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At least 199 records · Page 11

Joint Acceptance Attenuation Factor of Integrated Pressure with Unsteady Pressure-Sensitive Paint Measurements

The Unsteady Pressure-Sensitive Paint (uPSP) is widely used to measure the surface pressure of scaled models in wind tunnel tests. Compared to the conventional pressure transducers, uPSP has the advantage of high spatial resolution. With multiple high-speed Complementary Metal Oxide Superconductor (CMOS) cameras, the uPSP data collected with the camera pixels are mapped to the surface grid of the scaled model and converted to pressure. The shot noise is the dominant component of the noise in the uPSP measurement. The integrated pressure is usually computed on the grid nodes of a user-defined patch. The effect of shot noise is reduced in the integrated pressure on the patch; however, the measurement of the aerodynamic pressure may also be attenuated by the decorrelation of the flow pressure field being measured. This paper discusses the Joint Acceptance Attenuation Factor (JAAF) of the integrated pressure with uPSP measurements. The JAAF, a function of frequency, is defined as the ratio of the Power Spectral Density (PSD) of the integrated aerodynamic pressure on the patch to the average PSD of the aerodynamic pressure on the grid nodes of the patch. In this paper, the JAAF is investigated for the integrated pressure on rectangular patches, whose edges are defined in the direction along the streamline or across the streamline. Based on the assumption that the surface pressure field can be described by the Corcos model, the closed-form formulas to compute the JAAFs of the integrated pressure on the discrete grid nodes of a rectangular patch and over the continuous area of a rectangular patch are derived respectively. It is shown that the JAAF of the integrated pressure over the continuous area of a rectangular patch is the limit of that on discrete nodes of the rectangular patch when the number of nodes in each row or column goes to infinity. The closed-form formulas of the JAAF derived in this paper, with estimated parameters of the model, are verified with the measurements of the uPSP and the conventional pressure transducer collected in the Space Launch System Ascent Unsteady Aerodynamics Test at NASA Ames Research Center in November 2017. The closed-form formulas of the JAAF of the integrated pressure on the rectangular patches, based on the Corcos model, provide an efficient method to estimate the attenuation of integration by the decorrelation of the flow pressure field and set references for the comparison of the spectrum of the integrated uPSP measurements and the conventional pressure transducer measurements. The work described in this paper is a part of NASA’s development of a new state-of-the-art uPSP capability in production wind tunnels. Funding was provided by the NASA Aerosciences Evaluation and Test Capabilities Portfolio Office.

acoustics↗

Joint Acceptance Attenuation Factor of Integrated Pressure with Unsteady Pressure-Sensitive Paint Measurements

The Unsteady Pressure-Sensitive Paint (uPSP) is widely used to measure the surface pressure of scaled models in wind tunnel tests. Compared to the conventional pressure transducers, uPSP has the advantage of high spatial resolution. With multiple high-speed Complementary Metal Oxide Superconductor (CMOS) cameras, the uPSP data collected with the camera pixels are mapped to the surface grid of the scaled model and converted to pressure. The shot noise is the dominant component of the noise in the uPSP measurement. The integrated pressure is usually computed on the grid nodes of a user-defined patch. The effect of shot noise is reduced in the integrated pressure on the patch; however, the measurement of the aerodynamic pressure may also be attenuated by the decorrelation of the flow pressure field being measured. This paper discusses the Joint Acceptance Attenuation Factor (JAAF) of the integrated pressure with uPSP measurements. The JAAF, a function of frequency, is defined as the ratio of the Power Spectral Density (PSD) of the integrated aerodynamic pressure on the patch to the average PSD of the aerodynamic pressure on the grid nodes of the patch. In this paper, the JAAF is investigated for the integrated pressure on rectangular patches, whose edges are defined in the direction along the streamline or across the streamline. Based on the assumption that the surface pressure field can be described by the Corcos model, the closed-form formulas to compute the JAAFs of the integrated pressure on the discrete grid nodes of a rectangular patch and over the continuous area of a rectangular patch are derived respectively. It is shown that the JAAF of the integrated pressure over the continuous area of a rectangular patch is the limit of that on discrete nodes of the rectangular patch when the number of nodes in each row or column goes to infinity. The closed-form formulas of the JAAF derived in this paper, with estimated parameters of the model, are verified with the measurements of the uPSP and the conventional pressure transducer collected in the Space Launch System Ascent Unsteady Aerodynamics Test at NASA Ames Research Center in November 2017. The closed-form formulas of the JAAF of the integrated pressure on the rectangular patches, based on the Corcos model, provide an efficient method to estimate the attenuation of integration by the decorrelation of the flow pressure field and set references for the comparison of the spectrum of the integrated uPSP measurements and the conventional pressure transducer measurements. The work described in this paper is a part of NASA’s development of a new state-of-the-art uPSP capability in production wind tunnels. Funding was provided by the NASA Aerosciences Evaluation and Test Capabilities Portfolio Office.

