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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 19 records

Development of Hybrid Sensor Arrays for Sensor Arrays for Simultaneous Measurement of Pressure and Shear Stress Distribution

This document reports on the progress in developing hybrid sensors for the simultaneous measurement of pressure and shear stress. The key feature for the success of the proposed hybrid sensor array is the ability to deposit Cu-Ni alloy with proper composition (55 - 45) on a silicon wafer to form a strain gage. This alloy strain gage replaces the normally used Si strain gages in MEMS, which are highly nonlinear and temperature dependent. The copper nickel, with proper composition (55 - 45), was successfully deposited on a silicon wafer with a few trials during this period of the project. Pictures of the Cu-Ni alloy strain gage and the x-ray spectra indicating the composition are shown. The planned tests are also reviewed.

Source record↗

Improving the geometric fidelity of imaging systems employing sensor arrays

A sensor assembly to be carried on an aircraft or spacecraft which will travel along an arbitrary flight path, for providing an image of terrain over which the craft travels, is disclosed. The assembly includes a main linear sensor array and a plurality of auxiliary sensor arrays oriented parallel to, and at respectively different distances from, the main array. By comparing the image signals produced by the main sensor array with those produced by each auxiliary array, information relating to variations in velocity of the craft carrying the assembly can be obtained. The signals from each auxiliary array will provide information relating to a respectively different frequency range.

Jones, Kenneth L.↗

Geometric fiedlity of imaging systems employing sensor arrays

A sensor assembly to be carried on an aircraft or spacecraft which will travel along an arbitrary flight path, for providing an image of terrain over which the craft travels. The assembly includes a main linear sensor array and a plurality of auxiliary sensor arrays oriented parallel to, and at respectively different distances from, the main array. By comparing the image signals produced by the main sensor array with those produced by each auxiliary array, information relating to variations in velocity of the craft carrying the assembly can be obtained. The signals from each auxiliary array will provide information relating to a respectively different frequency range.

Jones, Kenneth L.↗

Phase discriminating capacitive array sensor system

A phase discriminating capacitive sensor array system which provides multiple sensor elements which are maintained at a phase and amplitude based on a frequency reference provided by a single frequency stabilized oscillator. Sensor signals provided by the multiple sensor elements are controlled by multiple phase control units, which correspond to the multiple sensor elements, to adjust the sensor signals from the multiple sensor elements based on the frequency reference. The adjustment made to the sensor signals is indicated by output signals which indicate the proximity of the object. The output signals may also indicate the closing speed of the object based on the rate of change of the adjustment made, and the edges of the object based on a sudden decrease in the adjustment made.

Vranish, John M.↗

Faster Array Training and Rapid Analysis for a Sensor Array Intended for an Event Monitor in Air

Environmental monitoring, in particular, air monitoring, is a critical need for human space flight. Both monitoring and life support systems have needs for closed loop process feedback and quality control for environmental factors. Monitoring protects the air environment and water supply for the astronaut crew and different sensors help ensure that the habitat falls within acceptable limits, and that the life support system is functioning properly and efficiently. The longer the flight duration and the farther the destination, the more critical it becomes to have carefully monitored and automated control systems for life support. There is an acknowledged need for an event monitor which samples the air continuously and provides near real-time information on changes in the air. Past experiments with the JPL ENose have demonstrated a lifetime of the sensor array, with the software, of around 18 months. We are working on a sensor array and new algorithms that will incorporate transient sensor responses in the analysis. Preliminary work has already showed more rapid quantification and identification of analytes and the potential for faster training time of the array. We will look at some of the factors that contribute to demonstrating faster training time for the array. Faster training will decrease the integrated sensor exposure to training analytes, which will also help extend sensor lifetime.

