Inorganic Halide Perovskite Nanowires/Conjugated Polymer Heterojunction-Based Optoelectronic Synaptic Transistors for Dynamic Machine Vision.

Inspired by the retina, artificial optoelectronic synapses have groundbreaking potential for machine vision. The field-effect transistor is a crucial platform for optoelectronic synapses that is highly sensitive to external stimuli and can modulate conductivity. On the basis of the decent optical absorption, perovskite materials have been widely employed for constructing optoelectronic synaptic transistors. However, the reported optoelectronic synaptic transistors focus on the static processing of independent stimuli at different moments, while the natural visual information consists of temporal signals. Here, we report CsPbBrI2 nanowire-based optoelectronic synaptic transistors to study the dynamic responses of artificial synaptic transistors to time-varying visual information for the first time. Moreover, on the basis of the dynamic synaptic behavior, a hardware system with an accuracy of 85% is built to the trajectory of moving objects. This work offers a new way to develop artificial optoelectronic synapses for the construction of dynamic machine vision systems.

Characterization of an imported HIV-1 A1/A7/G recombinant in China.

BACKGROUND: International migration has accelerated the HIV-1 spread across national borders, gradually reducing the restrictions on the geographical distribution of HIV-1 subtypes. Subtypes A and G are globally recognized as the third and sixth most dominant HIV-1 genotypes, mainly prevalent in Africa, but rarely detected in China. Here we reported an imported HIV-1 recombinant which was composed of sub-subtypes A1 and A7 of subtype A and subtype G genes in a Chinese female. This virus was the first HIV-1 recombinant including A7 genes reported in the world. CASE PRESENTATION: The near full-length genome (NFLG) was obtained from the plasma sample of the female in an HIV-1 molecular epidemiological survey with 853 participants in China. Phylogenetic analyses showed that this NFLG sequence contains three A7 segments, four G segments and one A1 segment with seven breakpoints, and all these segments were closely related to HIV-1 references circulating in Africa. The evidence from epidemiological investigation indicated that this female participant had a more-than-two-years heterosexual contact history with a fixed partner from Nigeria, a country in west Africa, which further supported the results of phylogenetic analyses. By the Bayesian phylogenetic analyses, the times of most recent common ancestors (tMRCA) of the partial pol gene (nt2308-3284, A7 region) and full-length vpr-vpu plus partial env gene (nt5534-6858, G region) were estimated around 1989 and 1984, respectively. CONCLUSIONS: In this study, by using the NFLG sequencing, we identified an imported HIV-1 A1/A7/G recombinant which was estimated to originate around 1980s in Africa and introduced into China with international migration. This study highlighted the complexity of the global HIV-1 epidemic, the necessity of using genome sequences to determine HIV-1 genotypes and the importance of real-time monitoring of HIV-1 infection among international migrants and travelers.

Identification of a novel HIV-1 second-generation circulating recombinant form (CRF136_0107) among MSM in China.

OBJECTIVE: To investigate the molecular epidemiology of HIV-1 in Heilongjiang, China, and try to spot signs of new circulating recombinant form (CRF) in this region. DESIGN: A molecular epidemiological study was conducted in Heilongjiang, China during 2011-2020. METHODS: Plasma samples were collected from three HIV-1-positive patients (two MSM and one man lacking risk factor information). The near full-length genome sequences (NFLGs) of a novel CRF were then obtained and subjected to phylogenetic analysis using Mega 7.0.26. Recombination analysis was performed by the jumping profile Hidden Markov Model (jpHMM). Finally, the origin time of this novel CRF was inferred using the Bayesian phylogenetic analysis in Beast v1.10.4. RESULTS: The three NFLGs formed a distinct monophyletic cluster in the neighbor-joining (NJ) tree. Recombination analysis revealed that the recombinant genome was composed of five segments derived from CRF01_AE, subtypes B, and C, but further confirmed to be a second-generation recombinant form of CRF01_AE/CRF07_BC by a comparison of genome maps and subregion phylogenetic analysis and, therefore, designated as CRF136_0107. With Bayesian phylogenetic analysis, CRF136_0107 was estimated to originate around 2010-2011. CONCLUSION: A novel HIV-1 CRF01_AE/CRF07_BC second-generation CRF called CRF136_0107 was identified among MSM in Heilongjiang, a northeast province of China.

