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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

NbV_BCC_SolidSolution_128atoms_VASP6

We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution binary alloys niobium-vanadium (Nb-V). The electronic structures of alloys have been calculated using Vienna Ab initio Simulation Package (VASP). Within this package the DFT approach is used to reduce many-body Schrodinger equation to set of single particle Kohn-Sham (KS) equations. The generalized electronic exchange-correlation functional is described by generalized gradient approximation with the Perdew-Burke-Ernzerhof parametrization. The electron-ion interactions is described by pseudopotentials developed within the plane-wave basis projector augmented-wave (PAW) approach \cite{PAW}. These pseudopotentials are available at the VASP portal (http://cms.mpi.univie.ac.at/vasp/). Our calculations have been run with the pseudopotentials treating s and p semi-core states as valence in case for the elements Nb and V. The electronic densities and potentials are expanded over plane-waves with energy cutoff of 350 eV. 2x2x2 k-mesh and normal precision were used. The alloys were modeled by supercell containing 128 randomly distributed atoms. At initial step the atoms occupy perfect bcc lattice cites. This initial structure was optimized until energy changes less than 1e-6 eV, while forces acting on atoms don't exceed 1e-2 eV/angstrom. The electron-ion interaction is described by PAW pseudopotentials. The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 4. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites. We collected data for a total of 3,100 randomized atomic structures over 31 chemical compositions. The calculations have been collected on NERSC-Perlmutter and OLCF-Summit using the VASP 6.3.2. The VASP calculations for every atomic structure have been performed in 2 main steps: 1. Starting from an ideal body-centered-cubic (BCC) structure, geometry optimization with low precision has been executed to perform a preliminary optimization of the atomic structure. The output for this calculations is available in the files 0.CONTCAR, 0.OUTCAR, rlx1.out. 2. Using the atomic structure resulting from the preliminary geometry optimization, a second geometry optimization has been performed using normal precision. The output for this calculations is available in the files CONTCAR, OUTCAR, rlx2.out, vaspout.h5, and vasprun.xml. Cases 1-10 have been run without generating the file 'vaspout.h5'. Every chemical composition sampled across the composition range in the dataset has its own directory. The convention used to name the directories for binary alloys is AXBY, where A and B refer to the constituents, whereas X and Y are positive integers that represent the number of atoms for each constituent and their values still sum up to 128. Each atomic structure associated with a specific chemical composition has its own sub-directory within the directory of the corresponding chemical composition. The sub-directories for each atomic structure for each chemical composition are named 'case-*', where * is a positive integer that spans all the values from 1 through 100, extremes included. The files contained in each sub-directory 'case-*' for each atomic structure are as follows: FILES contained in each subdirectory with name case-N where N ranges between 11 and 100, extremes included: 1. INCAR: input file that contains various parameters and settings for controlling the behavior of the electronic structure calculations 2. KPOINTS: input file that specifies the Bloch vectors (k points) used to sample the Brillouin zone 3. 0.POSCAR: input file that defines the atomic structure of a system 4. 0.CONTCAR: output file that provides the atomic positions and cell parameters after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 5. 0.OUTCAR: output file that contains detailed information about the progress of a calculation after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 6. rlx1.out: file with diagnostic information about the execution of the first geometry optimization with precision variable set to PREC=Low in the INCAR file 7. POSCAR: input file that defines the atomic structure of a system after the first geometry optimization has been run at low precision. This represents the input for the second geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 8. CONTCAR: output file that provides the atomic positions and cell parameters after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 9. OUTCAR: output file that contains detailed information about the progress of a calculation after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 10. rlx2.out: file with diagnostic information about the execution of the second geometry optimization with precision variable set to PREC=Normal in the INCAR file 11. vaspout.h5: hierarchical HDF5 file containing the inputs and outputs of a VASP calculation. To analyze the data in this file we recommend using py4vasp. This file is only produced if the VASP version used is compiled with HDF5 support 12. vasprun.xml: contains similar information to OUTCAR, but in an xml format. Subdirectories with name case-N, where N ranges between 1 and 10 (extremes included) contain all the files listed above except 'vaspout.h5'. Subdirectories with name case-N, where N ranges between 41 and 60 (extremes included), contain a duplicate copy of the files listed above except for KPOINTS. The names of the duplicate files end with -bis, and correspond to a second VASP calculation that has converged to a different optimized geometry. This research is sponsored by the Artificial Intelligence Initiative as part of the Laboratory Directed Research and Development (LDRD) Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725. This work used resources of the Oak Ridge Leadership Computing Facility, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725, under Directorate Discretionary awards MAT025 (Materials Science) and LRN026 (Machine Learning), and INCITE award MAT201. This work also used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, under award ERCAP0025216. REFERENCES (1) Kresse, G. and Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. review B 47, 558 (1993). (2) Kresse, G. and Hafner, J. Ab initio molecular-dynamics simulation of the liquid-metal-amorphous-semiconductor transition in germanium. Phys. Rev. B 49, 14251 (1994) (3) Kresse, G. and Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. materials science 6, 15-50 (1996) (4) Kresse, G. and Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. review B 54, 11169 (1996) (5) Kresse, G. and Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. review b 59, 1758 (1999)

