based zero-dimensional (0D) VRFB model in a neural network to assure model generalization for various battery operation conditions. However, limited by the simplifications of the 0D model, the PCDNN cannot capture sharp voltage changes in the extreme SOC regions. To improve the accuracy of voltage prediction at extreme ranges, we introduce a second (enhanced) DNN to mitigate the prediction errors carried from the 0D model itself and call the resulting approach enhanced PCDNN (ePCDNN). By comparing with experimental data, we demonstrate that the ePCDNN approach can accurately capture the voltage response throughout the charge–discharge cycle, including the tail region of the voltage discharge curve. The loss function for training the ePCDNN is designed to be flexible by adjusting the weights of the physics-constrained DNN and the enhanced DNN. In conclusion, this allows the ePCDNN framework to be transferable to battery systems with variable physical model fidelity.

25 ENERGY STORAGE↗