acoustics↗

Analysis of Dynamic Mode Decomposition Outputs of Unsteady Pressure-Sensitive Paint Measurements in the NASA Wind Tunnel Tests

This paper discusses the Dynamic Mode Decomposition (DMD) outputs of the Unsteady Pressure-Sensitive Paint (uPSP) measurements, which were collected with four Phantom high-speed cameras at a constant sample frequency in the Ascent Transient Aerodynamics Test (ATAT) of the Space Launch System (SLS) Block 1 cargo vehicle in the 11-by-11-foot transonic test section of the Unitary Plan Wind Tunnel (UPWT) at NASA Ames Research Center in September 2019. In this paper, the effectiveness to use the DMD outputs of uPSP measurements in the diagnosis and analysis of the aerodynamic and acoustic phenomena in the SLS ATAT is demonstrated. The work described in the paper is a part of NASA’s development of a new state-of-the-art uPSP capability in production wind tunnels. Funding was provided by the NASA Aerosciences Evaluation and Test Capabilities (AETC) Project.

acoustics↗

Technology Maturation of Wireless Harsh Environment Sensors For Improved Condition Based Monitoring Of Coal Fired Power Generation

The overall goal of this project was to demonstrate and develop the usage of high-temperature (HT) harsh-environment (HE) wireless surface acoustic wave resonator (SAWR) sensor technology to promote reliable maintenance through condition-based maintenance (CBM) for field applications in harsh service conditions associated with power plant environments. The project aimed to advance the HT HE wireless SAWR sensor technology from TRL 5 to TRL 7. In addition to HT HE wireless temperature sensing, efforts were dedicated during this project to investigate, develop and increase the TRL from 3 to 5 for the following technologies: (a) HT HE strain sensors to address additional CBM monitoring needs, such as boiler tube mechanical / thermal stresses, which can provide early indications for boiler tube cracking and failure; and (b) HT aluminum nitride (AlN) and scandium aluminum nitride (ScAlN) based piezoelectric thin film fabrication and implementation of SAW sensors, with the goal of releasing the need to use single crystal piezoelectric materials for SAWRs and thus broaden possible technology applications to non-planar and harder to modify surfaces. To achieve the goals mentioned above, UMaine and its partner, Environetix Technologies Corporation, established partnerships with the following power plants: Longview Power (Maidsville, WV), a coal-fired power plant; Penobscot Energy Recovery Corp (PERC, Orrington, ME), a waste-to-energy power plant; and the UMaine Steam Plant (Orono, ME), an oil / natural gas power plant. To realize wireless HT HE SAWR sensor systems in these harsh service conditions, the University of Maine research team worked with Environetix and these power plants to define, design, fabricate, test and validate a mature prototype wireless temperature SAWR sensor system for boiler tube applications within the HT HE of the reheater pass damper chamber to directly and wirelessly monitor the temperature at eighteen independent boiler tube locations. The system included three levels, or “tiers”, of wireless communication to enable remote monitoring: Tier 1, the wireless link in the reheater pass damper chamber directly accessing the sensors on the boilers; Tier 2, the wireless local area network link, transmitting processed sensor information within the power plant to the Tier 3, a commercial wireless signal carrier company for secure remote data monitoring outside of the power plant. Regarding the wireless sensor system installed at Longview Power, temperature information from the boilers was continuously transmitted from the Longview boilers at Maidsville, WV, to Environetix headquarters, Orono, ME, over a 34 month period, when the system was finally decommissioned. Strain sensors and piezoelectric ScAlN thin film sensors were successfully installed on the exhaust duct at the UMaine Steam Power plant. The advances in wireless strain sensors and thin film piezoelectric film fabrication and testing were performed mostly in UMaine laboratories and field tested at the UMaine Steam Plant, due to its close proximity to UMaine/Environetix, access to the plant facility, and due to difficulties in accessing the other power plants during the COVID shut-down period. The project accomplished the TRL level increase of the targeted CBM technologies through the successful fabrication, installation, test, and validation of dedicated and commercial wireless sensor systems, utilizing the three different power plants. The outcomes of this project, including the wireless sensor data capability, are expected to yield an advance for CBM in harsh power plant environments. The reduction of maintenance costs, improved safety during plant operation, and increased power plant efficiency will lead to increased revenues (i.e., fewer forced outages) due to better process monitoring enabled by the wireless HT HE SAWR temperature sensor technology.

