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Background: Chronic n-Hexane poisoning is prevalent among workers in small and micro printing industries in China. Despite this, there is limited research on occupational health risk assessment in these sectors. Conducting comprehensive risk assessments at key positions and proposing effective countermeasures are essential., Methods: Data were collected from 84 key positions across 32 small and micro-sized printing enterprises. Air samples were tested for n-Hexane exposure levels in accordance with Chinese standards. Five risk assessment models were employed: COSHH, EPA, MOM, ICMM, and Technical Guide GBZ/T 289-2017 of China. The consistency of results across these models was analyzed., Results: Workers in 84 job positions were categorized into four exposure groups, with exposure to n-Hexane for 8-10 h daily, 5-6 days weekly. Most positions operated with low automation levels (96.9% in printing, 5.9% in oil blending, and 42.9% in pasting), while others were manual. Localized ventilation rates were notably low in oil blending (23.5%), cleaning (14.3%), and pasting (9.5%) groups. n-Hexane concentrations exceeded Chinese occupational limits in 15.6% of printing, 17.7% of oil blending, and 21.4% of cleaning groups. Risk assessment models identified over 60% of work groups as high risk. Significant differences ( p  < 0.05) were found among the seven risk assessment methods. Consistency analysis revealed moderate agreement between the Chinese synthesis index and exposure index methods ( k  = 0.571, p  < 0.01)., Conclusion: The Chinese synthesis and exposure index methods from Technical Guide GBZ/T 289-2017 are practical and reliable for assessing n-Hexane exposure risks in small and micro printing enterprises. Cleaning and printing roles were found to be at the highest risk for n-Hexane exposure. These findings provide valuable insights for targeted risk management strategies to protect workers' health in the industry., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Hu, Chen, Zhong, Chen, Cai and Cai.)

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 CdCl 2 co-doped CsPbBr 3 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.

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., (© 2024. The Author(s).)

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 10 8 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., (© 2024 Wiley‐VCH GmbH.)

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 PEA 2 PbBr 4 /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%.

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., (© 2024 Wiley‐VCH GmbH.)

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 CsPbBrI 2 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.

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 (CaCl 2 ) 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.

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., (© 2024. The Author(s).)

Reservoir computing has attracted considerable attention due to its low training cost. However, existing neuromorphic hardware, focusing mainly on shallow-reservoir computing, faces challenges in providing adequate spatial and temporal scales characteristic for effective computing. Here, we report an ultra-short channel organic neuromorphic vertical transistor with distributed reservoir states. The carrier dynamics used to map signals are enriched by coupled multivariate physics mechanisms, while the vertical architecture employed greatly increases the feedback intensity of the device. Consequently, the device as a reservoir, effectively mapping sequential signals into distributed reservoir state space with 1152 reservoir states, and the range ratio of temporal and spatial characteristics can simultaneously reach 2640 and 650, respectively. The grouped-reservoir computing based on the device can simultaneously adapt to different spatiotemporal task, achieving recognition accuracy over 94% and prediction correlation over 95%. This work proposes a new strategy for developing high-performance reservoir computing networks., (© 2024. The Author(s).)