High-Contrast Bidirectional Optoelectronic Synapses based on 2D Molecular Crystal Heterojunctions for Motion Detection.

Light-stimulated optoelectronic synaptic devices are fundamental compositions of the neuromorphic vision system. However, there are still huge challenges to achieving both bidirectional synaptic behaviors under light stimuli and high performance. Herein, a bilayer 2D molecular crystal (2DMC) p-n heterojunction is developed to achieve high-performance bidirectional synaptic behaviors. The 2DMC heterojunction-based field effect transistor (FET) devices exhibit typical ambipolar properties and remarkable responsivity (R) of 3.58×104 A W-1 under weak light as low as 0.008 mW cm-2 . Excitatory and inhibitory synaptic behaviors are successfully realized by the same light stimuli under different gate voltages. Moreover, a superior contrast ratio (CR) of 1.53×103 is demonstrated by the ultrathin and high-quality 2DMC heterojunction, which transcends previous optoelectronic synapses and enables application for the motion detection of the pendulum. Furthermore, a motion detection network based on the device is developed to detect and recognize classic motion vehicles in road traffic with an accuracy exceeding 90%. This work provides an effective strategy for developing high-contrast bidirectional optoelectronic synapses and shows great potential in the intelligent bionic device and future artificial vision.

Stretchable Transistor-Structured Artificial Synapses for Neuromorphic Electronics.

Stretchable synaptic transistors, a core technology in neuromorphic electronics, have functions and structures similar to biological synapses and can concurrently transmit signals and learn. Stretchable synaptic transistors are usually soft and stretchy and can accommodate various mechanical deformations, which presents significant prospects in soft machines, electronic skin, human-brain interfaces, and wearable electronics. Considerable efforts have been devoted to developing stretchable synaptic transistors to implement electronic device neuromorphic functions, and remarkable advances have been achieved. Here, this review introduces the basic concept of artificial synaptic transistors and summarizes the recent progress in device structures, functional-layer materials, and fabrication processes. Classical stretchable synaptic transistors, including electric double-layer synaptic transistors, electrochemical synaptic transistors, and optoelectronic synaptic transistors, as well as the applications of stretchable synaptic transistors in light-sensory systems, tactile-sensory systems, and multisensory artificial-nerves systems, are discussed. Finally, the current challenges and potential directions of stretchable synaptic transistors are analyzed. This review presents a detailed introduction to the recent progress in stretchable synaptic transistors from basic concept to applications, providing a reference for the development of stretchable synaptic transistors in the future.

Ultralow-Power Vertical Transistors for Multilevel Decoding Modes.

Organic field-effect transistors with parallel transmission and learning functions are of interest in the development of brain-inspired neuromorphic computing. However, the poor performance and high power consumption are the two main issues limiting their practical applications. Herein, an ultralow-power vertical transistor is demonstrated based on transition-metal carbides/nitrides (MXene) and organic single crystal. The transistor exhibits a high JON of 16.6 mA cm-2 and a high JON /JOFF ratio of 9.12 × 105 under an ultralow working voltage of -1 mV. Furthermore, it can successfully simulate the functions of biological synapse under electrical modulation along with consuming only 8.7 aJ of power per spike. It also permits multilevel information decoding modes with a significant gap between the readable time of professionals and nonprofessionals, producing a high signal-to-noise ratio up to 114.15 dB. This work encourages the use of vertical transistors and organic single crystal in decoding information and advances the development of low-power neuromorphic systems.

Self-powered high-sensitivity all-in-one vertical tribo-transistor device for multi-sensing-memory-computing.

Devices with sensing-memory-computing capability for the detection, recognition and memorization of real time sensory information could simplify data conversion, transmission, storage, and operations between different blocks in conventional chips, which are invaluable and sought-after to offer critical benefits of accomplishing diverse functions, simple design, and efficient computing simultaneously in the internet of things (IOT) era. Here, we develop a self-powered vertical tribo-transistor (VTT) based on MXenes for multi-sensing-memory-computing function and multi-task emotion recognition, which integrates triboelectric nanogenerator (TENG) and transistor in a single device with the simple configuration of vertical organic field effect transistor (VOFET). The tribo-potential is found to be able to tune ionic migration in insulating layer and Schottky barrier height at the MXene/semiconductor interface, and thus modulate the conductive channel between MXene and drain electrode. Meanwhile, the sensing sensitivity can be significantly improved by 711 times over the single TENG device, and the VTT exhibits excellent multi-sensing-memory-computing function. Importantly, based on this function, the multi-sensing integration and multi-model emotion recognition are constructed, which improves the emotion recognition accuracy up to 94.05% with reliability. This simple structure and self-powered VTT device exhibits high sensitivity, high efficiency and high accuracy, which provides application prospects in future human-mechanical interaction, IOT and high-level intelligence.

