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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Optical recognition of constructs using hyperspectral imaging and detection (ORCHID)

Abstract Challenges to deep sample imaging have necessitated the development of special techniques such as spatially offset optical spectroscopy to collect signals that have travelled through several layers of tissue. However, these techniques provide only spectral information in one dimension (i.e., depth). Here, we describe a general and practical method, referred to as Optical Recognition of Constructs Using Hyperspectral Imaging and Detection (ORCHID). The sensing strategy integrates (1) the spatial offset detection concept by computationally binning 2D optical data associated with digital offsets based on selected radial pixel distances from the excitation source; (2) hyperspectral imaging using tunable filter; and (3) digital image binding and collation. ORCHID is a versatile modality that is designed to collect optical signals deep inside samples across three spatial (X, Y, Z) as well as spectral dimensions. The ORCHID method is applicable to various optical techniques that exhibit narrow-band structures, from Raman scattering to quantum dot luminescence. Samples containing surface-enhanced Raman scattering (SERS)-active gold nanostar probes and quantum dots embedded in gel were used to show a proof of principle for the ORCHID concept. The resulting hyperspectral data cube is shown to spatially locate target emitting nanoparticle volumes and provide spectral information for in-depth 3D imaging.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Linearly dispersive bands at the onset of correlations in K 𝑥 ⁢C 60 films

Molecular crystals are a flexible platform to induce novel electronic phases. Due to the weak forces between molecules, intermolecular distances can be varied over larger ranges than interatomic distances in atomic crystals. On the other hand, the hopping terms are generally small, which results in narrow bands, strong correlations, and heavy electrons. Here, by growing K x C 60 fullerides on hexagonal layered Bi 2 Se 3 , we show that upon doping the series undergoes a Mott transition from a molecular insulator to a correlated metal and an in-gap state evolves into highly dispersive Dirac-like fermions at half filling, where superconductivity occurs. This picture challenges the commonly accepted description of the low-energy quasiparticles as appearing from a gradual electron doping of the conduction states and suggests an intriguing parallel with the more famous family of the cuprate superconductors. More in general, it indicates that molecular crystals offer a viable route to engineer electron-electron interactions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Application of machine learning to estimate fireball characteristics and their uncertainty from infrared spectral data

Experiments or events involving high explosives (HE) can be monitored remotely by infrared (IR) sensors to gather information about the configuration or materials involved in the device. Researchers at the Air Force Institute of Technology (AFIT) developed a phenomenological model for HE fireball spectra in the IR range that allows for parameters to be extracted from Fourier transform infrared (FTIR) data. This model includes parameters tied to physical characteristics of the fireball: temperature, size, soot, and gas concentrations. Previous works have sought to recover these parameters by the fitting of either whole spectra or select wavenumber bands to this phenomenological model. Difficulties arise due to the complex relationships between the parameters to be fit. Uncertainty quantification of the estimated fireball parameters is also problematic since HE experiments do not have any ground truth information on the parameters. It is suggested that artificial neural network (ANN) based approaches may be well suited to this problem, because of their ability to capture complex and highly nonlinear relationships. As such, this work seeks to explore the efficacy of deep artificial neural networks (DNNs) for this problem of parameter recovery from spectra and to also investigate the uncertainty of recovering the fireball parameters from FTIR data. Networks are designed using the hyperparameter optimization tool Hyperopt and trained/tested on artificial data generated using the phenomenological model developed by AFIT. The results of applying the network to the artificial data set are compared to a physics-based band approach that uses a selected number of bands based on their physical properties. Information on the uncertainty of estimating parameters from remotely sensed experimental data is obtained by treating the accuracy of the DNN model on artificial data as an upper bound and by examining the impact of emissivity due to soot on parameter estimation error; the results for artificial data are likely to be optimistic as compared to recovering parameters from experimental data.

