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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 289 records · Page 16

Embedded acoustic sensing and monitoring techniques for small modular reactors

The goal of this project was to study the applicability of specific innovative instrumentation techniques for assessing parameters needed for safe small modular reactor operation and safeguarding of nuclear material. Small modular reactor core designs are currently being developed to provide energy more effectively and efficiently than in the past because they can be built as modules at fabrication sites and then transported to a power-producing facility. However, these modules and/or the final core will often be sealed and not accessible again until disposal. Instead of instruments that access the core directly, during and after operation, to monitor flux/dose and structural integrity, as current power plants use, new sensors need to be designed that can be built into the reactor initially to determine operating history, structural integrity through operation of the system, and nuclear material accountancy after shutdown and before disposition of the core. Embedded sensors already exist that can provide neutron flux, gamma dose, and temperatures, but techniques to expand upon these for assessing structural health and material inventory in the system over time need to be developed. Structural health assessments include the detection and imaging of cracks in the components that could eventually cause radioactive fission products to be released.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Development of risk mitigation guidance for sensor placement inside mechanically ventilated enclosures – Phase 1

Guidance on Sensor Placement was identified as the top research priority for hydrogen sensors at the 2018 HySafe Research Priority Workshop on hydrogen safety in the category Mitigation, Sensors, Hazard Prevention, and Risk Reduction. This paper discusses the initial steps (Phase 1) to develop such guidance for mechanically ventilated enclosures. This work was initiated as an international collaborative effort to respond to emerging market needs related to the design and deployment equipment for hydrogen infrastructure that is often installed in individual equipment cabinets or ventilated enclosures. The ultimate objective of this effort is to develop guidance for an optimal sensor placement such that, when integrated into a facility design and operation, will allow earlier detection at lower levels of incipient leaks, leading to significant hazard reduction. Reliable and consistent early warning of hydrogen leaks will allow for the risk mitigation by reducing or even eliminating the probability of escalation of small leaks into large and uncontrolled events. To address this issue, a study of a real-world mechanically ventilated enclosure containing GH2 equipment was conducted, where CFD modeling of the hydrogen dispersion (performed by AVT and UQTR, and independently by the JRC) was validated by the NREL Sensor laboratory using a Hydrogen Wide Area Monitor (HyWAM) consisting of a 10-point gas and temperature measurement analyzer. In the release test, helium was used as a hydrogen surrogate. Expansion of indoor releases to other larger facilities (including parking structures, vehicle maintenance facilities and potentially tunnels) and incorporation into QRA tools, such as HyRAM is planned for Phase 2. It is anticipated that results of this work will be used to inform national and international standards such as NFPA 2 Hydrogen Technologies Code, Canadian Hydrogen Installation Code (CHIC) and relevant ISO/TC 197 and CEN documents.

08 HYDROGEN↗

High-Performance Piezo-Electrocatalytic Sensing of Ascorbic Acid with Nanostructured Wurtzite Zinc Oxide

We report nanostructured piezoelectric semiconductors offer unprecedented opportunities for high-performance sensing in numerous catalytic processes of biomedical, pharmaceutical, and agricultural interests, leveraging piezocatalysis that enhances the catalytic efficiency with the strain-induced piezoelectric field. Here, we design and demonstrate for the first time a cost-efficient, high-performance piezo-electrocatalytic sensor for detecting L-ascorbic acid (AA), a critical chemical for many organisms, metabolic processes, and medical treatments. We prepared ZnO nanorods and nanosheets to characterize and compare their efficacy for the piezo-electrocatalysis of AA. The electrocatalytic efficacy of AA was significantly boosted by the piezoelectric polarization induced in the nanostructured semiconducting ZnO catalysts. We elucidated the charge transfer between the strained ZnO nanostructures and AA to reveal the mechanism for the related piezo-electrocatalytic process. The low-temperature synthesis of high-quality ZnO nanostructures allows the low-cost, scalable production and integration directly into wearable electrocatalytic sensors whose performance could be boosted by otherwise wasted mechanical energy from the working environment, e.g., the human-generated mechanical signals.

