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At least 703 records · Page 39

Two-Tone Spectroscopy of 3D SRF Cavities to Understand Two-Level System Loss

So-called two-level system (TLS) defects are among the most detrimental sources of loss and decoherence in superconducting quantum devices, and their microscopic nature still poorly understood. We develop a two-tone spectroscopy technique to characterize the spectral line width of TLS. This knowledge will help to distinguishes various types of TLS defects. In our experiments we use the fundamental TM010 pass band modes of 9-cell elliptical SRF cavities to probe spectral properties of TLS in native niobium oxide formed on the inside walls of the resonator. We pump one of the modes (4¿/9 through 8¿/9) with continuous high-power to saturate TLSs that couple to this frequency, and we probe the Q-factor of the ¿-mode. We observe increase of the quality factor of the probed ¿-mode when one of the neighboring modes is pumped. Extremely high quality factors of the pass band modes and their relative proximity in the frequency space allow us to estimate the width of the spectral hole burned in the TLS bath absorption spectrum which is related to the line spectral width of the TLS defects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Collective Energy Transport of Excitons in Two-dimensional Materials

Electronic thermal transport and thermoelectric measurements are pursued in this project to obtain unique insights into the unusual collective energy transport behaviors in two-dimensional (2D) heterostructures. Electronic thermal transport and thermoelectric measurements are essential techniques for characterizing bulk superconductors by probing the heat-carrying quasi-particles. Thermoelectric and electronic thermal transport measurements are expanded in this work beyond bulk systems to probe interactions among electrons, holes, and phonons in 2D heterostructures. In one experiment, a microbridge platform is advanced to demonstrate field-effect resistive-thermometry measurements of the electronic thermal conductivity of graphene heterostructures. Together with first principles theoretical calculations and analytical models, the experimental results suggest that tunable electron coupling with flexural phonons provides a knob to control quantum matters in graphene heterostructures with broken reflection symmetry. In another experiment, the Seebeck coefficient (S) is measured to probe interlayer interactions in electron-hole bilayers that are predicted to give rise to the emergence of a variety of correlated states. As a measure of the entropy, the measured S reveals the signature of electric injection of interlayer excitons in transition metal dichalcogenide (TMD) structures.

36 MATERIALS SCIENCE↗

Addressing Experimental Challenges in Probing Dark Energy with Accuracy and Precision with the Rubin Observatory Legacy Survey of Space & Time (LSST)

With support from this award, the Stanford group under the leadership of PI Patricia Burchat focused on pixel-level algorithms that are key to the investigation of dark energy with the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The work was carried out through strong engagement in the DOE-supported LSST Dark Energy Science Collaboration (DESC), for which the PI served as Deputy Spokesperson (07/2019 - 07/2021) and Technical Coordinator (07/2021 - 07/2023). Members of the Burchat group are Full DESC members and are among scientists who have been accepted to join the Rubin Observatory System Integration, Test, and Commissioning (SIT-Com) effort. The specific intellectual focus of the group was the optimization of gravitational lensing as a probe of the evolution of the distribution of dark matter in space and time to learn about the nature of dark energy. The Stanford group pursued an integrated research program to understand in detail, and then remediate or calibrate, systematic effects that could limit the sensitivity of the LSST to cosmic shear as a dark energy probe -- particularly those related to our understanding of the atmospheric point spread function (PSF), challenges associated with blended galaxy images, and impacts of residual camera artifacts. Key to this work was developing, enhancing, and validating the fidelity of simulations that play a key role in the development of our understanding of subtle systematic biases and then using these simulations to develop techniques to characterize and mitigate biases, and associated algorithms for implementation in the LSST or DESC science pipelines. The group’s work included contributions to the open-source GalSim simulation package, which is widely used in the community; simulations and studies of spatial correlations of atmospheric PSFs; studies of temporal correlations of the atmospheric PSF; impacts of chromatic PSFs on cosmic shear calibration; continued studies of anisotropic Gaussian process interpolation of PSF models across the focal plane; and measuring and mitigating impacts of residual camera artifacts on cosmic shear. A primary impact of this work is that it increases the scientific discovery potential of the DOE and NSF investments in the Rubin Observatory Legacy Survey of Space \& Time, by addressing challenges in interpreting astronomical images through more accurate descriptions of the blurring of images due to the atmosphere. Specifically, this work impacts our ability to understand the fundamental nature of dark energy.

