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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Maximizing the Radar Generalized Image Quality Equation for Bistatic SAR Using Waveform Frequency Agility

The radar generalized image quality equation (RGIQE) is a metric used to measure both monostatic and bistatic synthetic aperture radar (BSAR) image quality, it is a function of signal-to-noise ratio (SNR) and 2-D bandwidth. The 2-D bandwidth is equal to the area of the transfer function’s (TF) passband region. With the exception of side-looking monostatic geometries, almost all monostatic and bistatic geometries have skewed passband shapes when waveform frequency parameters remain unchanged from pulse to pulse. Most synthetic aperture radar (SAR) applications require a rectangular-shaped passband region, this is achieved by inscribing a rectangular region within the skewed intrinsic passband region. Increasing skewness results in less inscription area reducing 2-D bandwidth, image SNR, and thus RGIQE capacity. In this article, a waveform with frequency agility is used to rectify the skewness that degrades RGIQE capacity. By changing the waveform’s center frequency and instantaneous bandwidth from pulse to pulse in a particular manner, the intrinsic passband region can be de-skewed. The de-skewed shape maximizes the inscription area thus maximizing 2-D bandwidth, image SNR, and RGIQE capacity. Here, three examples are given in this article, one monostatic geometry, and two bistatic geometries. RGIQE capacity is increased by 52.02%, 44.42%, and 79.09% for the three examples.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Evaluation of the Nanometrics Centaur Digitizer

Sandia National Laboratories has tested and evaluated a new digitizer, the Centaur, manufactured by Nanometrics, Inc. This digitizer is used to record sensor output for seismic and infrasound monitoring applications. The purpose of the digitizer evaluation was to measure the performance characteristics in such areas as power, sensitivity, self-noise, dynamic range, system noise, modified noise power ration, relative transfer function, analog bandwidth, harmonic distortion, common mode, cross talk, timing tag accuracy and timing drift. The Centaur provides six channels of 24 bit digitization, three of which may be transmitted utilizing CD1.1 protocol.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Guralp Affinity Digitizer Evaluation

Sandia National Laboratories has tested and evaluated a new digitizer, the Affinity, manufactured by Guralp Systems. This digitizer is used to record sensor output for seismic and infrasound monitoring applications. The purpose of the digitizer evaluation was to measure the performance characteristics in such areas as sensitivity, power, self-noise, dynamic range, system noise, relative transfer function, modified noise power ratio, analog bandwidth, harmonic distortion, common mode, cross talk, timing tag accuracy and timing drift. The Affinity provides eight, rather the typical six, channels of 24 bit high sample rate digitization, all of which may be transmitted utilizing the CD1.1 protocol, at multiple sample rates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Performance Prediction of Big Data Transfer Through Experimental Analysis and Machine Learning

Big data transfer in next-generation scientific ap- plications is now commonly carried out over connections with guaranteed bandwidth provisioned in High-performance Net- works (HPNs) through advance bandwidth reservation. To use HPN resources efficiently, provisioning agents need to carefully schedule data transfer requests and allocate appropriate band- widths. Such reserved bandwidths, if not fully utilized by the requesting user, could be simply wasted or cause extra overhead and complexity in management due to exclusive access. This calls for the capability of performance prediction to reserve bandwidth resources that match actual needs. Towards this goal, we employ machine learning algorithms to predict big data transfer perfor- mance based on extensive performance measurements, which are collected over a span of several years from a large number of data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated HPN testbeds. We first identify a comprehensive list of attributes involved in a typical big data transfer process, including end host system configurations, network connection properties, and control parameters of data transfer methods. We then conduct an in-depth exploratory analysis of their impacts on application- level throughput, which provides insights into big data transfer performance and motivates the use of machine learning. We also investigate the applicability of machine learning algorithms and derive their general performance bounds for performance prediction of big data transfer in HPNs. Experimental results show that, with appropriate data preprocessing, the proposed machine learning-based approach achieves 95% or higher pre- diction accuracy in up to 90% of the cases with very noisy real-life performance measurements.

