MXene based saturation organic vertical photoelectric transistors with low subthreshold swing

MXene-Ti3C2Tx-Based Neuromorphic Computing: Physical Mechanisms, Performance Enhancement, and Cutting-Edge Computing

Neuromorphic devices have shown great potential in simulating the function of biological neurons due to their efficient parallel information processing and low energy consumption. MXene-Ti3C2Tx, an emerging two-dimensional material, stands out as an ideal candidate for fabricating neuromorphic devices. Its exceptional electrical performance and robust mechanical properties make it an ideal choice for this purpose. This review aims to uncover the advantages and properties of MXene-Ti3C2Tx in neuromorphic devices and to promote its further development. Firstly, we categorize several core physical mechanisms present in MXene-Ti3C2Tx neuromorphic devices and summarize in detail the reasons for their formation. Then, this work systematically summarizes and classifies advanced techniques for the three main optimization pathways of MXene-Ti3C2Tx, such as doping engineering, interface engineering, and structural engineering. Significantly, this work highlights innovative applications of MXene-Ti3C2Tx neuromorphic devices in cutting-edge computing paradigms, particularly near-sensor computing and in-sensor computing. Finally, this review carefully compiles a table that integrates almost all research results involving MXene-Ti3C2Tx neuromorphic devices and discusses the challenges, development prospects, and feasibility of MXene-Ti3C2Tx-based neuromorphic devices in practical applications, aiming to lay a solid theoretical foundation and provide technical support for further exploration and application of MXene-Ti3C2Tx in the field of neuromorphic devices.

Toward Switching and Fusing Neuromorphic Computing: Vertical Bulk Heterojunction Transistors with Multi-Neuromorphic Functions for Efficient Deep Learning

The combination of artificial neural networks (ANN) and spiking neural networks (SNN) holds great promise for advancing artificial general intelligence (AGI). However, the reported ANN and SNN computational architectures are independent and require a large number of auxiliary circuits and external algorithms for fusion training. Here, a novel vertical bulk heterojunction neuromorphic transistor (VHNT) capable of emulating both ANN and SNN computational functions is presented. TaOx-based electrochemical reactions and PDVT-10/N2200-based bulk heterojunctions are used to realize spike coding and voltage coding, respectively. Notably, the device exhibits remarkable efficiency, consuming a mere 0.84 nJ of energy consumption for a single multiply accumulate (MAC) operation with excellent linearity. Moreover, the device can be switched to spiking neuron and self-activation neuron by simply changing the programming without auxiliary circuits. Finally, the VHNT-based artificial spiking neural network (ASNN) fusion simulation architecture is demonstrated, achieving 95% accuracy for Canadian-Institute-For-Advanced-ResearchResearch-10 (CIFARResearch-10) dataset while significantly enhancing training speed and efficiency. This work proposes a novel device strategy for developing high-performance, low-power, and environmentally adaptive AGI.

Engineering Steep Subthreshold Swings in High-Performance Organic Field-Effect Transistor Sensors

Organic field-effect transistor (OFET)-based sensors have gained considerable attention for information perception and processing in developing artificial intelligent systems owing to their amplification function and multiterminal regulation. Over the last few decades, extensive research has been conducted on developing OFETs with steep subthreshold swings (SS) to achieve high-performance sensing. In this review, based on an analysis of the critical factors that are unfavorable for a steep SS in OFETs, the corresponding representative strategies for achieving steep SS are summarized, and the advantages and limitations of these strategies are comprehensively discussed. Furthermore, a bridge between SS and OFET sensor performance is established. Subsequently, the applications of OFETs with steep SS in sensor systems, including pressure sensors, photosensors, biochemical sensors, and electrophysiological signal sensors. Lastly, the challenges faced in developing OFET sensors with steep SS are discussed. This study provides insights into the design and application of high-performance OFET sensor systems.

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

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

Functionalized MXene ink enables environmentally stable printed electronics

Establishing dependable, cost-effective electrical connections is vital for enhancing device performance and shrinking electronic circuits. MXenes, combining excellent electrical conductivity, high breakdown voltage, solution processability, and two-dimensional morphology, are promising candidates for contacts in microelectronics. However, their hydrophilic surfaces, which enable spontaneous environmental degradation and poor dispersion stability in organic solvents, have restricted certain electronic applications. Herein, electrohydrodynamic printing technique is used to fabricate fully solution-processed thin-film transistors with alkylated 3,4-dihydroxy-L-phenylalanine functionalized Ti3C2Tx (AD-MXene) as source, drain, and gate electrodes. The AD-MXene has excellent dispersion stability in ethanol, which is required for electrohydrodynamic printing, and maintains high electrical conductivity. It outperformed conventional vacuum-deposited Au and Al electrodes, providing thin-film transistors with good environmental stability due to its hydrophobicity. Further, thin-film transistors are integrated into logic gates and one-transistor-one-memory cells. This work, unveiling the ligand-functionalized MXenes' potential in printed electrical contacts, promotes environmentally robust MXene-based electronics (MXetronics).

