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At least 1,225 records · Page 68

Self-assembled vertically aligned nanocomposite systems integrated on silicon substrate: Progress and future perspectives

Silicon (Si) integration is a critical step for implementing functional oxides into Si-based electronic devices, considering the advantages of low-cost and scalability of Si substrates. In the past decade, self-assembled vertically aligned nanocomposites (VANs) have attracted enormous research interest owing to their unique multifunctionalities and highly tunable physical properties as well as their one-step self-assembly process. Most of the VAN thin films have been reported to grow epitaxially on single crystalline oxide substrates, however, with limited systems reported on Si substrates due to the very large lattice mismatch between oxides and Si lattices. In this review, the current progress for self-assembled VAN systems integrated on a Si substrate is summarized. Buffer layered enabled VAN growth has been proven to be an effective approach for improving the epitaxial quality of oxide-oxide and oxide-metal VAN systems, while direct growth is preferred in nitride-metal VAN systems. Furthermore, the material versatility enables the Si-integrated VAN thin films to exhibit distinct physical properties such as ferromagnetism, ferroelectricity, magnetoresistance, as well as unique optical properties. The review also summarizes the various parameters for tuning the growth morphologies and corresponding properties for the VAN systems, including phase molar ratio, deposition frequency, buffer layers, background pressure, etc. Finally, future perspectives are discussed including new VAN system exploration, physical properties tuning, as well as design and fabrication of Si-based nanoelectronics and nanophotonic devices applications.

36 MATERIALS SCIENCE↗

Fast External Quantum Efficiency Measurements of Photovoltaic Modules

The external quantum efficiency (EQE) or associated spectral response is widely used to evaluate the performance of photovoltaics, light emitting diodes, photodetectors, photodiodes, semiconductor lasers, laser-induced refrigeration of solids etc. For photovoltaic (PV) devices, The EQE is used to determine the spectral mismatch correction that is used to convert a performance measurement from a non-ideal simulator spectrum to a standard spectrum in PV device calibrations. Moreover, EQE can provide important insight into the physics of a PV device. For instance, the EQE shape can be used to infer mechanisms limiting the performance of the device. However, EQE measurements of full-size PV modules remain a challenge in the PV community due to rare availability of reliable module QE measurement tools worldwide and the size and complexity of module architecture that comprises several cells connected in strings (series or/and parallel). Here, we use a customized nondestructive tool made of high-power light emitting diodes to perform high-throughput EQE measurements on PV modules. Circuit simulations show that the measurement system can safely be used to measure both crystalline silicon and thin film-based PV modules with series connected cells without the risk of damage through reverse bias. In addition, EQE mapping combined with electroluminescence show a strong correlation and provide a way to determine both spatial non-uniformity of the spectral response and defects/degradation effects across the module.

PV module↗

Feature Extraction for Pipeline Defects Inspection Based Upon Distributed Acoustic Fiber Optic Sensing Data

Fiber-optic distributed acoustic sensing (DAS) is becoming an increasingly important tool for real-time monitoring of energy and civil infrastructure structural health such as pipelines. We present a systematic theoretical study of the potential for DAS to be directly coupled with guided ultrasonic waves typically used in conventional acoustic non-destructive evaluation (NDE) methods for real-time pipeline health monitoring. We are referring to this innovative new NDE technique as ultrasonic guided wave and optical fiber sensor fusion. In the practical application of DAS coupled with guided ultrasonic waves, the structural design of (1) the specific guided waves excited, (2) the physical installation of the acoustic transducers and the fiber optic sensors, and (3) the functional performance specifications (gauge length, sensitivity, Etc.) of fiber optic DAS have an important influence on overall capabilities of the monitoring system. Meanwhile, physics-based analysis of acoustic waves is still a challenge due to the complex nature of the Lamb wave when it propagates, scatters, and disperses in the presence of structural defects. In this work, we simulate carbon steel pipes relevant for oil and gas pipeline applications with diameters of approximately 6-12” and wall thickness of 0.5” as the objects to be monitored. By establishing and implementing these capabilities, we seek to pursue an in-depth study on structural parameter optimization of DAS network, measurement range, and signal processing with an ultimate goal of increasing the sensitivity and efficacy of DAS to defect identification for various modes of corrosion expected in practice. To study the characteristics of scattered acoustic waves and performance of DAS for defect identification, we simulated the response of DAS for multiple pipe structures, defect types, and DAS sensor network configuration using finite element software Ansys, then the properties of signal response are extracted to construct defect-sensitive features. The raw data simulated, and the associated features extracted can ultimately be utilized as annotated training data to benchmark various designs for DAS applications, guided acoustic excitation sources, and learning model parameters to enhance early detection of potentially problematic defects.

