Perovskite-Doped Modulated Color-Selective Photosynaptic Transistors for Target Object Recognition.

The processing of multicolor noisy images in visual neuromorphic devices requires selective absorption at specific wavelengths; however, it is difficult to achieve this because the spectral absorption range of the device is affected by the type of material. Surprisingly, the absorption range of perovskite materials can be adjusted by doping. Herein, a CdCl2 co-doped CsPbBr3 nanocrystal-based photosensitive synaptic transistor (PST) is reported. By decreasing the doping concentration, the response of the PST to short-wavelength light is gradually enhanced, and even weak light of 40 µW·cm-2 can be detected. Benefiting from the excellent color selectivity of the PST device, the device array is applied to feature extraction of target blue items and removal of red and green noise, which results in the recognition accuracy of 95% for the noisy MNIST data set. This work provides new ideas for the application of novel transistors integrating sensors and storage computing.

Multidimensional Deep Ultraviolet (DUV) Synapses Based on Organic/Perovskite Semiconductor Heterojunction Transistors for Antispoofing Facial Recognition Systems.

Reliably discerning real human faces from fake ones, known as antispoofing, is crucial for facial recognition systems. While neuromorphic systems offer integrated sensing-memory-processing functions, they still struggle with efficient antispoofing techniques. Here we introduce a neuromorphic facial recognition system incorporating multidimensional deep ultraviolet (DUV) optoelectronic synapses to address these challenges. To overcome the complexity and high cost of producing DUV synapses using traditional wide-bandgap semiconductors, we developed a low-temperature (≤70 °C) solution process for fabricating DUV synapses based on PEA2PbBr4/C8-BTBT heterojunction field-effect transistors. This method enables the large-scale (4-in.), uniform, and transparent production of DUV synapses. These devices respond to both DUV and visible light, showing multidimensional features. Leveraging the unique ability of the multidimensional DUV synapse (MDUVS) to discriminate real human skin from artificial materials, we have achieved robust neuromorphic facial recognition with antispoofing capability, successfully identifying genuine human faces with an accuracy exceeding 92%.

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.

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.

Novel Semiconductive Ternary Hybrid Heterostructures for Artificial Optoelectronic Synapses.

Synaptic devices that mimic biological synapses are considered as promising candidates for brain-inspired devices, offering the functionalities in neuromorphic computing. However, modulation of emerging optoelectronic synaptic devices has rarely been reported. Herein, a semiconductive ternary hybrid heterostructure is prepared with a D-D'-A configuration by introducing polyoxometalate (POM) as an additional electroactive donor (D') into a metalloviologen-based D-A framework. The obtained material features an unprecedented porous 8-connected bcu-net that accommodates nanoscale [α-SiW12 O40 ]4- counterions, displaying uncommon optoelectronic responses. Besides, the fabricated synaptic device based on this material can achieve dual-modulation of synaptic plasticity due to the synergetic effect of electron reservoir POM and photoinduced electron transfer. And it can successfully simulate learning and memory processes similar to those in biological systems. The result provides a facile and effective strategy to customize multi-modality artificial synapses in the field of crystal engineering, which opens a new direction for developing high-performance neuromorphic devices.

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.

Exploring the Dual Characteristics of CH3OH Adsorption to Metal Atomic Structures on Si (111)-7 × 7 Surface.

Metal atoms were deposited on an Si (111)-7 × 7 surface, and they were adsorbed with alcohol gases (CH3OH/C2H5OH/C3H7OH). Initially, CnH2n+1OH adsorption was simply used as an intermediate layer to prevent the chemical reaction between metal and Si atoms. Through scanning tunneling microscopy (STM) and a mass spectrometer, the CnH2n+1OH dissociation process is further derived as the construction of a surface quasi-potential with horizontal and vertical directions. With the help of three typical metal depositions, the surface characteristics of CH3OH adsorption are more clearly presented in this paper. Adjusting the preheating temperature, the difference of thermal stability between CH3O- and H+ could be obviously derived in Au deposition. After a large amount of H+ was separated, the isolation characteristic of CH3O- was discussed in the case of Fe deposition. In the process of building a new metal-CH3O--H+ model, the dual characteristics of CH3OH were synthetically verified in Sn deposition. CH3O- adsorption is prone to influencing the interaction between the metal deposition and substrate surface in the vertical direction, while H+ adsorption determines the horizontal behavior of metal atoms. These investigations lead one to believe that, to a certain extent, the formation of regular metal atomic structures on the Si (111)-7 × 7-CH3OH surface is promoted, especially according to the dual characteristics and adsorption models we explored.

