Search

Neuromorphic computing targets realizing biomimetic or intelligence systems capable of processing abundant tasks in parallel analogously to our brain, and organic electrochemical transistors (OECTs) that rely on the mixed ionic-electronic synergistic couple possess significant similarity to biological systems for implementing synaptic functions. However, the lack of reliable stretchability for synaptic OECTs, where mechanical deformation occurs, leads to consequent degradation of electrical performance. Herein, we demonstrate stretchable synaptic OECTs by adopting a three-dimensional poly(3-hexylthiophene) (P3HT)/styrene-ethylene-butylene-styrene (SEBS) blend porous elastic film for neuromorphic computing. Such architecture shows the full capability to emulate biological synaptic behaviors. Adjusting the accumulated layer numbers of porous film enables tunable OECT output and hysteresis, resulting in transition in plasticity. Especially, with a trilayer porous film, large-scale conductance and hysteresis are endorsed for efficient mimicking of memory-dependent synapse behavior. Benefitted from the interconnected three-dimensional porous structures, corresponding stretchable synaptic OECTs exhibit excellent mechanical robustness when stretched at a 30% strain, and maintain reliable electrical characteristics after 500 stretching cycles. Furthermore, near-ideal weight updates with near-zero nonlinearities, symmetricity in long-term potentiation (LTP) and depression, and applications for image simulation are validated. This work paves a universal design strategy toward high-performance stretchable neuromorphic computing architecture and could be extended to other flexible/stretchable electronics. [ABSTRACT FROM AUTHOR]

The emergence of ionic-junction devices has attracted growing interests due to the potential of serving as signal transmission and translation media between electronic devices and biological systems using ions. Among them, fiber-shaped iontronics possesses a great advantage in implantable applications owing to the unique one-dimensional geometry. However, fabricating stable ionic-junction on curved surfaces remains a challenge. Here, we developed a polyelectrolyte based ionic-junction fiber via an integrated opposite charge grafting method capable of large-scale continuous fabrication. The ionic-junction fibers can be integrated into functions such as ionic diodes and ionic bipolar junction transistors, where rectification and switching of input signals are implemented. Moreover, synaptic functionality has also been demonstrated by utilizing the fiber memory capacitance. The connection between the ionic-junction fiber and sciatic nerves of the mouse simulating end-to-side anastomosis is further performed to realize effective nerve signal conduction, verifying the capability for next-generation artificial neural pathways in implantable bioelectronics. Ionic-junction devices are difficult to integrate with fiber-shaped tissues like nerves and muscles for applications in implantable bioelectronics due to their large size and bulk structure. Authors realize here easy to implant fiber-shaped iontronics through an integrated opposite charge grafting process, enabling the construction of ionic logic gates and artificial neural pathways. [ABSTRACT FROM AUTHOR]

Organic electrochemical transistors (OECTs) and OECT-based circuitry offer great potential in bioelectronics, wearable electronics and artificial neuromorphic electronics because of their exceptionally low driving voltages (<1 V), low power consumption (<1 µW), high transconductances (>10 mS) and biocompatibility1–5. However, the successful realization of critical complementary logic OECTs is currently limited by temporal and/or operational instability, slow redox processes and/or switching, incompatibility with high-density monolithic integration and inferior n-type OECT performance6–8. Here we demonstrate p- and n-type vertical OECTs with balanced and ultra-high performance by blending redox-active semiconducting polymers with a redox-inactive photocurable and/or photopatternable polymer to form an ion-permeable semiconducting channel, implemented in a simple, scalable vertical architecture that has a dense, impermeable top contact. Footprint current densities exceeding 1 kA cm−2 at less than ±0.7 V, transconductances of 0.2–0.4 S, short transient times of less than 1 ms and ultra-stable switching (>50,000 cycles) are achieved in, to our knowledge, the first vertically stacked complementary vertical OECT logic circuits. This architecture opens many possibilities for fundamental studies of organic semiconductor redox chemistry and physics in nanoscopically confined spaces, without macroscopic electrolyte contact, as well as wearable and implantable device applications.Vertical organic electrochemical transistors demonstrating unprecedented performances in both p- and n-type operation modes have been synthesized from new electro-active and ion-permeable semiconducting polymers by the interface engineering of electro-active blend layers. [ABSTRACT FROM AUTHOR]

