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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 163 records · Page 9

An Investigation of Strategies for Sensing Window Attachment Position: Survey of Candidate Technologies, Evaluation, and Deployment Recommendations

While windows are desirable feature in buildings for views, daylighting, and aesthetics, it is important to recognize that windows are a major contributor to a building’s energy load. Interior window coverings, such as shades and blinds, can help improve the energy performance of windows without sacrificing the benefits; however, while appropriate use of window coverings provide the potential for energy savings, there is little consensus regarding how occupants typically use these window attachments, which sometimes puts into question how much energy they actually save in an occupied home. Automated shading control strategies can reduce the uncertainty of energy savings; however, users can overwrite pre-defined schedules or write their own shade control programs to reach their personal comfort and privacy goals. Because it is difficult to identify how occupants interact with window shades, it is difficult to identify the energy savings potential of blinds. To address this problem, this study was developed to identify a candidate sensor that can be deployed to sense blind position. The intended application for this sensor is deployment in energy efficiency field studies so that shade usage can be measured to better understand results and identify the energy impact of specific window attachment technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Flexible Vanadium Dioxide Photodetectors for Visible to Longwave Infrared Detection at Room Temperature

Abstract Flexible optoelectronics is a rapidly growing field, with a wide range of potential applications. From wearable sensors to bendable solar cells, curved displays, and curved focal plane arrays, the possibilities are endless. The criticality of flexible photodetectors for many of these applications is acknowledged, however, devices that are demonstrated thus far are limited in their spectral range. In this study, flexible photodetectors are demonstrated using a VO x nanoparticle ink, with an extremely broad operating wavelength range of 0.4 to 20 µm. This ink is synthesized using a simple and scalable wet‐chemical process. These photodetectors operate at room temperature and exhibit minimal variance in performance even when bent at angles of up to 100 ° at a bend radius of 6.4 mm. In addition, rigorous strain testing of 100 bend and release cycles revealed a photoresponse with a standard deviation of only 0.55%. This combination of mechanical flexibility, wide spectral response, and ease of fabrication makes these devices highly desirable for a wide range of applications, including low‐cost wearable sensors and hyperspectral imaging systems.

36 MATERIALS SCIENCE↗

Application of Distributed Fiber Optic Strain Sensors to LMQXFA Cold Mass Welding

The future High Luminosity upgrade of the Large Hadron Collider (HL-LHC) at CERN will include the low-beta inner triplets (Q1, Q2a/b, Q3) for two LHC insertion regions. The Q1, Q3 components consist of eight 10 m-long LMQXFA cryo-assemblies fabricated by the HL-LHC Accelerator Upgrade Project. Each LMQXFA Cold mass contains two Nb 3 Sn magnets connected in series. A stainless-steel shell is welded around the two magnets before the insertion into the cryostat. There is a limit on how much coil preload increase induced by the shell welding is allowed. Distributed Rayleigh backscattering fiber optics sensors were used for the first time to obtain a strain map over a wide area of a Nb 3 Sn magnet cold mass shell. Finally, data were collected during welding of the first LMQXFA cold mass and the results confirm that the increase of the coil pole azimuthal pre-stress after welding do not exceed requirements.

43 PARTICLE ACCELERATORS↗

A bacterial sensor taxonomy across earth ecosystems for machine learning applications