36 MATERIALS SCIENCE↗
DOE OSTI2025

Comparison of removal and spatial mark‐resight models for estimating wild pig density

Density estimation is critical to effectively manage invasive species and elucidate areas of highest concern. For wild pigs (Sus scrofa), the ability to estimate density is complicated because of their variable home range sizes and social structure. Common methods for estimating density (e.g., mark-recapture) may be unsuitable in management applications because additional data needs to be collected before and after management. Removal models offer a suitable alternative to estimate density changes following management and can be applied broadly across areas where management of wild pigs is ongoing. We collected wild pig removal and camera trap data from 25 private properties ranging in size from approximately 0.5 km 2 to 95 km 2 across 3 ecoregions in South Carolina, USA, from 2020–2023. We compared factors affecting consistency and precision of property-level density estimates between removal and spatial mark-resight (SMR) models. In general, excluding 1 large outlier, density estimates from removal models were between 0.60 and 15.85 wild pigs/km 2 (median = 5.34) with a median coefficient of variation (CV) of 0.76 and 95% confidence intervals for the CV between 0.70 and 0.94. Similarly, excluding 1 large outlier, density estimates from SMR were between 0.22 and 30.97 wild pigs/km 2 (median = 5.48) with a median CV of 0.39 and 95% confidence intervals for the CV between 0.38 and 1.20. We found the precision of removal models was affected primarily by the number of wild pigs dispatched in the removal period (3 months) and the ecoregion in which they were removed. None of the covariates, including the number of recaptures (a corresponding measure of sample size), influenced precision of the SMR models, although recaptures did influence the density estimates. At the individual property level, density estimates from our 2 estimators were dissimilar from each other in approximately 80% of instances, although none of the covariates we examined influenced dissimilarity. Our results provide unique insight into how sample size affects density estimates using 2 common methods and into novel SMR models that incorporate both marked and unmarked detections. In addition, the density estimates in this study can be used as a reference for wild pig densities in common land cover types throughout the southeastern United States.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Quantifying replication through repeated analysis of UVM-A, a liquid reference material for cosmogenic 10 Be and 26 Al studies