20 FOSSIL-FUELED POWER PLANTS↗

The Octopus processor for the CMS L1 muon trigger for High Luminosity LHC

The upgraded L1 muon trigger system of the CMS experiment in the High Luminosity Large Hadron Collider is based on custom processors featuring large Field Programmable Gate Arrays (FPGAs) connected by large numbers of optical links. These provide the I/O bandwidth and power necessary to process the complex algorithms used during the collection of physics data. The design and performance requirements of these processors creates significant challenges in signal integrity, power delivery, and thermal management. In this paper we describe the Octopus processor, featuring a large Xilinx Virtex Ultrascale+ FPGA and up to 128 links interfaced to optics through high quality twin-ax copper cables. Results on signal integrity at 25 Gb/s and the first demonstration of 50+ Gb/s links with pluggable optics in CMS are also shown, demonstrating bit error rates below 10 –15 at a 95% confidence level. The thermal performance is measured inside an Advanced-TCA crate with acceptable thermal margins up to 200 W of chip power. Future improvements are mentioned, potentially allowing operation at up to 300 W.

Instruments & Instrumentation↗

EFQPSK Versus CERN: A Comparative Study

This report presents a comparative study on Enhanced Feher's Quadrature Phase Shift Keying (EFQPSK) and Constrained Envelope Root Nyquist (CERN) techniques. These two techniques have been developed in recent times to provide high spectral and power efficiencies under nonlinear amplifier environment. The purpose of this study is to gain insights into these techniques and to help system planners and designers with an appropriate set of guidelines for using these techniques. The comparative study presented in this report relies on effective simulation models and procedures. Therefore, a significant part of this report is devoted to understanding the mathematical and simulation models of the techniques and their set-up procedures. In particular, mathematical models of EFQPSK and CERN, effects of the sampling rate in discrete time signal representation, and modeling of nonlinear amplifiers and predistorters have been considered in detail. The results of this study show that both EFQPSK and CERN signals provide spectrally efficient communications compared to filtered conventional linear modulation techniques when a nonlinear power amplifier is used. However, there are important differences. The spectral efficiency of CERN signals, with a small amount of input backoff, is significantly better than that of EFQPSK signals if the nonlinear amplifier is an ideal clipper. However, to achieve such spectral efficiencies with a practical nonlinear amplifier, CERN processing requires a predistorter which effectively translates the amplifier's characteristics close to those of an ideal clipper. Thus, the spectral performance of CERN signals strongly depends on the predistorter. EFQPSK signals, on the other hand, do not need such predistorters since their spectra are almost unaffected by the nonlinear amplifier, Ibis report discusses several receiver structures for EFQPSK signals. It is observed that optimal receiver structures can be realized for both coded and uncoded EFQPSK signals with not too much increase in computational complexity. When a nonlinear amplifier is used, the bit error rate (BER) performance of the CERN signals with a matched filter receiver is found to be more than one decibel (dB) worse compared to the bit error performance of EFQPSK signals. Although channel coding is found to provide BER performance improvement for both EFQPSK and CERN signals, the performance of EFQPSK signals remains better than that of CERN. Optimal receiver structures for CERN signals with nonlinear equalization is left as a possible future work. Based on the numerical results, it is concluded that, in nonlinear channels, CERN processing leads towards better bandwidth efficiency with a compromise in power efficiency. Hence for bandwidth efficient communications needs, CERN is a good solution provided effective adaptive predistorters can be realized. On the other hand, EFQPSK signals provide a good power efficient solution with a compromise in band width efficiency.