Burchat, Patricia Rose↗

Weak Gravitational Lensing around Low Surface Brightness Galaxies in the DES Year 3 Data

We present galaxy-galaxy lensing measurements using a sample of low surface brightness galaxies (LSBGs) drawn from the Dark Energy Survey Year 3 (Y3) data as lenses. LSBGs are diffuse galaxies with a surface brightness dimmer than the ambient night sky. These dark-matter-dominated objects are intriguing due to potentially unusual formation channels that lead to their diffuse stellar component. Given the faintness of LSBGs, using standard observational techniques to characterize their total masses proves challenging. Weak gravitational lensing, which is less sensitive to the stellar component of galaxies, could be a promising avenue to estimate the masses of LSBGs. Our LSBG sample consists of 23,790 galaxies separated into red and blue color types at g - i ≥ 0.60 and g - i < 0.60 , respectively. Combined with the DES Y3 shear catalog, we measure the tangential shear around these LSBGs and find signal-to-noise ratios of 6.67 for the red sample, 2.17 for the blue sample, and 5.30 for the full sample. We use the clustering redshifts method to obtain redshift distributions for the red and blue LSBG samples. Assuming all red LSBGs are satellites, we fit a simple model to the measurements and estimate the host halo mass of these LSBGs to be log(M host /M ⊙ ) = $12.98^{+0.10}_{-0.11}$. We place a 95% upper bound on the subhalo mass at log(M sub /M ⊙ ) < 11.51. By contrast, we assume the blue LSBGs are centrals, and place a 95% upper bound on the halo mass at log(M host /M ⊙ ) < 11.84. We find that the stellar-to-halo mass ratio of the LSBG samples is consistent with that of the general galaxy population. This work illustrates the viability of using weak gravitational lensing to constrain the halo masses of LSBGs.

79 ASTRONOMY AND ASTROPHYSICS↗

Synthesis and Physical Properties of NbMnP Single Crystals

Single crystalline NbMnP was grown by the high-temperature solution growth technique and characterized by room temperature X-ray diffraction, temperature- and field-dependent magnetization, temperature-dependent resistivity, and heat capacity measurements. NbMnP is isostructural to TiNiSi with the space group of Pnma. Physical characterizations suggest that NbMnP is metallic and goes through an anti-ferromagnet transition at around 230 K with a weak magnetic anisotropy. A small ferromagnetic component is found to be perpendicular to [010].

Zhao, Jianda↗

Method and apparatus for evaluating superconducting tunnel junction detector noise versus bias voltage

A technique for characterizing the noise behavior of a superconducting tunnel junction (STJ) detector as a function of its applied bias voltage Vb by stepping the STJ's bias voltage across a predetermined range and, at each applied bias, making multiple measurements of the detector's current, calculating their mean and their standard deviation from their mean, and using this standard deviation as a measure of the STJ detector's noise at that applied bias. Because the method is readily executed under computer control, it is particularly useful when large numbers of STJ detectors require biasing, as in STJ detector arrays In a preferred implementation, the STJ is measured under computer control by attaching it to a digital spectrometer comprising a digital x-ray processor (DXP) coupled to a preamplifier that can set the STJ's bias voltage Vb using a digital-to-analog converter (DAC) controlled by the DXP.

Warburton, William K.↗

Reduced Order Models Generation for HTGRs Pebble Shuffling Procedure Optimization Studies

This report provides an initial study for producing reduced-order models (ROMs) of pebble-bed high temperature gas reactor (HTGR) models for the purposes of design optimization. As an initial study, this work is meant to be exploratory---identifying useful workflows and methods for ROM generation---and not meant to be a catch-all analysis of HTGR ROM generation and usage for optimization. This report summarizes three tasks performed in Fiscal Year 2022: 1) the creation of HTGR model, 2) the sensitivity analysis of model design parameters, and 3) an introduction to ROM generation techniques. The representative HTGR model created in this work is a multiphysics equilibrium-core using the BlueCRAB (comprehensive reactor analysis bundle) reactor analysis application, coupling four physical phenomena: neutronics, streamline depletion, porous flow thermal hydraulics, and pebble heat conduction. Part of the model creation was identifying some design parameters and quantities of interest that are relevant in an optimization analysis and adjustable in the model. The sensitivity analysis utilized a polynomial chaos expansion methodology to compute global sensitivity metrics. This analysis showed that thermal hydraulics parameters and quantities of interest had a relatively small impact on simulation results. Finally, the ROM generation work involved exploring three different ROM methodologies: polynomial regression, a Gaussian process, and artificial neural networks. Using a cross-validation technique to characterize ROM performance, the Gaussian process and single-layer artificial neural networks showed the most promising results. Overall, this study was insightful and the lessons learned will be invaluable for the eventual development of an HTGR design optimization workflow.