sensing array↗

Particle sensor array

A particle sensor array which in a preferred embodiment comprises a static random access memory having a plurality of ion-sensitive memory cells, each such cell comprising at least one pull-down field effect transistor having a sensitive drain surface area (such as by bloating) and at least one pull-up field effect transistor having a source connected to an offset voltage. The sensitive drain surface area and the offset voltage are selected for memory cell upset by incident ions such as alpha-particles. The static random access memory of the present invention provides a means for selectively biasing the memory cells into the same state in which each of the sensitive drain surface areas is reverse biased and then selectively reducing the reversed bias on these sensitive drain surface areas for increasing the upset sensitivity of the cells to ions. The resulting selectively sensitive memory cells can be used in a number of applications. By way of example, the present invention can be used for measuring the linear energy transfer of ion particles, as well as a device for assessing the resistance of CMOS latches to Cosmic Ray induced single event upsets. The sensor of the present invention can also be used to determine the uniformity of an ion beam.

Buehler, Martin G.↗

Signal Processing of Multiplexed Optical PWM Signals for Sensor Arrays in Nuclear Environments

Safe and effective generation of terrestrial nuclear power greatly benefits from the actionable data provided by the array of sensors located throughout a plant to provide a holistic online indication of reactor operation. This array includes sensors for monitoring coolant flow and pressure, temperature and heat transfer, radiation levels, structure health monitoring, and other critical parameters for reactor operation. While sensors capable of measuring these parameters have been developed, the electronics used in the pre-amplification and analog-to-digital conversion of the small signals they produce are extremely sensitive and susceptible to damage by high-temperatures and radiation environments nuclear reactors encounter while generating power. The small signals from sensors in nuclear power plants (NPPs) are transmitted over long cable runs which introduce dispersion artifacts into the signals of interest as well as electromagnetic interference (EMI) from lighting fixtures, pumps, mains electricity, and other equipment. To overcome these challenges, a front-end digitization (FREND) platform has been developed to use radiation-tolerant electronics to multiplex, amplify, and optically encode signals from an array of sensors for transmission over an optical fiber to mitigate dispersion and EMI artifacts from long runs of electrical cabling. To recover the optically transmitted data, a signal processing scheme based on 1-dimensional template matching to an indexing channel is described herein and demonstrated to have an effective bit-depth of 9.2 bits (1%). This scheme has been validated in proof-of-concept, non-nuclear testing and preliminary experimental results show good agreement between the measured optical output and and sensor input signals. The FREND system represents a low-loss data link between sensors in nuclear environments and data acquisition hardware which is aimed at improving the signal-to-noise ratio of the data acquired from these sensors to provide better information to operators and researchers.

Sweeney, Dan↗

A minimum assumption approach to MEG sensor array design

Objective. Our objective is to formulate the problem of the magnetoencephalographic (MEG) sensor array design as a well-posed engineering problem of accurately measuring the neuronal magnetic fields. This is in contrast to the traditional approach that formulates the sensor array design problem in terms of neurobiological interpretability the sensor array measurements. Approach. We use the vector spherical harmonics (VSH) formalism to define a figure-of-merit for an MEG sensor array. We start with an observation that, under certain reasonable assumptions, any array of m perfectly noiseless sensors will attain exactly the same performance, regardless of the sensors' locations and orientations (with the exception of a negligible set of singularly bad sensor configurations). We proceed to the conclusion that under the aforementioned assumptions, the only difference between different array configurations is the effect of (sensor) noise on their performance. We then propose a figure-of-merit that quantifies, with a single number, how much the sensor array in question amplifies the sensor noise. Main results. We derive a formula for intuitively meaningful, yet mathematically rigorous figure-of-merit that summarizes how desirable a particular sensor array design is. We demonstrate that this figure-of-merit is well-behaved enough to be used as a cost function for a general-purpose nonlinear optimization methods such as simulated annealing. We also show that sensor array configurations obtained by such optimizations exhibit properties that are typically expected of 'high-quality' MEG sensor arrays, e.g. high channel information capacity. Significance. Our work paves the way toward designing better MEG sensor arrays by isolating the engineering problem of measuring the neuromagnetic fields out of the bigger problem of studying brain function through neuromagnetic measurements.

