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At least 1,063 records · Page 59

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DOE OSTI2023

Mapping and imaging ionizing radiation in two and three dimensions

A two-dimensional imaging system and a two-dimensional or three-dimensional optical tomographic mapping system, each employing gas scintillation induced by ionizing radiation, i.e., radioluminescence, and corresponding methods, are disclosed. The systems may employ one or more cameras and corresponding UV filters (potentially solar blind filters) for imaging a radioluminescent scene. For two-dimensional or three-dimensional mapping, the resultant UV images are spatially registered with one another and then reconstructed to form a three-dimensional tomographic map of the ionizing radiation. The two-dimensional map is a plane of the three-dimensional map. The UV images may be spatially registered by using a reference source, optionally, a calibrated reference source allowing dosimetry calculations for the ionizing radiation. Molecular nitrogen is the primary candidate for the radioluminescent gas, though a controlled ambient in a chamber of nitric oxide, argon, krypton, or xenon may be employed. The reconstruction process employs an algebraic reconstruction technique or an Abel inversion.

Bentz, Brian Z.↗

DOE OSTI2026

Neural Posterior Estimation for Scalable and Accurate Inverse Parameter Inference in Li-Ion Batteries

Diagnosing the internal state of Li-ion batteries is critical for battery research, operation of real-world systems, and prognostic evaluation of remaining lifetime. By using physics-based models to perform probabilistic parameter estimation via Bayesian calibration, diagnostics can account for the uncertainty due to model fitness, data noise, and the observability of any given parameter. However, Bayesian calibration in Li-ion batteries using electrochemical data is computationally intensive even when using a fast surrogate in place of physics-based models, requiring many thousands of model evaluations. A fully amortized alternative is neural posterior estimation (NPE). NPE shifts the computational burden from the parameter estimation step to data generation and model training, reducing the parameter estimation time from minutes to milliseconds, enabling real-time applications. The present work shows that NPE can infer parameters equally or more accurately than Bayesian calibration, even if it leads to higher voltage reconstruction errors. We also demonstrate that the higher computational costs for data generation are tractable even in high-dimensional cases (ranging from 6 to 27 estimated parameters). The NPE method also offers several interpretability advantages over Bayesian calibration, such as local parameter sensitivity to specific regions of the voltage curve. The NPE method is demonstrated using an experimental fast charge dataset, with parameter estimates validated against measurements of loss of lithium inventory and loss of active material. The implementation is made available in a companion repository (https://github.com/NatLabRockies/BatFIT).

25 ENERGY STORAGE↗

DOE OSTI2021

Characterizing the magnetic fields of nearby molecular clouds using submillimeter polarization observations

Of all the factors that influence star formation, magnetic fields are perhaps the least well understood. The goal of this paper is to characterize the 3D magnetic field properties of nearby molecular clouds through various methods of statistically analysing maps of polarized dust emission. Our study focuses on nine clouds, with data taken from the Planck Sky Survey as well as data from the Balloon-borne Large Aperture Submillimeter Telescope for Polarimetry observations of Vela C. We compare the distributions of polarization fraction (p), dispersion in polarization angles ($\mathcal {S}$), and hydrogen column density (N H ) for each of our targeted clouds. To broaden the scope of our analysis, we compare the distributions of our clouds’ polarization observables with measurements from synthetic polarization maps generated from numerical simulations. We also use the distribution of polarization fraction measurements to estimate the inclination angle of each cloud’s cloud-scale magnetic field. We obtain a range of inclination angles associated with our clouds, varying from 16° to 69°. We establish inverse correlations between p and both $\mathcal {S}$ and NH in almost every cloud, but we are unable to establish a statistically robust $\mathcal {S}$ versus NH trend. By comparing the results of these different statistical analysis techniques, we are able to propose a more comprehensive view of each cloud’s 3D magnetic field properties. These detailed cloud analyses will be useful in the continued studies of cloud-scale magnetic fields and the ways in which they affect star formation within these molecular clouds.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

A hybrid data-driven and model-based approach for computationally efficient stochastic unit commitment and economic dispatch under wind and solar uncertainty