42 ENGINEERING↗
DOE OSTI2020

Termination switching of antiferromagnetic proximity effect in topological insulator

This work reports the ferromagnetism of topological insulator, (Bi,Sb) 2 Te 3 (BST), with a Curie temperature of approximately 120 K induced by magnetic proximity effect (MPE) of an antiferromagnetic CrSe. The MPE was shown to be highly dependent on the stacking order of the heterostructure, as well as the interface symmetry: Growing CrSe on top of BST results in induced ferromagnetism, while growing BST on CrSe yielded no evidence of an MPE. Cr-termination in the former case leads to double-exchange interactions between Cr 3+ surface states and Cr 2+ bulk states. This Cr 3+ -Cr 2+ exchange stabilizes the ferromagnetic order localized at the interface and magnetically polarizes the BST Sb band. In contrast, Se-termination at the CrSe/BST interface yields no detectable MPE. These results directly confirm the MPE in BST films and provide critical insights into the sensitivity of the surface state.

42 ENGINEERING↗
DOE OSTI2024

Friction stir processing on a strontium modified, thin-wall, vacuum-assisted high-pressure die-cast Aural-5 alloy to improve tensile and fatigue performance

Here, this study explores the application of friction stir processing (FSP) to enhance the material properties of Sr-modified Aural-5 alloy, with a focus on improved tensile and fatigue properties. Aural-5 is a well-known vacuum-assisted high-pressure die-cast (HPDC) Al-Si7-Mg alloy used in the automotive industry to reduce vehicle weight, enhance fuel efficiency, and lower carbon emissions. This alloy modifies its material chemistry with Sr for fine fibrous networks of eutectic silicon and manganese (Mn) to reduce die soldering. It has significantly less iron (Fe) content resulting in the elimination of detrimental needle-shaped Fe-bearing ß-phase intermetallic and improving ductility. The initial microstructure of as-received HPDC Aural-5 exhibits shrinkage porosity in the middle section, a dendritic microstructure with fibrous Al-Si eutectic colonies, a shear-band structure beneath the die-wall, large dendritic externally solidified crystals (ESCs), needle-shaped Mg 2 Si phase and significant second-phase particulates. Some of those microstructural features, such as porosity, ESCs, needle-shaped Mg 2 Si phase, and large second-phase particles, serve as initiation sites for cracks under mechanical loading, resulting in adverse effects on tensile properties, particularly ductility. FSP effectively transforms the microstructure into a wrought configuration with uniform particle distribution by eliminating porosity and disintegrating dendrites, eutectic colonies, ESCs, second-phase particles, and shear-band structures. FSP-driven microstructure modification enhances yield strength and tensile ductility by ~30% and ~35%, respectively. The fatigue life of the material in a bending mode configuration (stress ratio R = 0.1) after FSP exhibits enhancements ranging from 2.0 to 3.9 times that of the original HPDC Aural-5 alloy, depending on the applied stress level.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Metastability and Degradation of CdTe Solar Cells Investigated by nm-Scale Electrical Potential Imaging

We report on investigations of reversible metastability and irreversible degradation of MZO/CdSeTe/CdTe devices from the perspective of electric field across the device using Kelvin probe force microscopy (KPFM). The device showed reversible transitions between the light-soak state (LSS) with the best device efficiency and the dark-soak state (DSS) with an inferior efficiency. However, it showed an irreversible degradation state (DgS) driven by long-hour light soaking at an elevated temperature. The nm-scale KPFM electric field imaging on cross-sections of the devices revealed different anomalous electric field profiles. The electric field at the LSS exhibits a main peak inside the CdSeTe layer but not at the MZO/CdSeTe heterointerface, demonstrating that working junction of the device is a buried homojunction (BHJ). At the DSS, a second electric field peak was observed at the MZO/CdSeTe interface with a similar strength to the main BHJ, which probably caused the decrease in fill factor at the DSS. At the DgS, the electric field peak at the MZO/CdSeTe interface increased significantly and a third electric field was measured at the back contact of the device. Device modeling using COMSOL and in alignment with both the electric field and device current-voltage curves suggest that a slightly low n-doped CdSeTe in the region near the MZO/CdSeTe interface caused the BHJ, and that either a loss of MZO doping or increase of the conduction band offset spike due to long-term stress caused the fill factor-dominated degradation and the increased electric field near the MZO/CdSeTe interface at the DgS. The former, MZO doping decrease, is more plausible by referring the related literature.

