Array Device Research Articles

Numerical Study of SQUID Array Responses Due to Asymmetric Junction Parameters

Superconducting quantum interference device arrays have been extensively studied for their high magnetic field sensitivity. The performance of these devices strongly depends on the characteristic parameters of their Josephson junctions, i.e. their critical currents and shunt resistances. Using a resistively shunted junction model and including thermal noise, we perform a numerical investigation of the effects of asymmetric Josephson junctions by independently studying variations in the critical currents and junction resistances. We compare the voltage response of a dc-SQUID with a 1D parallel SQUID array and study the maximum transfer function dependence on the number of junctions in parallel, the screening parameter and thermal noise strength. Our results show that the maximum transfer function and linearity increase with the number of junctions in parallel for arrays with different junction resistances, in contrast to SQUID arrays with identical junctions or with spreads in the critical currents.

Complex‐order controller design examples and their implementation

AbstractA systematic method for approximating the complex‐order Laplacian operator by realizable integer‐order transfer functions is presented in this work. The realization is performed by a simple structure where only one active element is used. Thanks to the employment of complex‐order impedances, both integrators and differentiators can be readily implemented by the same core simply by interchanging the associated impedance locations. The validity of the presented concept is verified through simulation and experimental results, using the OrCAD PSpice suite and a Field Programmable Analog array device.

HMT: A Hardware-centric Hybrid Bonsai Merkle Tree Algorithm for High-performance Authentication

The Bonsai Merkle tree (BMT) is a widely used tree structure for authentication of metadata such as encryption counters in a secure computing system. Common BMT algorithms were designed for traditional Von Neumann architectures with a software-centric implementation in mind and as such, they are predominantly recursive and sequential in nature. However, the modern heterogeneous computing platforms employing Field-Programmable Gate Array (FPGA) devices require concurrency-focused algorithms to fully utilize the versatility and parallel nature of such systems. The recursive nature of traditional BMT algorithms makes them challenging to implement in such hardware-based setups. Our goal for this work is to introduce HMT, a hardware-friendly BMT algorithm that enables the verification and update processes to function independently and provides the benefits of relaxed update while being comparable to the eager update in terms of update complexity. The methodology of HMT contributes both novel algorithmic revisions and innovative hardware techniques to implementing BMT. We mathematically demonstrate the challenges of potentially unbounded recursions in relaxed BMT updates. To solve this problem, we use a partitioned BMT caching scheme that allocates a separate write-back cache for each BMT level—thus allowing for low and fixed upper bounds for dirty evictions compared to the traditional BMT caches. Then we introduce the aforementioned hybrid BMT algorithm that is hardware-targeted, parallel, and relaxes the update depending on BMT cache hit but makes the update conditions more flexible compared to lazy update to save additional write-backs. Deploying this new algorithm, we have designed a new BMT controller with a dataflow architecture including speculative buffers and parallel write-back engines to facilitate performance-enhancing mechanisms (like multiple concurrent authentication and independent updates) that were not possible with the conventional lazy algorithm. Our empirical performance measurements on a Xilinx U200 accelerator FPGA have demonstrated that HMT can achieve up to 7× improvement in bandwidth and 4.5× reduction in latency over lazy-update BMT baseline and up to 14% faster execution in standard benchmarks compared to a state-of-the-art, eager-update BMT solution.

Sub-micro organic light emitting diode arrays defined by tip-induced resist hollow structures