Stochastic unit commitment (UC) and economic dispatch (ED) are imperative in dealing with uncertainty in renewable forecast for power system operation and planning such that the overall expected production cost is minimized over the planning horizon. However, accurate calculation of the expected production cost requires assessment of a very large number of different scenarios of uncertain renewable resources, such as solar and wind, which is practically infeasible to simulate in real time. This article proposes a hybrid datadriven and physics-based model-predictive paradigm to efficiently solve for stochastic unit commitment and economic dispatch considering uncertainty in wind and solar power forecasts. Here, the novelty of the approach lies in decoupling the production cost estimation from the unit commitment and economic dispatch optimization problems under uncertainty without compromising on the fidelity of the solutions. A data-driven machine learning model is first developed to predict the mean optimal production cost. A physics-based inverse problem is then solved to get the stochastic UC and ED profiles from the expected cost. The presented approach considers, for the first time, solar uncertainty in UC/ED determination and enables efficient and accurate propagation of wind and solar uncertainty to estimate the statistics of the production cost. The effectiveness of the developed approach is demonstrated systematically on a stylized RTS-GMLC single-node system. The overall framework predicts the expected cost 62.5% more accurately than the existing state-of-the-art, on unforeseen days during the entire year, and yields, for the first time, the associated physically consistent UC and ED profiles. The solutions are also shown to be flexible in providing adequate daily reserves to address any statistical deviations from probabilistic power forecasts. The computational time associated with the presented method is only about 10 s compared to over 24 h needed for a conventional stochastic UC/ED determination under uncertainty on an Intel Core i9 processor with 32 GB of RAM.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Geometric origin of the intrinsic transverse spin transport in a canted-antiferromagnet/heavy-metal heterostructure

We theoretically study the conditions under which an intrinsic spin Nernst effect–a transverse spin current induced by an applied temperature gradient–can occur in a canted-antiferromagnet insulator, such as LaFeO 3 and other materials of the same family. The spin Nernst effect may provide a microscopic mechanism for an experimentally observed anomalous thermovoltage in LaFeO 3 /Pt heterostructures, where spin is transferred across the insulator/metal interface when a temperature gradient is applied to LaFeO 3 parallel to the interface. We find that LaFeO 3 exhibits an intrinsic spin Nernst effect when inversion symmetry is broken on the axes parallel to both the applied temperature gradient and the direction of spin transport, which can result in a spin injection across the insulator/metal interface. Furthermore, our paper provides a general derivation of a symmetry-breaking-induced spin Nernst effect, which may open a path to engineering a finite spin Nernst effect in systems where it would otherwise not arise.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Correction and verification of x-ray imaging crystal spectrometer analysis on Wendelstein 7-X through x-ray ray tracing

X-ray ray tracing is used to develop ion-temperature corrections for the analysis of the X-ray Imaging Crystal Spectrometer (XICS) used at Wendelstein 7-X (W7-X) and perform verification on the analysis methods. The XICS is a powerful diagnostic able to measure ion-temperature, electron-temperature, plasma flow, and impurity charge state densities. While these systems are relatively simple in design, accurate characterization of the instrumental response and validation of analysis techniques are difficult to perform experimentally due to the requirement of extended x-ray sources. For this reason, a ray tracing model has been developed that allows characterization of the spectrometer and verification of the analysis methods while fully considering the real geometry of the XICS system and W7-X plasma. Through the use of ray tracing, several important corrections have been found that must be accounted for in order to accurately reconstruct the ion-temperature profiles. The sources of these corrections are described along with their effect on the analyzed profiles. The implemented corrections stem from three effects: (1) effect of sub-pixel intensity distribution during de-curving and spatial binning, (2) effect of sub-pixel intensity distribution during forward model evaluation and generation of residuals, and (3) effect of defocus and spherical aberrations on the instrumental response. Possible improvements to the forward model and analysis procedures are explored, along with a discussion of trade-offs in terms of computational complexity. Finally, the accuracy of the tomographic inversion technique in stellarator geometry is investigated, providing for the first time a verification exercise for inversion accuracy in stellarator geometry and a complete XICS analysis tool-chain.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Measurement of proton quenching in a plastic scintillator detector

The non-linear energy response of the plastic scintillator EJ-260 is measured with the MicroCHANDLER detector, using neutron beams of energy 5 to 27 MeV at the Triangle Universities Nuclear Laboratory. The first and second order Birks' constants are extracted from the data, and found to be $k_B = (8.70 \pm 0.93)\times 10^{-3}\ {\rm g/cm^2/MeV}$ and $k_C = (1.42 \pm 1.00) \times 10^{-5}\ {\rm (g/cm^2/MeV)^2}$. This result covers a unique energy range that is of direct relevance for fast neutron backgrounds in reactor inverse beta decay detectors. Furthermore, these measurements will improve the energy non-linearity modeling of plastic scintillator detectors. In particular, the updated energy response model will lead to an improvement of fast neutron modeling for detectors based on the CHANDLER reactor neutrino detector technology.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Determination of neutron irradiation temperatures of SiC using electrical resistivity method