30 DIRECT ENERGY CONVERSION↗

Bidirectional Suzuki Catalyst Transfer Polymerization of Poly( p -phenylene)

Suzuki catalyst transfer polymerization (SCTP) has emerged as an effective method for accessing length-controlled π-conjugated poly(p-phenylene). Regio-controlled functional group sequencing along the backbone and the chain ends of synthetic polymers remains a challenge for the successful integration of organic semiconductors in sensors and electronic devices. Here, we report a bidirectional SCTP system based on dinuclear palladium(II) initiators. Functional groups transferred during the initiation and termination steps unlock independently addressable synthetic handles at the polymer core and respective chain ends. These functional groups open opportunities for late-stage regio-controlled and chemoselective derivatizations. Control over key polymer parameters, including molecular weight (M n ), dispersity ( Đ = M w /M n ), degree of polymerization ( DP ), termination efficiency, and functional group interconversion, is corroborated by size exclusion chromatography (SEC) and NMR spectroscopy. The modular design of SCTP initiators, in combination with commercially available terminating groups, represents a highly flexible toolbox for late-stage polymer conjugation, e.g., chemoselective anchoring groups for integration with functional electronics or bioorthogonal conjugation for molecular sensing.

Aldehydes↗

Low-phase-noise surface-acoustic-wave oscillator using an edge mode of a phononic band gap

Low-phase-noise microwave-frequency integrated oscillators provide compact solutions for various applications in signal processing, communications, and sensing. Surface acoustic waves (SAWs), featuring orders-of-magnitude shorter wavelength than electromagnetic waves at the same frequency, enable integrated microwave-frequency systems with much smaller footprint on chip. SAW devices also allow higher-quality (Q) factors than electronic components at room temperature. Here, we demonstrate a low-phase-noise gigahertz-frequency SAW oscillator on 128°Y-cut lithium niobate, where the SAW resonator occupies a footprint of 0.05 mm 2 . Leveraging phononic crystal band-gap-edge modes to balance between Q factors and insertion losses, our 1-GHz SAW oscillator features a low phase noise of -132.5 dBc/Hz at a 10-kHz offset frequency and an overlapping Hadamard deviation of 6.5 × 10 -10 at an analysis time of 64 ms. The SAW resonator-based oscillator holds high potential in developing low-noise sensors and acousto-optic integrated circuits.

42 ENGINEERING↗

Multimodal sensor fusion for real-time standoff estimation in directed energy deposition

In Laser Powder-based Direct Energy Deposition (LP-DED) systems, achieving consistency, precision and quality of produced parts requires tight control over printing parameters. One of the critical parameters is the standoff distance. Maintaining an optimal standoff height is crucial for achieving correct laser power density and powder catchment efficiency, as both laser and powder streams are focused at this distance. Here, this study introduces a novel approach using multimodal sensor fusion to predict standoff height in real-time. The proposed system integrates two low-profile, cost-effective sensors: an RGB coaxial camera and a high frequency and high dynamic range microphone. By utilizing a simple fully connected neural network, trained on a limited dataset, data fusion of these sensors allowed for the real-time prediction of the standoff height. The results demonstrate high resolution and accuracy of the predictions across multiple geometries and a wide range of standoff heights. This approach offers a simple, and cost-effective solution for real-time standoff height monitoring and lays the groundwork for future integration into commercial LP-DED systems.

42 ENGINEERING↗

Parallelized telecom quantum networking with an ytterbium-171 atom array

The integration of quantum computers and sensors into a quantum network enables new capabilities in quantum information science. Most networks with atom-like qubits operate at visible or near-ultraviolet wavelengths and require conversion to the telecom band for long-distance communication, which reduces efficiency and potentially introduces noise. In this article we report high-fidelity entanglement between ytterbium-171 atoms and optical photons generated directly in the telecommunication band, where fibre loss is low. The nuclear spin of the atom is entangled with a single photon in the time-bin basis, yielding a high atom-measurement-corrected atom–photon Bell state fidelity. This can be further improved by addressing photon measurement errors. By imaging the atom array onto an optical fibre array, we also implement a parallelized networking protocol that can increase the remote entanglement rate proportionately with the number of channels. We also preserve coherence on a memory qubit during operations on communication qubits. These results support the integration of atomic systems into scalable quantum networks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Air quality and health impacts of the 2020 wildfires in California