Fabrication of micro-nanoscaled organic light-emitting diodes (OLEDs) with uniformity and scalability has emerged as a promising technology in next-generation displays and light sources. Patterning polymer resist into well-defined structures is a crucial step in the fabrication of optoelectronic device arrays, especially for cost-effectively fabricating lithographical sub-micro resist structures. Atomic force microscopy (AFM) ploughing is promising for patterning high-resolution polymer resist structures owing to nanoscaled resolution, high controllability, with relatively low cost under flexible working conditions. However, the defects of structures resulting from polymer debris contamination or spin-coated film exfoliation in ploughing procedure limit their further application in fabrication of device arrays. Herein, lithographical poly(methyl methacrylate) (PMMA) resist patterns in micro-nanoscale with excellent reproducibility and uniformity are achieved via AFM mechanical ploughing at the optimized lithography conditions. Taking use of the isolated PMMA cavities as current channels, we fabricate prototype OLED arrays with pixels of 500 nm and 1 μm. This work paves the way for developing a tip-based mechanical lithography approach to fabricate micro-nanoscaled optoelectronic devices in a simple and low-cost way.

Microlens array device for laser light shaping in laser scanning smart headlights.

We present, what we believe to be, a novel microlens array (MLA) scheme for laser light shaping in laser scanning smart headlight. The laser spot has a Gaussian distribution that may reach a high peak power density in the central part, which is called hot spot. When the laser beam is applied to a phosphor plate for luminous conversion, the hot spot of Gaussian beam causes thermal quench and decreases luminous efficacy. To avoid this effect, an MLA is used, so as to achieve a uniform energy distribution. In this study, we propose a laser scanning smart headlight fabricated by a new MLA structure, with an arrangement providing both light uniformity and shaping. The novel MLA is designed by two-dimensional micro-concave lens array yielding a flat-top beam. The flexible fabrication process employs laser drilling to shape the micro-hole array on the glass substrate surface and then etch it to form MLA without requiring any mask lithography process. The full-width half maximum (FWHM) of light output distribution can be adjusted by the glass etching parameters, and the light distribution could be controlled by the arranged layout of the array. Thus, beams with FWHM divergence ranging from 5° to 34° has been fabricated and characterized. The typical pixel shape is a rectangle with two different FWHMs in two orthogonal directions, and the fabrication method achieves this goal as well. This novel design and unique maskless process of the MLAs is a promising tool for development the next generation laser scanning smart headlight.

In-situ artificial retina with all-in-one reconfigurable photomemristor networks

Despite that in-sensor processing has been proposed to remove the latency and energy consumption during the inevitable data transfer between spatial-separated sensors, memories and processors in traditional computer vision, its hardware implementation for artificial neural networks (ANNs) with all-in-one device arrays remains a challenge, especially for organic-based ANNs. With the advantages of biocompatibility, low cost, easy fabrication and flexibility, here we implement a self-powered in-sensor ANN using molecular ferroelectric (MF)-based photomemristor arrays. Tunable ferroelectric depolarization was intentionally introduced into the ANN, which enables reconfigurable conductance and photoresponse. Treating photoresponsivity as synaptic weight, the MF-based in-sensor ANN can operate analog convolutional computation, and successfully conduct perception and recognition of white-light letter images in experiments, with low processing energy consumption. Handwritten Chinese digits are also recognized and regressed by a large-scale array, demonstrating its scalability and potential for low-power processing and the applications in MF-based in-situ artificial retina.

Comprehensive High-Quality Three-Dimensional Display System Based on a Simplified Light-Field Image Acquisition Method and a Full-Connected Deep Neural Network.

We propose a high-quality, three-dimensional display system based on a simplified light field image acquisition method, and a custom-trained full-connected deep neural network is proposed. The ultimate goal of the proposed system is to acquire and reconstruct the light field images with possibly the most elevated quality from the real-world objects in a general environment. A simplified light field image acquisition method acquires the three-dimensional information of natural objects in a simple way, with high-resolution/high-quality like multicamera-based methods. We trained a full-connected deep neural network model to output desired viewpoints of the object with the same quality. The custom-trained instant neural graphics primitives model with hash encoding output the overall desired viewpoints of the object within the acquired viewing angle in the same quality, based on the input perspectives, according to the pixel density of a display device and lens array specifications within the significantly short processing time. Finally, the elemental image array was rendered through the pixel re-arrangement from the entire viewpoints to visualize the entire field-of-view and re-constructed as a high-quality three-dimensional visualization on the integral imaging display. The system was implemented successfully, and the displayed visualizations and corresponding evaluated results confirmed that the proposed system offers a simple and effective way to acquire light field images from real objects with high-resolution and present high-quality three-dimensional visualization on the integral imaging display system.