The irradiation temperature of silicon carbide (SiC) was determined post-irradiation by examination of the recovery of the electrical resistivity due to thermal annealing in a rapid heating/cooling optical furnace. High-purity, high-resistivity grade SiC is routinely used as a passive temperature monitor in neutron irradiation studies at the High Flux Isotope Reactor (HFIR), and this paper presents an alternative automated technique for determination of the irradiation temperature the SiC experienced. Neutron collisions with the atoms results in displaced lattice atoms (interstitials) that act as electron donors yielding a significant decrease in electrical resistivity. The irradiation defects become thermodynamically unstable and start to recombine, when annealed above the irradiation temperature, resulting in a recovery of the electrical resistivity. The resistivity is measured at a fixed elevated temperature above ambient, which is below the target irradiation temperature. When the resistivity is plotted as a function of annealing temperatures, a clear increase is observed due to the recovery of irradiation defects. We have demonstrated that this electrical resistivity measurement of SiC is effective to determine irradiation temperature of SiC. In conclusion, energy levels of various defects in SiC were calculated from Arrhenius plots of electrical conductivity versus inverse temperature.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Method for estimating the density of high-level nuclear waste glass

A database of over 1100 silicate glass compositions and densities was compiled and used to evaluate the efficacy of an algorithm for estimating the density of silicate glass compositions. We sought to develop a parsimonious algorithm based on the additivity of partial molar volumes of individual oxide components weighted by their mole fraction in a glass composition. Bound molar volumes were used for oxides in which the density of the oxide bound in a glass matrix was previously determined. The bound molar volumes were known for oxides covering 97.5 mole percent of the database compositional space. The measured glass densities were plotted against the estimated glass densities and a linear regression yielded an R 2 adj. = 0.95 and a slope and intercept of approximately one and zero, respectively. This regression suggests that glass densities estimated by the algorithm, within analysis uncertainty, are equal to the measured densities of the glasses. In addition to the development of the density estimation, we corroborated many of the referenced bound molar volume data used in the parameterization of the estimation algorithm via linear regression of the individual partial molar volumes versus the inverse measured densities (specific volumes) of the glasses in the database.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Describing hadronization via histories and observables for Monte-Carlo event reweighting

We introduce a novel method for extracting a fragmentation model directly from experimental data without requiring an explicit parametric form, called Histories and Observables for Monte-Carlo Event Reweighting (HOMER), consisting of three steps: the training of a classifier between simulation and data, the inference of single fragmentation weights, and the calculation of the weight for the full hadronization chain. We illustrate the use of HOMER on a simplified hadronization problem, a q\bar{q} q q ‾ string fragmenting into pions, and extract a modified Lund string fragmentation function f(z) f ( z ) . We then demonstrate the use of HOMER on three types of experimental data: (i) binned distributions of high-level observables, (ii) unbinned event-by-event distributions of these observables, and (iii) full particle cloud information. After demonstrating that f(z) f ( z ) can be extracted from data (the inverse of hadronization), we also show that, at least in this limited setup, the fidelity of the extracted f(z) f ( z ) suffers only limited loss when moving from (i) to (ii) to (iii). Public code is available at https://gitlab.com/uchep/mlhad.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Efficient Optimization of Plasma Radiation Detector Configurations using Imperfect Inference Models

The configurations of instruments fielded on an experiment affect the amount of information captured and the quality of subsequent inference. Here, we investigate the problem of optimizing plasma x-ray radiation detectors in a magneto-inertial fusion experiment at Sandia National Laboratories. It is impossible to directly measure properties such as the temperature of the thermonuclear fusion plasma produced in these experiments because of the extreme environment and destructive nature of the experiment. Among other diagnostics, several detectors are placed with significant standoff from the fusion target to capture the x-rays emitted by the fusion plasma, which can be used to infer some of its properties. To optimize the configuration of these detectors, a high-fidelity model (HFM) is used for simulating outputs and a low-fidelity model (LFM) is used for inference. We develop methods based on A- and L-optimality criteria that are efficient to compute while explicitly accounting for the discrepancy between the HFM and the LFM. The method allows us to find detector configurations that perform similarly to or better than the configuration obtained using an existing sampling-based optimization method while decreasing computational time by a factor of 50. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.