Botulinum neurotoxin serotype A (BoNT/A) can cause flaccid paralysis of muscles, an illness fatal to human, by entering neurons and blocking neurotransmitter release. The process was mediated by three receptors. A specific monoclonal antibody anti-D23, designated as ML419, targeting the ectodomain (D23) of fibroblast growth factor receptor 3 (FGFR3), one of the three receptors, was screened and capable of disturbing the recognition of BoNT/A and FGFR3. ML419 was screened from 14 stable positive hybridoma cell lines, and was subcloned, sequenced, and classified as IgG2a(κ) subclass. ML419 binds the D23 domain of FGFR3 with high affinity (K D ∼0.26 nM), and prevents the BoNT/A from entering Neuro-2a cells effectively. In vivo data showed that, 200 μg of ML419 could completely protect all the mice against with 5 MLD 50 BoNT/A, while 100 μg of ML419 could protected 60% of the mice. Collectively, our results indicated that ML419 served as a good candidate for further development of therapeutics for BoNT/A., Competing Interests: Declaration of competing interest No potential conflicts of interest were disclosed., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Cartilage damage is difficult to heal and poses a serious problem to human health as it can lead to osteoarthritis. In this work, we explore the application of biological 3D printing to manufacture new cartilage scaffolds to promote cartilage regeneration. The hydrogel made by mixing sodium alginate (SA) and gelatin (GA) has high biocompatibility, but its mechanical properties are poor. The addition of hydroxyapatite (HA) can enhance its mechanical properties. In this paper, the preparation scheme of the SA-GA-HA composite hydrogel cartilage scaffold was explored, the scaffolds prepared with different concentrations were compared, and better formulations were obtained for printing and testing. Mathematical modeling of the printing process of the bracket, simulation analysis of the printing process based on the mathematical model, and adjustment of actual printing parameters based on the results of the simulation were performed. The cartilage scaffold, which was printed using Bioplotter 3D printer, exhibited useful mechanical properties suitable for practical needs. In addition, ATDC-5 cells were seeded on the cartilage scaffolds and the cell survival rate was found to be higher after one week. The findings demonstrated that the fabricated chondrocyte scaffolds had better mechanical properties and biocompatibility, providing a new scaffold strategy for cartilage tissue regeneration.

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 3.58×10 4 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 1.53×10 3 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., (© 2023 Wiley-VCH GmbH.)

Realizing multi-modal information recognition tasks which can process external information efficiently and comprehensively is an urgent requirement in the field of artificial intelligence. However, it remains a challenge to achieve simple structure and high-performance multi-modal recognition demonstrations owing to the complex execution module and separation of memory processing based on the traditional complementary metal oxide semiconductor (CMOS) architecture. Here, we propose an efficient sensory memory processing system (SMPS), which can process sensory information and generate synapse-like and multi-wavelength light-emitting output, realizing diversified utilization of light in information processing and multi-modal information recognition. The SMPS exhibits strong robustness in information encoding/transmission and the capability of visible information display through the multi-level color responses, which can implement the multi-level pain warning process of organisms intuitively. Furthermore, different from the conventional multi-modal information processing system that requires independent and complex circuit modules, the proposed SMPS with unique optical multi-information parallel output can realize efficient multi-modal information recognition of dynamic step frequency and spatial positioning simultaneously with the accuracy of 99.5% and 98.2%, respectively. Therefore, the SMPS proposed in this work with simple component, flexible operation, strong robustness, and highly efficiency is promising for future sensory-neuromorphic photonic systems and interactive artificial intelligence., (© 2023. The Author(s).)

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., (© 2023 Wiley-VCH GmbH.)

Limited by the inherent energy loss (E loss ) in carrier transport process, the device efficiency of organic solar cells shows inferior to traditional inorganic photovoltaic devices. Generally, molecular design, morphology optimization and interfacial engineering are usually required to alleviate E loss . Here, vertical field-effect organic photovoltaic (VFEOPV) by integrating an bulk-heterojunction (BHJ) organic photovoltaic (OPV) with vertical field effect transistor (VFET) is invented, in which VFET generates a large, uneven, internal electric field, eliminating the requirement for driving force to dissociate excitons and prevents non-radiative recombination in OPV. In this way, the performance of solar cell can be well controlled by the gate voltage of VFET and the E loss of VFEOPVs based on J71: ITIC system is dramatically reduced below 0.2 eV, significantly improving power conversion efficiency (PCE) from 10% to 18% under gate voltage of 0.9 V, which only causes negligible additional power consumption (~10 -4 mJ/cm 2 ). Besides, the device also exhibits multi-functionality including transistor and phototransistors with excellent photodector performance. This work provides a new and general strategy to improve the OPV performance which is compatible with present optimization methods, and can be applied to improve PCE of other types of solar cells such as Perovskite and inorganic solar cells., (© 2023. The Author(s).)

