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DOE OSTI2018

Wearable sweat sensors

© 2018 Macmillan Publishers Limited, Part of Springer Nature. All Rights Reserved. Sweat potentially contains a wealth of physiologically relevant information, but has traditionally been an underutilized resource for non-invasive health monitoring. Recent advances in wearable sweat sensors have overcome many of the historic drawbacks of sweat sensing and such sensors now offer methods of gleaning molecular-level insight into the dynamics of our bodies. Here we review key developments in sweat sensing technology. We highlight the potential value of sweat-based wearable sensors, examine state-of-The-Art devices and the requirements of the underlying components, and consider ways to tackle data integrity issues within these systems. We also discuss challenges and opportunities for wearable sweat sensors in the development of personalized healthcare.

Bariya, M↗

DOE OSTI2019

Structural determination of Enzyme-Graphene Nanocomposite Sensor Material

State-of-the-art ultra-sensitive blood glucose-monitoring biosensors, based on glucose oxidase (GOx) covalently linked to a single layer graphene (SLG), will be a valuable next generation diagnostic tool for personal glycemic level management. We report here our observations of sensor matrix structure obtained using a multi-physics approach towards analysis of small-angle neutron scattering (SANS) on graphene-based biosensor functionalized with GOx under different pH conditions for various hierarchical GOx assemblies within SLG. We developed a methodology to separately extract the average shape of GOx molecules within the hierarchical assemblies. The modeling is able to resolve differences in the average GOx dimer structure and shows that treatment under different pH conditions lead to differences within the GOx at the dimer contact region with SLG. The coupling of different analysis methods and modeling approaches we developed in this study provides a universal approach to obtain detailed structural quantifications, for establishing robust structure-property relationships. This is an essential step to obtain an insight into the structure and function of the GOx-SLG interface for optimizing sensor performance.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Assessment of the Impact of Realistic Sensor Physics and the Integration of Ex-Core Sensors on Reactor Power Synthesis

In the work documented in this report, a weighting function–based core power synthesis method was applied to multiple Monte Carlo N-Particle (MCNP) reactor models, which are informed based on simulated self-powered neutron detector (SPND) responses. The weighting function method used has been coined the point-based iterative (PBI) method. The goal of this application is to assess the impact of considering realistic sensor physics in the generation of the simulated SPND outputs as well as to consider how the synthesis is impacted based on the inclusion of ex-core detectors in the model. The NuScale small modular reactor (SMR) and Westinghouse AP1000 pressurized water reactor (PWR) are the models that served as the testbeds for the assessment of realistic sensor physics; this was achieved by using Geant4 SPND models in comparison with analytical models, such that the effect of electron transport in realistic SPND geometries in the Geant4 model can be understood in terms of synthesis error and convergence time. The comparison was considered for fuel burnup–induced perturbations, for a range of sensor string densities and synthesized power distribution axial fidelities. The Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor MCNP model was used to assess the impact of ex-core sensors; this was done by performing synthesis with and without the ex-core detectors and by quantifying the synthesis error and number of iterations associated with Gaussian-type perturbations in many locations in the core. The TAMU TRIGA model was particularly pertinent for this study because of the interest in future experimental tests with SPNDs in this reactor, as well as the ease of modifying the MCNP model to include ex-core detectors with heterogeneously described response functions. Results from the comparison between the Geant4 and analytical SPND models indicate that similar average and maximum synthesis errors were obtained for burnup-induced perturbations in both the NuScale SMR and the AP1000. This was true for a range of sensor string densities and axial fidelities. However, there were marked differences between both the Geant4 and analytically informed models in terms of the iterations required to converge on the synthesized power distribution. Namely, the Geant4-informed models tended to lead to fewer iterations, except for a few sensor–core configurations that had particularly numerous iterations. Results from the ex-core sensor assessment with the TAMU TRIGA model indicate that the inclusion of ex-core sensors drastically reduces the synthesis error of Gaussian-type perturbations close to the edge of the core, and it slightly reduces synthesis errors for perturbations closer to the center of the core. This was achieved with a minimal increase in computational cost—that is, the number of iterations required for convergence. The errors were identified to be in the same location as the perturbation in the core, indicating that the methodology remains robust for unperturbed regions of the core. A secondary result from this study with the TAMU TRIGA was yielded by analysis of the neutron flux levels in the in-core and ex-core sensor locations of the core; these flux levels indicate that SPNDs could be used as both in-core and ex-core sensors, so long as the emitter material is sensitive to thermal neutrons. The results from these studies provide a quantitative understanding of the importance of considering realistic sensor physics and including ex-core sensors to perform accurate and timely power distribution synthesis of a reactor core.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1975