BHJ↗
DOE OSTI2025

Refining the two-band model for highly compensated semimetals using thermoelectric coefficients

In studying compensated semimetals, the two-band model has proven extremely useful in capturing electrical conductivity under magnetic field, as a function of density and mobility of electronlike and holelike carriers. However, it rarely offers practical insight into magnetothermoelectric properties. Here, in this work, we report the field dependence of thermoelectric (TE) coefficients in a highly compensated semimetal NbSb 2 , where we find the Seebeck (𝑆 𝑥⁢𝑥 ) and Nernst (𝑆 𝑥⁢𝑦 ) coefficients increase quadratically and linearly with applied magnetic field, respectively. Such field dependence was predicted in previous work that studied a system of two parabolic bands, within semiclassical Boltzmann transport theory when the following two conditions are simultaneously met: 𝜔 𝑐 ⁢𝜏 ≫ 1 and tan ⁡𝜃 𝐻 ≪ 1, where 𝜔 𝑐 and 𝜏 refer to the cyclotron frequency and relaxation time, respectively, and 𝜃 𝐻 is the Hall angle. Under these conditions, we find the field dependence of the TE coefficients directly provides a relation between the electronlike (𝑛 𝑒 ) and holelike (𝑛 ℎ ) carrier densities, which in turn can be used to refine two-band model fitting. With this, we find the compensation factor ($\frac{|Δ⁢𝑛|}{𝑛_{𝑒}}$, where Δ⁢𝑛 = 𝑛 𝑒 −𝑛 ℎ ) of NbSb 2 is two orders of magnitude smaller than what was found in unrestricted fitting, resulting in a larger saturation-field scale for magnetoresistance. Within the same framework of the semiclassical theory, we also deduce that the thermoelectric Hall angle tan⁡ 𝜃 𝛾 = $\frac{𝑆_{𝑥⁢𝑦}}{𝑆_{𝑥⁢𝑥}}$ can be expressed as ($\frac{Δ⁢𝑛}{𝑛_{𝑒}}$ ×𝜔 𝑐 ⁢𝜏) −1 , which serves as a parameter to predict the degree of compensation. Our findings offer crucial insights into identifying empirical conditions for field-induced enhancement of TE performance and into engineering-efficient thermoelectric devices based on semimetallic materials.

electrical conductivity↗
DOE OSTI2020

Synthesis of Co‐Doped MoS 2 Monolayers with Enhanced Valley Splitting

Abstract Internal magnetic moments induced by magnetic dopants in MoS 2 monolayers are shown to serve as a new means to engineer valley Zeeman splitting (VZS). Specifically, successful synthesis of monolayer MoS 2 doped with the magnetic element Co is reported, and the magnitude of the valley splitting is engineered by manipulating the dopant concentration. Valley splittings of 3.9, 5.2, and 6.15 meV at 7 T in Co‐doped MoS 2 with Co concentrations of 0.8%, 1.7%, and 2.5%, respectively, are achieved as revealed by polarization‐resolved photoluminescence (PL) spectroscopy. Atomic‐resolution electron microscopy studies clearly identify the magnetic sites of Co substitution in the MoS 2 lattice, forming two distinct types of configurations, namely isolated single dopants and tridopant clusters. Density functional theory (DFT) and model calculations reveal that the observed enhanced VZS arises from an internal magnetic field induced by the tridopant clusters, which couples to the spin, atomic orbital, and valley magnetic moment of carriers from the conduction and valence bands. The present study demonstrates a new method to control the valley pseudospin via magnetic dopants in layered semiconducting materials, paving the way toward magneto‐optical and spintronic devices.