With the modernization and intelligent of industrial equipment and systems, the challenges of dynamic characteristics, failure dependency and uncertainties have aroused by the increasing of system complexity. Besides, various types of components may follow different life distributions which bring the multiple life distributions problem in systems. In order to model the impact of time dependency and epistemic uncertainty on the failure behavior of system, this paper combines the flexible dynamic modeling with the uncertainty expression. Its advantages are intuitively graphical representation and reasoning that brought by evidential network (EN). After that, the discrete time dynamic evidential network (DT-DEN) is introduced to analyze the reliability of complex systems, and the network inference mechanism is clearly defined. The evidence theory and original definition and inference mechanism of conventional EN is firstly recommended, and the DT-DEN is further presented. Furthermore, the multiple life distributions are synthesized into the DT-DEN to tackle the epistemic uncertainty and mixed life distribution challenges. Specifically, the dynamic logic gates are converted into equivalent DENs with distinguished conditional mass tables, and then the belief interval of system reliability can be calculated by network forward reasoning. Finally, the availability and efficiency of the proposed method is verified by some numerical examples. [ABSTRACT FROM AUTHOR]

In this paper, a novel parameterized generative adversarial network (GAN) is proposed where the parameters are introduced to enhance the performance of image segmentation. The developed algorithm is applied to the image-based crack detection problem on the thermal data obtained through the non-destructive testing process. A new regularization term, which contains three tunable hyperparameters, embedded into the objective function of the GAN in order to improve the contrast ratio of certain areas of the image so as to benefit the crack detection process. To automate the selection of the optimal hyperparameters of the GAN, a new particle swarm optimization (PSO) algorithm is put forward where a neighborhood-based velocity updating strategy is developed for the purpose of thoroughly exploring the problem space. The proposed PSO-based GAN algorithm is shown to 1) work well in detecting cracks on the thermal data generated by the eddy current pulsed thermography technique; and 2) outperforms other conventional GAN algorithms. [ABSTRACT FROM AUTHOR]

In this paper, an improved generative adversarial network (GAN) is proposed for the crack detection problem in electromagnetic nondestructive testing (NDT). To enhance the contrast ratio of the generated image, two additional regulation terms are introduced in the loss function of the underlying GAN. By applying an appropriate threshold to the segmentation of the generated image, the real crack areas and the fake crack areas (which are affected by the noises) are accurately distinguished. Experiments are carried out to show the superiority of the improved GAN over the original one on crack detection tasks, where a real-world NDT dataset is exploited that consists of magnetic optical images obtained using the electromagnetic NDT technique. [ABSTRACT FROM AUTHOR]

As a popular nondestructive testing (NDT) technique, thermal imaging test demonstrates competitive performance in crack detection, especially for detecting subsurface cracks. In thermal imaging test, the temperature of the crack area is higher than that of the non-crack area during the NDT process. By extracting the features of the thermal image sequences, the temperature curve of each spatial point is employed for crack detection. Nevertheless, the quality of thermal images is influenced by the noises due to the complex thermal environment in NDT. In this paper, a modified generative adversarial network (GAN) is employed to improve the image segmentation performance. To improve the feature extraction ability and alleviate the influence of noises, a penalty term is put forward in the loss function of the conventional GAN. A data preprocessing method is developed where the principle component analysis algorithm is adopted for feature extraction. The data argumentation technique is utilized to guarantee the quantity of the training samples. To validate its effectiveness in thermal imaging NDT, the modified GAN is applied to detect the cracks on the eddy current pulsed thermography NDT dataset. [ABSTRACT FROM AUTHOR]

Underground pipelines suffered severe external breakage caused by excavation devices due to arbitral road excavation. Acoustic signal-based recognition has recently shown effectiveness in underground pipeline network surveillance. However, merely relying on recognition may lead to a high false alarm rate. The reason is that underground pipelines are generally paved along a fixed direction and excavations out of the region also trigger the surveillance system. To enhance the reliability of the surveillance system, the direction-of-arrival (DOA) estimation of target sources is combined into the recognition algorithm to reduce false detections in this paper. Two hybrid recognition algorithms are developed. The first one employs extreme learning machine (ELM) for acoustic recognition followed by a focusing matrix-based multiple signal classification algorithm (ELM-MUSIC) for DOA estimation. The second introduces a decision matrix (DM) to characterize the statistic distribution of results obtained by ELM-MUSIC. Real acoustic signals collected by a cross-layer sensor array are conducted for performance comparison. Four representative excavation devices working in a metro construction site are used to generate the signal. Multiple scenarios of the experiments are designed. Comparisons show that the proposed ELM-MUSIC and DM algorithms outperform the conventional focusing matrix based MUSIC (F-MUSIC). In addition, the improved DM method is capable of localizing multiple devices working in order. Two hybrid acoustic signal recognition and source direction estimation algorithms are developed for excavation device classification in this paper. The novel recognition combining DOA estimation scheme can work efficiently for underground pipeline network protection in the real-world complex environment. [ABSTRACT FROM AUTHOR]