Recent Progress of Self-Supported Metal Oxide Nano-Porous Arrays in Energy Storage Applications.

The demand for high-performance and cost-effective energy storage solutions for mobile electronic devices and electric vehicles has been a driving force for technological advancements. Among the various options available, transitional metal oxides (TMOs) have emerged as a promising candidates due to their exceptional energy storage capabilities and affordability. In particular, TMO nanoporous arrays fabricated by electrochemical anodization technique demonstrate unrivaled advantages including large specific surface area, short ion transport paths, hollow structures that reduce bulk expansion of materials, and so on, which have garnered significant research attention in recent decades. However, there is a lack of comprehensive reviews that discuss the progress of anodized TMO nanoporous arrays and their applications in energy storage. Therefore, this review aims to provide a systematic detailed overview of recent advancements in understanding the ion storage mechanisms and behavior of self-organized anodic TMO nanoporous arrays in various energy storage devices, including alkali metal ion batteries, Mg/Al-ion batteries, Li/Na metal batteries, and supercapacitors. This review also explores modification strategies, redox mechanisms, and outlines future prospects for TMO nanoporous arrays in energy storage.

Comparative Analysis of the Filling Mass of Vertical Heat Exchanger Tubes on the Thermal Environment of Arched Greenhouses

The greenhouse’s energy consumption is a major limiting factor for output and development. To address this, it is necessary to adopt green and low-carbon heating technologies to replace traditional fuels. This will not only help conserve energy but will also reduce emissions, thereby improving the thermal environmental conditions for agriculture. This paper aims to research and develop a vertical heat exchange tube array device specifically designed for greenhouses. The focus is on enhancing the passive heat absorption and heat storage efficiency of the device and its influence on the thermal environment of the greenhouse. In order to improve the heat absorption and storage efficiency of the heat exchanger device and its impact on the greenhouse thermal environment, experimental comparative analysis was conducted using air, water, and phase-change materials as working fluids inside the pipes. Through a combination of experiments and simulations, it was verified that the heat exchanger device is capable of actively regulating the greenhouse thermal environment. The results show that heat exchangers of all three types of working fluids can effectively improve the stability of soil temperature and play a “shifting the peak and filling the valley” role in regulating the indoor air temperature while positively regulating the relative humidity of the air. Notably, when the working fluid is a phase-change material, it has the most significant impact on the thermal environment of the greenhouse.

FPGA-based fault analysis for 7-level switched ladder multi-level inverter using decision tree algorithm

The proposed method involves the fault analysis of the inverter switches present in the multi-level inverter (MLI) circuitry. The decision tree machine learning algorithm is incorporated for the fault analysis of the inverter switches. The multi-level inverter utilized in this work is a 7-level switched ladder multi-level inverter. There is 4 number of switches in the design of a 7-level inverter driven by the non-carrier digital pulse width modulation signals. The non-carried-based digital pulse-width modulator (DPWM) generation is generated using the event angle for the 7-level of the switched ladder inverter. The proposed method investigates the stuck-at-fault occurrences of the 4 switches in the inverter by manipulating the decision tree parameters such as entropy, information gain, and decision tree. Based on the decision tree, the very high-speed integrated circuit hardware description language (VHDL) code is developed by making use of the behavioral modeling and validated for the power, area in the Xilinx Vivado tool. The real-time feasibility is verified for the proposed method by synthesizing the developed VHDL code in the field programmable gate array (FPGA) device.