A Molecular Coordination Strategy for Regulating the Interface of MoS2 Field Effect Transistors

Chemically modifying monolayer two-dimensional transition metal dichalcogenides (TMDs) with organic molecules provides a wide range of possibilities to regulate the electronic and optoelectronic performance of both materials and devices. However, it remains challenging to chemically attach organic molecules to monolayer TMDs without damaging their crystal structures. Herein, we show that the Mo atoms of monolayer MoS2 (1L-MoS2) in defect states can coordinate with both catechol and 1,10-phenanthroline (Phen) groups, affording a facile route to chemically modifying 1L-MoS2. Through the design of two isomeric molecules (LA2 and LA5) comprising catechol and Phen groups, we show that attaching organic molecules to Mo atoms via coordinative bonds has no negative effect on the crystal structure of 1L-MoS2. Both theoretical calculation and experiment results indicate that the coordinative strategy is beneficial for (i) repairing sulfur vacancies and passivating defects; (ii) achieving a long-term and stable n-doping effect; and (iii) facilitating the electron transfer. Field effect transistors (FETs) based on the coordinatively modified 1L-MoS2 show high electron mobilities up to 120.3 cm2 V-1 s-1 with impressive current on/off ratios over 109. Our results indicate that coordinatively attaching catechol- or Phen-bearing molecules may be a general method for the nondestructive modification of TMDs.

Recent progress in emerging two-dimensional organic-inorganic van der Waals heterojunctions

Two-dimensional (2D) materials have attracted significant attention in recent decades due to their exceptional optoelectronic properties. Among them, to meet the growing demand for multifunctional applications, 2D organic-inorganic van der Waals (vdW) heterojunctions have become increasingly popular in the development of optoelectronic devices. These heterojunctions demonstrate impressive capability to synergistically combine the favourable characteristics of organic and inorganic materials, thereby offering a wide range of advantages. Also, they enable the creation of innovative device structures and introduce novel functionalities in existing 2D materials, avoiding the need for lattice matching in different material systems. Presently, researchers are actively working on improving the performance of devices based on 2D organic-inorganic vdW heterojunctions by focusing on enhancing the quality of 2D materials, precise stacking methods, energy band regulation, and material selection. Therefore, this review presents a thorough examination of the emerging 2D organic-inorganic vdW heterojunctions, including their classification, fabrication, and corresponding devices. Additionally, this review offers profound and comprehensive insight into the challenges in this field to inspire future research directions. It is expected to propel researchers to harness the extraordinary capabilities of 2D organic-inorganic vdW heterojunctions for a wider range of applications by further advancing the understanding of their fundamental properties, expanding the range of available materials, and exploring novel device architectures. The ongoing research and development in this field hold potential to unlock captivating advancements and foster practical applications across diverse industries.

Performance analysis of solution-processed nanosheet strain sensors-a systematic review of graphene and MXene wearable devices

Nanotechnology has led to the realisation of many potentialInternet of Thingsdevices that can be transformative with regards to future healthcare development. However, there is an over saturation of wearable sensor review articles that essentially quote paper abstracts without critically assessing the works. Reported metrics in many cases cannot be taken at face value, with researchers overly fixated on large gauge factors. These facts hurt the usefulness of such articles and the very nature of the research area, unintentionally misleading those hoping to progress the field. Graphene and MXenes are arguably the most exciting organic and inorganic nanomaterials for polymer nanocomposite strain sensing applications respectively. Due to their combination of cost-efficient, scalable production and device performances, their potential commercial usage is very promising. Here, we explain the methods for colloidal nanosheets suspension creation and the mechanisms, metrics and models which govern the electromechanical properties of the polymer-based nanocomposites they form. Furthermore, the many fabrication procedures applied to make these nanosheet-based sensing devices are discussed. With the performances of 70 different nanocomposite systems from recent (post 2020) publications critically assessed. From the evaluation of these works using universal modelling, the prospects of the field are considered. Finally, we argue that the realisation of commercial nanocomposite devices may in fact have a negative effect on the global climate crisis if current research trends do not change.