Young MSM changed temporal HIV-1 epidemic pattern in Heilongjiang Province, China.

Background: Human immunodeficiency virus type 1 (HIV-1) epidemic in China is featured by geographical diversity of epidemic patterns. Understanding the characteristics of regional HIV-1 epidemic allows carrying out targeted prevention and controlling measures. This seven-year cross-sectional study was conducted in Heilongjiang, one province of Northeast China, where newly diagnosed infection is fast increasing yearly, but temporal HIV-1 epidemic trend is largely unknown. Methods: Information of 1,006 newly diagnosed HIV-1-infected participants were collected before antiretroviral therapy during 2010-2016 in Heilongjiang province. HIV-1 genotype was identified based on the viral gag and env gene sequences. Recent infection was determined by Limiting-Antigen Avidity assays. Comparison analyses on the median ages, CD4 counts, proportions of stratified age groups and CD4 count groups, and rates of recent HIV-1 infection among different population and sampling times were performed to understand temporal HIV-1 epidemic features. Results: Homosexual contact among men who have sex with men (MSM) was the main transmission route and CRF01_AE was the most dominant HIV-1 genotype. During 2010-2016, the HIV-1 epidemic showed three new changes: the median age continued to decline, the cases with a CD4 count more than 500 cells/µl (CD4hi cases) disproportionally expanded, and the recent HIV-1 infection rate steadily increased. MSM cases determined the temporal trend of HIV-1 epidemic here. Increase of young MSM cases (aged <30 years) made the main contribution to the younger age trend of MSM cases. These young MSM exhibited a higher median CD4 count, a higher proportion of CD4hi cases, and a higher rate of recent HIV-1 infection than cases aged 30 years and more. MSM infected by CRF01_AE virus mostly affected HIV-1 epidemic patterns among MSM population. Conclusion: Young MSM have become a new hotspot and vulnerable group for HIV-1 transmission in Heilongjiang Province, Northeast China. The rapid increase in the number of young MSM cases, mainly those with CRF01_AE infection, changed temporal HIV-1 epidemic pattern here. Measures for prevention and control of HIV-1 infection among this population are urgently needed in the future.

Programmable ferroelectric bionic vision hardware with selective attention for high-precision image classification.

Selective attention is an efficient processing strategy to allocate computational resources for pivotal optical information. However, the hardware implementation of selective visual attention in conventional intelligent system is usually bulky and complex along with high computational cost. Here, programmable ferroelectric bionic vision hardware to emulate the selective attention is proposed. The tunneling effect of photogenerated carriers are controlled by dynamic variation of energy barrier, enabling the modulation of memory strength from 9.1% to 47.1% without peripheral storage unit. The molecular polarization of ferroelectric P(VDF-TrFE) layer enables a single device not only multiple nonvolatile states but also the implementation of selective attention. With these ferroelectric devices are arrayed together, UV light information can be selectively recorded and suppressed the with high current decibel level. Furthermore, the device with positive polarization exhibits high wavelength dependence in the image attention processing, and the fabricated ferroelectric sensory network exhibits high accuracy of 95.7% in the pattern classification for multi-wavelength images. This study can enrich the neuromorphic functions of bioinspired sensing devices and pave the way for profound implications of future bioinspired optoelectronics.

Bioinspired Artificial Motion Sensory System for Rotation Recognition and Rapid Self-Protection.