Borah, Deva K.↗

The development of a power spectral density processor for C and L band airborne radar scatterometer sensor systems

A real-time signal processor was developed for the NASA/JSC L-and C-band airborne radar scatterometer sensor systems. The purpose of the effort was to reduce ground data processing costs. Conversion of two quadrature channels of data (like and cross polarized) was made to obtain Power Spectral Density (PSD) values. A chirp-z transform (CZT) approach was used to filter the Doppler return signal and improved high frequency and angular resolution was realized. The processors have been tested with record signals and excellent results were obtained. CZT filtering can be readily applied to scatterometers operating at other wavelengths by altering the sample frequency. The design of the hardware and software and the results of the performance tests are described in detail.

Harrison, D. A., III↗

Powder Bed Fusion Laser Beam Metals Additive Manufacturing: Process Monitoring Approaches for Qualification and Certification

The use of in-situ process monitoring is of interest to lower the cost of inspection for the qualification of powder bed fusion laser beam metal (PBF-LB/M) additively manufactured (AM) parts. Precise monitoring of the PBF-LB/M AM build process constitutes a multi-scale and multi-discipline task. There are several significant challenges to the in-situ approach: the synchronization of sensor signals to process steps; the physical interpretation and classification of sensor signals; managing very large datasets; and comparing the inputs with the observed monitoring signals. At NASA Langley Research Center, a configurable architecture additive testbed has been developed to monitor the build process with synchronized sensors. The philosophy and method adopted for the synchronization of the cameras with laser power and position throughout a complex PBF-LB/M AM build will be described. The synchronized in-situ monitoring signals are compared with ex-situ nondestructive inspection, x-ray computed tomography (XCT). Such comparisons permit a better understanding of how the sequential process actions of LPBF-AM can affect build quality. The multi-scale and complex process of printing additively manufactured (AM) parts can have unexpected, but predictable, build conditions that result in material microstructure variability. This presentation will describe an additive manufacturing model-based process metric (AM-PM) computational method that is a fully parallel reduced order modeling approach developed to evaluate the evolution of AM processes. This method couples the known sequence of the AM process with a physically informed nearest neighbors’ calculation to map the conditions of a part-scale build. The result is a map of the build that is derived directly from build files or in-situ process monitoring sensors. The methodology of the approach will be described and mapped to the porosity observed from XCT for a complex PBF-LB/M build. Such comparative results develop understanding of how the sequential process actions can affect the PBF-LB/M AM build quality and microstructure variability.

Laser Powder Bed Fusion↗

Tutorial on forming through-silicon vias

Through-silicon vias (TSVs) are a critical technology for three-dimensional integrated circuit technology. These through-substrate interconnects allow electronic devices to be stacked vertically for a broad range of applications and performance improvements such as increased bandwidth, reduced signal delay, improved power management, and smaller form-factors. There are many interdependent processing steps involved in the successful integration of TSVs. This article provides a tutorial style review of the following semiconductor fabrication process steps that are commonly used in forming TSVs: deep etching of silicon to form the via, thin film deposition to provide insulation, barrier, and seed layers, electroplating of copper for the conductive metal, and wafer thinning to reveal the TSVs. Recent work in copper electrochemical deposition is highlighted, analyzing the effect of accelerator and suppressor additives in the electrolyte to enable void-free bottom-up filling from a conformally lined seed metal.

42 ENGINEERING↗

Digital spectral estimation and modeling of Space Shuttle flight data

Application of the digital signal processing technique of autoregressive-moving-average (ARMA) modeling to the estimation of power spectra and shock spectra from Space Shuttle lift-off flight accelerograms is described in this paper. The background for application to ARMA of lift-off accelerograms which are non-stationary in nature is exemplified through a step-by-step discussion of actual numerical results. Included is a discussion of pertinent mathematical background for the ARMA approximations. Potential areas for application of ARMA modeling in payload integration activities are suggested.