97 MATHEMATICS AND COMPUTING↗

Studying single-electron traps in newly fabricated Skipper-CCDs for the Oscura experiment using the pocket-pumping technique

Understanding and characterizing very low-energy (⁠ ∼eV) background sources is a must in rare-event searches. Oscura, an experiment aiming to probe electron recoils from sub-GeV dark matter using a 10 kg skipper-CCD detector, has recently fabricated its first two batches of sensors. In this work, we present the characterization of defects/contaminants identified in the buried-channel region of these newly fabricated skipper-CCDs. These defects/contaminants produce deferred charge from trap emission in the images next to particle tracks, which can be spatially resolved due to the sub-electron resolution achieved with these sensors. Using the trap-pumping technique, we measured the energy and cross section associated with these traps in three Oscura prototype sensors from different fabrication batches which underwent different gettering methods during fabrication. Results suggest that the type of defects/contaminants is more closely linked to the fabrication batch rather than to the gettering method used. The exposure-dependent single-electron rate (SER) of one of these sensors was measured ∼100 m underground, yielding (1.8±0.3)×10−3e−/pix/day at 131 K. The impact of the identified traps on the measured exposure-dependent SER is evaluated via a Monte Carlo simulation. Results suggest that the exposure-dependent SER of Oscura prototype sensors would be lower in lower background environments as expected.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

An insight into microscopy and analytical techniques for morphological, structural, chemical, and thermal characterization of cellulose

Cellulose obtained from plants is a bio-polysaccharide and the most abundant organic polymer on earth that has immense household and industrial applications. Hence, the characterization of cellulose is important for determining its appropriate applications. In this article, we review the characterization of cellulose morphology, surface topography using microscopic techniques including optical microscopy, transmission electron microscopy, scanning electron microscopy, and atomic force microscopy. Additionally, other physicochemical characteristics like crystallinity, chemical composition, and thermal properties are studied using techniques including X-ray diffraction, Fourier transform infrared, Raman spectroscopy, nuclear magnetic resonance, differential scanning calorimetry, and thermogravimetric analysis. This review may contribute to the development of using cellulose as a low-cost raw material with anticipated physicochemical properties.

59 BASIC BIOLOGICAL SCIENCES↗

Accelerator Physics at NSLS-II: Research Accomplishments in 2023

NSLS-II accelerator physicists provided operation support for user operations and machine start-ups, carried out routine lattice characterization, and produced regular reports on beam dynamics. The commissioning of a superconducting wiggler for the HEX beamline is complete, and the wiggler effects on beam dynamics have been studied. A Facility Improvement Project for absolute lattice characterization has been approved and funded. We implemented and tested a new orbit-based technique of lattice characterization and correction. We developed a theory to calculate the beam-induced power in ceramic vacuum chambers and a new convergence map technique for nonlinear lattice characterization. We continued working on the NSLS-II upgrade including lattice development, commissioning a low-energy complex bend prototype, analyzing beam sensitivity to various errors, implementing higher-harmonic RF cavities, studying collective effects, and assessing FEL options. We also supported lattice optimization and beam diagnostics development for the EIC project. Main research accomplishments achieved in 2023, are summarized in this report.

43 PARTICLE ACCELERATORS↗

Ice processes in Antarctica: identification via multi-wavelength active and passive measurements and model evaluation (Final Report)

This project is based on new multi-frequency radar observations collected during the AWARE field campaign in 2016 at McMurdo Station by the ARM Mobile facility. Three scientific goals have been achieved. We have developed ice and mixed-phase cloud microphysics retrievals from multi-wavelength radar observations and ancillary observations, generally applicable at ARM sites. These technique generally better characterize the size of the ice crystals, their equivalent water content and the degree of riming better than using single wavelength techniques. We have characterized ice microphysical properties and ice processes via multi-frequency signatures. We have identified a unique mode in the McMurdo dataset appearing at quite cold temperature that we have attributed to riming processes. Triple frequency radar measurements unfortunately were available only for a short period but our work lays the foundation for building climatological and testing their replicability in models. Simultaneously case studies from the AWARE campaign have been exploited to evaluate and improve the NASA GISS ModelE3 climate model, including selection of case studies for combined goals of (i) running side-by-side using large-eddy simulation (LES) and ModelE3 in single-column model (SCM) mode and (ii) fingerprinting cloud processes in multi-wavelength radar observations. The different components of this work have contributed to 15 published papers with two currently under review.