Yun, Daqing↗
DOE OSTI2021

Non-Contact Mass Density and Thermal Conductivity Measurements of Organic Thin Films Using Frequency–Domain Thermoreflectance

Thin-film organic materials are broadly used to study amorphous stabilization of active pharmaceuticals, control explosive detonation phenomena, and introduce insulation in novel thermal barriers. Their synthesis, however, introduces defects and thickness variations that warrant careful characterization of local thermophysical properties such as thermal conductivity and mass density. In this study, wide bandwidth (200 Hz to 20 MHz) frequency–domain thermoreflectance (FDTR) is demonstrated to simultaneously extract the thermal conductivity and mass density of 1 μm physical vapor-deposited indomethacin films on Si and SiO 2 substrates, as well as 10 and 100 μm films on Si. By assuming a bulk specific heat capacity, mass densities are determined with FDTR measurements of volumetric heat capacity and are in good agreement with the literature, as well as models based upon a dependence on porosity and the kinetic theory for phonons. Lastly, it is found that for broad-band FDTR measurements, insulating substrates provide improved fidelity for the extraction of thermal conductivity and volumetric heat capacity in organic thin films. Overall, this work demonstrates the potential for FDTR as a non-contact method to determine microscale mass density variations across the surface and thickness of organic thin films.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Ion temperature and rotation fluctuation measurements with ultra-fast charge exchange recombination spectroscopy (UF-CHERS) in the DIII-D tokamak

An upgraded detector and several optimizations have significantly improved the Ultra-Fast Charge Exchange Recombination Spectroscopy (UF-CHERS) diagnostic sensitivity to ion temperature and parallel velocity fluctuations at turbulence relevant spatio-temporal scales. Normalized broadband ion temperature and parallel velocity fluctuations down to x̃x∼1% (x = Ti, v∥) and up to ∼450 kHz have been measured in a variety of plasmas. The multi-field nature of the CHERS technique also allows measurements of the cross-phase angles of the fluctuating fields. UF-CHERS is optimized to observe emissions from the electron exchange reaction between intrinsic C6+ and hydrogenic neutral beam injected particles near 529 nm. UF-CHERS consists of two chords separated by ∼1 cm radially, less than the turbulence correlation length in DIII-D plasmas, which enables correlated measurements to suppress incoherent electronic and photon noise. The optical components of the spectrometer include a volume-phase-holographic grating with >90% transmission between 528 and 530 nm and f/2 200-mm lenses, selected to maximize the optical efficiency and photon flux. Diffracted light from each chord is collected in eight spectral bins, each with a bandwidth of ∼0.25 nm, and detected and amplified by chilled avalanche photodiodes and custom high-gain, wide bandwidth low-noise preamplifiers to achieve the optimal signal-to-noise ratio. The resulting signals are digitized at 1 MHz, 103–104× faster than the conventional CHERS diagnostics. Spatial coverage is achieved by repositioning a motorized fiber tray between plasmas. UF-CHERS measurements will advance the understanding of turbulent ion transport and contribute to the validation of transport models and simulations.

Truong, D. D. (ORCID:0000000285732539)↗
DOE OSTI2025

Universal Magnetic Phases in Twisted Bilayer MoTe 2

Twisted bilayer MoTe 2 (tMoTe 2 ) has emerged as a robust platform for exploring correlated topological phases, yet the evolution of its magnetism and topology with twist angle remains an open question. Here, we systematically map the magnetic phase diagram of tMoTe 2 by using local optical spectroscopy and scanning nanoSQUID-on-tip magnetometry. We identify spontaneous ferromagnetism at filling factors ν = −1 and −3 across twist angles from 2.1° to 3.7°, revealing a universal, twist-angle-insensitive ferromagnetic phase. At 2.1°, we further observe robust ferromagnetism at ν = −5, absent at larger twist angles. Temperature-dependent measurements reveal a contrasting twist-angle dependence of the Curie temperatures between ν = −1 and −3, indicating a distinct interplay between the exchange interactions and bandwidth for the two Chern bands. Despite broken time-reversal symmetry, no topological gap is detected at ν = −3. Furthermore, our results establish a global framework for understanding and controlling magnetic order in tMoTe 2 .

Insulators↗
DOE OSTI2023

Single-trial classification of evoked responses to auditory tones using OPM- and SQUID-MEG