Spanos, P. D.↗

Using a microgravity environment to probe wave turbulence

The experimental key to observing stochasticity or turbulence in a distribution of interacting propagating waves is the achievement of high amplitude and the use of a medium with a large coefficient of nonlinearity. The research indicates that capillary waves are the best means of observing this phenomenon; however, gravitational modifications of the capillary wave dispersion law greatly reduce the large coefficient of nonlinearity. Thus, a search for wave turbulence in a large drop of fluid that is positioned in a microgravity experiment was conducted. Capillary waves that run around the surface of the drop are excited, and their power spectrum and higher order correlations are analyzed for wave turbulence. The theoretical calculations indicate that modulations of the power spectrum should propagate as second sound waves. These issues have consequences for signal processing and plasma confinement.

Putterman, S.↗

Spline screw multiple rotations mechanism

A system for coupling two bodies together and for transmitting torque from one body to another with mechanical timing and sequencing is reported. The mechanical timing and sequencing is handled so that the following criteria are met: (1) the bodies are handled in a safe manner and nothing floats loose in space, (2) electrical connectors are engaged as long as possible so that the internal processes can be monitored throughout by sensors, and (3) electrical and mechanical power and signals are coupled. The first body has a splined driver for providing the input torque. The second body has a threaded drive member capable of rotation and limited translation. The embedded drive member will mate with and fasten to the splined driver. The second body has an embedded bevel gear member capable of rotation and limited translation. This bevel gear member is coaxial with the threaded drive member. A compression spring provides a preload on the rotating threaded member, and a thrust bearing is used for limiting the translation of the bevel gear member so that when the bevel gear member reaches the upward limit of its translation the two bodies are fully coupled and the bevel gear member then rotates due to the input torque transmitted from the splined driver through the threaded drive member to the bevel gear member. An output bevel gear with an attached output drive shaft is embedded in the second body and meshes with the threaded rotating bevel gear member to transmit the input torque to the output drive shaft.

Vranish, John M.↗

Wearable Wireless Telemetry System for Implantable BioMEMS Sensors

Telemetry systems of a type that have been proposed for the monitoring of physiological functions in humans would include the following subsystems: Surgically implanted or ingested units that would comprise combinations of microelectromechanical systems (MEMS)- based sensors [bioMEMS sensors] and passive radio-frequency (RF) readout circuits that would include miniature loop antennas. Compact radio transceiver units integrated into external garments for wirelessly powering and interrogating the implanted or ingested units. The basic principles of operation of these systems are the same as those of the bioMEMS-sensor-unit/external-RFpowering- and-interrogating-unit systems described in "Printed Multi-Turn Loop Antennas for Biotelemetry" (LEW-17879-1) NASA Tech Briefs, Vol. 31, No. 6 (June 2007), page 48, and in the immediately preceding article, "Hand-Held Units for Short-Range Wireless Biotelemetry" (LEW-17483-1). The differences between what is reported here and what was reported in the cited prior articles lie in proposed design features and a proposed mode of operation. In a specific system of the type now proposed, the sensor unit would comprise mainly a capacitive MEMS pressure sensor located in the annular region of a loop antenna (more specifically, a square spiral inductor/ antenna), all fabricated as an integral unit on a high-resistivity silicon chip. The capacitor electrodes, the spiral inductor/antenna, and the conductor lines interconnecting them would all be made of gold. The dimensions of the sensor unit have been estimated to be about 110.4 mm. The external garment-mounted powering/ interrogating unit would include a multi-turn loop antenna and signal-processing circuits. During operation, this external unit would be positioned in proximity to the implanted or ingested unit to provide for near-field, inductive coupling between the loop antennas, which we have as the primary and secondary windings of an electrical transformer.

Simons, Rainee N.↗

Smart Pixels: In-pixel AI for on-sensor data filtering

We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-principle for a Phase III upgrade at the Large Hadron Collider (LHC) pixel detector. The first version of the ROIC consists of two matrices of 256 smart pixels, each 25$\times$25 µm\textsuperscript{2} in size. Each pixel consists of a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. The frontend is capable of synchronously digitizing the sensor charge within 25 ns. Measurement results show an equivalent noise charge (ENC) of $\sim$30e\textsuperscript{-} and a total dispersion of $\sim$100e\textsuperscript{-} The second version of the ROIC uses a fully connected two-layer neural network (NN) to process information from a cluster of 256 pixels to determine if the pattern corresponds to highly desirable high-momentum particle tracks for selection and readout. The digital NN is embedded in-between analog signal processing regions of the 256 pixels without increasing the pixel size and is implemented as fully combinatorial digital logic to minimize power consumption and eliminate clock distribution, and is active only in the presence of an input signal. The total power consumption of the neural network is $\sim$ 300 $\mu$W. The NN performs momentum classification based on the generated cluster patterns and even with a modest momentum threshold, it is capable of 54.4\% – 75.4\% total data rejection, opening the possibility of using the pixel information at 40MHz for the trigger. The total power consumption of analog and digital functions per pixel is $\sim$ 6 $\mu$W per pixel, which corresponds to $\sim$ 1 W/cm\textsuperscript{2} staying within the experimental constraints.