As one of the most common synergies between the exteroceptors and proprioceptors, the synergy between visual and vestibule enables the human brain to judge the state of human motion, which is essential for motion recognition and human self-protection. Hence, in this work, an artificial motion sensory system (AMSS) based on artificial vestibule and visual is developed, which consists of a tribo-nanogenerator (TENG) as a vestibule that can sense rotation and synaptic transistor array as retina. The principle of temporal congruency has been successfully realized by multisensory input. In addition, pattern recognition results show that the accuracy of multisensory integration is more than 15% higher than that of single sensory. Moreover, due to the rotation recognition and visual recognition functions of AMSS, we realized multimodal information recognition including angles and numbers in the spiking correlated neural network (SCNN), and the accuracy rate reached 89.82%. Besides, the rapid self-protection of a human was successfully realized by AMSS in the case of simulated amusement rides, and the reaction time of multiple motion sensory integration is only one-third of that of a single vestibule. The development of AMSS based on the synergy of simulated vision and vestibule will show great potential in neural robot, artificial limbs, and soft electronics.

Artificial Tactile Sensing System with Photoelectric Output for High Accuracy Haptic Texture Recognition and Parallel Information Processing.

Developing multifunctional artificial sensory systems is an important task for constructing future artificial neural networks. A system with multisignal output capability is highly required by the rising demand for high-throughput data processing in the Internet of Things (IoT) society. Here, a novel dual-output artificial tactile sensing (DOATS) system with parallel output of photoelectric signals was proposed. Because of the ionic-electronic coupling mechanism in light-emitting synaptic (LES) devices in the DOATS system, modulating electric current and light emission can coexist through ion accumulation and electron-hole recombination. As a result, the DOATS system can realize the simulation of human tactile information, and the recognition of 16 kinds of fabrics was demonstrated with an accuracy rate of 94.1%. A photoelectric hybrid artificial neural network was proposed, which achieved efficient and accurate multitask operation. The DOATS system proposed in this work is promising for implementing photoelectric hybrid neural network and promoting the development of interactive artificial intelligence.

MXene based saturation organic vertical photoelectric transistors with low subthreshold swing.

Vertical transistors have attracted enormous attention in the next-generation electronic devices due to their high working frequency, low operation voltage and large current density, while a major scientific and technological challenge for high performance vertical transistor is to find suitable source electrode. Herein, an MXene material, Ti3C2Tx, is introduced as source electrode of organic vertical transistors. The porous MXene films take the advantage of both partially shielding effect of graphene and the direct modulation of the Schottky barrier at the mesh electrode, which significantly enhances the ability of gate modulation and reduces the subthreshold swing to 73 mV/dec. More importantly, the saturation of output current which is essential for all transistor-based applications but remains a great challenge for vertical transistors, is easily achieved in our device due to the ultra-thin thickness and native oxidation of MXene, as verified by finite-element simulations. Finally, our device also possesses great potential for being used as wide-spectrum photodetector with fast response speed without complex material and structure design. This work demonstrates that MXene as source electrode offers plenty of opportunities for high performance vertical transistors and photoelectric devices.

Bi-mode electrolyte-gated synaptic transistor via additional ion doping and its application to artificial nociceptors.

Multiple types of synaptic transistors that are capable of processing electrical signals similar to the biological neural system hold enormous potential for application in parallel computing, logic circuits and peripheral detection. However, most of these presented synaptic transistors are confined to a single mode of synaptic plasticity under an electrical stimulus, which tremendously limits efficient memory formation and the multifunctional integration of synaptic transistors. Here, we proposed a bi-mode electrolyte-gated synaptic transistor (BEST) with two dynamic processes, the formation of an electrical double layer (EDL) and electrochemical doping (ECD) by tuning the applied voltages, thereby allowing volatile and non-volatile behavior, which is associated with additional ion doping and nanoscale ionic transport. Benefiting from two controllable dynamic processes, we surprisingly found a third state in the transfer curves besides the "off" and "on" states. Moreover, utilizing this unique property, an artificial nociceptor with multilevel modulation of sensitivity was realized based on our bi-mode device. Finally, a haptic sensory system was constructed to exhibit robotic motion that revealed a unique threshold switching behavior, indicating the applicability to peripheral sensing circuits. Hence, the presented bi-mode synaptic transistor provides promising prospects in achieving multiple-mode integrated devices and simplifying neural circuits, which shows great potential in the development of artificial intelligence.

High-Density Reconfigurable Synaptic Transistors Targeting a Minimalist Neural Network.