Abstract Objective. Optically pumped magnetometers (OPMs) are emerging as a near-room-temperature alternative to superconducting quantum interference devices (SQUIDs) for magnetoencephalography (MEG). In contrast to SQUIDs, OPMs can be placed in a close proximity to subject’s scalp potentially increasing the signal-to-noise ratio and spatial resolution of MEG. However, experimental demonstrations of these suggested benefits are still scarce. Here, to compare a 24-channel OPM-MEG system to a commercial whole-head SQUID system in a data-driven way, we quantified their performance in classifying single-trial evoked responses. Approach. We measured evoked responses to three auditory tones in six participants using both OPM- and SQUID-MEG systems. We performed pairwise temporal classification of the single-trial responses with linear discriminant analysis as well as multiclass classification with both EEGNet convolutional neural network and xDAWN decoding. Main results. OPMs provided higher classification accuracies than SQUIDs having a similar coverage of the left hemisphere of the participant. However, the SQUID sensors covering the whole helmet had classification scores larger than those of OPMs for two of the tone pairs, demonstrating the benefits of a whole-head measurement. Significance. The results demonstrate that the current OPM-MEG system provides high-quality data about the brain with room for improvement for high bandwidth non-invasive brain–computer interfacing.

Iivanainen, Joonas (ORCID:0000000160344604)↗
DOE OSTI2019

SOI-MEMS Bulk Piezoresistive Displacement Sensor: A Comparative Study of Readout Circuits

Performance of several readout circuits, when applied to a MEMS-based bulk piezoresistive displacement sensor is compared in this study. The sensor comprises a pair of tilted clamped-guided silicon beams whose bulk piezoresistivity is used for displacement sensing. Wheatstone half-bridge, constant-voltage, and constant-current circuits are implemented to measure resistance changes of this sensor. We report full characterization of the sensor with these circuits and explore the sensor’s important characteristics such as linearity, bandwidth, and noise. The results reveal that the constant-current circuit provides the highest sensitivity at equal-power bias condition. Here, we find that the resolution of the sensor is degraded from 1.6 nm with the Wheatstone half-bridge and constant-voltage circuits to about 4.2 nm with the constant-current configuration. In the frequency domain, the sensor captures the full dynamics of the MEMS nanopositioner up to 20 kHz with all readout circuits.

42 ENGINEERING↗
DOE OSTI2020

Silicon photonic chip for 16-channel wavelength division (de-)multiplexing in the O-band

We experimentally demonstrate a silicon photonic chip-scale 16-channel wavelength division multiplexer (WDM) operating in the O-band. The silicon photonic chip consists of a common-input bus waveguide integrated with a sequence of 16 spectral add-drop filters implemented by 4-port contra-directional Bragg couplers and resonant cladding modulated perturbations. The combination of these features reduces the spectral bandwidth of the filters and improves the crosstalk. An apodization of the cladding modulated perturbations between the bus and the add/drop waveguides is used to optimize the strength of the coupling coefficient in the propagation direction to reduce the intra-channel crosstalk on adjacent channels. The fabricated chip was validated experimentally with a measured intra-channel crosstalk of ∼−18.9 dB for a channel spacing of 2.6 nm. The multiplexer/demultiplexer chip was also experimentally tested with a 10 Gbps data waveform. The resulting eye-pattern indicates that this approach is suitable for datacenter WDM-based interconnects in the O-band with large aggregate bandwidths.

Davis, Jordan A. (ORCID:0000000343483295)↗
DOE OSTI2022

Ultra-broadband quadrature squeezing with thin-film lithium niobate nanophotonics

Squeezed light is a key quantum resource that enables quantum advantages for sensing, networking, and computing applications. The scalable generation and manipulation of squeezed light with integrated platforms are highly desired for the development of quantum technology with continuous variables. In this Letter, we demonstrate squeezed light generation with thin-film lithium niobate integrated photonics. Parametric down-conversion is realized with quasi-phase matching using ferroelectric domain engineering. With sub-wavelength mode confinement, efficient nonlinear processes can be observed with single-pass configuration. We measure 0.56 ± 0.09 dB quadrature squeezing (∼2.6 dB inferred on-chip). The single-pass configuration further enables the generation of squeezed light with large spectral bandwidth up to 7 THz. This work represents a significant step towards the on-chip implementation of continuous-variable quantum information processing.

Chen, Pao-Kang↗
DOE OSTI2021

Phase-shifted Bragg gratings in a foundry silicon nitride platform

Bragg gratings are key optical elements for applications in communications, sensing, and lasers. Phase-shifted Bragg gratings are a special case where the simple periodic structure is altered to allow a narrow spectral passband within the optical bandgap. Here, we demonstrate phase-shifted silicon nitride gratings fabricated using 193 nm deep ultraviolet lithography (DUV) on the AIM Photonics 300 mm silicon photonics foundry line. We measure the grating properties and verify the results with a transfer-matrix method (TMM) model. The standard grating expressions for extracting the coupling coefficient κ and bandwidth do not apply and are updated to account for the phase shift. These results inform future designs for on-chip grating filters and distributed feedback (DFB) lasers.

