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%.

Toward grouped-reservoir computing: organic neuromorphic vertical transistor with distributed reservoir states for efficient recognition and prediction.

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.

RNF8 depletion attenuates hepatocellular carcinoma progression by inhibiting epithelial-mesenchymal transition and enhancing drug sensitivity.

Despite substantial advances that have been made in understanding the etiology of hepatocellular carcinoma (HCC), the early-stage diagnosis and treatment of advanced-stage HCC remain a major challenge. RNF8, an E3 ligase important for the DNA damage response, has been proven to facilitate the progression of breast and lung cancer, but its role in HCC remains unclear. In this study, we find that the expression of RNF8 is up-regulated in HCC tissues and positively correlated with poor prognosis of HCC. Furthermore, silencing RNF8 by siRNAs attenuates the migration of HCC cells and inhibits epithelial-mesenchymal transition (EMT) by regulating the expressions of proteins including N-cadherin, ß-catenin, snail, and ZO-1. Moreover, Kaplan‒Meier survival analysis shows that high RNF8 expression predicts poor survival benefits from sorafenib. Finally, cell viability assay demonstrates that RNF8 depletion enhances the sensitivity of HCC cells to sorafenib and lenvatinib treatment. We hypothesize that the inhibitory role of RNF8 in EMT and its enhancing effects on anti-cancer drugs orchestrate the protective effects of RNF8 deficiency in HCC, which indicates its potential in clinical application.

A sensory memory processing system with multi-wavelength synaptic-polychromatic light emission for multi-modal information recognition.

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.

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

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

High-performance vertical field-effect organic photovoltaics.

Limited by the inherent energy loss (Eloss) 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 Eloss. 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 Eloss 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 (~10-4mJ/cm2). 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.

Ultralow-Power Vertical Transistors for Multilevel Decoding Modes.

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

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

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

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

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

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

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

Vertical Channel Inorganic/Organic Hybrid Electrochemical Phototransistors with Ultrahigh Responsivity and Fast Response Speed.

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 × 107 A/W, detectivity of ≈1.49 × 1013 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.

RNF8 Promotes Epithelial-Mesenchymal Transition in Lung Cancer Cells via Stabilization of Slug.

RNF8 (ring finger protein 8), a RING finger E3 ligase best characterized for its role in DNA repair and sperm formation via ubiquitination, has been found to promote tumor metastasis in breast cancer recently. However, whether RNF8 also plays a role in other types of cancer, especially in lung cancer, remains unknown. We show here that RNF8 expression levels are markedly increased in human lung cancer tissues and negatively correlated with the survival time of patients. Overexpression of RNF8 promotes the EMT process and migration ability of lung cancer cells, while knockdown of RNF8 demonstrates the opposite effects. In addition, overexpression of RNF8 activates the PI3K/Akt signaling pathway, knockdown of RNF8 by siRNA inhibits this activation, and pharmacologic inhibition of PI3K/Akt in RNF8-overexpressing cells also reduces the expression of EMT markers and the ability of migration. Furthermore, RNF8 is found to directly interact with Slug and promoted the K63-Ub of Slug, and knockdown of Slug disrupts RNF8-dependent EMT in A549 cells, whereas overexpression of Slug rescues RNF8-dependent MET in H1299 cells, and depletion of RNF8 expression by shRNA inhibits metastasis of lung cancer cells in vivo. Taken together, these results indicate that RNF8 is a key regulator of EMT process in lung cancer and suggest that inhibition of RNF8 could be a useful strategy for lung cancer treatment. IMPLICATIONS: This study provides a new mechanistic insight into the novel role of RNF8 and identifies RNF8 as a potential new therapeutic target for the treatment of lung cancer.