SEPS guidance and navigation autonomy selection via mission analysis

A systematic rationale for selecting a cost-effective guidance and navigation (G & N) autonomy level for the solar electric propulsion stage (SEPS) vehicle is developed. After a definition of autonomy levels, a mission analysis is performed for representative SEPS missions using realistic G & N sensor hardware. Cost data for fabricating, integrating and refurbishing onboard avionics hardware and the ground costs corresponding to each autonomy level are generated. Results are presented that indicate performance of various G & N sensor hardware sets and the dominating factors which influence G & N autonomy level selection.

Causey, W.↗

NASA NTRS2011

Capacitance Based Moisture Sensing for Microgravity Plant Modules: Sensor Design and Considerations

Life support systems for growing plants in microgravity should strive for providing optimal growing conditions and increased automation. Accurately tracking soil moisture content can forward both of these aims, so an attempt was made to instrument a microgravity growth module currently in development, the VEGGIE rooting pillow, in order to monitor moisture levels. Two electrode systems for a capacitance-based moisture sensor were tested. Trials with both types of electrodes showed a linear correlation between observed capacitance and water content over certain ranges of moisture within the pillows. Overall, both types of the electrodes and the capacitance-based moisture sensor are promising candidates for tracking water levels for microgravity plant growth systems.

Schaber, Chad L.↗

NASA NTRS2004

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

Source record↗

NASA NTRS2012

Advanced Fire Detector for Space Applications

A document discusses an optical carbon monoxide sensor for early fire detection. During the sensor development, a concept was implemented to allow reliable carbon monoxide detection in the presence of interfering absorption signals. Methane interference is present in the operating wavelength range of the developed prototype sensor for carbon monoxide detection. The operating parameters of the prototype sensor have been optimized so that interference with methane is minimized. In addition, simultaneous measurement of methane is implemented, and the instrument automatically corrects the carbon monoxide signal at high methane concentrations. This is possible because VCSELs (vertical cavity surface emitting lasers) with extended current tuning capabilities are implemented in the optical device. The tuning capabilities of these new laser sources are sufficient to cover the wavelength range of several absorption lines. The delivered carbon monoxide sensor (COMA 1) reliably measures low carbon monoxide levels even in the presence of high methane signals. The signal bleed-over is determined during system calibration and is then accounted for in the system parameters. The sensor reports carbon monoxide concentrations reliably for (interfering) methane concentrations up to several thousand parts per million.

Kutzner, Joerg↗

DOE OSTI2023

Spatial and temporal variation in forest transpiration across a forested boreal peatland complex

Transpiration is a globally important component of evapotranspiration. Careful upscaling of transpiration from point measurements is thus crucial for quantifying water and energy fluxes. In spatially heterogeneous landscapes common across the boreal biome, upscaled transpiration estimates are difficult to determine due to variation in local environmental conditions (e.g., basal area, soil moisture, permafrost). Here, we sought to determine stand-level attributes that influence transpiration scalars for a forested boreal peatland complex consisting of sparsely treed wetlands and densely treed permafrost plateaus as land cover types. The objectives were to quantify spatial and temporal variability in stand-level transpiration, and to identify sources of uncertainty when scaling point measurements to the stand-level. Using heat ratio method sap flow sensors, we determined sap velocity for black spruce and tamarack for 2-week periods during peak growing season in 2013, 2017 and 2018. We found greater basal area, drier soils, and the presence of permafrost increased daily sap velocity in individual trees, suggesting that local environmental conditions are important in dictating sap velocity. When sap velocity was scaled to stand-level transpiration using gridded 20 × 20 m resolution data across the ~10 ha Scotty Creek ForestGEO plot, we observed significant differences in daily plot transpiration among years (0.17–0.30 mm), and across land cover types. Daily transpiration was lowest in grid-cells with sparsely treed wetlands compared to grid-cells with well-drained and densely treed permafrost plateaus, where daily transpiration reached 0.80 mm, or 30% of the daily evapotranspiration. When transpiration scalars (i.e., sap velocity) were not specific to the different land cover types (i.e., permafrost plateaus and wetlands), scaled stand-level transpiration was overestimated by 42%. To quantify the relative contribution of tree transpiration to ecosystem evapotranspiration, we recommend that sampling designs stratify across local environmental conditions to accurately represent variation associated with land cover types, especially with different hydrological functioning as encountered in rapidly thawing boreal peatland complexes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Spin-squeezing for improving optical quantum sensors [Slides]