Pipeline Defects Inspection, Fiber-optic sensors, ↗

Using synthetic infrared spectra derived from n/k optical constants for standoff detection of chemical deposits

We report results from a recent field experiment to test the validity of using physics-based synthetic infrared spectra to serve as endmembers in a spectral database targeted at chemical deposits. Specifically, the optical constants n and k, (the real and imaginary part of the refractive index) were used to first model infrared reflectance spectra for different thicknesses of chemical layers (e.g. acetaminophen, methylphosphonic acid – MPA, etc.) on various conducting and insulating substrates such as aluminum, wood, and glass. In the experimental portion of the research, thin films of the solid and liquid analytes were deposited onto such substrates to form micron-thick layers of the analytes at different thicknesses: Standoff data from an imaging instrument were then recorded and analyzed to not only identify the different analytes, but also quantify the layer/deposit thickness. To gauge success, the detection results using the synthetic data were compared to the results from hemispherical reflectance (HRF) spectra that were collected for the same sample planchets measured in the field via standoff methods. Preliminary results indicate good agreement between the synthetic reference data as compared to the lab-measured HRF data in terms of their ability to quantitatively reduce longwave infrared data. Specifically, modeled IR spectra for acetaminophen on an aluminum planchet at various thicknesses (1, 2, 5, 10, 15, and 20 µm) were synthesized and compared with standoff field reflectance data as well as HRF laboratory reflectance spectra for two samples: a 5.2 µm- and 12.8 µm-thick layer of acetaminophen on aluminum. Using a first-order approximation, analysis of the field data estimates the thicknesses of the samples to be 2 and 10 µm for the two samples, respectively, while the HRF laboratory data yields thickness estimates of between 5-10 µm and 10 µm, respectively. Both yield reasonable estimates, with the uncertainty most likely due to factors yet to be accounted for in the synthetic spectra such as light scattering.

complex index of refraction, optical constants, hy↗

Development of spectroscopic tools for nuclear forensics signatures development

The Savannah River National Laboratory (SRNL) has been developing advanced spectroscopic tools for the characterization of plutonium-bearing compounds with the intent to develop material and process signatures for nuclear forensics. Plutonium in a production, refining, or finishing facility will exist in many forms including oxide precursors (PuF4, PuF3, Pu oxalate, etc.), oxide, and metal. The ability to identify plutonium in each of these chemical forms and determine their processing history is crucial for the development of spectroscopic signatures. This presentation will focus on our work to develop and apply spectroscopic tools at SRNL using doubled-walled cells (DWC) to characterize the thermal decomposition of oxalates, calcination chemistry, alpha-decay-induced chemistry, age dating since last calcination, and other signatures related to plutonium processing.