Modulation of the plasticity of an all-metal oxide synaptic transistor via laser irradiation.

Artificial intelligence devices that can mimic human brains are the foundation for building future artificial neural networks. A key step in mimicking biological neural systems is the modulation of synaptic weight, which is mainly achieved by various engineering approaches using material design, or modification of the device structure. Here, we realize the modulation of the synaptic weight of a Ta2O5/ITO-based all-metal oxide synaptic transistor via laser irradiation. Prior to the deposition of the active layer and electrodes, a femtosecond laser was used to irradiate the surface of the insulator layer. Typical synaptic characteristics such as excitatory postsynaptic current, paired pulse facilitation and long-term potentiation were successfully simulated under different laser intensities and scanning rates. In particular, we demonstrate for the first time that laser irradiation could control the quantity of oxygen vacancies in the Ta2O5 thin film, leading to precise modulation of the synaptic weight. Our research provides an instantaneous (<1 s), convenient and low-temperature approach to improving synaptic behaviors, which could be promising for neuromorphic computing hardware design.

All-metal oxide synaptic transistor with modulatable plasticity.

The artificial neural system has attracted tremendous attention in the field of artificial intelligence due to operate mode of parallel computation which is superior to traditional Von Neumann computers in processing complex sensory data and real-time situations with extremely low power dissipation. Remarkable progress has been made in the hardware-based electric-double-layer synaptic transistors as its modulation by ion movement is similar to biological synapse for the past few years. Unfortunately, long-term potentiation (LTP) timescale is still a big challenge in hardware-based electric-double-layer synaptic transistors which is essential to processing capacity and memory formation. Meanwhile, the effect of ion concentration on the synaptic plasticity has rarely been reported. Here, a solid state electrolyte-gated transistor using Ta2O5 as dielectric layer with unique ionic composition was demonstrated and the regulation of synaptic weight was realized by changing ion concentration. Both the potentiation and depression of synaptic weight such as excitatory post-synaptic current, inhibitory response (IPSC), paired pulse facilitation as well as LTP were successfully simulated. More importantly, oxygen vacancy content was tuned for the first time to modulate synaptic plasticity by varying film thickness and gas ratio, through which the intensity and duration of memory were enhanced with appropriate vacancy concentration. It indicated that appropriate vacancy concentration avoided the effects of internal electric field induced by ion excess, leading to a long-term memory. These results reveal a promising path to improve memory capacity of artificial synapse via ion modulation.

TEM8 functions as a receptor for uPA and mediates uPA-stimulated EGFR phosphorylation.

BACKGROUND: TEM8 is a cell membrane protein predominantly expressed in tumor endothelium, which serves as a receptor for the protective antigen (PA) of anthrax toxin. However, the physiological ligands for TEM8 remain unknown. RESULTS: Here we identified uPA as an interacting partner of TEM8. Binding of uPA stimulated the phosphorylation of TEM8 and augmented phosphorylation of EGFR and ERK1/2. Finally, TEM8-Fc, a recombinant fusion protein comprising the extracellular domain of human TEM8 linked to the Fc portion of human IgG1, efficiently abrogated the interaction between uPA and TEM8, blocked uPA-induced migration of HepG2 cells in vitro and inhibited the growth and metastasis of human MCF-7 xenografts in vivo. uPA, TEM8 and EGFR overexpression and ERK1/2 phosphorylation were found co-located on frozen cancer tissue sections. CONCLUSIONS: Taken together, our data provide evidence that TEM8 is a novel receptor for uPA, which may play a significant role in the regulation of tumor growth and metastasis.