Husko, Chad (ORCID:0000000271252518)↗
DOE OSTI2022

Carrier Dynamics of Polar, Semipolar, and Nonpolar InGaN/GaN LEDs Measured by Small-Signal Electroluminescence

The carrier dynamics in InGaN/GaN light-emitting diodes (LEDs) are directly tied to their efficiency and maximum modulation speed, which are important metrics for solid-state lighting, displays, and optical communication. In this work, we measure the carrier dynamics of a variety of InGaN/GaN LEDs using small-signal electroluminescence methods [1]. A rate equation approach and associated small-signal circuit are used to model carrier injection, recombination in the active region, recombination in the cladding regions, and carrier escape. The model is fit to the measured optical frequency response (S21) and input impedance (S11) of the LEDs to extract the various carrier lifetimes, the carrier density, and the radiative and non-radiative recombination rates. We specifically study planar nonpolar and semipolar LEDs, which show record-high modulation speeds for III-nitride LEDs and present the modulation characteristics of core-shell nanowire-based LEDs. The planar nonpolar m-plane ($101\bar{0}$) micro-LEDs achieve a record-high -3dB modulation bandwidth for a III-nitride LED of 1.5 GHz [2]. The -3dB response of an electrically injected nanowire-based micro-LED with nonpolar facets is also reported, showing a -3dB bandwidth of 1.2 GHz [3]. The high speed is attributed to the shorter carrier lifetime associated with the nonpolar orientation. We also study the carrier dynamics in semipolar ($20\bar{2}\bar{1}$) LEDs for various temperatures [4]. Finally, we present carrier dynamics measurements on commercial-grade c-plane epitaxy for various active region designs, including a wavelength series and a growth quality series. The wavelength series offers insight into the contributions of the quantum confined Stark effect (QCSE) and InGaN material quality on the green gap [5]. The growth quality series investigates the role of non-radiative centers on the LED performance. Extraction of the carrier dynamics using small-signal electroluminescence offers insight into the factors limiting the efficiency and high-speed performance of III-nitride emitters and can be leveraged to ultimately improve the devices.

LEDs, InGaN, electroluminescence, bandwidth, modul↗
DOE OSTI2021

Multiplexable intrinsic Fabry-Pérot interferometers inscribed by femtosecond laser for vibration measurement in high temperature environments

This article reports fabrication technique and demodulation algorithm developments to use multiplexable intrinsic Fabry-Pérot interferometer (IFPI) fiber sensor array for distributed vibration measurements at high temperatures. Using femtosecond laser direct writing scheme, IFPI array were fabricated through laser-induced Type II scattering points in single mode fiber cores. Reflection spectra of IFPI array were demodulated in real-time using modified Bunemen frequency analysis. The demodulation algorithm, which was implemented using a photodetector-array spectrometer, achieves 64-nε dynamic strain resolution at 1-kHz spectral acquisition rate and 2-kHz maximum vibration bandwidth. Performance and stabilities of IFPI sensor array were characterized from room temperatures to 800 °C. The static strain resolution was 0.6 με and the minimum detectable dynamic strain amplitude was 23 nε/√Hz at 800 °C. The multiplex performance was also tested by measuring dynamic strain in time domain through six IFPI sensor array fabricated in one fiber. This paper presents an integrated and low-cost sensing solution to perform distributed vibration measurements in harsh environments.

42 ENGINEERING↗
DOE OSTI2022

Development of a Laser Ultrasonics-based Approach for Rapid Screening of High Entropy Alloys

This project utilized a laser ultrasonic technique to systematically study temperature-induced evolution of material properties in a set of interrelated binary alloys and a high entropy alloy (HEA) fabricated using arc-melting and spark plasma sintering processes. This technique involved the use of a nanosecond duration, high-intensity pulsed laser to thermo-elastically generate ultrasonic waves that propagate in the bulk of the metal alloy. Sub-nanometer-scale displacements associated with the propagating bulk ultrasonic waves were detected along the epicenter on the opposite surface of the sample using a 1 GHz bandwidth photorefractive interferometer. Phase transformations and microstructural changes were inferred from the temperature-dependent trends in the bulk acoustic velocities and features in the ultrasonic epicentral waveforms measured in the binary alloys. These inferences were then correlated with electron/optical microscopy observations and predictions using calculations of phase diagrams (CALPHAD). The results showed that the laser-generated ultrasonic pulses were strongly influenced by changes in material microstructure and could accurately track thermally driven phase transformations and detect the presence of microscale heterogeneities (grain boundaries, dendritic structures, etc.) in the set of binary alloy samples. The measurement approach was then applied to a quinary HEA sample for estimating phase transition temperature and determining microstructural heterogeneity. The rapid, non-contact and non-destructive ultrasonic testing approach demonstrated here is amenable to high throughput combinatorial investigations that can be applied to graded composition HEAs produced using advanced manufacturing methods. When paired with atomistic simulations and CALPHAD modeling, this approach can overcome the bottlenecks faced by current material characterization methods in efficiently screening the vast discovery space of HEAs that spans over a hundred million unique quinary alloy compositions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