Villa-Aleman, Eliel↗

Helmholtz vibrations in bowed strings

We report for almost 160 years, it has been known that Helmholtz oscillations, unique to vibrating strings in bowed instruments (violin, cello, etc.), have two distinct regimes: “slip” and “stick.” During the slip regime, the force at the bow-string interaction is attributed to friction between the sliding bow hair and the vibrating string, with a friction coefficient that decreases with increasing relative velocity. Yet the hair-string interaction during the stick regime is less understood. We propose that the interaction force during the stick regime is proportional to the product of the longitudinal acoustic impedance of the bow hair to the relative bow-string velocity. We validate this hypothesis by solving the string's differential equation of motion, including an enhanced formulation to avoid parasitic high-frequency oscillations. This physical model enables us to analyze, in real time, the characteristics of the Helmholtz oscillations, including the string shape, excitation of harmonics, Schelleng ripples, and string energy, showing that the bowed string gains energy during the stick regime and loses energy during the slip regime.

36 MATERIALS SCIENCE↗

A comparison of smartphone and infrasound microphone data from a fuel air explosive and a high explosive

For prompt detection of large (>1 kt) above-ground explosions, infrasound microphone networks and arrays are deployed at surveyed locations across the world. Denser regional and local networks are deployed for smaller explosions, however, they are limited in number and are often deployed temporarily for experiments. With the expanded interest in smaller yield explosions targeted at vulnerable areas such as population centers and key infrastructures, the need for more dense microphone networks has increased. An “attritable” (affordable, reusable, and replaceable) and flexible alternative can be provided by smartphone networks. Explosion signals from a fuel air explosive (thermobaric bomb) and a high explosive with trinitrotoluene equivalent yields of 6.35 and 3.63 kg, respectively, were captured on both an infrasound microphone and a network of smartphones. The resulting waveforms were compared in time, frequency, and time-frequency domains. The acoustic waveforms collected on smartphones produced a filtered explosion pulse due to the smartphone's diminishing frequency response at infrasound frequencies (<20 Hz) and was found difficult to be used with explosion characterization methods utilizing waveform features (peak overpressure, impulse, etc.). However, the similarities in time frequency representations and additional sensor inputs are promising for other explosion signal identification and analysis. As an example, a method utilizing the relative acoustic amplitudes for source localization using the smartphone sensor network is presented.

47 OTHER INSTRUMENTATION↗

A fivefold UO$_2^{2+}$ node is a path to dodecagonal quasicrystal approximants in coordination polymers [plus supplemental information]

Aperiodic formations continue to focus interest in areas ranging from advanced scientific theories to practical everyday applications. Starting from diverse and tightly bonded intermetallic compounds, this world showed an important breakthrough toward the so-called soft systems of meso/macroscale: liquid crystals, thin films, polymers, proteins, etc. This work opens a route for making bulk quasicrystals (QC) in an unprecedented but very common area, with molecular ligands. Since these systems are, to a large extent, transparent, they extend the possible areas of QC application to previously unreachable corners, e.g., photonics. We combined efficient bridging ligands with uranyl pentagonal bonding centers and, unexpectedly, brought the unique attributes of f-element coordination chemistry to an interdisciplinary area of aperiodic formations. Taking advantage of the planar coordination of uranyl ions, we were able to direct the structure expansion solely in two directions with a characteristic snub square tiling, a predicted but previously unobtainable dodecagonal approximant.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Learning the solution operator of parametric partial differential equations with physics-informed DeepONets

Partial differential equations (PDEs) play a central role in the mathematical analysis and modeling of complex dynamic processes across all corners of science and engineering. Their solution often requires laborious analytical or computational tools, associated with a cost that is markedly amplified when different scenarios need to be investigated, for example, corresponding to different initial or boundary conditions, different inputs, etc. In this work, we introduce physics-informed DeepONets, a deep learning framework for learning the solution operator of arbitrary PDEs, even in the absence of any paired input-output training data. We illustrate the effectiveness of the proposed framework in rapidly predicting the solution of various types of parametric PDEs up to three orders of magnitude faster compared to conventional PDE solvers, setting a previously unexplored paradigm for modeling and simulation of nonlinear and nonequilibrium processes in science and engineering.