Bayesian optimization↗

DOE OSTI2021

Shell-structure and asymmetry effects in level densities

Level density [Formula: see text] is derived for a nuclear system with a given energy [Formula: see text], neutron [Formula: see text], and proton [Formula: see text] particle numbers, within the semiclassical extended Thomas–Fermi and periodic-orbit theory beyond the Fermi-gas saddle-point method. We obtain [Formula: see text], where [Formula: see text] is the modified Bessel function of the entropy [Formula: see text], and [Formula: see text] is related to the number of integrals of motion, except for the energy [Formula: see text]. For small shell structure contribution one obtains within the micro–macroscopic approximation (MMA) the value of [Formula: see text] for [Formula: see text]. In the opposite case of much larger shell structure contributions one finds a larger value of [Formula: see text]. The MMA level density [Formula: see text] reaches the well-known Fermi gas asymptote for large excitation energies, and the finite micro-canonical limit for low excitation energies. Fitting the MMA [Formula: see text] to experimental data on a long isotope chain for low excitation energies, due mainly to the shell effects, one obtains results for the inverse level density parameter [Formula: see text], which differs significantly from that of neutron resonances.

Physics↗

DOE OSTI2026

Computing neutrino cross sections from Euclidian responses

Energy integrated neutrino cross sections are integrals of nuclear responses weighted with kinematic prefactors. We decompose the prefactors into a limited set of functions of energy transfer and show the relevant integrals are the moments of the responses, and integrals weighted with $1/(a+ω)^n$ with $n\leq 2$. These can be directly obtained from the Euclidean response, avoiding the need for inversion of the Laplace transform. As a proof of concept we study the procedure with toy-model responses for the quasielastic peak. We show that the different contributions can be straightforwardly organized in terms of relative importance, and how flux-averaged cross sections can be obtained. Using a realistic model for the response and numerical uncertainty we show that it is feasible to obtain the required integrals from the Euclidean response, with large uncertainties only for the third moment. Due to kinematic restrictions, the integrals contain contributions from the unphysical region for neutrino scattering, coming from high-momentum nucleons. We show that (in the absence of two-body currents) robust corrections for this contamination are obtained from the single-nucleon momentum distribution. These results present an opportunity to compute certain neutrino cross sections with ab-initio methods with controlled uncertainties.

Nikolakopoulos, A. [Washington U., Seattle]↗

DOE OSTI2026

Computing neutrino cross sections from Euclidian responses

Nikolakopoulos, A. [Washington U., Seattle]↗

DOE OSTI2021

A Uranium(II) Arene Complex That Acts as a Uranium(I) Synthon

We report two-electron reduction of the amidate-supported U(III) mono(arene) complex U(TDA) 3 (2) with KC 8 yields the anionic bis(arene) complex [K[2.2.2]cryptand][U(TDA) 2 ] (3) (TDA = N-(2,6-di-isopropylphenyl)pivalamido). EPR spectroscopy, magnetic susceptibility measurements, and calculations using DFT as well as multireference CASSCF methods all provide strong evidence that the electronic structure of 3 is best represented as a 5f 4 U(II) metal center bound to a monoreduced arene ligand. Reactivity studies show 3 reacts as a U(I) synthon by behaving as a two-electron reductant toward I 2 to form the dinuclear U(III)–U(III) triiodide species [K[2.2.2]cryptand][(UI(TDA) 2 ) 2 (μ-I)] (6) and as a three-electron reductant toward cycloheptatriene (CHT) to form the U(IV) complex [K[2.2.2]cryptand][U(η 7 -C 7 H 7 )(TDA) 2 (THF)] (7). The reaction of 3 with cyclooctatetraene (COT) generates a mixture of the U(III) anion [K[2.2.2]cryptand][U(TDA) 4 ] (1-crypt) and U(COT) 2 , while the addition of COT to complex 2 instead yields the dinuclear U(IV)–U(IV) inverse sandwich complex [U(TDA) 3 ] 2 (μ-η 8 :η 3 -C 8 H 8 ) (8). Two-electron reduction of the homoleptic Th(IV) amidate complex Th(TDA) 4 (4) with KC 8 gives the mono(arene) complex [K[2.2.2]cryptand][Th(TDA) 3 (THF)] (5). The C–C bond lengths and torsion angles in the bound arene of 5 suggest a direduced arene bound to a Th(IV) metal center; this conclusion is supported by DFT calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Soil architecture and subsurface stratigraphic heterogeneities across land-lake interfaces along Lake Erie.