Microbial communities have evolved to colonize all ecosystems of the planet, from the deep sea to the human gut. Microbes survive by sensing, responding, and adapting to immediate environmental cues. This process is driven by signal transduction proteins such as histidine kinases, which use their sensing domains to bind or otherwise detect environmental cues and “transduce” signals to adjust internal processes. We hypothesized that an ecosystem’s unique stimuli leave a sensor “fingerprint,” able to identify and shed insight on ecosystem conditions. To test this, we collected 20,712 publicly available metagenomes from Host-associated, Environmental, and Engineered ecosystems across the globe. We extracted and clustered the collection’s nearly 18M unique sensory domains into 113,712 similar groupings with MMseqs2. We built gradient-boosted decision tree machine learning models and found we could classify the ecosystem type (accuracy: 87%) and predict the levels of different physical parameters (R2 score: 83%) using the sensor cluster abundance as features. Feature importance enables identification of the most predictive sensors to differentiate between ecosystems which can lead to mechanistic interpretations if the sensor domains are well annotated. To demonstrate this, a machine learning model was trained to predict patient’s disease state and used to identify domains related to oxygen sensing present in a healthy gut but missing in patients with abnormal conditions. Moreover, since 98.7% of identified sensor domains are uncharacterized, importance ranking can be used to prioritize sensors to determine what ecosystem function they may be sensing. Furthermore, these new predictive sensors can function as targets for novel sensor engineering with applications in biotechnology, ecosystem maintenance, and medicine.

97 MATHEMATICS AND COMPUTING↗

Integrating Hybrid-Clustering and Localized Regression for Time Synchronization of a Hierarchical Underwater Acoustic Sensor Array

Time synchronization is a critical requirement for the application of underwater acoustic sensor network (UWSN). Although a number of time synchronization protocols have been proposed for UWSN, none of them can be directly applied to autonomous acoustic receivers due to lack of hardware platform to communicate with each other. In this paper, we propose a machine learning-based time synchronization framework for autonomous receiver arrays, using the Juvenile Salmon Acoustic Telemetry System as a case study. The proposed framework consists of array partition and time synchronization. Using detections of receiver attached beacons as input, this framework synchronizes all receiver clocks to a root receiver clock. The framework has been successfully used in a field study at Trevallyn Dam forebay in Tasmania, Australia.

Fu, Tao↗

Application and Certification of Comparative Vacuum Monitoring Sensors for Structural Health Monitoring of 737 Wing Box Fittings

Multi-site fatigue damage, hidden cracks in hard-to-reach locations, disbonded joints, erosion, impact, and corrosion are among the major flaws encountered in today's extensive fleet of aging aircraft and space vehicles. The use of in-situ sensors for real-time health monitoring of aircraft structures are a viable option to overcome inspection impediments stemming from accessibility limitations, complex geometries, and the location and depth of hidden damage. Reliable, structural health monitoring systems can automatically process data, assess structural condition, and signal the need for human intervention. Prevention of unexpected flaw growth and structural failure can be improved if on-board health monitoring systems are used to continuously assess structural integrity. Such systems are able to detect incipient damage before catastrophic failures occurs. Condition-based maintenance practices could be substituted for the current time-based maintenance approach. Other advantages of on-board distributed sensor systems are that they can eliminate costly, and potentially damaging, disassembly, improve sensitivity by producing optimum placement of sensors and decrease maintenance costs by eliminating more time- consuming manual inspections. This report presents a Sandia Labs-aviation industry effort to move SHM into routine use for aircraft maintenance. This program addressed formal SHM technology validation and certification issues so that the full spectrum of concerns, including design, deployment, performance and certification were appropriately considered. The Airworthiness Assurance NDI Validation Center (AANC) at Sandia Labs, in conjunction with Boeing, Delta Air Lines, Structural Monitoring Systems Ltd., Anodyne Electronics Manufacturing Corp. and the Federal Aviation Administration (FAA) carried out a certification program to formally introduce Comparative Vacuum Monitoring (CVM) as a structural health monitoring solution to a specific aircraft wing box application. Validation tasks were designed to address the SHM equipment, the health monitoring task, the resolution required, the sensor interrogation procedures, the conditions under which the monitoring will occur, the potential inspector population, adoption of CVM into an airline maintenance program and the document revisions necessary to allow for routine use of CVM as an alternate means of performing periodic structural inspects. To carry out the validation process, knowledge of aircraft maintenance practices was coupled with an unbiased, independent evaluation. Sandia Labs designed, implemented, and analyzed the results from a focused and statistically-relevant experimental effort to quantify the reliability of the CVM system applied to the Boeing 737 Wing Box fitting application. All factors that affect SHM sensitivity were included in this program: flaw size, shape, orientation and location relative to the sensors, as well as operational and environmental variables. Statistical methods were applied to performance data to derive Probability of Detection (POD) values for CVM sensors in a manner that agrees with current nondestructive inspection (NDI) validation requirements and also is acceptable to both the aviation industry and regulatory bodies. This report presents the use of several different statistical methods, some of them adapted from NDI performance assessments and some proposed to address the unique nature of damage detection via SHM systems, and discusses how they can converge to produce a confident quantification of SHM performance An important element in developing SHM validation processes is a clear understanding of the regulatory measures needed to adopt SHM solutions along with the knowledge of the structural and maintenance characteristics that may impact the operational performance of an SHM system. This report describes the major elements of an SHM validation approach and differentiates the SHM elements from those found in NDI validation. The activities conducted in this program demonstrated the feasibility of routine SHM usage in general and CVM in particular for the application selected. They also helped establish an optimum OEM-airline-regulator process and determined how to safely adopt SHM solutions. This formal SHM validation will allow aircraft manufacturers and airlines to confidently make informed decisions about the proper utilization of CVM technology. It will also streamline the regulatory actions and formal certification measures needed to assure the safe application of SHM solutions.