After Clostridium tetani infects the human body, it propagates under anaerobic conditions and produces tetanus neurotoxin (TeNT). TeNT can affect the central nervous system, inhibit the release of neurotransmitters, and result in respiratory failure, which are the root causes of death in tetanus patients. Identifying monoclonal antibodies (mAbs) targeting TeNT with neutralizing activity is urgently needed for the prevention and treatment of tetanus infection. In this study, through immunizing BALB/c mice with tetanus toxoid (TT), we obtained six positive hybridoma cell lines (1A7, 2C7, 3A7, 3H4, 4C1, and 4E12). Antibody isotyping showed that the antibodies are all of the IgG1/κ subclass. Ascites fluid was prepared by allogeneic ascites induction and the antibodies were purified through protein G affinity chromatography columns. Purities of the produced murine mAbs were all greater than 95%. All six antibodies bound to linear epitopes, among which 3A7 bound to the TeNT/L domain and the other five antibodies bound to the TeNT/Hc domain. Moreover, the affinity constants of these six antibodies against the antigen were all in the nanomolar range, and the affinity of 4E12 antibody reached the picomolar range. Results from toxin-neutralization assays in mice showed that 2C7 antibody delayed animal death, while 1A7, 3A7, 3H4, and 4E12 antibodies conferred partial protection. Additionally, 4C1 antibody offered complete protection, as 200 μg of 4C1 antibody fully protected against toxin challenge with 10 LD 50 of TeNT and had a window period of 1 h. Antibody epitope grouping results revealed that the binding epitopes of 4C1 antibody were different from those of the other five antibodies. When 4C1 antibody was used in combination with another antibody, the neutralizing activities of antibodies were all evidently enhanced. Specifically, 4C1 combined with 3A7 antibody led to the greatest improvement in neutralizing activities, and 20 μg antibodies total (10 + 10 μg) fully protected against toxin challenge with 10 LD 50 . When 4E12, 3A7, and 4C1 antibodies were used in combination, 18 μg antibodies total (6 + 6 + 6 μg) completely neutralized 10 LD 50 toxin. The present study derived murine mAbs with neutralizing activities and laid the foundation for follow-up therapeutic drug development for TeNT poisoning as well as establishment of TeNT detection methods., Competing Interests: Declaration of Competing Interest No potential conflicts of interest were disclosed., (Copyright © 2023. Published by Elsevier B.V.)

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 J ON of 16.6 mA cm -2 and a high J ON /J OFF ratio of 9.12 × 10 5 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., (© 2022 Wiley-VCH GmbH.)

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., (© 2022. The Author(s).)

Background: A large-scale outbreak of Zika virus (ZIKV) has occurred in Brazil and other South American countries, and has rapidly spread to 60 countries and regions worldwide since 2015, but no approved anti-ZIKV vaccines are available as of 2021., Methods: We developed four types of anti-ZIKV DNA vaccine candidates: VPC-NS1, VPC-prME, VPC-prME-NS1, and VPC-EIII-NS1. They were developed against the structural proteins prM and E, and non-structural protein 1 (NS1) of ZIKV using the mammalian cell expression vector pcDNA3.1(+) as the backbone. For immunization, we intramuscularly injected mice with each vaccine candidate (n = 12 to 15 per group) on day 0 and day 14, with mice injected with phosphate-buffered saline (PBS) and pcDNA3.1(+) backbone vector as controls. On day 7, 21, and 35 after initial immunization, the effect of DNA vaccines was evaluated by ZIKV-specific humoral immunity determined by enzyme-linked immunosorbent assay (ELISA), ZIKV-specific T cell immunity determined by intracellular cytokine staining by flow cytometry and serum neutralization capacity determined by plaque reduction neutralization test (PRNT 50 ) assay., Results: The sequencing results showed that DNA vaccine vectors were successfully constructed. Western blotting and immunofluorescence results demonstrated the successful expression of immunogens carried by the DNA vaccines. On day 21 and 35 after the initial immunization, the levels of serum total immunoglobulin (Ig)G in all vaccine-given groups were slightly higher (approximately 1.5- to 2-fold) than those in the control groups. By contrast, ZIKV-specific IgG levels of all vaccine-given groups were significantly higher (approximately 10- to 1000- fold) than those of the control groups. The PRNT 50 assay showed that the average serum dilution factors for neutralizing half ZIKV virions from vaccine-given groups were at least 32-fold (highest, 93-fold), while the sera from control group showed no protection. For cellular immunity, the proportions of CD11b+ myeloid cells, CD19+ B lymphocytes and CD3+ T lymphocytes in the mouse spleens as well as the percentages of CD4+ and CD8+ subsets of T cell were not changed 35 days after initial immunization. By contrast, the proportions of ZIKV-specific CD4+T cell and CD8+T cell in all vaccine-given groups were 2- to 10-folds and 2- to 30-fold than those in the control groups, respectively., Conclusion: All four DNA vaccines designed for the ZIKV induced neutralizing IgGs and cellular immune responses against ZIKV. Particularly, VPC-EIII-NS1 induced high level of humoral response comparable to the vaccine candidate containing prM, E and NS1 polyprotein, suggesting a potent reduced ADE effect and reserved neutralizing activity. Our findings may provide guidance for improving safety of anti-ZIKV vaccines in the future., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