Spin-squeezing brief overview: Very high levels were achieved in various experiments; In the field of magnetometry, a very moderate spin squeezing was demonstrated (Romalis, Polzik, etc.); At some conditions, significant improvement is possible and this motivates our project; We proposed a significant spin squeezing demonstration for atomic magnetometry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1977

Investigation of a stall deterrent system utilizing an acoustic stall sensor

A simple rugged acoustic stall sensor which has an output proportional to angle of attack near wing stall has been evaluated on a Cessna 319 aircraft. A sensor position has been found on the wing where the sensor output is only slightly affected by engine power level, yaw angle, flap position and wing roughness. The NASA LRC General Aviation Simulator has been used to evaluate the acoustic sensor output as a control signal for active stall deterrent systems. It has been found that a simple control algorithm is sufficient for stall deterrence.

Bennett, A. G.↗

NASA NTRS2005

Wide Operational Range Thermal Sensor

Bolometer system and method for detecting, at BLIP levels, presence of radiation over a broad range of wavelengths in an infrared spectrum and in a temperature range from 20 K to as high as room temperature. The radiation is received by a Si crystal having a region that is doped with one or more of In, Ga, S, Se, Te, B, Al, P, As and Sb in a concentration ratio in a range such as 5 x 10(exp -11) to 5 x 10(exp -6). Change in electrical resistance delta R due to receipt of the radiation is measured through a change in voltage difference or current within the crystal, and the quantity delta R is converted to an estimate of the amount of radiation received. Optionally, incident radiation having an energy high enough to promote photoconductivity is removed before detection.

John H Goebel↗

NASA NTRS2013

Application of OMI, SCIAMACHY and GOME-2 Satellite SO2 Retrievals for Detection of Large Emission Sources

Retrievals of sulfur dioxide (SO2) from space-based spectrometers are in a relatively early stage of development. Factors such as interference between ozone and SO2 in the retrieval algorithms often lead to errors in the retrieved values. Measurements from the Ozone Monitoring Instrument (OMI), Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and Global Ozone Monitoring Experiment-2 (GOME-2) satellite sensors, averaged over a period of several years, were used to identify locations with elevated SO2 values and estimate their emission levels. About 30 such locations, detectable by all three sensors and linked to volcanic and anthropogenic sources, were found after applying low and high spatial frequency filtration designed to reduce noise and bias and to enhance weak signals to SO2 data from each instrument. Quantitatively, the mean amount of SO2 in the vicinity of the sources, estimated from the three instruments, is in general agreement. However, its better spatial resolution makes it possible for OMI to detect smaller sources and with additional detail as compared to the other two instruments. Over some regions of China, SCIAMACHY and GOME-2 data show mean SO2 values that are almost 1.5 times higher than those from OMI, but the suggested spatial filtration technique largely reconciles these differences.

SO2 retrievals↗

NASA NTRS1982

Mapping urban land cover from space: Some observations for future progress

The multilevel classification system adopted by the USGS for operational mapping of land use and land cover at levels 1 and 2 is discussed and the successes and failures of mapping land cover from LANDSAT digital data are reviewed. Techniques used for image interpretation and their relationships to sensor parameters are examined. The requirements for mapping levels 2 and 3 classes are considered.

Gaydos, L.↗

NASA NTRS2000

A Probabilistic Framework for the Validation and Certification of Computer Simulations

The paper presents a methodology for quantifying, propagating, and managing the uncertainty in the data required to initialize computer simulations of complex phenomena. The purpose of the methodology is to permit the quantitative assessment of a certification level to be associated with the predictions from the simulations, as well as the design of a data acquisition strategy to achieve a target level of certification. The value of a methodology that can address the above issues is obvious, specially in light of the trend in the availability of computational resources, as well as the trend in sensor technology. These two trends make it possible to probe physical phenomena both with physical sensors, as well as with complex models, at previously inconceivable levels. With these new abilities arises the need to develop the knowledge to integrate the information from sensors and computer simulations. This is achieved in the present work by tracing both activities back to a level of abstraction that highlights their commonalities, thus allowing them to be manipulated in a mathematically consistent fashion. In particular, the mathematical theory underlying computer simulations has long been associated with partial differential equations and functional analysis concepts such as Hilbert spares and orthogonal projections. By relying on a probabilistic framework for the modeling of data, a Hilbert space framework emerges that permits the modeling of coefficients in the governing equations as random variables, or equivalently, as elements in a Hilbert space. This permits the development of an approximation theory for probabilistic problems that parallels that of deterministic approximation theory. According to this formalism, the solution of the problem is identified by its projection on a basis in the Hilbert space of random variables, as opposed to more traditional techniques where the solution is approximated by its first or second-order statistics. The present representation, in addition to capturing significantly more information than the traditional approach, facilitates the linkage between different interacting stochastic systems as is typically observed in real-life situations.