54 ENVIRONMENTAL SCIENCES↗

Field-resolved space–time characterization of few-cycle structured light pulses

Accompanied by the rapid development of ultrafast laser platforms in recent decades, the spatiotemporal manipulation of ultrashort laser pulses has attracted much attention due to the potential for cutting-edge applications of structured light, including optical tweezers, optical communications, super-resolution imaging, time-resolved spectroscopy in molecules and quantum materials, and strong-field physics. Today, techniques capable of characterizing the full spatial, temporal, and polarization state properties of structured light are strongly desired. Here, we demonstrate a technique, termed 3D TIPTOE, for characterizing structured mid-infrared waveforms, which uses only a two-dimensional silicon-based image sensor as both the detector and the nonlinear medium. By combining the advantages of the sub-cycle time resolution afforded by nonlinear excitation and the spatial resolution inherent to the two-dimensional sensor, the 3D TIPTOE technique allows full characterization of structured electric fields, significantly reducing the complexity of detection compared to other techniques. The validity of the technique is established by measuring both few-cycle Bessel–Gaussian pulses and radially polarized femtosecond vector beams.

Liu, Yangyang (ORCID:0000000335205332)↗

An Investigation of Oxides of Tantalum Produced by Pulsed Laser Ablation and Continuous Wave Laser Heating

Recent progress has seen multiple Ta 2 O 5 polymorphs generated by different synthesis techniques. However, discrepancies arise when these polymorphs are produced in widely varying thermodynamic conditions and characterized using different techniques. This work aimed to characterize and compare Ta 2 O 5 particles formed at high and low temperatures using nanosecond pulsed laser ablation (PLA) and continuous wave (CW) laser heating of a local area of tantalum in either air or an 18 O 2 atmosphere. Scanning electron microscopy (SEM) and Raman spectroscopy of the micrometer-sized particles generated by PLA were consistent with either a localized amorphous Ta 2 O 5 phase or a similar, but not identical, crystalline β-Ta 2 O 5 phase. The Raman spectrum of the material formed at the point of CW laser impingement was in good agreement with the previously established ceramic “H-Ta 2 O 5 ” phase. TEM and electron diffraction analysis of these particles indicated the phase structure matched an oxygen-vacated superstructure of monoclinic H-Ta 2 O 5 . Further from the point of laser impingement, CW heating produced particles with a Raman spectrum that matched β-Ta 2 O 5 . We confirmed that the high-temperature ceramic phase characterized in previous work by Raman spectroscopy was the same monoclinic phase characterized in different work by TEM and could be produced by direct laser heating of metal in air.

36 MATERIALS SCIENCE↗

Revealing Local Structures through Machine-Learning-Fused Multimodal Spectroscopy

Atomistic structures of materials offer valuable insights into their functionality. Determining these structures remains a fundamental challenge in materials science, especially for systems with defects. While both experimental and computational methods exist, each has limitations in resolving nanoscale structures. Core-level spectroscopies, such as X-ray absorption (XAS) or electron energy-loss spectroscopies (EELS), have been used to determine the local bonding environment and structure of materials. Recently, machine learning (ML) methods have been applied to extract structural and bonding information from XAS/EELS data. However, frameworks relying solely on a single data stream, defined as characterization data derived from a single element using one technique, are often insufficient because multiple local environments can yield similar spectral features, making it challenging to differentiate between competing structural hypotheses. Here, in this work, we address this challenge by integrating multimodal ab initio simulations, experimental data acquisition, and ML techniques for structure characterization. Our goal is to determine local structures and properties using EELS and XAS data from multiple elements and edges. To showcase our approach, we use various lithium nickel manganese cobalt (NMC) oxide compounds which are used for lithium ion batteries, including those with oxygen vacancies and antisite defects, as the sample material system. We successfully inferred local element content, ranging from lithium to transition metals, with quantitative agreement with experimental data. Beyond local element inference, we find that ML model based on multimodal spectroscopic data is able to determine whether local defects such as oxygen vacancy and antisites are present, a task which is impossible for single mode spectra or other experimental techniques. Furthermore, our framework is able to provide physical interpretability, bridging spectroscopy with the local atomic and electronic structures.

battery↗

LLNL FY22 Aging and Lifetimes Exit Criteria (Milestone 8118, GC#5)

This report introduces a novel characterization tool that can rapidly collect in-situ time-dependent oxide thickness and hydride growth data together with spatial data using while-light interferometry. White-light interferometry is a non-destructive and non-contact optical surface profiling technique for materials characterization that offers excellent lateral and vertical resolution. A depleted uranium sample was used to assess the ability of white-light interferometry to provide quantitative corrosion reaction rates at metal surfaces for by hydriding and oxidation and compare this technique to existing characterization tools for capturing early-stage hydride and oxide growth kinetics.

36 MATERIALS SCIENCE↗