Zhou, Jiadong↗
DOE OSTI2020

Tire bead

A tire for a motor vehicle having at least one carcass ply comprised of a crown portion and two axially opposite side portions terminating in beads for mounting the tire on a rim. A tread band and a belt structure are interposed between the carcass structure and the bead. Each bead includes on elongated cord comprised of a first yarn, such as aramid, having a melting or decomposition point T1, and a second yarn, such as nylon, having a melting point T 2 , wherein T 1 >T 2 , and T 2 is greater than 40° C.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Quantum coherence tomography of light-controlled superconductivity

The coupling between superconductors and oscillation cycles of light pulses, i.e., lightwave engineering, is an emerging control concept for superconducting quantum electronics. Although progress has been made towards terahertz-driven superconductivity and supercurrents, the interactions able to drive non-equilibrium pairing are still poorly understood, partially due to the lack of measurements of high-order correlation functions. In particular, the sensing of exotic collective modes that would uniquely characterize light-driven superconducting coherence, in a way analogous to the Meissner effect, is very challenging but much needed. Here we report the discovery of parametrically driven superconductivity by light-induced order-parameter collective oscillations in iron-based superconductors. The time-periodic relative phase dynamics between the coupled electron and hole bands drives the transition to a distinct parametric superconducting state out-of-equalibrium. This light-induced emergent coherence is characterized by a unique phase–amplitude collective mode with Floquet-like sidebands at twice the Higgs frequency. We measure non-perturbative, high-order correlations of this parametrically driven superconductivity by separating the terahertz-frequency multidimensional coherent spectra into pump–probe, Higgs mode and bi-Higgs frequency sideband peaks. We find that the higher-order bi-Higgs sidebands dominate above the critical field, which indicates the breakdown of susceptibility perturbative expansion in this parametric quantum matter.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

On the design and performance of InGaN/Si double-junction photocathodes

Via a combined theoretical and experimental study, we have investigated the synthesis and performance characteristics of InGaN/Si double-junction photoelectrochemical (PEC) water splitting devices, which promise a theoretical solar-to-hydrogen conversion efficiency ~30% under AM 1.5G one-sun illumination. The double-junction photocathodes consist of a p + -InGaN top light absorber and a Si bottom p-n junction, which are connected through a nanowire tunnel junction. The effect of indium composition of the top light absorber as well as the impact of p-type Mg dopant incorporation on the PEC performance was studied. Experimentally, the sample with 32% indium composition showed a maximum photocurrent density of ~9 mA/cm 2 at 0.4 mV vs reverse hydrogen electrode (RHE) with applied bias photon-to-current efficiency (ABPE) of ~9.5%. An optimum p-type doping level ~1 × 10 17 cm -3 was also identified, which results in the best device performance as a result of optimum surface band bending as well as vertical charge carrier (hole) transport. These results also show a good agreement with our theoretical analysis. This work provides significant insights in advancing the design and development of high efficiency PEC devices for artificial photosynthesis using industry ready materials, e.g., Si and GaN, to achieve large-scale, low-cost onsite hydrogen fuel production.

42 ENGINEERING↗
DOE OSTI2021

Reconfiguration of Amorphous Complex Oxides: A Route to a Broad Range of Assembly Phenomena, Hybrid Materials, and Novel Functionalities

This work demonstrate that reconfiguration of amorphous oxide layers drives the assembly of oxide-based and freestanding nanomembranes into 3D structures with a radius of a few hundred nanometers. Reconfiguration-driven assembly is a versatile approach to impart large strains and strain gradients in a broad palette of complex oxides. This capability allows for manipulating and enhancing ferroelectricity, flexoelectricity, piezoelectricity, superconductivity, and ferromagnetism in complex oxides. Moreover, by the approach presented in this work, strain-engineered oxides are obtained in the form of 3D structures that can be fabricated in parallel on any substrate, including large-area and single crystalline semiconductor substrates. This approach will create a vast expanse of possibilities to investigate and leverage strain-tunable effects in amorphous, poly-crystalline, and single-crystalline complex oxides. Reconfiguration-driven assembly of NMs also allows combining different materials in a radial geometry and through scalable processes. For example, radial superlattices of Si (or GaAs) and various complex oxides or alternating layers of different complex oxides (e.g., SrTiO 3 and LaAlO 3 ) could be fabricated by release and heating of bilayer NMs. Here, a broad palette of electronic band structures and spin–orbit interactions could then be obtained by tailoring the curvature of the self-assembled NMs and the materials that the heterostructure comprises.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Dispersion-Engineered Deep Sub-Wavelength Plasmonic Metasurfaces for Broadband Seira Applications