60 APPLIED LIFE SCIENCES↗

Sensor arrays for detecting microorganisms

A sensor array for detecting a microorganism comprising first and second sensors electrically connected to an electrical measuring apparatus, wherein the sensors comprise a region of nonconducting organic material and a region of conducting material compositionally that is different than the nonconducting organic material and an electrical path through the regions of nonconducting organic material and the conducting material. A system for identifying microorganisms using the sensor array, a computer and a pattern recognition algorithm, such as a neural net are also disclosed.

Lewis, Nathan S.↗

Nanowire sensor, sensor array, and method for making the same

The present invention relates to a nanowire sensor and method for forming the same. More specifically, the nanowire sensor comprises at least one nanowire formed on a substrate, with a sensor receptor disposed on a surface of the nanowire, thereby forming a receptor-coated nanowire. The nanowire sensor can be arranged as a sensor sub-unit comprising a plurality of homogeneously receptor-coated nanowires. A plurality of sensor subunits can be formed to collectively comprise a nanowire sensor array. Each sensor subunit in the nanowire sensor array can be formed to sense a different stimulus, allowing a user to sense a plurality of stimuli. Additionally, each sensor subunit can be formed to sense the same stimuli through different aspects of the stimulus. The sensor array is fabricated through a variety of techniques, such as by creating nanopores on a substrate and electrodepositing nanowires within the nanopores.

Yun, Minhee↗

Comparison of Machine Learning Algorithms for Natural Gas Identification with Mixed Potential Electrochemical Sensor Arrays

Mixed-potential electrochemical sensor arrays consisting of indium tin oxide (ITO), La 0.87 Sr 0.13 CrO 3 , Au, and Pt electrodes can detect the leaks from natural gas infrastructure. Algorithms are needed to correctly identify natural gas sources from background natural and anthropogenic sources such as wetlands or agriculture. We report for the first time a comparison of several machine learning methods for mixture identification in the context of natural gas emissions monitoring by mixed potential sensor arrays. Random Forest, Artificial Neural Network, and Nearest Neighbor methods successfully classified air mixtures containing only CH 4 , two types of natural gas simulants, and CH 4 +NH 3 with >98% identification accuracy. The model complexity of these methods were optimized and the degree of robustness against overfitting was determined. Finally, these methods are benchmarked on both desktop PC and single-board computer hardware to simulate their application in a portable internet-of-things sensor package. The combined results show that the random forest method is the preferred method for mixture identification with its high accuracy (>98%), robustness against overfitting with increasing model complexity, and had less than 10 ms training time and less than 0.1 ms inference time on single-board computer hardware.

03 NATURAL GAS↗

Concepts and Development of Bio-Inspired Distributed Embedded Wired/Wireless Sensor Array Architectures for Acoustic Wave Sensing in Integrated Aerospace Vehicles

This paper discusses the modeling of acoustic emissions in plate structures and their sensing by embedded or surface bonded piezoelectric sensor arrays. Three different modeling efforts for acoustic emission (AE) wave generation and propagation are discussed briefly along with their advantages and disadvantages. Continuous sensors placed at right angles on a plate are being discussed as a new approach to measure and locate the source of acoustic waves. Evolutionary novel signal processing algorithms and bio-inspired distributed sensor array systems are used on large structures and integrated aerospace vehicles for AE source localization and preliminary results are presented. These systems allow for a great reduction in the amount of data that needs to be processed and also reduce the chances of false alarms from ambient noises. It is envisioned that these biomimetic sensor arrays and signal processing techniques will be useful for both wireless and wired sensor arrays for real time health monitoring of large integrated aerospace vehicles and earth fixed civil structures. The sensor array architectures can also be used with other types of sensors and for other applications.

Ghoshal, Anindya↗

Mapping Capacitive Coupling Among Pixels in a Sensor Array

An improved method of mapping the capacitive contribution to cross-talk among pixels in an imaging array of sensors (typically, an imaging photodetector array) has been devised for use in calibrating and/or characterizing such an array. The method involves a sequence of resets of subarrays of pixels to specified voltages and measurement of the voltage responses of neighboring non-reset pixels.