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.

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., (© 2022. The Author(s).)

SARS-COV-2 is prevalent all over the world, causing more than six million deaths and seriously affecting human health. At present, there is no specific drug against SARS-COV-2. Protein phosphorylation is an important way to understand the mechanism of SARS -COV-2 infection. It is often expensive and time-consuming to identify phosphorylation sites with specific modified residues through experiments. A method that uses machine learning to make predictions about them is proposed. As all the methods of extracting protein sequence features are knowledge-driven, these features may not be effective for detecting phosphorylation sites without a complete understanding of the mechanism of protein. Moreover, redundant features also have a great impact on the fitting degree of the model. To solve these problems, we propose a feature selection method based on ensemble learning, which firstly extracts protein sequence features based on knowledge, then quantifies the importance score of each feature based on data, and finally uses the subset of important features as the final features to predict phosphorylation sites., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Liu, Cui, Chen and Liu.)

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.

Phage has high specificity for its host recognition. As a natural enemy of bacteria, it has been used to treat super bacteria many times. Identifying phage proteins from the original sequence is very important for understanding the relationship between phage and host bacteria and developing new antimicrobial agents. However, traditional experimental methods are both expensive and time-consuming. In this study, an ensemble learning-based feature selection method is proposed to find important features for phage protein identification. The method uses four types of protein sequence-derived features, quantifies the importance of each feature by adding perturbations to the features to influence the results, and finally splices the important features among the four types of features. In addition, we analyzed the selected features and their biological significance., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Liu, Cui, Chen and Liu.)

Donor-acceptor (D-A) alignment that integrates D-A pairs into the modular and versatile crystalline metal-organic frameworks is a powerful strategy to precisely fabricate multifunctional materials with unique optoelectronic properties and applications at the molecular level. Herein, we reported an unprecedented threefold interpenetrating D-A hybrid framework by incorporating an electron-deficient linear viologen zwitterion into the lead-halide systems. The 1D iodoplumbate nanoribbon and interpenetrating close-packed D-A structure endowed this hitherto unknown semiconductive alignment with the anisotropic conductivity and high stability. When used in a thermal sensor, it presented exceptional electrical properties with a high sensitivity (high thermal index B of 4671 K) and decent temperature coefficient of resistivity (0.72% °C -1 ) in wide operational temperature ranges (40-220 °C), which are among the best of the related thermistors. This work develops a pathway to bridge the gaps between hybrid materials and electron devices.

Anomalous negative phototransistors in which the channel current decreases under light illumination hold potential to generate novel and multifunctional optoelectronic applications. Although a variety of design strategies have been developed to construct such devices, NPTs still suffer from far lower device performance compared to well-developed positive phototransistors (PPTs). In this work, a novel 1D/2D molecular crystal p-n heterojunction, in which p-type 1D molecular crystal (1DMC) arrays are embedded into n-type 2D molecular crystals (2DMCs), is developed to produce ultrasensitive NPTs. The p-type 1DMC arrays act as light-absorbing layers to induce p-doping of n-type 2DMCs through charge transfer under illumination, resulting in ineffective gate control and significant negative photoresponses. As a result, the NPTs show remarkable performances in photoresponsivity (P) (1.9 × 10 8 ) and detectivity (D*) (1.7 × 10 17 Jones), greatly outperforming previously reported NPTs, which are one of the highest values among all organic phototransistors. Moreover, the device exhibits intriguing characteristics undiscovered in PPTs, including precise control of the threshold voltage by controlling light signals and ultrasensitive detection of weak light. As a proof-of-concept, the NTPs are demonstrated as light encoders that can encrypt electrical signals by light. These findings represent a milestone for negative phototransistors, and pave the way for the development of future novel optoelectronic applications., (© 2022 Wiley-VCH GmbH.)