Enormous synaptic devices are required to build a parallel, precise, and efficient neural computing system. To further improve the energy efficiency of neuromorphic computing, a single high-density synaptic (HDS) device with multiple nonvolatile synaptic states is suggested to reduce the number of synaptic devices in the neural network, although such a powerful synaptic device is rarely demonstrated. Here, a photoisomerism material, namely, diarylethene, whose energy level varies with the wavelength of illumination is first introduced to construct a powerful HDS device. The multiple synaptic states of the HDS device are intrinsically converted under UV-vis regulation and remain nonvolatile after the removal of illumination. More importantly, the conversion is reconfigurable and reversible under different light conditions, and the synaptic characteristics are comprehensively mimicked in each state. Finally, compared with a two-layer multilayer perceptron (MLP) architecture based on static synaptic devices, the HDS device-based architecture reduces the device number by 16 times to achieve a minimalist neural computing structure. The invention of the HDS device opens up a revolutionary paradigm for the establishment of a brain-like network.

High-Performance Organic Synaptic Transistors with an Ultrathin Active Layer for Neuromorphic Computing.

In recent years, much attention has been focused on two-dimensional (2D) material-based synaptic transistor devices because of their inherent advantages of low dimension, simultaneous read-write operation and high efficiency. However, process compatibility and repeatability of these materials are still a big challenge, as well as other issues such as complex transfer process and material selectivity. In this work, synaptic transistors with an ultrathin organic semiconductor layer (down to 7 nm) were obtained by the simple dip-coating process, which exhibited a high current switch ratio up to 106, well off state as low as nearly 10-12 A, and low operation voltage of -3 V. Moreover, various synaptic behaviors were successfully simulated including excitatory postsynaptic current, paired pulse facilitation, long-term potentiation, and long-term depression. More importantly, under ultrathin conditions, excellent memory preservation, and linearity of weight update were obtained because of the enhanced effect of defects and improved controllability of the gate voltage on the ultrathin active layer, which led to a pattern recognition rate up to 85%. This is the first work to demonstrate that the pattern recognition rate, a crucial parameter for neuromorphic computing can be significantly improved by reducing the thickness of the channel layer. Hence, these results not only reveal a simple and effective way to improve plasticity and memory retention of the artificial synapse via thickness modulation but also expand the material selection for the 2D artificial synaptic devices.

Controlling Native Oxidation of HfS2 for 2D Materials Based Flash Memory and Artificial Synapse.

Two-dimensional (2D) materials based artificial synapses are important building blocks for the brain-inspired computing systems that are promising in handling large amounts of informational data with high energy-efficiency in the future. However, 2D devices usually rely on deposited or transferred insulators as the dielectric layer, resulting in various challenges in device compatibility and fabrication complexity. Here, we demonstrate a controllable and reliable oxidation process to turn 2D semiconductor HfS2 into native oxide, HfOx, which shows good insulating property and clean interface with HfS2. We then incorporate the HfOx/HfS2 heterostructure into a flash memory device, achieving a high on/off current ratio of ∼105, a large memory window over 60 V, good endurance, and a long retention time over 103 seconds. In particular, the memory device can work as an artificial synapse to emulate basic synaptic functions and feature good linearity and symmetry in conductance change during long-term potentiation/depression processes. A simulated artificial neural network based on our synaptic device achieves a high accuracy of ∼88% in MNIST pattern recognition. Our work provides a simple and effective approach for integrating high-k dielectrics into 2D material-based memory and synaptic devices.

High-Performance Vertical Organic Phototransistors Enhanced by Ferroelectrics.

Organic phototransistors with high sensitivity and responsivity to light irradiance have great potential applications in national defense, meteorology, industrial manufacturing, and medical security. However, undesired dark current and photoresponsivity limit their practical applications. Here, a novel vertical organic phototransistor combined with ferroelectric materials is developed. The device structure has nanometer channel length, which can effectively separate photogenerated carriers and reduce the probability of carrier recombination and defect scattering, thus improving the device performance of phototransistors. Moreover, by inserting the poly(vinylidene fluoride-co-trifluoroethylene) (P(VDF-TrFE)) ferroelectric layer, the Schottky barrier at the interface between the semiconductor and source can be adjusted by the polarization of the external electric field, which can effectively reduce the dark current of the phototransistor to further improve the device performance. Therefore, our phototransistors exhibit a high photoresponsivity of more than 5.7 × 105A/W, an outstanding detectivity of 1.15 × 1018 Jones, and an excellent photosensitivity of 5 × 107 under 760 nm light illumination, which are better than those of conventional lateral organic phototransistors. This work provides a new approach for the development of high-performance phototransistors, which opens a new pathway for organic phototransistors in practical application.