Seshadri, Suresh↗

Monte Carlo Techniques for Calculations of Charge Deposition and Displacement Damage from Protons in Visible and Infrared Sensor Arrays

This slide presentation examines motivation for Monte Carlo methods, charge deposition in sensor arrays, displacement damage calculations, and future work. The discussion of charge deposition sensor arrays includes Si active pixel sensor APS arrays and LWIR HgCdTe FPAs. The discussion of displacement damage calculations includes nonionizing energy loss (NIEL), HgCdTe NIEL calculation results including variance, and implications for damage in HgCdTe detector arrays.

Marshall, Paul↗

Development of Microfabricated Chemical Gas Sensors and Sensor Arrays for Aerospace Applications

Aerospace applications require the development of chemical sensors with capabilities beyond those of commercially available sensors. In particular, factors such as minimal sensor size, weight, and power consumption are particularly important. Development areas which have potential aerospace applications include launch vehicle leak detection, engine health monitoring, fire detection, and environmental monitoring. Sensor development for these applications is based on progress in three types of technology: 1) Micromachining and microfabrication (Microsystem) technology to fabricate miniaturized sensors. 2) The use of nanocrystalline materials to develop sensors with improved stability combined with higher sensitivity. 3) The development of high temperature semiconductors, especially silicon carbide. However, due to issues of selectivity and cross-sensitivity, individual sensors are limited in the amount of information that they can provide in environments that contain multiple chemical species. Thus, sensor arrays are being developed to address detection needs in such multi-species environments. This paper discusses the needs of space applications as well as the point-contact sensor technology and sensor arrays being developed to address these needs. Sensors to measure hydrogen, hydrocarbons, hydrazine, nitrogen oxides (NO,), carbon monoxide, oxygen, and carbon dioxide are being developed as well as arrays for leak, fire, and emissions detection. Demonstrations of the technology will also be discussed. It is concluded that microfabricated sensor technology has significant potential for use in a range of aerospace applications.

Hunter, G. W.↗

Analyzing Responses of Chemical Sensor Arrays

NASA is developing a third-generation electronic nose (ENose) capable of continuous monitoring of the International Space Station s cabin atmosphere for specific, harmful airborne contaminants. Previous generations of the ENose have been described in prior NASA Tech Briefs issues. Sensor selection is critical in both (prefabrication) sensor material selection and (post-fabrication) data analysis of the ENose, which detects several analytes that are difficult to detect, or that are at very low concentration ranges. Existing sensor selection approaches usually include limited statistical measures, where selectivity is more important but reliability and sensitivity are not of concern. When reliability and sensitivity can be major limiting factors in detecting target compounds reliably, the existing approach is not able to provide meaningful selection that will actually improve data analysis results. The approach and software reported here consider more statistical measures (factors) than existing approaches for a similar purpose. The result is a more balanced and robust sensor selection from a less than ideal sensor array. The software offers quick, flexible, optimal sensor selection and weighting for a variety of purposes without a time-consuming, iterative search by performing sensor calibrations to a known linear or nonlinear model, evaluating the individual sensor s statistics, scoring the individual sensor s overall performance, finding the best sensor array size to maximize class separation, finding optimal weights for the remaining sensor array, estimating limits of detection for the target compounds, evaluating fingerprint distance between group pairs, and finding the best event-detecting sensors.

Zhou, Hanying↗

Analysis and design of a surface-wave-scanned optical sensor array

This paper treats a scheme for converting the information of the spatial pattern of light of an image into a time-varying voltage pattern by the use of acoustic surface waves. After a brief review of earlier work, the application of the scheme to vidicon-type applications is tested by a feasibility calculation. This is followed by a consideration of various physical configurations possible and some experimental results. The rest of the paper deals with the subject of sensor array design. Included here are discussions of system components, methods of computation used, optimization, and the design of some integrated sensor arrays. The work shows that an integrated acoustically scanned array sensor of 250 or more elements per line in a 5 cm length, with scanning at TV frame rates, should be possible.

Shaw, K. A.↗

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↗