Ghanem, Roger↗

DOE OSTI2023

Material Effects on Electron-Capture Decay in Cryogenic Sensors

Several current searches for physics beyond the standard model are based on measuring the electron-capture (EC) decay of radionuclides implanted into cryogenic high-resolution sensors. The sensitivity of these experiments has already reached the level where systematic effects related to atomic state energy changes from the host material are a limiting factor. One example is a neutrino mass study based on the nuclear EC decay of 7 Be to 7 Li inside cryogenic Ta-based sensors. Here, to understand the material effects at the required level, we use density-functional theory to model the electronic structure of lithium atoms in different atomic environments of the polycrystalline Ta absorber film. The calculations reveal that the Li 1s binding energies can vary by more than 2 eV due to insertion at different lattice sites, at grain boundaries, in disordered Ta, and in the vicinity of various impurities. However, the total range of Li 1s shifts does not exceed 4 eV, even for extreme amorphous disorder. Furthermore, when investigating the effects on the Li 2s levels, we find broadening of more than 5 eV due to hybridization with the Ta band structure. Material effects are shown to contribute significantly to peak broadening in Ta-based sensors that are used to search for physics beyond the standard model in the EC decay of 7 Be, but they do not explain the full extent of observed broadening. Understanding these in-medium effects will be required for current- and future-generation experiments that observe low-energy radiation from the EC decay of implanted isotopes to evaluate potential limitations on the measurement sensitivity.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Radiation tolerance study on irradiated AC-coupled, poly-silicon biased, p-on-n silicon strip sensors developed in India

The silicon sensors to be deployed in the next generation high energy physics experiments for operation in high luminosity scenarios, will require a high level of radiation tolerance. AC-coupled silicon strip sensors integrated with biasing poly-silicon resistors have been fabricated in collaboration with the Bharat Electronics Limited foundry using 4 inch n-type wafers in p-on-n configuration. Several sensors were irradiated with protons at different fluences at the Karlsruhe Cyclotron facility under the Advanced European Infrastructures for Detectors at Accelerators (AIDA) program. This paper reports on these radiation hardness study performed on the AC-coupled silicon sensors fabricated in India. The characterization comprises of electrical tests, including total current, voltage and strip scans and charge collection studies.

AC-coupled↗

DOE OSTI2020

Photonic microresonator based sensor for selective nitrate ion detection

Sensing nitrate concentrations in soil with high sensitivity and selectivity using field-deployable compact sensor platforms is a sought-after goal for environment and agriculture applications. This study demonstrates a new optically based nitrate sensing platform based on ion-selective membrane (ISM) functionalized chip-scale photonic micro-ring resonators. Our approach relies upon measurements of resonance shifts in the micro-resonators and leverages the excellent, though little studied, optical properties of ISMs. Using a high-quality micro-ring resonator, a nitrate ion-selective photonic sensor exhibits a detection limit down to 0.1 parts per million (ppm) and enables nitrate concentration measurements in the 1-100 ppm level, appropriate for soil science and agriculture. Importantly, the sensor also shows high selectivity over other competing anions in soil, such as Cl - and NO 2 - . Here, we argue that this chip-scale approach can be incorporated into compact sensor platforms.

47 OTHER INSTRUMENTATION↗

NASA NTRS1999

A Force to Reckon With

Through a licensing agreement with NASA, Face International Corporation has successfully commercialized ferroelectric actuator/sensor technology developed at Langley Research Center. Face International manufactures both ferroelectric actuators and sensors under the trademark "Thunder" (Thin Layer Composite Unimorph Ferroelectric Driver and Sensor). As actuators the Thunder technology provides a high level of movement not seen before in piezoelectric devices. Crystal structures generate electricity when stressed and move when voltage is applied. As sensors, the technology can be used in such applications as microphones, non-destructive testing, and vibration sensing. Thunder technology is being researched as a noise reduction device for aircraft engines. The technology is durable enough to be used in harsh environments, making it applicable to many commercial applications.

Source record↗