The electric bus driven by the wheel-side motor has a natural advantage for the driving stability control of the vehicle because the torque of each driving wheel is independently controllable. Based on the advantages of the artificial neural network control algorithm, this paper designs a direct yaw torque control strategy based on neural network PID control, and combines the steering characteristics of the vehicle to distribute the driving torque. The co-simulation results of Matlab/Simulink and TruckSim show that the designed control strategy can effectively reduce the vehicle's center of mass slip angle and lateral acceleration under medium and high speed conditions, and ensure the stable driving of the bus., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Chen, Zheng, Chen, Zhu and Gao.)

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, Ti 3 C 2 T x , 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., (© 2022. The Author(s).)

Asamitocins are maytansinoids produced by Actinosynnema pretiosum ssp. auranticum ATCC 31565 (A. pretiosum ATCC 31565), which have a structure similar to that of maytansine, therefore serving as a precursor of maytansine in the development of antibody-drug conjugates (ADCs). Currently, there are more than 20 known derivatives of ansamitocins, among which ansamitocin P-3 (AP-3) exhibits the highest antitumor activity. Despite its importance, the application of AP-3 is restricted by low yield, likely due to a substrate competition mechanism underlying the synthesis pathways of AP-3 and its byproducts. Given that N-demethylansamitocin P-3, the precursor of AP-3, is regulated by asm25 and asm10 to synthesize AGP-3 and AP-3, respectively, asm25 is predicted to be an inhibitory gene for AP-3 production. In this study, we inactivated asm25 in A. pretiosum ATCC 31565 by CRISPR-Cas9-guided gene editing. asm25 depletion resulted in a more than 2-fold increase in AP-3 yield. Surprisingly, the addition of isobutanol further improved AP-3 yield in the asm25 knockout strain by more than 6 times; in contrast, only a 1.53-fold increase was found in the WT strain under the parallel condition. Thus, we uncovered an unknown function of asm25 in AP-3 yield and identified asm25 as a promising target to enhance the large-scale industrial production of AP-3., Competing Interests: The authors have declared that no competing interests exist.

Objectives: The objectives of this study were to compare the adult occupant injury risk on specific body regions in frontal and rear impact and to investigate the effect of those crash conditions and occupant-related factors on the injury risk., Method: Data from the NASS-CDS and Crash Investigation Sampling System were studied for crashes during 2000 to 2019 involving model year 2000 to 2020 motor vehicles, including frontal collisions and rear-end collisions. The injury risk by specific body regions were compared by descriptive statistics, and logistic regression models were developed to examine the effects of various factors on injury risk by specific body regions, controlling for crash type (frontal impact and rear impact), vehicle impact speed, vehicle impact location, vehicle model year, and occupant gender, age, belt use, and seating position., Results: After controlling for the confounding factors, the occupants in frontal impact had higher overall injury risk than in rear impact (at Maximum Abbreviated Injury Scale [MAIS] 3+; odds ratio [OR] = 6.23; 95% confidence interval [CI] [6.06-6.40]), except for lower neck/spine injury risk at MAIS 1+ (OR = 0.47; 95% CI [0.46-0.47]). The impact speed (at MAIS 3+; OR = 1.10; 95% CI [1.10-1.10]) and aging (at MAIS 3+; OR = 1.05; 95% CI [1.05-1.05]) increase overall injury risk, and the unbelted occupants had higher overall injury risk than belted occupants not only in frontal impact (at MAIS 3+; OR = 4.04; 95% CI [3.98-4.10]), but also in rear impact (at MAIS 3+; OR = 28.4; 95% CI [26.4-30.5]). Females had higher overall injury risk than males in frontal impact (at MAIS 3+; OR = 2.01; 95% CI [1.99-2.04]) but not in rear impact (at MAIS 3+; OR = 0.77; 95% CI [0.73-0.81])., Conclusions: Occupants in rear impact had lower injury risk than in frontal impact at MAIS 1+ to MAIS 3+, except for neck/spine at MAIS 1+. The belt restraint was effective not only in frontal impact but also in rear impact. This study provided injury risk references for current vehicles that may provide insight to the potential injury risk of rear-facing occupants in future vehicle configurations.