Abstract Background Wildfires in 2020 ravaged California to set the annual record of area burned to date. Clusters of wildfires in Northern California surrounded the Bay Area covering the skies with smoke and raising the air pollutant concentrations to hazardous levels. This study uses the Fire Inventory from the National Center for Atmospheric Research database and the Community Multiscale Air Quality model to estimate the effects of wildfire emissions on air quality during the period from August 16 to October 28 of 2020. In addition, low-cost sensor data for fine particulate matter (PM 2.5 ) from the PurpleAir network is used to enhance modeled PM 2.5 concentrations. The resulting impacts on ozone and PM 2.5 are used to quantify the health impacts caused by wildfires using the Benefits Mapping and Analysis Program – Community Edition. Results Wildfire activity significantly increased direct PM 2.5 emissions and emissions of PM 2.5 and ozone precursors. Direct PM 2.5 emissions surged up to 38 times compared to an average day. Modeling results indicated that wildfires alone led to a rise in ozone daily maximum 8-h average by up to 10 ppb and exceeded PM 2.5 air quality standards in numerous locations by up to 10 times. While modeled PM 2.5 concentrations were lower than measurements, correcting these with PurpleAir data improved the accuracy. The correction using PurpleAir data increased estimates of wildfire-induced mortality due to PM 2.5 exposure by up to 16%. Conclusions The increased hospital admissions and premature mortality attributed to wildfires were found to be comparable to the health impacts avoided by strategies aimed at meeting ozone and PM2.5 air quality standards. This suggests that widespread wildfire emissions can negate years of efforts dedicated to controlling air pollution. The integration of low-cost sensor data proved invaluable in refining the estimates of health impacts from PM2.5 resulting from wildfires.

54 ENVIRONMENTAL SCIENCES↗

Ultra-Low SWaP CO 2 Sensing for Demand Control Ventilation (Final Report)

In this project PARC and Energy ETC aimed to develop an ultra-low cost, size, weight, and power (SWaP) printed CO 2 sensor system for occupancy detection to enable Demand Control Ventilation (DCV) on a per-room basis. The CO 2 sensor technology is based on the temperature variation when CO 2 reversibly physisorbs to a highly conductive and high surface area sorbent surface, and is compatible with integration with PARC innovations in printed sensors and flexible electronics, for which PARC is a globally leading research center. The printed CO 2 sensor itself is designed to be compatible with PARC’s “peel-and-stick” platform of ultra-low power, low-cost, distributed sensors, and to facilitate real-time DCV based on overall indoor air quality (IAQ). Previously, PARC has developed flexible hybrid electronics (FHE) compatible materials to measure humidity, temperature, light, strain, and gases such as carbon monoxide, methane, ammonia, and hydrogen sulfide. Through this project, PARC developed FHE-compatible materials to measure CO 2 . Thus, with one <$15 FHE “peel-and-stick” based sensor node, a building management system (BMS) will be able to capture a complete picture of the indoor environment. This includes IAQ, light, temperature, and other comfort factors that impact building operations. Combined with optimized DCV, this low-cost sensor capability can be a key enabler of annual primary energy savings of ~ 0.3-0.4 Quad in commercial buildings while ensuring healthy IAQ. Energy ETC is a leader in supplier-agnostic BMS deployments and will design the commissioning and deployment procedures to maximize system interoperability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Time-resolved X-ray diffraction diagnostic development for the National Ignition Facility

Here we present the development of an experimental platform that can collect four frames of x-ray diffraction data along a single line of sight during laser-driven, dynamic-compression experiments at the National Ignition Facility. The platform is comprised of a diagnostic imager built around ultrafast sensors with a 2-ns integration time, a custom target assembly that serves also to shield the imager, and a 10-ns duration, quasi-monochromatic x-ray source produced by laser-generated plasma. We demonstrate the performance with diffraction data for Pb ramp compressed to 150 GPa and illuminated by a Ge x-ray source that produces ∼7 × 10 11 , 10.25-keV photons/ns at the 400 μm diameter sample.

36 MATERIALS SCIENCE↗

Embedding of Fiber Optic Sensors in Stainless Steel for Sensing in Harsh Environments

Structural health monitoring is critical for components working in harsh environments to assess their safety and integrity. This can be realized with advanced sensors, such as fiber optic sensors, embedded in these components. Recent studies have used ultrasonic consolidation (UC) and laser-based additive manufacturing (AM) techniques to embed fiber optic sensors in metals. However, sensor embedding using these techniques has been challenging, with gaps and voids around the embedded fiber. Successful embedding of fiber optic sensors requires good contact between the fiber and the matrix to eliminate potential gas/liquid leaks in critical systems such as in nuclear and aerospace services. Defect-free fiber/matrix bond is also essential for accurate measurement of parameters of interest, such as temperature and strain. This study developed a novel fiber embedding technique based on electric field-assisted sintering (EFAS). Sapphire optical fibers with diameters of 125 µm and 250 µm were embedded in stainless steel (SS) 316L using EFAS. The embedding was completed by sintering SS 316L powders at a pressure of 50MPa, hold time of 5 min, and temperatures of 1000°C, 1100°C, and 1200°C. Joule heating mechanism during EFAS enabled rapid sintering of the SS 316L powder with resulting sample densities over 99%. Microscopy analysis performed on the cross-sections revealed a defect-free bond between the embedded fiber and SS 316L. The good integrity of the embedded fiber was evidenced by optical transmittance measurement. Optical attenuation of the fiber before and after embedment was examined in the near-infrared region. Scanning electron microscopy was employed to investigate the grain morphology of SS 316L near the embedded fiber. Hardness distribution in the sintered part was also investigated to study the effect of the embedded fiber on the mechanical properties of the as-fabricated component. The results indicated that EFAS was able to embed fiber in SS with good fiber functionality and part quality.