Surface enhanced infrared absorption (SEIRA) spectroscopy is a powerful tool in which plasmonically enhanced electromagnetic fields provide high-sensitivity molecular detection. Most SEIRA platforms operate at a single resonant frequency, which must be tuned to match that of the target molecule, and commonly rely on time-consuming lithographic techniques. This study presents a high-throughput and cost-effective plasmonic metasurface for broadband, tunable, and strong infrared signal enhancement. The platform is built upon the principle of dispersion-engineered plasmonic Fabry–Pérot (FP) nanocavity arrays. It offers 1) tight squeezing of infrared (IR) photons into deep sub-wavelength nano-volumes and 2) spectrally tunable near-field enhancements of up to ≈10 6 , two to three orders of magnitude higher than most optical metasurface systems. By coupling multilayer nano-thin film deposition and nanoskiving fabrication techniques, the dispersive FP metasurfaces can be rapidly and reproducibly constructed in a scalable and lithography-free manner. Using IR spectroscopy, the selective and sensitive label-free detection of a molecular monolayer is achieved at a range of frequencies. An enhancement factor of nearly 10 5 is measured at the carbonyl (C = O) vibrational marker band of the molecule. The confluence of high field enhancement, broadband plasmonic response, and facile fabrication makes this metasurface a promising platform for SEIRA spectroscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Snapshot multispectral imaging using a diffractive optical network

Abstract Multispectral imaging has been used for numerous applications in e.g., environmental monitoring, aerospace, defense, and biomedicine. Here, we present a diffractive optical network-based multispectral imaging system trained using deep learning to create a virtual spectral filter array at the output image field-of-view. This diffractive multispectral imager performs spatially-coherent imaging over a large spectrum, and at the same time, routes a pre-determined set of spectral channels onto an array of pixels at the output plane, converting a monochrome focal-plane array or image sensor into a multispectral imaging device without any spectral filters or image recovery algorithms. Furthermore, the spectral responsivity of this diffractive multispectral imager is not sensitive to input polarization states. Through numerical simulations, we present different diffractive network designs that achieve snapshot multispectral imaging with 4, 9 and 16 unique spectral bands within the visible spectrum, based on passive spatially-structured diffractive surfaces, with a compact design that axially spans ~72 λ m , where λ m is the mean wavelength of the spectral band of interest. Moreover, we experimentally demonstrate a diffractive multispectral imager based on a 3D-printed diffractive network that creates at its output image plane a spatially repeating virtual spectral filter array with 2 × 2 = 4 unique bands at terahertz spectrum. Due to their compact form factor and computation-free, power-efficient and polarization-insensitive forward operation, diffractive multispectral imagers can be transformative for various imaging and sensing applications and be used at different parts of the electromagnetic spectrum where high-density and wide-area multispectral pixel arrays are not widely available.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Suitability of Altair FEKO's Computational Electromagnetic Techniques for Tree Model Scattering and Penetration at Ku-band

Foliage penetration (FOPEN) radar at lower frequencies (VHF, UHF) is a well-studied area with many contributions. However, there is growing interest in using higher Ku-band frequencies (12-18 GHz) for FOPEN. Specifically, the reduced wavelength sizes provide some key saliencies for developing more optimized detection solutions. The disadvantage is that exploiting Ku-band for FOPEN is complicated because higher frequencies have pronounced scattering effects due to their smaller wavelengths. A methodology h as been developed to model and simulate FOPEN problems that characterize the phenomenology of Ku-band electromagnetic ( EM ) wave transmissions through moderate foliage. The details of this research (i.e. the realistic tree models, simulation setup and results) are documented in multiple reports. The main focus of this report is to describe the preliminary validation and verification of Altair FEKO, the computational EM (CEM) software used for this research, as well as present a simplified symmetrical tree model and an introductory CAD tree model.