42 ENGINEERING↗

Fiber-optic sensor packaging assessment and benchmarking for embedded sensing applications

Fiber optic-based sensing for non-destructive evaluation (NDE) and structural health monitoring of various infrastructure and energy assets is an increasingly important sensing scheme. Because of their immunity to electromagnetic interferences, versatility in sensing mechanisms and designs as well as capability for distributed sensing, the fiber optic sensing is of great interest for embedding within infrastructures using advanced manufacturing methods. However, the protection of fiber optic sensors during advanced manufacturing-based embedding is an important aspect for infrastructure monitoring in practice. While successful installation of fiber optic sensors has been accomplished through application of epoxy or adhesives on infrastructure surfaces, there has been only limited investigation of fiber protection packaging schemes which are compatible with in-situ repair techniques such as the metallic cold-spray. With increasing interest and importance of cold spray-based repair processes, the integration of fiber optic sensors simultaneously during the repair is equally important. In this work, we focus our efforts on investigating various types of packaging schemes for their compatibility and integrability on the surfaces of metallic structures such as oil and gas pipelines during an in-situ repair coating. First, we consider sandblasting using silica sand particles of various size for optical fibers on the surface of a metallic coupon as a useful proxy test of sensor packaging stability. Structural damage of packaging is characterized by means of optical microscopy and the optical integrity of embedded fiber optic cables is examined using optical backscatter reflectometry (OBR). In addition, initial investigation of metallic cold-spray embedded fiber optic cables under various packaging on metallic substrates is also considered with early conclusions and future directions.

Fiber-optic sensors, Sensors packaging, Metallic C↗

Fully‐Printed Ion Sensor Arrays for Measuring Agricultural Nitrogen and Potassium Concentrations Using Nernstian and AI Models

Abstract The chemical composition of growing media is a key factor for plant growth, impacting agricultural yield and sustainability. However, there is a lack of affordable chemical sensors for ubiquitous nutrient ion monitoring in agricultural applications. This work investigates using fully printed ion‐sensor arrays to measure the concentrations of nitrate, ammonium, and potassium in mixed‐electrolyte media. Ion sensor arrays composed of nitrate, ammonium, and potassium ion‐selective electrodes and a printed silver‐silver chloride (Ag/AgCl) reference electrode are fabricated and characterized in aqueous solutions in a range of concentrations that encompass what is typical for agricultural growing media (0.01 m m –1 m ). The sensors are also tested in mixed‐electrolyte solutions of NaNO 3 , NH 4 Cl, and KCl of varying concentrations, and the recorded potentials are input into Nernstian and artificial neural network models to compare the prediction accuracy of the models against ground truth. The artificial neural network models demonstrated higher accuracy over the Nernstian model, and the model using only ion‐sensor inputs is 7.5% more accurate than the Nernstian model under the same conditions. By enabling more precise and efficient fertilizer application, these sensor arrays coupled to computational models can help increase crop yields, optimize resource use, and reduce environmental impact.