H∞ Robust Control of a Large-Piston MEMS Micromirror for Compact Fourier Transform Spectrometer Systems.

Incorporating linear-scanning micro-electro-mechanical systems (MEMS) micromirrors into Fourier transform spectral acquisition systems can greatly reduce the size of the spectrometer equipment, making portable Fourier transform spectrometers (FTS) possible. How to minimize the tilting of the MEMS mirror plate during its large linear scan is a major problem in this application. In this work, an FTS system has been constructed based on a biaxial MEMS micromirror with a large-piston displacement of 180 µm, and a biaxial H∞ robust controller is designed. Compared with open-loop control and proportional-integral-derivative (PID) closed-loop control, H∞ robust control has good stability and robustness. The experimental results show that the stable scanning displacement reaches 110.9 µm under the H∞ robust control, and the tilting angle of the MEMS mirror plate in that full scanning range falls within ±0.0014°. Without control, the FTS system cannot generate meaningful spectra. In contrast, the FTS yields a clean spectrum with a full width at half maximum (FWHM) spectral linewidth of 96 cm-1 under the H∞ robust control. Moreover, the FTS system can maintain good stability and robustness under various driving conditions.

Vital Staining of Bacteria by Sunset Yellow Pigment.

In this study, we describe a method for discriminating pathogenic bacteria with a dye. First, we determined that among several colours tested, the sunset yellow pigment easily coloured Escherichia coli bacteria yellow. Next, we demonstrated that E. coli O157:H7, Shigella flexneri O301, Staphylococcus aureus and Bacillus subtilis could all be well marked by sunset yellow pigment. Finally, we performed bacterial viability assays and found there was no effect on bacterial growth when in co-culture with sunset yellow. Our results suggest that sunset yellow is suitable pigment to dye microorganisms.

Aggregation of Ribosomal Protein S6 at Nucleolus Is Cell Cycle-Controlled and Its Function in Pre-rRNA Processing Is Phosphorylation Dependent.

Ribosomal protein S6 (rpS6) has long been regarded as one of the primary r-proteins that functions in the early stage of 40S subunit assembly, but its actual role is still obscure. The correct forming of 18S rRNA is a key step in the nuclear synthesis of 40S subunit. In this study, we demonstrate that rpS6 participates in the processing of 30S pre-rRNA to 18S rRNA only when its C-terminal five serines are phosphorylated, however, the process of entering the nucleus and then targeting the nucleolus does not dependent its phosphorylation. Remarkably, we also find that the aggregation of rpS6 at the nucleolus correlates to the phasing of cell cycle, beginning to concentrate in the nucleolus at later S phase and disaggregate at M phase. J. Cell. Biochem. 117: 1649-1657, 2016. © 2015 Wiley Periodicals, Inc.

Argonaute 2 and nasopharyngeal carcinoma: a genetic association study and functional analysis.

BACKGROUND: Argonaute 2 (AGO2), a central component of RNA-induced silencing complex, plays critical roles in cancer. We examined whether the single nucleotide polymorphisms (SNPs) of AGO2 were related to the risk of nasopharyngeal carcinoma (NPC). METHODS: Twenty-five tag SNPs within AGO2 were genotyped in Guangxi population consisting of 855 NPC patients and 1036 controls. The SNPs significantly associated with NPC were further replicated in Guangdong population consisting of 996 NPC patients and 972 controls. Functional experiments were conducted to examine the biologic roles of AGO2 in NPC. RESULTS: A significantly increased risk of advanced lymph node metastasis of NPC was identified for the AGO2 rs3928672 GA + AA genotype compared with GG genotype in both the Guangxi and Guangdong populations (combined odd ratio = 2.08, 95 % confidence interval = 1.44-3.01, P = 8.60 × 10(-5)). Moreover, the AGO2 protein expression levels of rs3928672 GA + AA genotype carriers were higher than the GG genotype carriers in the NPC tissues (P = 0.041), and AGO2 was significantly over-expressed in NPC tissues compared with non-cancerous nasopharyngeal tissues (P = 0.011). In addition, AGO2 knockdown reduced cell proliferation, induced apoptosis, and inhibited migration of NPC cells. Furthermore, gene expression microarray showed that genes altered following AGO2 knockdown were clustered in tumorigenesis and metastasis relevant pathways. CONCLUSIONS: Our findings suggest that the genetic polymorphism in AGO2 may be a risk factor for the advanced lymph node metastasis of NPC in Chinese populations, and AGO2 acts as an oncogene in the development of NPC.