42 ENGINEERING↗
DOE OSTI2021

Harnessing Photoelectrochemistry for Wastewater Nitrate Treatment Coupled with Resource Recovery

Wastewater is a misplaced resource well suited to recover nutrients, value-added chemicals, energy, and clean water. A photoelectrochemical device is proposed to transform wastewater nitrates to ammonia and nitrous oxide, coupled with water oxidation. Numerical models were developed to quantify the dependence of process efficiencies and nitrogen-removal rates on light absorber band gaps, electrocatalytic kinetic parameters, competing oxygen reduction and hydrogen evolution reactions, and the reacting nitrate species concentrations that affect the mass-transfer limited current densities. With a single light-absorber and state-of-the-art catalysts, optimal solar-to-chemical efficiencies of 7% and 10% and nitrogen-removal rates of 260 and 395 gN m -2 day -1 are predicted for nitrate reduction to ammonia and nitrous oxide, respectively. The influence of competing reactions on the performance depends on the nitrate concentration and band gap of the light absorber modeled. Oxygen reduction is more dominant than hydrogen evolution to compete with the nitrate reduction reaction, but it is mass-transfer limited. Even with kinetic parameters that enhanced the driving forces for the competing reactions, the performance is only minimally affected by these reactions for optimally selected band gaps and nitrate concentrations larger than 100 mM. Here, theoretically predicted peak nitrogen removal rates and specific energy intensities are competitive with reported estimates for electrochemical and Sharon-Anammox processes for ammonia recovery and nitrogen removal, respectively. This result, together with the added benefit of harnessing sunlight to produce value-added products, indicates promise in the photoelectrochemical approach as a tertiary pathway to recover nutrients and energy from wastewater nitrates.

25 ENERGY STORAGE↗
DOE OSTI2024

Band Heater Heat Flux Characterization Using Inverse Heat Conduction Problem Models

Abstract An experimental apparatus was constructed to correlate water flowrate and temperature rise under an external band heater. Due to the physical characteristics of the band heater, its transient heating behavior is unknown. This paper investigates the application of inverse heat conduction problem (IHCP) methods to characterize the heat flux from the band heater. Three experiments with different heating times (5, 10, and 20 s) and no flowrate were conducted to measure the transient temperature under the 400 W band heater. Type-T thermocouples measure surface temperature at the centerline of the band heater. The experimental results are computed with five different heat conduction models. The models are chosen to identify how the heat flux response varies from a simplified to a realistic model. Additionally, the results of the experimental heat flux are compared to the manufacturer band heater data (58.9 kW/m2) for each model. The minimum time needed for the heater to fully energize the system is from 10 to 12 s. The residuals for each model are analyzed and used to evaluate the appropriateness of the five different models. The results show that the use of simpler models can achieve results similar to those of complex models, with less time and computational cost.

Engineering↗
DOE OSTI2023

Platform-agnostic waveguide integration of high-speed photodetectors with evaporated tellurium thin films

Many attractive photonics platforms still lack integrated photodetectors due to inherent material incompatibilities and lack of process scalability, preventing their widespread deployment. Here, we address the problem of scalably integrating photodetectors in a photonics-platform-independent manner. Using a thermal evaporation and deposition technique developed for nanoelectronics, we show that tellurium, a quasi-2D semi-conductive element, can be evaporated at low temperatures directly onto photonic chips to form air-stable, high-speed, ultrawide-band photodetectors. We demonstrate detection from visible (520 nm) to short-wave infrared (2.4 µm), a bandwidth of more than 40 GHz, and platform-independent scalable integration with photonic structures in silicon, silicon nitride, and lithium niobate.

42 ENGINEERING↗