97 MATHEMATICS AND COMPUTING↗

A long-life lithium-oxygen battery via a molecular quenching/mediating mechanism

The advancement of lithium-oxygen (Li-O 2 ) batteries has been hindered by challenges including low discharge capacity, poor energy efficiency, severe parasitic reactions, etc. We report an Li-O 2 battery operated via a new quenching/mediating mechanism that relies on the direct chemical reactions between a versatile molecule and superoxide radical/Li 2 O 2 . The battery exhibits a 46-fold increase in discharge capacity, a low charge overpotential of 0.7 V, and an ultralong cycle life >1400 cycles. Featuring redox-active 2,2,6,6-tetramethyl-1-piperidinyloxy moieties bridged by a quenching-active perylene diimide backbone, the tailor-designed molecule acts as a redox mediator to catalyze discharge/charge reactions and serves as a reusable superoxide quencher to chemically react with superoxide species generated during battery operation. The all-in-one molecule can simultaneously tackle issues of parasitic reactions associated with superoxide radicals, singlet oxygen, high overpotentials, and lithium corrosion. The molecular design of multifunctional additives combining various capabilities opens a new avenue for developing high-performance Li-O 2 batteries.

25 ENERGY STORAGE↗

Tracing Carbon Metabolism with Stable Isotope Metabolomics Reveals the Legacy of Diverse Carbon Sources in Soil

Tracking the metabolic activity of whole soil communities can improve our understanding of the transformation and fate of carbon in soils. For this work, we used stable isotope metabolomics to trace 13 C from nine labeled carbon sources into the water-soluble metabolite pool of an agricultural soil over time. Soil was amended with a mixture of all nine sources, with one source isotopically labeled in each treatment. We compared changes in the 13 C enrichment of metabolites with respect to carbon source and time over a 48-day incubation and contrasted differences between soluble sources (glucose, xylose, amino acids, etc.) and insoluble sources (cellulose and palmitic acid). Whole soil metabolite profiles varied singularly by time, while the composition of 13 C-labeled metabolites differed primarily by carbon source (R 2 = 0.68) rather than time (R 2 = 0.07), with source-specific differences persisting throughout incubations. The 13 C labeling of metabolites from insoluble carbon sources occurred slower than that from soluble sources but yielded a higher average atom percent (atom%) 13 C in metabolite markers of biomass (amino acids and nucleic acids). The 13 C enrichment of metabolite markers of biomass stabilized between 5 and 15 atom% 13 C by the end of incubations. Temporal patterns in the 13 C enrichment of tricarboxylic acid cycle intermediates, nucleobases (uracil and thymine), and by-products of DNA salvage (allantoin) closely tracked microbial activity. Our results demonstrate that metabolite production in soils is driven by the carbon source supplied to the community and that the fate of carbon in metabolites do not generally converge over time as a result of ongoing microbial processing and recycling.

59 BASIC BIOLOGICAL SCIENCES↗

Sulfur Metabolites Play Key System-Level Roles in Modulating Denitrification

Competition between nitrate-reducing bacteria (NRB) and sulfate-reducing bacteria (SRB) for resources in anoxic environments is generally thought to be governed largely by thermodynamics. It is now recognized that intermediates of nitrogen and sulfur cycling (e.g., hydrogen sulfide, nitrite, etc.) can also directly impact NRB and SRB activities in freshwater, wastewater, and sediment and therefore may play important roles in competitive interactions. Here, through comparative transcriptomic and metabolomic analyses, we have uncovered mechanisms of hydrogen sulfide- and cysteine-mediated inhibition of nitrate respiratory growth for the NRB Intrasporangium calvum C5. Specifically, the systems analysis predicted that cysteine and hydrogen sulfide inhibit growth of I. calvum C5 by disrupting distinct steps across multiple pathways, including branched-chain amino acid (BCAA) biosynthesis, utilization of specific carbon sources, and cofactor metabolism. Here, we have validated these predictions by demonstrating that complementation with BCAAs and specific carbon sources relieves the growth inhibitory effects of cysteine and hydrogen sulfide. We discuss how these mechanistic insights give new context to the interplay and stratification of NRB and SRB in diverse environments.