FPGA Implementation of Compact Hardware Accelerators for Ring-Binary-LWE-based Post-quantum Cryptography

Post-quantum cryptography (PQC) has recently drawn substantial attention from various communities owing to the proven vulnerability of existing public-key cryptosystems against the attacks launched from well-established quantum computers. The Ring-Binary-Learning-with-Errors (RBLWE), a variant of Ring-LWE, has been proposed to build PQC for lightweight applications. As more Field-Programmable Gate Array (FPGA) devices are being deployed in lightweight applications like Internet-of-Things (IoT) devices, it would be interesting if the RBLWE-based PQC can be implemented on the FPGA with ultra-low complexity and flexible processing. However, thus far, limited information is available for such implementations. In this article, we propose novel RBLWE-based PQC accelerators on the FPGA with ultra-low implementation complexity and flexible timing. We first present the process of deriving the key operation of the RBLWE-based scheme into the proposed algorithmic operation. The corresponding hardware accelerator is then efficiently mapped from the proposed algorithm with the help of algorithm-to-architecture implementation techniques and extended to obtain higher-throughput designs. The final complexity analysis and implementation results (on a variety of FPGAs) show that the proposed accelerators have significantly smaller area-time complexities than the state-of-the-art designs. Overall, the proposed accelerators feature low implementation complexity and flexible processing, making them desirable for emerging FPGA-based lightweight applications.

Analogue Artificial Synaptic Performance of Self‐Rectifying Resistive Switching Device

AbstractThe immense increase of unstructured data require novel computing systems that can process the input data with low power and parallel processing. This functionality is similar to that of human brains that are composed of numerous neurons, synapses, and their complex connections. To mimic the functionality of the human brain with an electronic device, the resistive switching device and crossbar array has attracted considerable attention for artificial synaptic devices and integrated systems, respectively. For this purpose, the self‐rectifying resistive switching cell based on the Si:ZrOx thin film is developed and its reliability characteristics are tested. Four achievements are highlighted in this study. 1) The retention characteristic is improved by the adoption of TaOx thin film as an oxygen reservoir layer. 2) The asymmetric electrodes can make the self‐rectifying resistive cell (SRC) have sufficient rectifying characteristic. 3) The linearity of conductance update has a dominant effect on the inference performance compared to that of the conductance range variation. 4) The device of the interface‐type resistive switching shows a high enough device yield in the crossbar array device and exhibits reliable multiply‐and‐accumulate operations in the crossbar array to mimic the human brain‐inspired computing system.

A versatile, bioengineered skin reconstruction device designed for use in austere environments.

Austere environments in which access to medical facilities, medical personnel, or even water and electricity is limited or unavailable pose unique challenges for medical device product design. Currently existing skin substitutes are severely inadequate for the treatment of severe burns, chronic wounds, battlefield injuries, or work-related injuries in resource-limited settings. For such settings, an ideal device should be biocompatible, bioresorbable, promote tissue healing, not require trained medical personnel for deployment and use, and should enable topical drug delivery. As proof of concept for such a device, silk fibroin and an antioxidant hyaluronic acid derivative were chosen as primary constituents. The final formulation was selected to optimize tensile strength while retaining mechanical compliance and protection from reactive oxygen species (ROS). The ultimate tensile strength of the device was 438.0KPa. Viability of dermal fibroblasts challenged with ROS-generating menadione decreased to 49.7% of control, which was rescued by pre-treatment with the hyaluronic acid derivative to 85.0% of control. The final device formulation was also tested in a standardized, validated, in vitro skin irritation test which revealed no tissue damage or statistical difference from control. Improved topical drug delivery was achieved via an integrated silk fibroin microneedle array and selective device processing to generate crosslinked/through pores. The final device including these features showed a 223% increase in small molecule epidermal permeation relative to the control. Scaffold porosity and microneedle integrity before and after application were confirmed by electron microscopy. Next, the device was designed to be self-adherent to enable deployment without the need of traditional fixation methods. Device tissue adhesive strength (12.0MPa) was evaluated and shown to be comparable to a commercial adhesive surgical drape (12.9MPa) and superior to an over-the-counter liquid bandage (4.1MPa). Finally, the device's wound healing potential was assessed in an in vitro full-thickness skin wound model which showed promising device integration into the tissue and cellular migration into and above the device. Overall, these results suggest that this prototype, specifically designed for use in austere environments, is mechanically robust, is cytocompatible, protects from ROS damage, is self-adherent without traditional fixation methods, and promotes tissue repair.