High-Performance Organic Electrochemical Transistors with Nanoscale Channel Length and Their Application to Artificial Synapse.

Organic electrochemical transistors (OECTs) have attracted considerable interests for various applications ranging from biosensors to digital logic circuits and artificial synapses. However, the majority of reported OECTs utilize large channel length up to several or several tens of micrometers, which limits the device performance and leads to low transistor densities. Here, we demonstrate a new design of vertical OECT architecture with a nanoscale channel length down to ∼100 nm. The devices exhibit a high on-state current of over 20 mA under a low bias voltage of 0.5 V, a fast transient response of less than 300 µs, and an extraordinary transconductance up to 68.88 mS, representing a record-high value for OECTs. The excellent electrical performance is attributed to the novel structure with a nanoscale channel length defined by the channel material thickness, which is intrinsically different from that of conventional OECTs with the channel length limited by the lithography resolution. Owing to the low thermal budget, we fabricate flexible devices on a flexible substrate, which exhibit unprecedented endurance characteristics and mechanical robustness after 1000 blending cycles. Furthermore, the proposed device is capable of mimicking biological inhibitory synapses for application in intelligent artificial neural networks. Our work not only pushes the performance limit of OECTs but also opens up a new design of OECTs for high-performance biosensors, digital logic, and neuromorphic devices.

Nonvolatile Multilevel Photomemory Based on Lead-Free Double Perovskite Cs2AgBiBr6 Nanocrystals Wrapped Within SiO2 as a Charge Trapping Layer.

Floating gate transistor photomemory (FGTPM) has been regarded as one of the most prospective nonvolatile photomemory devices because of its compatibility with transistor-based circuits, nondestructive reading, and multilevel storage. Until now, owing to the excellent photoelectric properties, lead-based perovskite nanocrystals (PNCs) have been applied in most of the perovskite-based FGTPM devices and embedded in the polymer matrix as the charge trapping layer. However, the polymer matrix and its solvent would degrade the structure of the PNCs, resulting in the loss of their unique photoresponse ability. In addition, lead-based perovskites have environmental unfriendliness and poor stability. Hence, a novel nonvolatile FGTPM based on oligomeric silica (OS) wrapped lead-free double perovskite Cs2AgBiBr6 NCs was demonstrated for the first time. Acting synchronously as the protection layer for the discrete Cs2AgBiBr6 NCs and charge tunneling layer for the FGTPM device, the OS layer can achieve controllable thickness by adjusting the process parameters, leading to an adjustment of storage properties with a larger memory window (58 V). Owing to the excellent photoresponse ability of the Cs2AgBiBr6@OS composite layer, the FGTPM device exhibited high-performance with repeatable multilevel nonvolatile photomemory and precise photoresponse ability of wavelength/time/power-dependent photoirradiation without extra gate biasing.

High-performance Nonvolatile Organic Photoelectronic Transistor Memory Based on Bulk Heterojunction Structure.

Depending on the storage mechanisms, organic field-effect transistor (OFET) memory is usually divided into floating gate memory, ferroelectric memory, and polymer-electret-based memory. In this work, a new type of nonvolatile OFET memory is proposed by simply blending a p-type semiconductor and a n-type semiconductor without using an extra trapping layer. The results show that the memory window can be effectively modulated by the dopant concentration of the n-type semiconductor. With the addition of a 5% n-type semiconductor, blending devices exhibit a large memory window up to 57.7 V, an ON/OFF current ratio (ION/IOFF) ≈ 105, and a charge retention time of over 10 years, which is comparable or even better than those of most of the traditional OFET memories. The discontinuous n-type semiconductor is set as a charge-trapping center for charge storage due to the quantum well-like organic heterojunctions. The generalization of this method is also investigated in other organic systems. Moreover, the blend devices are also applied to optical memory and show multilevel optical storage, which are further scaled up to 8 × 8 array to map up two-dimensional (2D) optical images with long-term retention and reprogramming characteristic. The results reveal that the novel system design has great potential application in the field of digital image memory and photoelectronic system.