36 - MATERIALS SCIENCE↗

Semiconductor-compatible topological digital alloys

Recently, GeSn alloys have attracted much interest for direct-gap infrared photonics and as potential topological materials which are compatible with the semiconductor industry. However, for photonics, the high-Sn content required leads to low detectivity, associated with poor material quality, and the (>35 %) Sn required for topological properties have been out of reach experimentally. Here, we demonstrate that by patterning the Sn distribution within Ge, the electronic properties have a far greater tunability than is possible with the random alloy. For the GeSn δ-digital alloy (DA) formed by confining Sn atoms in atomic layer(s) along the [111] direction of Ge, we show that ∼ 10 % Sn can lead to a triple-point semimetal. These findings are understood in terms of Sn ordering causing spatial separation of Sn and Ge band edges, leading to band inversion. This mechanism can also lead to a weak topological insulator, Weyl semimetal, and enables tunable direct bandgaps down to 2 meV, covering the entire infrared range. This DA induced topological properties are also identified in compound semiconductors, such as InAs 1-x Sb x , showing the general applicability of the DA design for realizing topological properties on conventional semiconductor platforms. Furthermore, our findings not only point to a new class of currently unexplored topological systems accessible by epitaxy, but also establish the promise of low-Sn GeSn DAs for application as infrared laser diodes and photodetectors in Si photonic integrated circuits and infrared image sensors.

3D topological semimetal↗

Self-powered ocean buoy using a disk-type triboelectric nanogenerator with a mechanical frequency regulator

Triboelectric nanogenerator (TENG) systems have been demonstrated to generate power with high density. However, the electrical output power obtained from wave energy harvesting using TENG systems is typically limited to several milliwatts. To address this limitation and support various ocean buoy systems, an efficient method to scale-up TENG systems is required. In this paper, we present a self-powered ocean buoy (SPOB) incorporating a disk-type, soft-contact, mechanical frequency regulator TENG (DSMFR-TENG). The mechanical frequency regulator (MFR) enables the conversion of low-frequency wave energy to high-speed mechanical rotation, facilitating high power generation with the disk-type TENG. Here, the SPOB was tested in a wave tank, reaching a peak power output of 470 mW and an average power output of 130 mW after the MFR released the rotational energy. To further enhance the functionality of the buoy, the DSMFR-TENG and a microcontroller, temperature sensor, and acoustic transmitter were integrated with the SPOB. The acoustic transmitter successfully transmitted signals 7, 23, and 30 times over a one-minute period at wave frequencies of 0.33 Hz, 0.5 Hz, and 1 Hz, respectively, thereby demonstrating the power supply capability of the TENG system for ocean buoys.

42 ENGINEERING↗

Incubating advances in integrated photonics with emerging sensing and computational capabilities

As photonic technologies grow in multidimensional aspects, integrated photonics holds a unique position and continuously presents enormous possibilities for research communities. Applications include data centers, environmental monitoring, medical diagnosis, and highly compact communication components, with further possibilities continuously growing. Herein, we review state-of-the-art integrated photonic on-chip sensors that operate in the visible to mid-infrared wavelength region on various material platforms. Among the different materials, architectures, and technologies leading the way for on-chip sensors, we discuss the optical sensing principles that are commonly applied to biochemical and gas sensing. Our focus is on passive optical waveguides, including dispersion-engineered metamaterial-based structures, which are essential for enhancing the interaction between light and analytes in chip-scale sensors. We harness a diverse array of cutting-edge sensing technologies, heralding a revolutionary on-chip sensing paradigm. Our arsenal includes refractive-index-based sensing, plasmonics, and spectroscopy, which forge an unparalleled foundation for innovation and precision. Furthermore, we include a brief discussion of recent trends and computational concepts, incorporating Artificial Intelligence & Machine Learning (AI/ML) and deep learning approaches over the past few years to improve the qualitative and quantitative analysis of sensor measurements.