59 BASIC BIOLOGICAL SCIENCES↗

Lithologic controls on microfracturing from legacy underground nuclear explosions

Detection and verification of underground nuclear explosions (UNEs) can be improved with a better understanding of the nature and extent of explosion-induced damage in rock and the effect of this damage on radionuclide migration. Much of the previous work in this area has focused on centimeter- to meter-scale manifestations of damage, but to predict the effect of damage on permeability for radionuclide migration, observations at smaller scales are needed to determine deformation mechanisms. Based on studies of tectonic deformation in tuff, we expected that the heterogeneous tuff layers would manifest explosion-induced damage differently, with welded tuffs showing more fractures and nonwelded tuffs showing more deformation bands. In comparing post-UNE samples with lithologically matched pre-UNE equivalents, we observed damage in multiple lithologies of tuff through quantitative microfracture densities. We find that the texture (e.g., from deposition, welding, alteration, etc.) affects fracture densities, with stronger units fracturing more than weaker units. While we see no evidence of expected deformation bands in the nonwelded tuffs, we do observe, as expected, much larger microfracture densities at close range (<50 m) to the explosive source. We also observe a subtle increase in microfracture densities in post-UNE samples, relative to pre-UNE equivalents, in all lithologies and depths. The fractures that are interpreted to be UNE-induced are primarily transgranular and grain-boundary microfractures, with intragranular microfracture densities being largely similar to those of pre-UNE samples. This work has implications for models of explosion-induced damage and how that damage may affect flow pathways in the subsurface.

58 GEOSCIENCES↗

Elastic Bayesian Model Calibration

Functional data are ubiquitous in scientific modeling. For instance, quantities of interest are modeled as functions of time, space, energy, density, etc. Uncertainty quantification methods for computer models with functional response have resulted in tools for emulation, sensitivity analysis, and calibration that are widely used. However, many of these tools do not perform well when the computer model’s parameters control both the amplitude variation of the functional output and its alignment (or phase variation). This paper introduces a framework for Bayesian model calibration when the model responses are misaligned functional data. The approach generates two types of data out of the misaligned functional responses: (1) aligned functions so that the amplitude variation is isolated and (2) warping functions that isolate the phase variation. These two types of data are created for the computer simulation data (both of which may be emulated) and the experimental data. The calibration approach uses both types so that it seeks to match both the amplitude and phase of the experimental data. The framework is careful to respect constraints that arise, especially when modeling phase variation, and is framed in a way that it can be done with readily available calibration software. In conclusion, we demonstrate the techniques on two simulated data examples and on two dynamic material science problems: a strength model calibration using flyer plate experiments and an equation of state model calibration using experiments performed on the Sandia National Laboratories’ Z-machine.

97 MATHEMATICS AND COMPUTING↗

Measures of azimuthal anisotropy in high-energy collisions

Azimuthal anisotropy is a key observation made in ultrarelativistic heavy-ion collisions. This phenomenon has played a crucial role in the development of the field over the last two decades. In addition to its interest for studying the quark-gluon plasma, which was the original motivation, it is sensitive to the properties of incoming nuclei, in particular to the nuclear deformation and to the nuclear skin. The azimuthal anisotropy is therefore of crucial importance when relating low-energy nuclear structure to high-energy nuclear collisions. Furthermore, this article is an elementary introduction to the various observables used in order to characterize azimuthal anisotropy, which go under the names of v 2 {2}, v 3 {2}, v 2 {4}, etc. The intended audience is primarily physicists working in the field of nuclear structure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Exploring baryon resonances with transition generalized parton distributions: status and perspectives