In this study, in-situ produced cosmogenic nuclide sample preparation and analysis is a complicated, multi-step process with numerous possible sources of error, many of which have not been robustly quantified. Here, we use a liquid reference material (UVM-A) to test whether the analytic precision associated with individual isotopic ratios (n = 96) measured at two Accelerator Mass Spectrometry facilities (Lawrence Livermore National Laboratory and Purdue Rare Isotope Measurement Laboratory) accurately represents the range of values determined for aliquots prepared in a single laboratory over a period of five years. We find that 10 Be/ 9 Be ratios measured at the different accelerator facilities (n = 26 and n = 70) have statistically indistinguishable central tendencies, matching to within 0.1 %. Based on this large dataset, we suggest preliminary consensus values for UVM-A of 1.45 ± 0.06 x 10 -13 for 10 Be/ 9 Be (mean, one standard deviation, n = 96) and 4.47 ± 0.22 x 10 -13 for 26 Al/ 27 Al (mean, one standard deviation, n = 27). For both 10 Be/ 9 Be and 26 Al/ 27 Al, the relative standard deviations of the measured ratios are similar to the reported analytic uncertainties of sample measurement, suggesting that sample preparation introduced little if any additional scatter beyond the uncertainty of isotopic analysis. This dataset demonstrates that robust sample preparation and measurement can generate isotope ratio data reproducible at the level of counting statistics.

58 GEOSCIENCES↗
DOE OSTI2026

Sampling off-axis neutrino fluxes with the short-baseline near detector

The short-baseline near detector (SBND), the near detector in the short-baseline neutrino program at Fermi National Accelerator Laboratory, is located just 110 m from the booster neutrino beam target. Thanks to this close proximity, relative to its 4 m × 4 m front face, neutrinos enter SBND over a range of angles from 0° to approximately 1.6°, enabling the detector to sample variations in the neutrino flux as a function of the angle—a technique known as precision reaction-independent spectrum measurement (PRISM), referred to here as SBND-PRISM. In this paper, we show how muon- and electron-neutrino fluxes vary as a function of the neutrino beam axis angle and how this can be exploited to expand the physics potential of SBND. We make use of a model that predicts an angle-dependent electron-neutrino excess signal to illustrate this effect, such as 𝜈 𝜇 → 𝜈 𝑒 oscillations. We present how SBND-PRISM provides a method to add robustness against uncertainties in cross-section modeling and, more generally, uncertainties that do not depend on the spatial position of neutrino interaction inside the detector. The fluxes, along with their associated covariance matrices, are made publicly available with this publication.

Abratenko, P. [Tufts University]↗
DOE OSTI2023

A Physics-Based Data-Driven Approach for Modeling of Environmental Degradation in Elastomers

Abstract Elastomers are now commonly used in a number of industries, including aerospace, structure, transportation, shipbuilding, and automotive, due to their excellent workability, formability, and flexibility. During their activity, elastomers are subjected to harsh environmental conditions, which decreases their resilience. False predictions made early in their lives can have major financial and environmental implications. Elastomers’ performance and properties, such as strength, durability, and density, are influenced by chemical changes in these materials, known as degradation, which occurs over time. This process can alter the morphology of a polymer matrix as well as cause chain scission and cross-linking, resulting in different behaviors than that of the unaged material. To demonstrate the effect of thermaloxidative aging on the mechanical behavior of elastomers, several experimental and theoretical models have been proposed. In view of the large volume of experimental data available on micro-structural evolution in the course of aging, we propose a physics-based data-driven approach to overcome the shortcomings of both phenomenological and micro-mechanical models. This work presents a novel thermodynamically consistent, multiagent machine-learned model for predicting the constitutive behavior of cross-linked elastomers during environmental aging, such as thermo-oxidative and hydrolytic aging for various states of deformation. Single mechanism degradation changes the polymer matrix over time where it is causing chain scission, reduction of cross-links, and morphology change. To capture the idealized Mullins effect and permanent set due to the effect of single aging mechanisms on nonlinear mechanical responses of elastomers, we propose a data-driven model for simulating inelastic elements in a polymer matrix. By using a sequential order reduction, we were able to reduce the 3D stress-strain tensor mapping problem to a small number of super-constrained 1D mapping problems. To systematically classify such mapping problems into a few categories, an assembly of multiple replicated conditional neural network learning agents (L-agents) is used based on our recent work. Each category is represented by a different type of agent. The effect of deformation history, aging time, and aging temperature is captured by this model. The model is validated using a broad collection of data, ranging from our experimental results to data from the literature. In addition, thermodynamic consistency and frame independence are investigated. The most significant achievements of this model are its precision, simplicity, and prediction of inelasticity under various states of deformation. The model’s accuracy and simplicity make it a good option for commercial and industrial applications. Conveniently, due to the model modular nature, it can be expanded in the future to include viscoelasticity and non-isotropic formation for better precision.