ARMing the Edge: Designing Edge Computing–Capable Machine Learning Algorithms to Target ARM Doppler Lidar Processing

Abstract There is a need for long-term observations of cloud and precipitation fall speeds in validating and improving rainfall forecasts from climate models. To this end, the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) site at Lamont, Oklahoma, hosts five ARM Doppler lidars that can measure cloud and aerosol properties. In particular, the ARM Doppler lidars record Doppler spectra that contain information about the fall speeds of cloud and precipitation particles. However, due to bandwidth and storage constraints, the Doppler spectra are not routinely stored. This calls for the automation of cloud and rain detection in ARM Doppler lidar data so that the spectral data in clouds can be selectively saved and further analyzed. During the ARMing the Edge field experiment, a Waggle node capable of performing machine learning applications in situ was deployed at the ARM SGP site for this purpose. In this paper, we develop and test four algorithms for the Waggle node to automatically classify ARM Doppler lidar data. We demonstrate that supervised learning using a ResNet50-based classifier will classify 97.6% of the clear-air images and 94.7% of cloudy images correctly, outperforming traditional peak detection methods. We also show that a convolutional autoencoder paired with k -means clustering identifies 10 clusters in the ARM Doppler lidar data. Three clusters correspond to mostly clear conditions with scattered high clouds, and seven others correspond to cloudy conditions with varying cloud-base heights.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Near-infrared noise in intense electron bunches

This article investigates electron bunch density fluctuations in the 1 −10 μ⁢m wavelength range, focusing on their impact on coherent electron cooling (CEC) in hadron storage rings. In this study, we compare the shot-noise model with experimental observations using bandwidth-filtered near-infrared optical transition radiation (OTR) photodiode signals, where the transverse bunch size is much larger than the OTR wavelength of interest. The relativistic electron bunch (𝛾 ≈ 50) parameters are close to those proposed for the coherent electron cooler in the electron-ion collider (EIC) project. Preliminary feasibility experiments were conducted, and the noise factors are presented, supported by particle tracking. No major density fluctuations or effective cooling rate decrease were revealed for EIC CEC design parameters. Additionally, longitudinal-space-charge-induced microbunching for the chicane-compressed bunch was observed with coherent OTR enhancements up to 100 times, providing further calibration of the measurement method.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

High power edge-cum-surface emitting terahertz laser arrays phased locked by vacuum guided plasmon waves

Terahertz semiconductor quantum-cascade lasers (QCLs) are widely implemented with metallic cavities that support low-loss plasmonic optical modes at long wavelengths. However, resonant optical modes in such cavities suffer from poor radiative characteristics due to their subwavelength transverse dimensions. Consequently, single-mode terahertz QCLs with metallic cavities and large (>100 mW) output power have only been realized in the surface-emitting configuration that affords a large radiating surface. Here, we demonstrate a method to enhance radiative outcoupling from such plasmonic lasers for high-power emission in the edge-emitting (end-fire or longitudinal) direction. Single-sided plasmon waves propagating in vacuum are resonantly excited in surrounding medium of metallic cavities with the QCL semiconductor medium. The vacuum guided plasmon waves with a large wavefront phase-lock multiple metallic cavities longitudinally, which leads to intense radiation in multiple directions, including that in the longitudinal direction in a narrow single-lobed beam. The multicavity array radiates predominantly in a single spectral mode. A peak-power output of 260 mW and a slope efficiency of 303 mW/A are measured for the end-fire beam from a 3.3 THz QCL operating at 54 K in a Stirling cooler. Finally, single-mode operation and lithographic tuning across a bandwidth of ~150 GHz are demonstrated.

42 ENGINEERING↗