QCD gives rise to a rich spectrum of excited baryon states. Understanding their internal structure is important for many areas of nuclear physics, such as nuclear forces, dense matter, and neutrino-nucleus interactions. Generalized parton distributions (GPDs) are an established tool for characterizing the QCD structure of the ground-state nucleon. They are used to create 3D tomographic images of the quark/gluon structure and quantify the mechanical properties such as the distribution of mass, angular momentum, and forces in the system. Transition GPDs extend these concepts to N → N* transitions and can be used to characterize the 3D structure and mechanical properties of baryon resonances. They can be probed in high-momentum-transfer exclusive electroproduction processes with resonance transitions e + N → e' + M + N*, such as deeply-virtual Compton scattering (M = γ) or meson production (M = π, K, etc.), and in related photon/hadron-induced processes. This White Paper describes a research program aiming to explore baryon resonance structure with transition GPDs. This includes the properties and interpretation of the transition GPDs, theoretical methods for structures and processes, first experimental results from JLab 12 GeV, future measurements with existing and planned facilities (JLab detector and energy upgrades, COMPASS/AMBER, EIC, EicC, J-PARC, LHC ultraperipheral collisions), and the theoretical and experimental developments needed to realize this program.

Experimental Nuclear Physics↗

The nucleardatapy toolkit for simple access to experimental nuclear data, astrophysical observations, and theoretical predictions

Systematic comparisons across theoretical predictions for the properties of dense matter, nuclear physics data, and astrophysical observations (also called meta-analyses) are performed. Existing predictions for symmetric nuclear and neutron matter properties are considered, and they are shown in this paper as an illustration of the present knowledge. Asymmetric matter is constructed assuming the isospin asymmetry quadratic approximation. It is employed to predict the pressure at twice saturation energy-density based only on nuclear-physics constraints, and we find it compatible with the one from the gravitational-wave community. To make our meta-analysis transparent, updated in the future, and to publicly share our results, the Python toolkit nucleardatapy is described and released here. Hence, this paper accompanies nucleardatapy, which simplifies access to nuclear-physics data, including theoretical calculations, experimental measurements, and astrophysical observations. This Python toolkit is designed to easily provide data for: (i) predictions for uniform matter (from microscopic or phenomenological approaches); (ii) correlation among nuclear properties induced by experimental and theoretical constraints; (iii) measurements for finite nuclei (nuclear chart, charge radii, neutron skins or nuclear incompressibilities, etc.) and hypernuclei (single particle energies); and (iv) astrophysical observations. This toolkit provides data in a unified format for easy comparison and provides new meta-analysis tools. It will be continuously developed, and we expect contributions from the community in our endeavor.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Transmission estimation at the quantum Cramér-Rao bound with macroscopic quantum light

The field of quantum metrology seeks to apply quantum techniques and/or resources to classical sensing approaches with the goal of enhancing the precision in the estimation of a parameter beyond what can be achieved with classical resources. Theoretically, the fundamental minimum uncertainty in the estimation of a parameter for a given probing state is bounded by the quantum Cramér-Rao bound. From a practical perspective, it is necessary to find physical measurements that can saturate this fundamental limit and to show experimentally that it is possible to perform measurements with the required precision to do so. Here we perform experiments that saturate the quantum Cramér-Rao bound for transmission estimation over a wide range of transmissions when probing the system under study with a continuous wave bright two-mode squeezed state. To properly take into account the imperfections in the generation of the quantum state, we extend our previous theoretical results to incorporate the measured properties of the generated quantum state. For our largest transmission level of 84%, we show a 62% reduction over the optimal classical protocol in the variance in transmission estimation when probing with a bright two-mode squeezed state with -8 dB of intensity-difference squeezing. Given that transmission estimation is an integral part of many sensing protocols, such as plasmonic sensing, spectroscopy, calibration of the quantum efficiency of detectors, etc., the results presented promise to have a significant impact on a number of applications in various fields of research.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