Ghaderi, Aref↗
DOE OSTI2025

Automated tuning of a ring-assisted MZI-based interleaver for Kerr frequency combs

We demonstrate a compact ring-assisted Mach–Zehnder interferometer (RAMZI)-based silicon photonic interleaver with a 400 GHz free spectral range (FSR), featuring flat passbands exceeding a spectral range of 50 nm. Additionally, we introduce a novel, to the best of our knowledge, add-on structure and tuning method enabling automated compensation for fabrication imperfections, precise shaping of the RAMZI flat-top passbands, and alignment with Kerr comb lines. Experimental results have shown successful interleaving of eight channels of distributed-feedback (DFB) lasers as well as a 200 GHz Kerr comb, both achieving an extinction ratio of approximately 20 dB.

Wang, Songli (ORCID:0009000626380795)↗
DOE OSTI2020

Modeling Tree Foliage for Microwave Radar Transparency Study

The motivation for this report is to discuss and present some realistic tree models employed in computational electromagnetics (EM) simulations to study foliage penetration (FOPEN) at Ku-band. The detail obtained in these trees is unprecedented in FOPEN modeling since many studies in this area focus on lower frequencies where precise tree parameters are not required due to the associated large wavelengths relative to the tree dimensions. The focus of this study is in the Ku-band range where the wavelength is notably smaller and the details of the trees have more of an influence on EM waves (i.e. scattering, attenuating, reflecting, diffracting etc.). Therefore, explicit tree parameters are modeled. Also, moderate foliage is of most interest because with less dense foliage t here is a higher percentage of Ku-band transmission. The EM wave and foliage interaction s are simulated with the computational electromagnetics (CEM) Altair FEKO software. The realistic tree model s implemented for simulations are created in the computer-aided design (CAD) software Arbaro and the module CADFEKO that is offered in FEKO. Details of these tree models are provided, and EM simulation results will be discussed in a follow-on report

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

PIONEER: Studies of Rare Pion Decays

A next-generation rare pion decay experiment, PIONEER, is strongly motivated by several inconsistencies between Standard Model (SM) predictions and data pointing towards the potential violation of lepton flavor universality. It will probe non-SM explanations of these anomalies through sensitivity to quantum effects of new particles even if their masses are at very high scales. Measurement of the charged-pion branching ratio to electrons vs. muons $R_{e/\mu}$ is extremely sensitive to new physics effects. At present, the SM prediction for $R_{e/\mu}$ is known to 1 part in $10^4$, which is 15 times more precise than the current experimental result. An experiment reaching the theoretical accuracy will test lepton flavor universality at an unprecedented level, probing mass scales up to the PeV range. Measurement of pion beta decay, $\pi^+\to \pi^0 e^+ \nu (\gamma)$, with 3 to 10-fold improvement in sensitivity, will determine $V_{ud}$ in a theoretically pristine manner and test CKM unitarity, which is very important in light of the recently emerged tensions. In addition, various exotic rare decays involving sterile neutrinos and axions will be searched for with unprecedented sensitivity. The experiment design benefits from experience with the recent PIENU and PEN experiments at TRIUMF and the Paul Scherrer Institut (PSI). Excellent energy and time resolutions, greatly increased calorimeter depth, high-speed detector and electronics response, large solid angle coverage, and complete event reconstruction are all critical aspects of the approach. The PIONEER experiment design includes a 3$\pi$ sr 25 radiation length calorimeter, a segmented low gain avalanche detector stopping target, a positron tracker, and other detectors. Using intense pion beams, and state-of-the-art instrumentation and computational resources, the experiments can be performed at the PSI ring cyclotron.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Super-resolution surface slope metrology of x-ray mirrors