Daptomycin exerts rapid bactericidal activity against Bacillus anthracis without disrupting membrane integrity.

AIM: To examine whether the novel cyclic lipopeptide antibiotic daptomycin could be used to treat anthrax and to study the mechanisms underlying its bactericidal action against Bacillus anthracis. METHODS: Spore-forming B anthracis AP422 was tested. MIC values of antibiotics were determined. Cell membrane potential was measured using flow cytometric assays with membrane potential-sensitive fluorescent dyes. Cell membrane integrity was detected using To-Pro-3 iodide staining and transmission electron microscopy. K(+) efflux and Na(+) influx were measured using the fluorescent probes PBFI and SBFI-AM, respectively. RESULTS: Daptomycin exhibited rapid bactericidal activity against vegetative B anthracis with a MIC value of 0.78 µg/mL, which was comparable to those of ciprofloxacin and penicillin G. Furthermore, daptomycin prevented the germinated spores from growing into vegetative bacteria. Daptomycin concentration-dependently dissipated the membrane potential of B anthracis and caused K(+) efflux and Na(+) influx without disrupting membrane integrity. In contrast, both ciprofloxacin and penicillin G did not change the membrane potential of vegetative bacteria or spores. Penicillin G disrupted membrane integrity of B anthracis, whereas ciprofloxacin had no such effect. CONCLUSION: Daptomycin exerts rapid bactericidal action against B anthracis via reducing membrane potential without disrupting membrane integrity. This antibiotic can be used as an alternate therapy for B anthracis infections.

Coaxial 3D Bioprinting Process Research and Performance Tests on Vascular Scaffolds.

Three-dimensionally printed vascularized tissue, which is suitable for treating human cardiovascular diseases, should possess excellent biocompatibility, mechanical performance, and the structure of complex vascular networks. In this paper, we propose a method for fabricating vascularized tissue based on coaxial 3D bioprinting technology combined with the mold method. Sodium alginate (SA) solution was chosen as the bioink material, while the cross-linking agent was a calcium chloride (CaCl2) solution. To obtain the optimal parameters for the fabrication of vascular scaffolds, we first formulated theoretical models of a coaxial jet and a vascular network. Subsequently, we conducted a simulation analysis to obtain preliminary process parameters. Based on the aforementioned research, experiments of vascular scaffold fabrication based on the coaxial jet model and experiments of vascular network fabrication were carried out. Finally, we optimized various parameters, such as the flow rate of internal and external solutions, bioink concentration, and cross-linking agent concentration. The performance tests showed that the fabricated vascular scaffolds had levels of satisfactory degradability, water absorption, and mechanical properties that meet the requirements for practical applications. Cellular experiments with stained samples demonstrated satisfactory proliferation of human umbilical vein endothelial cells (HUVECs) within the vascular scaffold over a seven-day period, observed under a fluorescent inverted microscope. The cells showed good biocompatibility with the vascular scaffold. The above results indicate that the fabricated vascular structure initially meet the requirements of vascular scaffolds.

Toward Intelligent Display with Neuromorphic Technology.