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.

Metal atoms were deposited on an Si (111)-7 × 7 surface, and they were adsorbed with alcohol gases (CH 3 OH/C 2 H 5 OH/C 3 H 7 OH). Initially, C n H 2n+1 OH 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 C n H 2n+1 OH 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 CH 3 OH adsorption are more clearly presented in this paper. Adjusting the preheating temperature, the difference of thermal stability between CH 3 O - and H + could be obviously derived in Au deposition. After a large amount of H + was separated, the isolation characteristic of CH 3 O - was discussed in the case of Fe deposition. In the process of building a new metal-CH 3 O - -H + model, the dual characteristics of CH 3 OH were synthetically verified in Sn deposition. CH 3 O - 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-CH 3 OH surface is promoted, especially according to the dual characteristics and adsorption models we explored.

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.

Pinene, a natural active monoterpene, is widely used as a flavoring agent, perfume, medicine, and biofuel. Although genetically engineered microorganisms have successfully produced pinene, to date, the biological yield of pinene is much lower than that of semiterpenes (isoprene) and sesquiterpenes (farnesene). In addition to the low heterologous expression of geranyl pyrophosphate synthase (GPPS) and pinene synthase (PS), cytotoxicity due to accumulation of the monoterpene also limits the production of pinene in microorganisms. In this study, we attempted to use two strategies to increase the biological yield of pinene. By deleting the random coils of GPPS and PS alone or in combination, a strain with a 335% yield increase was obtained. Additionally, upon computer-guided molecular modeling and docking of GPPS with isopentenyl pyrophosphate (IPP), its substrate, the key sites located within the catalytic pocket for substrate binding, was predicted. After screening, a strain harboring the T273R mutation of GPPS was selected among a batch of mutations of the key sites with a 154% increase in pinene yield., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2021 Fei Chen et al.)

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 HfS 2 into native oxide, HfO x , which shows good insulating property and clean interface with HfS 2 . We then incorporate the HfO x /HfS 2 heterostructure into a flash memory device, achieving a high on/off current ratio of ∼10 5 , a large memory window over 60 V, good endurance, and a long retention time over 10 3 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.

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 10 6 , 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.

Organic phototransistors (OPTs) have attracted enormous attention because of their promising applications in sensing, communication, and imaging. Currently, most OPTs reported utilize field-effect transistors (FETs) with relative long channel length which usually has undesired amplification because of their inherent low transconductance originated from their low channel capacitance, limiting the further improvement of performance. Herein, a vertical channel hybrid electrochemical phototransistor with a nanoscale channel and large transconductance (VECPT) is invented for the first time to achieve ultrahigh photoresponsivity along with a fast response speed. Benefiting from the nanoscale channel length and large transconductance, the photo-generated carriers in channel can be efficiently dissociated, transported, and amplified into the enlarged photocurrent output. Therefore, the devices deliver substantially improved optoelectronic performances with a photoresponsivity as high as ≈2.99 × 10 7 A/W, detectivity of ≈1.49 × 10 13 Jones, and fast-speed response of ≈73 μs under a low voltage of 1 V, which are superior to those of the reported OPTs based on FETs. Moreover, the in situ Kelvin probe microscopy is performed to characterize the surface potential of device systems for better elucidating the photosensing mechanism. Furthermore, taking advantage of its excellent optoelectronic performance, an ultraviolet light monitoring system is constructed by integrating VECPT with a light-emitting diode, which also shows the real-time, high-sensitive, and controllable photoresponse threshold properties. All these results demonstrate the great potential of these electrochemical phototransistors and provide valuable insights into the design of the nanoscale channel length device system for high-performance photodetection.