A Generalized Block-Matrix Circuit for Closed-Loop Analog In-Memory Computing

Matrix-based computing is ubiquitous in an increasing number of present-day machine learning applications such as neural networks, regression and 5G communications. Conventional systems based on von-Neumann architecture are limited by the energy and latency bottleneck induced by the physical separation of the processing and memory units. Inmemory computing (IMC) is a novel paradigm where computation is performed directly within the memory, thus eliminating the need for constant data transfer. IMC has shown exceptional throughput and energy efficiency when coupled with crosspoint arrays of resistive memory devices in open-loop matrix-vector-multiplication and closed-loop inverse-matrix-vector multiplication (IMVM) accelerators. However, each application result in a different circuit topology, thus complicating the development of reconfigurable, general-purpose IMC systems. In this paper, we present a generalized closed-loop IMVM circuit capable of performing any linear matrix operation by proper memory remapping. We derive closed-form equations for the ideal input/ output transfer functions, static error, and dynamic behavior, introducing a novel continuous-time analytical model allowing for orders-of-magnitude simulation speedup with respect to SPICE-based solvers. The proposed circuit represents an ideal candidate for general-purpose accelerators of machine learning.

29‐4: Higher External Quantum Efficiency with Lower Current Density Injection of <10 μm Pixel Size Arrays for Display Application

In this paper, the gallium nitride (GaN) based Micro‐LED was fabricated based on a self‐aligned process with hydroxide treatment and ALD passivation from 100 μm down to 3 μm. The different current spreading performance was characterized based on the series resistance analysis. Then the size‐dependent carrier concentration profile was demonstrated via the capacitancevoltage measurement, identifying the various carrier injection behavior by different size. Finally, the external quantum efficiency and luminance versus current density dependence for array device and the single device was compared, revealing a higher efficiency at lower current density for array device, which is favorable for display application.

Josephson parametric circulator with same-frequency signal ports, 200 MHz bandwidth, and high dynamic range

We demonstrate a 3-port Josephson parametric circulator matched to 50 Ω using second order Chebyshev networks. The device notably operates with two of its signal ports at the same frequency and uses only two out-of-phase pumps at a single frequency. As a consequence, when operated as an isolator, it does not require phase coherence between the pumps and the signal, thus simplifying the requirements for its integration into standard dispersive qubit readout setups. The device utilizes parametric couplers based on a balanced bridge of rf-superconducting quantum interference device arrays, which offer purely parametric coupling and high dynamic range. We characterize the device by measuring its full 3 × 3 S-matrix as a function of frequency and the relative phase between the two pumps. We find up to 15 dB nonreciprocity over a 200 MHz signal band, port match better than 10 dB, low insertion loss of 0.6 dB, and saturation power exceeding −80 dBm.

In-vivo testing of a novel wireless intraspinal microstimulation interface for restoration of motor function following spinal cord injury.

Spinal cord injury causes a drastic loss in motor and sensory function. Intraspinal microstimulation (ISMS) is an electrical stimulation method developed for restoring motor function by activating the spinal networks below the level of injury. Current ISMS technology uses fine penetrating microwires to stimulate the ventral horn of the lumbar enlargement. The penetrating wires traverse the dura mater through a transdural conduit that connects to an implantable pulse generator. A wireless, fully intradural ISMS implant was developed to mitigate the potential complications associated with the transdural conduit, including tethering and leakage of cerebrospinal fluid. Two wireless floating microelectrode array (WFMA) devices were implanted in the lumbar enlargement of an adult domestic pig. Voltage transients were used to assess the electrochemical stability of the interface. Manual flexion and extension movements of the spine were performed to evaluate the mechanical stability of the interface. Post-mortem 9T MRI imaging was used to confirm the location of the electrodes. The WFMA-based ISMS interface successfully evoked extension and flexion movements of the hip joint. Stimulation thresholds remained stable following manual extension and flexion of the spine. The preliminary results demonstrate the surgical feasibility as well as the functionality of the proposed wireless ISMS system.