We present experimental, analytical, and numerical methods developed for reconstruction (deconvolution) of one-dimensional (1D) surface slope profiles over the spatial frequency range where the raw data are significantly perturbed due to the limited resolution of the measurement instrument. We characterize the spatial resolution properties of a profiler with the instrument's transfer function (ITF). To precisely measure the ITF, we apply a recently developed method utilizing test surfaces with 1D linear chirped height profiles of constant slope amplitude. Based on the results of the ITF calibration, we determine parameters of an analytical model for the ITF that is used in the original reconstruction software. Here, we treat surface slope metrology data obtained with the Optical Surface Measuring System (OSMS), using as a sensor an electronic autocollimator (AC) ELCOMAT-3000. The spatial resolution of the OSMS is limited by the size of the AC light-beam-collimating aperture. For the purposes of this investigation, the OSMS is equipped with a circular aperture with a diameter of 2.5 mm. This is a typical arrangement of most AC-based slope profilers developed for surface slope metrology of state-of-the-art x-ray mirrors. Using the example of surface slope metrology of two state-of-the-art elliptically shaped x-ray focusing mirrors, we demonstrate that the developed data reconstruction procedure allows us to significantly improve the accuracy of surface slope metrology with the OSMS over the spatial wavelength range from ~1.6 mm to 7 mm. Thus, the amplitude of the quasi-periodic error characteristic of the deterministic polishing process used appears to be higher by a factor of~2 than is apparent from the rough metrology data. Underestimation of the surface slope errors in this spatial wavelength range can lead to serious errors in the expected performance of x-ray mirrors in synchrotron beamlines, especially at modern light sources utilizing coherent x rays, where the perturbations can lead to increased speckle-like intensity variation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Improving the Precision of First-Principles Calculation of Parton Physics from Lattice Quantum Chromodynamics

Large momentum effective theory (LaMET) provides a general framework for computing the multi-dimensional partonic structure of the proton from first principles using lattice quantum chromodynamics (QCD). In this effective field theory approach, LaMET predicts parton distributions through a power expansion and perturbative matching of a class of Euclidean observables—quasi-distributions—evaluated at large proton momenta. Recent advances in lattice renormalization, such as the hybrid scheme with leading renormalon resummation, together with improved matching kernel that incorporates higher-loop corrections and resummations, have enhanced both the perturbative and power accuracy of LaMET, enabling a reliable quantification of theoretical uncertainties. Moreover, the Coulomb-gauge correlator approach further simplifies lattice analyses and improves the precision of transverse-momentum-dependent structures, particularly in the non-perturbative region. State-of-the-art LaMET calculations have already yielded certain parton observables with important phenomenological impact. In addition, the recently proposed kinematically enhanced lattice interpolation operators promise access to unprecedented proton momenta with greatly improved signal-to-noise ratios, which will extend the range of LaMET prediction and further suppress the power corrections. The remaining challenges, such as controlling excited-state contamination in lattice matrix elements and extracting gluonic distributions, are expected to benefit from emerging lattice techniques for ground-state isolation and noise reduction. Thus, lattice QCD studies of parton physics have entered an exciting stage of precision control and systematic improvement, which will have a broader impact for nuclear and particle experiments.

Zhao, Yong [Argonne National Laboratory (ANL), Arg↗
DOE OSTI2022

Monitoring the propagation of mechanical discontinuity using data-driven causal discovery and supervised learning