Goodrich, Payton [University of California Berkele↗

Aerosol jet printed 3 omega sensors for thermal conductivity measurement

The 3 omega (3ω) method is a trusted technique for measuring thermal conductivity—a fundamental material property of critical importance in a broad range of applications. However, traditional 3ω sensor processing requires some form of physical vapor deposition, such as metal evaporation or sputtering. These 3ω sensor deposition techniques limit the materials and sample sizes applicable to the 3ω method. This work demonstrates an aerosol jet printing method to directly print silver 3ω sensors that yield accurate temperature-dependent measurement up to 300 °C on materials with thermal conductivity ranging from 1 to 150 W/m K. The interrelationship between printed sensor geometry, sensor thermal stability, and applicability to the 3ω method is examined. Thermal conductivity measurement with 3ω sensors conventionally sintered at 300 °C agrees to independent laser flash measurement within 4% from room temperature to 150 °C. An unconventional rapid high-temperature sintering method is shown to produce sensors that agree within 3% of the laser flash measurements from room temperature to 300 °C. The rapid sintering profiles also reduced the sensor–substrate thermal boundary resistance of the printed sensors by as much as 88%. The direct printing of 3ω sensors creates opportunities for measurement of thermal transport properties in applications previously inapplicable to the 3ω method.

47 OTHER INSTRUMENTATION↗

Contracted, Not Converted: Photoluminescence Thermochromism in Ultrabright Pure Blue Emissive Hybrid Copper(I) Halide

Thermochromic luminescent materials are promising for applications such as sensors or display technologies. Understanding the mechanism of thermochromic luminescence in these materials plays an important role for their targeted applications. Here, a 0D copper(I) halide (TMP)2CuBr3 and 1D (TMP)Ag2Br3 (TMP = tetramethylphosphonium) are reported. While (TMP)Ag2Br3 is a weak light emitter, (TMP)2CuBr3 demonstrates ultrabright pure blue emission with photoluminescence (PL) quantum yield exceeding 90% within the temperature range 300–80 K. The emission in (TMP)2CuBr3 is attributed to the radiative recombination of self-trapped excitons (STEs) that arise localized on [CuBr3]2− anions. (TMP)2CuBr3 demonstrates excitation-selective PL thermochromism at low temperatures. In the literature, the origin of multiple STEs is often unclear in luminescent metal halides. Here, a detailed temperature-dependent spectroscopic and structural analysis suggests that the PL thermochromism in (TMP)2CuBr3 is associated with the appearance of a second STE state. The appearance of second STE is expected to have a structural origin, and it may be associated with the observed anomaly in thermal contraction near 200 K. The distinct PL features of melt-processible (TMP)2CuBr3 coupled with its remarkable photo- and thermal stability allow its consideration for practical optical applications, including temperature sensing.

Popy, Dilruba [University of Oklahoma, Norman]↗

Review—Electrolytic Metal Atoms Enabled Manufacturing of Nanostructured Sensor Electrodes