Design of a Sleep Modulation System with FPGA-Accelerated Deep Learning for Closed-loop Stage-Specific In-Phase Auditory Stimulation.

Closed-loop sleep modulation is an emerging research paradigm to treat sleep disorders and enhance sleep benefits. However, two major barriers hinder the widespread application of this research paradigm. First, subjects often need to be wire-connected to rack-mount instrumentation for data acquisition, which negatively affects sleep quality. Second, conventional real-time sleep stage classification algorithms give limited performance. In this work, we conquer these two limitations by developing a sleep modulation system that supports closed-loop operations on the device. Sleep stage classification is performed using a lightweight deep learning (DL) model accelerated by a low-power field-programmable gate array (FPGA) device. The DL model uses a single channel electroencephalogram (EEG) as input. Two convolutional neural networks (CNNs) are used to capture general and detailed features, and a bidirectional long-short-term memory (LSTM) network is used to capture time-variant sequence features. An 8-bit quantization is used to reduce the computational cost without compromising performance. The DL model has been validated using a public sleep database containing 81 subjects, achieving a state-of-the-art classification accuracy of 85.8% and a F1-score of 79%. The developed model has also shown the potential to be generalized to different channels and input data lengths. Closed-loop in-phase auditory stimulation has been demonstrated on the test bench.

A Universal Fabrication Strategy for High-Resolution Perovskite-Based Photodetector Arrays.

Metal halide perovskite photodetector arrays have demonstrated great potential applications in the field of integrated systems, optical communications, and health monitoring. However, the fabrication of large-scale and high-resolution device is still challenging due to their incompatibility with the polar solvents. Here, a universal fabrication strategy that utilizes ultrathin encapsulation-assisted photolithography and etching to create high-resolution photodetectors array with vertical crossbar structure is reported. This approach yields a 48 × 48 photodetector array with a resolution of 317 ppi. The device shows good imaging capability with a high on/off ratio of 3.3 × 105 and long-term working stability over 12h. Furthermore, this strategy can be applied to five different material systems, and is fully compatible with the existing photolithography and etching techniques, which are expected to have potential applications in the other high-density and solvent-sensitive devices array, including perovskite- or organic semiconductor-based memristor, light emitting diode displays, and transistors.

Enhancing the high-temperature energy storage performance of PEI dielectric film through deposition of high-dielectric PZT coating layer

Dielectric film capacitors are a highly ubiquitous and indispensable electronic component, serving a crucial role in a wide array of electronic devices and power systems. Despite their extensive use, polymer film capacitors are often hampered by the conduction loss that ensues when they are subjected to high electric fields and temperatures. As a result, this leads to a significant reduction in energy density and charge-discharge efficiency. To solve this issue, magnetron sputtering technology was used to create a sandwich structure made of polyetherimide (PEI) thin films with lead zirconate titanate (PZT) inorganic layers coated on both sides. This remarkable innovation has successfully introduced the high dielectric PZT layer in the PEI film/metal electrode, substantially augmenting the barrier height at the dielectric/polymer interface. This has also resulted in a marked decrease in conduction loss, as conclusively validated by the experimental findings. At 150 °C and with charge-discharge efficiency above 90%, the maximum discharged energy density is 3.26 J/cm3, which is increased by 263% compared to the pristine PEI films (1.24 J/cm3 at 290 MV/m and 150 °C). This study designed a unique inorganic barrier layer of PZT to increase the energy storage capability of polymer dielectric films in high-temperature environments.