The paper proposes a method for crack detection using the magnetic optic image. It presents a way to filter the magnetic domain spots based on the image segmentation method utilizing the connectivity principle of image. As the area of the crack is much bigger than the magnetic domain spots and there is a mutation in the point, whose normalized slope is beyond $$45^\circ $$ , between the crack and the magnetic domain spots after sorting the area value of them, the machinery could filter the magnetic domain spots. In order to filter the spots, how to select the threshold is very important. The paper presents a self-adapting selection method to choose the threshold which based the pixel filling model. There would be a fast changing point of the filling area curve when the area increases. There is a corresponding filling value that is considered as the good threshold. Based on the features, the detecting system can recognize the crack clearly and the results would confirmed it. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive sliding mode technique based on a fractional-order (FO) switching-type control law is designed to guarantee robust stability for uncertain 3D FO nonlinear systems. A novel FO switching-type control law is proposed to ensure the existence of the sliding motion in finite time. Appropriate adaptive laws are shown to tackle the uncertainty and external disturbance. The calculation formula of the reaching time is analyzed and computed. The reachability analysis is visualized to show how to obtain a shorter reaching time. A stability criterion of the FO sliding mode dynamics is derived based on indirect approach to Lyapunov stability. Advantages of the proposed control scheme are illustrated through numerical simulations. [ABSTRACT FROM AUTHOR]

HfO based resistive switching devices with thin AlO layer inserted between HfO and TiN top electrode (TE) and Pt bottom electrode (BE) were fabricated respectively. Both devices show robust bipolar resistive switching phenomenon. Experimental result reveals that TiN/AlO/HfO/Pt device with appropriately thick HfO film shows significant enhancement in performance as compared with other samples, having lower voltage and excellent uniformity. The role of inserted AlO layer and thickness of HfO film on resistive switching properties are discussed and clarified through comparative experiments, which is considered to be a doping effect. The experimental result is consistent with the model where resistive switching happens near TiN top electrode (TE) due to partial rupture and reconstruction of conducting filaments (CFs) assisted by the doping. The different doping profiles near top electrode of the samples were confirmed by XPS depth analysis. This work provides detailed information about the optimization of HfO based resistive switching device by a doping profile modification approach. [ABSTRACT FROM AUTHOR]

Copyright of SCIENCE CHINA Information Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Sub-threshold leakage is a major issue for low power circuits design, especially for SRAM design in SoC. Sub-threshold leakage can be decreased by scaling down supply voltage. However, this may dramatically increase the circuit delay. In this paper, we propose a novel 6 T SRAM array structure with a switch module which operates in the near threshold region to reduce the leakage current. In order to verify our proposed leakage reduction scheme, we designed and simulated an 8192 kB SRAM array based on a 16 KB single port SRAM cell memory model in 55 nm process. Several 6 T SRAM Array instances are implemented in 55-nm 1P6M CMOS technology to measure the standby current of the proposed scheme as well. With the proposed technique, we achieved 28.3% reduction for leakage current compared to traditional 6 T SRAM array, in standby mode where gate leakage is dominant. The total penalty is 2% area increase and 1% speed reduction. [ABSTRACT FROM AUTHOR]

A 6-bit 2 GS/s ADC was implemented using a 65 nm digital CMOS technology. The design is based on a single-channel flash ADC architecture, and utilizes interpolating and averaging techniques. A two-stage CML-CMOS high-speed hybrid comparator is designed for optimal speed and power performance. The total power consumption of the converter is 52 mW and the area is 0.24 mm. The ADC achieves 42.5 dB SFDR and 5.2 bit ENOB at input frequency of 123 MHz, and at Nyquist frequency 37.67 dB SFDR and 4.9 bit ENOB. [ABSTRACT FROM AUTHOR]