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 × 10 5 A/W, an outstanding detectivity of 1.15 × 10 18 Jones, and an excellent photosensitivity of 5 × 10 7 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.

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.

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 Cs 2 AgBiBr 6 NCs was demonstrated for the first time. Acting synchronously as the protection layer for the discrete Cs 2 AgBiBr 6 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 Cs 2 AgBiBr 6 @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.

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 ( I ON / I OFF ) ≈ 10 5 , 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.

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 Ta 2 O 5 /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 Ta 2 O 5 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.

Neuromorphic computing inspired by the neural systems in human brain will overcome the issue of independent information processing and storage. An artificial synaptic device as a basic unit of a neuromorphic computing system can perform signal processing with low power consumption, and exploring different types of synaptic transistors is essential to provide suitable artificial synaptic devices for artificial intelligence. Hence, for the first time, an electret-based synaptic transistor (EST) is presented, which successfully shows synaptic behaviors including excitatory/inhibitory postsynaptic current, paired-pulse facilitation/depression, long-term memory, and high-pass filtering. Moreover, a neuromorphic computing simulation based on our EST is performed using the handwritten artificial neural network, which exhibits an excellent recognition accuracy (85.88%) after 120 learning epochs, higher than most reported organic synaptic transistors and close to the ideal accuracy (92.11%). Such a novel synaptic device enriches the diversity of synaptic transistors, laying the foundation for the diversified development of the next generation of neuromorphic computing systems.

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 Ta 2 O 5 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.

Neuromorphic computation, which emulates the signal process of the human brain, is considered to be a feasible way for future computation. Realization of dynamic modulation of synaptic plasticity and accelerated learning, which could improve the processing capacity and learning ability of artificial synaptic devices, is considered to further improve energy efficiency of neuromorphic computation. Nevertheless, realization of dynamic regulation of synaptic weight without an external regular terminal and the method that could endow artificial synaptic devices with the ability to modulate learning speed have rarely been reported. Furthermore, finding suitable materials to fully mimic the response of photoelectric stimulation is still challenging for photoelectric synapses. Here, a floating gate synaptic transistor based on an L-type ligand-modified all-inorganic CsPbBr 3 perovskite quantum dots is demonstrated. This work provides first clear experimental evidence that the synaptic plasticity can be dynamically regulated by changing the waveforms of action potential and the environment temperature and both of these parameters originate from and are crucial in higher organisms. Moreover, benefiting from the excellent photoelectric properties and stability of quantum dots, a temperature-facilitated learning process is illustrated by the classical conditioning experiment with and without illumination, and the mechanism of synaptic plasticity is also demonstrated. This work offers a feasible way to realize dynamic modulation of synaptic weight and accelerating the learning process of artificial synapses, which showed great potential in the reduction of energy consumption and improvement of efficiency of future neuromorphic computing.

In this work, a novel vertical quantum-dot light-emitting transistor (VQLET) based on a vertical organic thin-film transistor is successfully fabricated. Benefiting from the new vertical architecture, the VQLET is able to afford an extremely high current density, which allows most of the organic thin film transistors (OTFT) even with low mobility (for instance, poly(3-hexylthiophene)) to drive a quantum-dot light-emitting diode (QLED), which was previously unavailable. Moreover, the hole injection barrier could be modulated by the additional gate electrode, which precisely optimizes the charge balance in the device, a critical issue in QLED, resulting in the precise control of current density and brightness of the VQLET. The VQLET shows a high performance with a maximum current efficiency of 37 cd/A. Furthermore, integrating OTFT and QLED into a single device, the VQLET features drastic advantages by realizing active matrix quantum-dot light-emitting diodes (AMQLEDs), which significantly reduces the number of transistors and frees the large area fraction occupied by transistors. Hence, these results indicate that the VQLET provides a new strategy for realizing a low-cost, solution-processed, high-performance OTFT-AMQLED for the flat panel display technology. Moreover, the novel design offers a unique method to exquisitely control the charge balance and maximize the efficiency the QLED.