Mechanical wave transmission through a material is influenced by the mechanical discontinuity in the material. The propagation of embedded discontinuities can be monitored by analyzing the wave-transmission measurements recorded by a multipoint sensor system placed on the surface of the material. The proposed workflow monitors the propagation of mechanical discontinuity through three stages, namely initial, intermediate, and final stages, by using supervised learning followed by data-driven causal discovery. To the end, the workflow processes the multipoint waveform measurements resulting from a single impulse source, while considering the effects of wave attenuation, dispersion and multiple wave-propagation modes due to the discontinuity and material boundaries. Among various feature reduction techniques ranging from decomposition methods to manifold approximation methods, the features derived based on statistical parameterizations of the measured waveforms lead to reliable monitoring that is robust to changes in precision, resolution, and signal-to-noise ratio of the multipoint sensor measurements. The numbers of zero-crossing, negative-turning, and positive turning in the waveforms are the strongest causal signatures of the propagation of mechanical discontinuity. Higher order moments of the waveforms, such as variance, skewness and kurtosis, are also strong causal signatures of the propagation. Finally, the newly discovered causal signatures confirm that the statistical correlations and conventional feature rankings are not always statistically significant indicators of causality.

42 ENGINEERING↗
DOE OSTI2025

Prototype acoustic positioning system for the Pacific Ocean Neutrino Experiment

We present the design and initial performance characterization of the prototype acoustic positioning system intended for the Pacific Ocean Neutrino Experiment. It comprises novel piezo-acoustic receivers with dedicated filtering- and amplification electronics installed in P-ONE instruments and is complemented by a commercial system comprised of cabled and autonomous acoustic pingers for sub-sea installation manufactured by Sonardyne Ltd. We performed an in-depth characterization of the acoustic receiver electronics and their acoustic sensitivity when integrated into P-ONE pressure housings. These show absolute sensitivities of up to -125 dB re V2/μPa2 in a frequency range of 10–40 kHz. We furthermore conducted a positioning measurement campaign in the ocean by deploying three autonomous acoustic pingers on the seafloor, as well as a cabled acoustic interrogator and a P-ONE prototype module deployed from a ship. Using a simple peak-finding detection algorithm, we observe high accuracy in the tracking of relative ranging times at approximately 230–280 μs at distances of up to 1600 m, which is sufficient for positioning detectors in a cubic-kilometer detector and which can be further improved with more involved detection algorithms. The tracking accuracy is further confirmed by independent ranging of the Sonardyne system and closely follows the ship's drift in the wind measured by GPS. The absolute positioning shows the same tracking accuracy with its absolute precision only limited by the large uncertainties of the deployed pinger positions on the seafloor.

Data analysis↗
DOE OSTI2020

The clustering of DESI-like luminous red galaxies using photometric redshifts

ABSTRACT We present measurements of the redshift-dependent clustering of a DESI-like luminous red galaxy (LRG) sample selected from the Legacy Survey imaging data set, and use the halo occupation distribution (HOD) framework to fit the clustering signal. The photometric LRG sample in this study contains 2.7 million objects over the redshift range of 0.4 < z < 0.9 over 5655 deg2. We have developed new photometric redshift (photo-z) estimates using the Legacy Survey DECam and WISE photometry, with σNMAD = 0.02 precision for LRGs. We compute the projected correlation function using new methods that maximize signal-to-noise ratio while incorporating redshift uncertainties. We present a novel algorithm for dividing irregular survey geometries into equal-area patches for jackknife resampling. For a five-parameter HOD model fit using the MultiDark halo catalogue, we find that there is little evolution in HOD parameters except at the highest redshifts. The inferred large-scale structure bias is largely consistent with constant clustering amplitude over time. In an appendix, we explore limitations of Markov chain Monte Carlo fitting using stochastic likelihood estimates resulting from applying HOD methods to N-body catalogues, and present a new technique for finding best-fitting parameters in this situation. Accompanying this paper, we have released the Photometric Redshifts for the Legacy Surveys catalogue of photo-z’s obtained by applying the methods used in this work to the full Legacy Survey Data Release 8 data set. This catalogue provides accurate photometric redshifts for objects with z < 21 over more than 16 000 deg2 of sky.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Tunneling spectroscopy of c -axis epitaxial cuprate junctions