In this paper, we present the concept of feedbackability and how to identify the Minimum Feedbackability Set of an arbitrary complex directed network. Furthermore, we design an estimator and a feedback controller accessing one MFS to realize actual feedback control, i.e. control the system to our desired state according to the estimated system internal state from the output of estimator. Last but not least, we perform numerical simulations of a small linear time-invariant dynamics network and a real simple food network to verify the theoretical results. The framework presented here could make an arbitrary complex directed network realize actual feedback control and deepen our understanding of complex systems. [ABSTRACT FROM AUTHOR]

We propose an improved method to estimate the varying topology of discrete-time dynamical networks using autosynchronization. The networks considered in this paper can be weighted or unweighted and directed or undirected, and the dynamics of each node can be nonuniform. Furthermore, we suggest using a moving-average filter to suppress the influence of noise on parameter estimation. Finally, several examples are illustrated to verify the theoretical results by numerical simulation. [ABSTRACT FROM AUTHOR]

Electrostatic discharge (ESD) failure has become an emerging challenge for radio frequency (RF) integrated circuits (ICs), which requires high ESD-protection for circuit applications in harsh environment. This paper discusses the design and optimization of an ultra-wideband (UWB) correlator circuit using ESDaware simulation design technique. Mixed-mode ESD simulation-design method and RF ESD characterization technique are presented for accurate ESD device design and ESD-induced parasitic effects extraction. The impact of ESD induced parasitic is carefully considered in the whole correlator design simulation by using a direct S-parameter insertion technique. The design is based on a commercial 0.18 μm RFCMOS technology. [ABSTRACT FROM AUTHOR]

A 133-500 MHz, 5.2 mW@500 MHz, 0.021 mm all digital delay-locked loop (ADDLL) is presented. The power and area reduction of the proposed ADDLL are achieved by implementing a high frequency ring oscillator (ROSC) to count the reference clocks such that the one-clock cycle delay chain and the phase detector in a conventional Master block are no longer needed. The proposed ADDLL has better immunity to PVT (process, voltage, and temperature) than most conventional DLLs, which do not update the control word signals after the locking process, since the control signals for slave delay line are updated in every 256 reference cycles. Fabricated in 0.13 um CMOS process, the measured RMS jitter is 10.83 ps at 500 MHz while the RMS jitter of the input signal is 9.97 ps. [ABSTRACT FROM AUTHOR]

This paper discusses critical aspects for co-design of ultra wideband (UWB) system-on-chip (SoC) and on-chip electrostatic discharge (ESD) protection, which are beyond the considerations on data rate and bandwidth. Impulse radio UWB system architecture has been defined with critical building blocks proposed and verified, including pulse generator, transmitter, low noise amplifier (LNA) and multiplier based correlator. ESD protection is well considered for each related block. Design examples have been implemented in a commercial RFCMOS processes to demonstrate the working principles for key UWB transmitter and receiver circuit blocks. UWB-ESD co-design techniques, simulation and measurement results for these UWB RF modules are presented in detail. [ABSTRACT FROM AUTHOR]

This paper overviews design for manufacturing (DFM) for IC design in nano-CMOS technologies. Process/device issues relevant to the manufacturability of ICs in advanced CMOS technologies will be presented first before an exploration on process/device modeling for DFM is done. The discussion also covers a brief introduction of DFM-aware of design flow and EDA efforts to better handle the design-manufacturing interface in very large scale IC design environment. [ABSTRACT FROM AUTHOR]

Proposes an optimization method for the geometry of large van der Waals system by discussing the parallel dimer of benzene. Key to the method; Functions of the optimization method for large supramolecular systems.

Optimizing deployment of charging base stations in wireless rechargeable sensor networks can considerably reduce the cost. Previously, the charging base stations are simply installed at some fixed special points (e.g., the grid points) after partitioning the area distributed by sensor nodes. In this paper, a new algorithm of planning the charging base stations is proposed based on the greedy algorithm and the location relationship of the sensor nodes. The proposed algorithm exploits the local search ability and avoids falling into an exponential increase of the number of the charging base stations (i.e., combinatorial explosion). The simulated results show that the proposed algorithm can result in less number and flexible deployed locations of the charging base stations. In addition, this algorithm provides a novel solution for the point coverage problems. [ABSTRACT FROM AUTHOR]