Parpillon, Benjamin↗

Smart Pixels: In-pixel AI for on-sensor data filtering

We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-principle for a Phase III upgrade at the Large Hadron Collider (LHC) pixel detector. The first version of the ROIC consists of two matrices of 256 smart pixels, each 25$\times$25 $\mu$m$^2$ in size. Each pixel consists of a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. The frontend is capable of synchronously digitizing the sensor charge within 25 ns. Measurement results show an equivalent noise charge (ENC) of $\sim$30e$^-$ and a total dispersion of $\sim$100e$^-$ The second version of the ROIC uses a fully connected two-layer neural network (NN) to process information from a cluster of 256 pixels to determine if the pattern corresponds to highly desirable high-momentum particle tracks for selection and readout. The digital NN is embedded in-between analog signal processing regions of the 256 pixels without increasing the pixel size and is implemented as fully combinatorial digital logic to minimize power consumption and eliminate clock distribution, and is active only in the presence of an input signal. The total power consumption of the neural network is $\sim$ 300 $\mu$W. The NN performs momentum classification based on the generated cluster patterns and even with a modest momentum threshold, it is capable of 54.4% - 75.4% total data rejection, opening the possibility of using the pixel information at 40MHz for the trigger. The total power consumption of analog and digital functions per pixel is $\sim$ 6 $\mu$W per pixel, which corresponds to $\sim$ 1 W/cm$^2$ staying within the experimental constraints.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Software breadboard study

The overall goal of this study was to develop new concepts and technology for the Comet Rendezvous Asteroid Flyby (CRAF), Cassini, and other future deep space missions which maximally conform to the Functional Specification for the NASA X-Band Transponder (NXT), FM513778 (preliminary, revised July 26, 1988). The study is composed of two tasks. The first task was to investigate a new digital signal processing technique which involves the processing of 1-bit samples and has the potential for significant size, mass, power, and electrical performance improvements over conventional analog approaches. The entire X-band receiver tracking loop was simulated on a digital computer using a high-level programming language. Simulations on this 'software breadboard' showed the technique to be well-behaved and a good approximation to its analog predecessor from threshold to strong signal levels in terms of tracking-loop performance, command signal-to-noise ratio and ranging signal-to-noise ratio. The successful completion of this task paves the way for building a hardware breadboard, the recommended next step in confirming this approach is ready for incorporation into flight hardware. The second task in this study was to investigate another technique which provides considerable simplification in the synthesis of the receiver first LO over conventional phase-locked multiplier schemes and in this approach, provides down-conversion for an S-band emergency receive mode without the need of an additional LO. The objective of this study was to develop methodology and models to predict the conversion loss, input RF bandwidth, and output RF bandwidth of a series GaAs FET sampling mixer and to breadboard and test a circuit design suitable for the X and S-band down-conversion applications.

Nuckolls, C.↗

Optoelectronic polymer memristors with dynamic control for power-efficient in-sensor edge computing

Abstract As the demand for edge platforms in artificial intelligence increases, including mobile devices and security applications, the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components. Here, we introduce low-power organic optoelectronic memristors with synergistic optical and mV-level electrical tunable operation for a dynamic “control-on-demand” architecture. Integrating signal sensing, featuring, and processing within the same memristors enables the realization of each in-sensor analogue reservoir computing module, and minimizes circuit integration complexity. The system achieves 97.15% fingerprint recognition accuracy while maintaining a minimal reservoir size and ultra-low energy consumption. Furthermore, we leverage wafer-scale solution techniques and flexible substrates for optimal memristor fabrication. By centralizing core functionalities on the same in-sensor platform, we propose a resilient and adaptable framework for energy-efficient and economical edge computing.

Optics↗