Atomically precise epitaxial structures are unique systems for tunneling spectroscopy that minimize extrinsic effects of disorder. We present a systematic tunneling spectroscopy study, over a broad doping, temperature, and bias range, in epitaxial c-axis La 2-x Sr x CuO 4 /La 2 CuO 4 /La 2-x Sr x CuO 4 heterostructures. The behavior of these superconductor/insulator/superconductor (SIS) devices is unusual. Down to 20 mK there is complete suppression of c-axis Josephson critical current with a barrier of only 2 nm of La 2 CuO 4 , and the zero-bias conductance remains at 20–30% of the normal-state conductance, implying a substantial population of in-gap states. Tunneling spectra show greatly suppressed coherence peaks. Furthermore, as the temperature is raised, the superconducting gap fills in rather than closing at T c . For all doping levels, the spectra show an inelastic tunneling feature at ~80 meV, suppressed as T exceeds T c . These nominally simple epitaxial cuprate junctions deviate markedly from expectations based on the standard Bardeen-Cooper-Schrieffer theory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Observation of the distribution of nuclear magnetization in a molecule

Precise experimental control and interrogation of molecules and calculations of their structure are enriching the investigation of nuclear and particle physics phenomena. Molecules containing heavy, octupole-deformed nuclei, such as radium, are of particular interest. Here, we report precision laser spectroscopy measurements and theoretical calculations of the structure of the radioactive radium monofluoride molecule 225 Ra 19 F. Our results reveal fine details of the short-range electron-nucleus interaction, indicating the high sensitivity of this molecule to the distribution of magnetization, within the radium nucleus. Here, these results provide a stringent test of the description of the electronic wave function inside the nuclear volume, highlighting the suitability of these molecules for investigating subatomic phenomena.

Nuclear structure↗
DOE OSTI2021

Methods—Design Guidelines for Tubular Flow-through Electrodes for Use in Electroanalytical Studies of Redox Reaction Kinetics

The tubular flow-through electrode (FTE) is a facile electroanalytical tool for investigating electrochemical reaction kinetics; however, its suitability for this purpose requires careful design and operation under conditions that guarantee uniform current distribution. In this perspective article, we provide a scaling analysis of the transport and reaction processes within a tubular FTE leading to quantitative guidelines for the FTE design and operation. Two dimensionless parameters (classical Wagner number Wa I and modified Wagner number incorporating the effect of mass transport Wa II ) are utilized to compare the magnitudes of the ohmic, activation and transport resistances of the tubular FTE, and to quantify its current distribution uniformity. With the aid of analytical modeling of the current distribution, optimal ranges for these two dimensionless parameters are defined so as to ascertain uniform current distribution. Application of these guidelines to a graphite tubular FTE is shown to enable the precise determination of the charge-transfer kinetics of the ferri/ferrocyanide redox reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Materials challenges for quantum technologies based on color centers in diamond

Emerging quantum technologies require precise control over quantum systems of increasing complexity. Defects in diamond, particularly the negatively charged nitrogen-vacancy center, are a promising platform with the potential to enable technologies ranging from ultra-sensitive nanoscale quantum sensors, to quantum repeaters for long distance quantum networks, to simulators of complex dynamical processes in many-body quantum systems, to scalable quantum computers. While these advances are due in large part to the distinct material properties of diamond, the uniqueness of this material also presents difficulties, and there is a growing need for novel materials science techniques for characterization, growth, defect control, and fabrication dedicated to realizing quantum applications with diamond. In this article we identify and discuss the major materials science challenges and opportunities associated with diamond quantum technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Beam correction for multi-pass arcs in FFA@CEBAF: status update

This work examines the multi-pass steering of six electron beams in an FFA arc ranging from approximately 10.5 GeV to 22 GeV. Shown here is an algorithm based on singular value decomposition (SVD) to successfully steer all six beams through the arc given precise knowledge of all beam positions at each of one hundred and one diagnostic locations with one hundred individual corrector magnets: that is successive application of SVD to different 100 × 101 response matrices—one for each beam energy. Further, a machine learning scheme is developed which only requires knowledge of the energy-averaged beam position at each location to provide equivalent steering. Extension of this scheme to other beam optics quantities as well as transverse and longitudinal coupling is explored.

Accelerator Physics↗