The identifying characteristic of an organic electrochemical transistor (OECT) is the coupling between ionic and electronic charges within the entire volume of the channel. In this work, by taking advantage of the volumetric nature of the OECTs' response, a novel flexible photodetector is reported for the first time based on all-solid-state OECT with an excellent responsivity of up to 6.7 × 10 6 A/W, detectivity as high as 3.6 × 10 13 Jones, and a fast response of ∼0.13 s in the visible range, which are superior to those of the majority of the reported organic phototransistors (OPTs) based on field-effect transistors (FETs) and even better than those of FET-based phototransistors with two-dimensional (MoS 2 and graphene) and perovskite materials. The high performance of the devices was ascribed to the combination of the higher carrier mobility of poly(3,4-ethylenedioxythiophene) doped with poly(styrene sulfonate) (PEDOT:PSS) as a channel and the volumetric nature of the OECTs' response, and the charge density of the volumetric channel was efficiently modulated by incident light compared to FETs. Moreover, OECT-based OPTs with quantum dots (CdSe/ZnS) as a light sensitizer were characterized under ultraviolet light, and they exhibited excellent photosensitivity, which further verified the superiority of OECT for phototransistors. Furthermore, a flexible image sensor was fabricated for the first time by integrating flexible OECTs-OPTs into a 10 × 10 array, which can clearly identify the target image under a bending state, indicating the great potential of OECTs-OPTs in the application of low-power, ultrasensitive flexible photodetectors and imaging technology.

Acute lung injury (ALI), a persistent lung inflammatory response syndrome, may evolve into acute respiratory distress syndrome (ARDS). Characterized by rapid onset, critical features, and a complex etiology, ALI remains a challenging critical respiratory disease. Recently, mesenchymal stem cells (MSCs) have provided a new solution for the treatment of ALI. We built a lipopolysaccharide (LPS)-induced ALI model in mice. After treatment with human umbilical cord mesenchymal stem cells (hUC-MSCs), FTY720, or a combination of hUC-MSCs and FTY207, the lung inflammatory response was apparently attenuated. To understand the mechanism underlying MSCs treatment of ALI at the genetic level, significant differentially expressed long non-coding RNAs (lncRNAs) between the treatment and model groups were analyzed using microarray technology. Moreover, genetic gene prediction, gene ontology (GO) analysis, pathway analysis, and transcription factor (TF) prediction were carried out. The results showed that a total of 66 lncRNAs were differentially expressed in all three treatment groups, including 8 up-regulated and 58 down-regulated lncRNAs. LncRNA A&#95;30&#95;P01029806 and A&#95;30&#95;P01029194, which were down-regulated, were involved in the signaling pathways closely related to ALI. Through further TF analysis, we identified several significant TFs which lay a foundation for revealing the mechanism underlying lncRNAs treatment of ALI. LncRNA A&#95;30&#95;P01029806 and A&#95;30&#95;P01029194 may serve as candidate biomarkers in the diagnosis and treatment of ALI., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Amorphous oxide semiconductor (AOS) field-effect phototransistors (FEPTs) are promising candidates for emerging photodetectors. Unfortunately, traditional lateral AOS FEPTs suffer from low photosensitivity, slow response time and inadequate mechanical flexibility, which restrict their widespread commercial application. In this work, novel AOS-based vertical field-effect phototransistor (VFEPT) arrays are presented, where the semiconducting layer and source and drain electrodes are deposited by inkjet printing. Benefitted from the unique vertical structure and ultrashort channel length, the exciton dissociation, carrier transfer, and collection efficiency were dramatically enhanced, resulting in excellent photoelectric performance in VFEPT devices, which was better than that of the traditional lateral AOS phototransistors. Moreover, flexible AOS VFEPT arrays were investigated for the first time on polyimide substrates. Due to the unique vertical architecture, the carrier transport was negligibly affected by the strain-induced in-plane cracks of the semiconductor channel layer during the mechanical bending process, which overcame the maximum bending limit of traditional lateral AOS thin-film transistors to ensure a transistor technique that gives notable mechanical robustness against repeated mechanical bending. Hence, this work provided a new pathway in emerging applications for AOS photodetectors with sensitivity, transparency, and flexibility.