Uploaded raw datasets from electrical resistivity tomography (ERT), ground penetrating radar (GPR), electromagnetic induction (EMI) and insitu sensors were acquired across land-lake interfaces along Lake Erie. These datasets were useful to delineate the soil architecture and subsurface stratigraphic heterogeneities. We combined multiple geophysical methods with lithostratigraphic logs from borehole cores and data from soil and borehole sensors to investigate spatial heterogeneities across land-lake interfaces. The apparent electrical conductivity (Eca) maps matched closely with the soil maps from public database and also detected additional soil units that were missing in the traditional soil maps. This implies that electromagnetic induction (EMI) could be relied upon for non invasive characterization of soils in sampling restricted sites where only non-invasive measurements are feasible. Results from electrical resistivity tomography (ERT) and Ground penetrating radar (GPR) are consistent with the surficial geology of the study area, and revealed that the vertical variabilities at the sites are mainly driven by stratigraphy.The ERT data (.stg) were acquired from three different sites portage river (PTR), crane creek (CRC) and old woman creek (OWC). The ".stg" files can be opened with ERT inversion software such as EarthImager, ResIpy or Res2DInv. The GPR data (.GPZ) were also acquired from the three sites, and the ".GPZ" data files can be opened with EKKO_project 5 software from Sensors & Software Inc., or with any other standard GPR software. The EM data (.csv) were acquired from the three sites while the soil sensor data (.csv) here were acquired only from crane creek site. The ".csv) files can be opened with MS Excel or any other spread sheet software.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

The Structural Characterisation and DFT-Aided Interpretation of Vibrational Spectra for Cyclo(l-Cys-d-Cys) Cyclic Dipeptide in a Solid State

Cyclic dipeptides with two intramolecular peptide bonds forming a six-membered 2,5-diketopiperazine ring are gaining significant attention due to their biological and chemical properties. Small changes in the local geometry of such molecules (from cis to trans) can lead to significant structural differences. This work presents the results of a study of cyclo(l-Cys-d-Cys), a dipeptide comprising two cysteine molecules in opposite chiral configurations, with the functional groups situated at both sides of the diketopiperazine ring. X-ray diffraction (XRD) experiment revealed that the molecule crystallises in the $P$-1 space group, which includes the centre of inversion. The IR and Raman vibrational spectra of the molecule were acquired and interpreted in terms of the potential energy distribution (PED) according to the results of density functional theory (DFT) calculations. The DFT-assisted analysis of energy frameworks for the hydrogen bond network within molecular crystals was performed to support the interpretation of X-ray structural data. The optimisation of the computational model based on three-molecule geometry sections from the crystallographic structure, selected to appropriately reflect the intermolecular interactions responsible for the formation of 1D molecular tapes in cyclo(l-Cys-d-Cys) crystal, allowed for better correspondence between theoretical and experimental vibrational spectra. This work can be considered the first complete structural characterisation of cyclo(l-Cys-d-Cys), complemented via vibrational spectroscopy results with full band assignment aided with the use of the DFT method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Analyzing rotational bands in odd-mass nuclei using effective field theory and Bayesian methods

We recently developed an Effective Field Theory (EFT) for rotational bands in odd-mass nuclei. Here we use EFT expressions to perform a Bayesian analysis of data on the rotational energy levels of 99 Tc, 155,157 Gd, 159 Dy, 167,169 Er, 167,169 Tm, 183 W, 235 U and 239 Pu. The error model in our Bayesian analysis includes both experimental and EFT truncation uncertainties. It also accounts for the fact that low-energy constants (LECs) at even and odd orders are expected to have different sizes. We use Markov Chain Monte Carlo (MCMC) sampling to explore the joint posterior of the EFT and error-model parameters and show both the LECs and the breakdown scale can be reliably determined. We extract the LECs up to fourth order in the EFT and find that, provided we correctly account for EFT truncation errors in our likelihood, results for lower-order LECs are stable as we go to higher orders. LEC results are also stable with respect to the addition of higher-energy data. We extract the expansion parameter for all the nuclei listed above and find a clear correlation between the extracted and the expected value of the inverse breakdown scale, W, based on the single-particle and vibrational energy scales. However, the W that actually determines the convergence of the EFT expansion is markedly smaller than would be naively expected based on those scales.

EFT↗