Sensing materials play a key role in the successful implementation of electrochemical sensors, and nanotechnology has emerged as an important and rapidly growing field for stimulating the innovation of high-performance sensors. The fabrication, characterization, and evaluation of the nanostructured electrodes are therefore a focus of this field. Compared to a variety of dry and wet technologies which have been extensively developed for this purpose, electrochemical methods are typically convenient, highly effective, and potentially low-cost for the production of different nanostructures. This minireview is designed to introduce a unique electrochemical method - electrolytic metal-atom enabled manufacturing (EM 2 ) and its application in electrochemical sensors. The EM 2 technique employs electrolytic metal atoms generated from their corresponding salt precursor as a tool to nanostructure a wide range of substrate electrodes used in electrochemical sensors, based on a one-pot electrochemical deposition and dissolution of the metal atoms in the same electrolyte bath. Briefly, the metal atoms are electrodeposited on a substrate electrode during the cathode reduction, and they are selectively removed from the substrate during the subsequent anode oxidation. Because of the interactions between the electrolytic metal atoms and the substrate atoms, the repetitive electrodeposition and dissolution of the former on the substrate enable the nanostructuration of the substrate, particularly within its surface layers. The nanostructured electrodes have demonstrated very attractive performance for the determination of numerous analytes, such as high sensitivity and selectivity, high interference tolerance, and low detection limits. However, the EM 2 technique and the application of the resulting nanostructured electrodes in electrochemical sensors and beyond have still been very limitedly investigated. In order to bring the community from academic, industries, agencies, and customers together to develop the EM 2 technique and advance electrochemical sensor systems, this minireview will introduce the thermodynamic and kinetic fundamentals of this technique, the characterization of resulting nanostructures, the analysis of their electrochemical behavior, and the implementation of this technique for the development of advanced sensor electrodes. Finally, an outlook with a focus on further research areas is provided.

Jiang, Junhua (ORCID:0000000324379812)↗

Novel Sensors for Particle Tracking: a Contribution to the Snowmass Community Planning Exercise of 2021

Five contemporary technologies are discussed in the context of their potential roles in particle tracking for future high energy physics applications. These include sensors of the 3D configuration, in both diamond and silicon, submicron-dimension pixels, thin film detectors, and scintillating quantum dots in gallium arsenide. Drivers of the technologies include radiation hardness, excellent position, vertex, and timing resolution, simplified integration, and optimized power, cost, and material.

Detectors↗

Novel Sensors for Particle Tracking: a Contribution to the Snowmass Community Planning Exercise of 2021

Five contemporary technologies are discussed in the context of their potential roles in particle tracking for future high energy physics applications. These include sensors of the 3D configuration, in both diamond and silicon, submicron-dimension pixels, thin film detectors, and scintillating quantum dots in gallium arsenide. Drivers of the technologies include radiation hardness, excellent position, vertex, and timing resolution, simplified integration, and optimized power, cost, and material.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Anti-distortion bioinspired camera with an inhomogeneous photo-pixel array

The bioinspired camera, comprising a single lens and a curved image sensor—a photodiode array on a curved surface—, was born of flexible electronics. Its economical build lends itself well to space-constrained machine vision applications. The curved sensor, much akin to the retina, helps image focusing, but the curvature also creates a problem of image distortion, which can undermine machine vision tasks such as object recognition. Here we report an anti-distortion single-lens camera, where 4096 silicon photodiodes arrayed on a curved surface in a nonuniform pattern assimilated to the distorting optics are the key to anti-distortion engineering. That is, the photo-pixel distribution pattern itself is warped in the same manner as images are warped, which correctively reverses distortion. Acquired images feature no appreciable distortion across a 120° horizontal view, as confirmed by their neural-network recognition accuracies. This distortion correction via photo-pixel array reconfiguration is a form of in-sensor computing.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Gain balanced nonlinear optical interferometer

A nonlinear fiber interferometer is disclosed suitable for fiber sensor and other applications. A first nonlinear fiber section amplifies probe and conjugate sidebands of a pump through four-wave mixing. A second section introduces a phase shift to be measured, for example from a sensor. A third nonlinear fiber section amplifies with phase-sensitive gain to increase signal-to-noise ratio. Based on phase-sensitive output power of probe and/or conjugate components, the phase shift can be measured. Superior performance can be obtained by balancing gain between the (first and third) nonlinear sections. Non-fiber, for example photonic integrated circuit, embodiments are disclosed. Differential sensing, alternative detection schemes, sensing applications, associated methods, and other variations are disclosed.

42 ENGINEERING↗