Jain, Sourabh (ORCID:0000000279923275)↗

Event-driven readout development: testing of the EDWARD65P1 chip with integrated event generators

Building on a prototype readout integrated circuit for segmented silicon sensors with the EDWARD event-driven readout architecture, the front-end in each pixel was replaced by a hardware generator to verify readout performance, ensuring no data loss, consistent priority handling, and speed verification. Here, this generator produces Poisson-distributed readout requests with individually tunable rates per pixel via a digitally controlled oscillator. The resulting EDWARD65P1 test ASIC is a 32×32 pixel matrix with a 100 μm pitch, equipped with digital event generators simulating radiation hits at user-defined rates. Test results for this new design are presented.

47 OTHER INSTRUMENTATION↗

Ampk alpha2 T172 activation dictates exercise performance and energy transduction in skeletal muscle

Adenosine 5′-monophosphate–activated protein kinase (AMPK) is an energetic sensor for metabolic regulation and integration. Here, we used CRISPR-Cas9 to generate nonactivatable Ampkα knock-in (KI) mice with mutation of threonine-172 phosphorylation site to alanine (T172A), circumventing the limitations of previous genetic interventions that disrupt the protein stoichiometry. KI mice of Ampkα2, but not Ampkα1, demonstrated phenotypic changes with increased fat-to-lean mass, impaired endurance exercise capacity, and diminished mitochondrial maximal respiration and conductance in skeletal muscle. Integrated temporal multiomics analysis (proteomics/phosphoproteomics/metabolomics) in skeletal muscle at rest and during exercise establishes a pleiotropic yet imperative role of Ampkα2 T172 activation for glycolytic and oxidative metabolism, mitochondrial respiration, and contractile function. There is a substantial overlap of skeletal muscle proteomic changes in Ampkα2 T172A KI mice with that of patients with type 2 diabetes. Our findings suggest that Ampkα2 T172 activation is critical for exercise performance and energy transduction in skeletal muscle and may serve as a therapeutic target for type 2 diabetes.

Bioenergetics↗

Enabling human–infrastructure interfaces for inspection using augmented reality

Decaying infrastructure maintenance cost allocation depends heavily on accurate and safe inspection in the field. New tools to conduct inspections can assist in prioritizing investments in maintenance and repairs. The industrial revolution termed as “Industry 4.0” is based on the intelligence of machines working with humans in a collaborative workspace. Contrarily, infrastructure management has relied on the human for making day-to-day decisions. New emerging technologies can assist during infrastructure inspections, to quantify structural condition with more objective data. However, today’s owners agree in trusting the inspector’s decision in the field over data collected with sensors. If data collected in the field is accessible during the inspections, the inspector decisions can be improved with sensors. New research opportunities in the human–infrastructure interface would allow researchers to improve the human awareness of their surrounding environment during inspections. This article studies the role of Augmented Reality (AR) technology as a tool to increase human awareness of infrastructure in their inspection work. The domains of interest of this research include both infrastructure inspections (emphasis on the collection of data of structures to inform management decisions) and emergency management (focus on the data collection of the environment to inform human actions). This article describes the use of a head-mounted device to access real-time data and information during their field inspection. The authors leverage the use of low-cost smart sensors and QR code scanners integrated with Augmented Reality applications for augmented human interface with the physical environment. This article presents a novel interface architecture for developing Augmented Reality–enabled inspection to assist the inspector’s workflow in conducting infrastructure inspection works with two new applications and summarizes the results from various experiments. The main contributions of this work to computer-aided community are enabling inspectors to visualize data files from database and real-time data access using an Augmented Reality environment.

Maharjan, D.↗

Project Title: Development of a Pipe Crawler Inspection Tool for Fossil Energy Power Plants (Final Report)

This research effort focuses on the development of a pipe crawler inspection tool for fossil energy power plants. The pipe crawler is tethered and can navigate through 2 inch pipes that are often found in various systems within a power plant. The crawler can navigate through straight pipes and 180 degree elbows and includes instrumentation that can assess the integrity of the pipes. The sensors include a UT sensor for measuring the thickness of the pipe, a range finder and a camera. An additional module is used to prep the surface of the pipe prior to taking thickness measurements. Both bench scale and engineering scale testing was conducted to demonstrate the concept. Multiple crawlers were created and tethered together to distribute the load of the tether so that the crawler can navigate longer pipe distances.

01 COAL, LIGNITE, AND PEAT↗