In the era of the Internet and the Internet of Things, display technology has evolved significantly toward full-scene display and realistic display. Incorporating "intelligence" into displays is a crucial technical approach to meet the demands of this development. Traditional display technology relies on distributed hardware systems to achieve intelligent displays but encounters challenges stemming from the physical separation of sensing, processing, and light-emitting modules. The high energy consumption and data transformation delays limited the development of intelligence display, breaking the physical separation is crucial to overcoming the bottlenecks of intelligence display technology. Inspired by the biological neural system, neuromorphic technology with all-in-one features is widely employed across various fields. It proves effective in reducing system power consumption, facilitating frequent data transformation, and enabling cross-scene integration. Neuromorphic technology shows great potential to overcome display technology bottlenecks, realizing the full-scene display and realistic display with high efficiency and low power consumption. This review offers a comprehensive summary of recent advancements in the application of neuromorphic technology in displays, with a focus on interoperability. This work delves into its state-of-the-art designs and potential future developments aimed at revolutionizing display technology.

Cross-layer transmission realized by light-emitting memristor for constructing ultra-deep neural network with transfer learning ability.

Deep neural networks have revolutionized several domains, including autonomous driving, cancer detection, and drug design, and are the foundation for massive artificial intelligence models. However, hardware neural network reports still mainly focus on shallow networks (2 to 5 layers). Implementing deep neural networks in hardware is challenging due to the layer-by-layer structure, resulting in long training times, signal interference, and low accuracy due to gradient explosion/vanishing. Here, we utilize negative ultraviolet photoconductive light-emitting memristors with intrinsic parallelism and hardware-software co-design to achieve electrical information's optical cross-layer transmission. We propose a hybrid ultra-deep photoelectric neural network and an ultra-deep super-resolution reconstruction neural network using light-emitting memristors and cross-layer block, expanding the networks to 54 and 135 layers, respectively. Further, two networks enable transfer learning, approaching or surpassing software-designed networks in multi-dataset recognition and high-resolution restoration tasks. These proposed strategies show great potential for high-precision multifunctional hardware neural networks and edge artificial intelligence.

Towards mixed physical node reservoir computing: light-emitting synaptic reservoir system with dual photoelectric output.

Memristor-based physical reservoir computing holds significant potential for efficiently processing complex spatiotemporal data, which is crucial for advancing artificial intelligence. However, owing to the single physical node mapping characteristic of traditional memristor reservoir computing, it inevitably induces high repeatability of eigenvalues to a certain extent and significantly limits the efficiency and performance of memristor-based reservoir computing for complex tasks. Hence, this work firstly reports an artificial light-emitting synaptic (LES) device with dual photoelectric output for reservoir computing, and a reservoir system with mixed physical nodes is proposed. The system effectively transforms the input signal into two eigenvalue outputs using a mixed physical node reservoir comprising distinct physical quantities, namely optical output with nonlinear optical effects and electrical output with memory characteristics. Unlike previously reported memristor-based reservoir systems, which pursue rich reservoir states in one physical dimension, our mixed physical node reservoir system can obtain reservoir states in two physical dimensions with one input without increasing the number and types of devices. The recognition rate of the artificial light-emitting synaptic reservoir system can achieve 97.22% in MNIST recognition. Furthermore, the recognition task of multichannel images can be realized through the nonlinear mapping of the photoelectric dual reservoir, resulting in a recognition accuracy of 99.25%. The mixed physical node reservoir computing proposed in this work is promising for implementing the development of photoelectric mixed neural networks and material-algorithm collaborative design.

Solution-Processed Ultralow Voltage Organic Transistors With Sharp Switching for Adaptive Visual Perception.

Neuromorphic visual systems can emulate biological retinal systems to perceive visual information under different levels of illumination, making them have considerable potential for future intelligent vehicles and vision automation. However, the complex circuits and high operating voltages of conventional artificial vision systems present great challenges for device integration and power consumption. Here, bioinspired synaptic transistors based on organic single crystal phototransistors are reported, which exhibit excitation and inhibition synaptic plasticity with time-varying. By manipulating the charge dynamics of the trapping centers of organic crystal-electret vertical stacks, organic transistors can operate below 1 V with record high on/off ratios close to 108 and sharp switching with a subthreshold swing of 59.8 mV dec-1. Moreover, the approach offers visual adaptation with highly localized modulation and over 98.2% recognition accuracy under different illumination levels. These bioinspired visual adaptation transistors offer great potential for simplifying the circuitry of artificial vision systems and will contribute to the development of machine vision applications.