Steep-slope vertical-transport transistors built from sub-5 nm Thin van der Waals heterostructures

Two-dimensional (2D) semiconductor-based vertical-transport field-effect transistors (VTFETs) - in which the current flows perpendicularly to the substrate surface direction - are in the drive to surmount the stringent downscaling constraints faced by the conventional planar FETs. However, low-power device operation with a sub-60 mV/dec subthreshold swing (SS) at room temperature along with an ultra-scaled channel length remains challenging for 2D semiconductor-based VTFETs. Here, we report steep-slope VTFETs that combine a gate-controllable van der Waals heterojunction and a metal-filamentary threshold switch (TS), featuring a vertical transport channel thinner than 5 nm and sub-thermionic turn-on characteristics. The integrated TS-VTFETs were realised with efficient current switching behaviours, exhibiting a current modulation ratio exceeding 1 × 108 and an average sub-60 mV/dec SS over 6 decades of drain current. The proposed TS-VTFETs with excellent area- and energy-efficiency could help to tackle the performance degradation-device downscaling dilemma faced by logic transistor technologies.

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.

MXene-based electrochemical devices applied for healthcare applications

The initial part of the review provides an extensive overview about MXenes as novel and exciting 2D nanomaterials describing their basic physico-chemical features, methods of their synthesis, and possible interfacial modifications and techniques, which could be applied to the characterization of MXenes. Unique physico-chemical parameters of MXenes make them attractive for many practical applications, which are shortly discussed. Use of MXenes for healthcare applications is a hot scientific discipline which is discussed in detail. The article focuses on determination of low molecular weight analytes (metabolites), high molecular weight analytes (DNA/RNA and proteins), or even cells, exosomes, and viruses detected using electrochemical sensors and biosensors. Separate chapters are provided to show the potential of MXene-based devices for determination of cancer biomarkers and as wearable sensors and biosensors for monitoring of a wide range of human activities.

Functional MXenes: Progress and Perspectives on Synthetic Strategies and Structure-Property Interplay for Next-Generation Technologies

MXenes are a class of 2D materials that include layered transition metal carbides, nitrides, and carbonitrides. Since their inception in 2011, they have garnered significant attention due to their diverse compositions, unique structures, and extraordinary properties, such as high specific surface areas and excellent electrical conductivity. This versatility has opened up immense potential in various fields, catalyzing a surge in MXene research and leading to note worthy advancements. This review offers an in-depth overview of the evolution of MXenes over the past 5 years, with an emphasis on synthetic strategies, structure-property relationships, and technological prospects. A classification scheme for MXene structures based on entropy is presented and an updated summary of the elemental constituents of the MXene family is provided, as documented in recent literature. Delving into the microscopic structure and synthesis routes, the intricate structure-property relationships are explored at the nano/micro level that dictate the macroscopic applications of MXenes. Through an extensive review of the latest representative works, the utilization of MXenes in energy, environmental, electronic, and biomedical fields is showcased, offering a glimpse into the current technological bottlenecks, such asstability, scalability, and device integration. Moreover, potential pathways for advancing MXenes toward next-generation technologies are highlighted.

Liquid-Film Rupture for Web-like Ag Nanowires toward High-Performance Organic Schottky Barrier Transistors

Organic vertical transistors are promising device with benefits such as high operation speed, high saturation current density, and low-voltage operation owing to their short channel length. However, a short channel length leads to a high off-current, which is undesirable because it affects the on-off ratio and power consumption. This study presents a breakthrough in the development of high-performance organic Schottky barrier transistors (OSBTs) with a low off-current by utilizing a near-ideal source electrode with a web-like Ag nanowire (AgNW) morphology. This is achieved by employing a humidity- and surface-tension-mediated liquid-film rupture technique, which facilitates the formation of well-connected AgNW networks with large pores between them. Therefore, the gate electric field is effectively transmitted to the semiconductor layer. Also, the minimized surface area of the AgNWs causes complete suppression of the off-current and induces ideal saturation of the OSBT output characteristics. p- and n-type OSBTs exhibit off-currents in the picoampere range with on/off ratios exceeding 106 and 105, respectively. Furthermore, complementary inverters are prepared using an aryl azide cross-linker for patterning, with a gain of >16. This study represents a significant milestone in the development of high-performance organic vertical transistors and verifies their applicability in organic electronic circuitry.

MXene based flexible photodetectors: progress, challenges, and opportunities

The growing interest in applying 2D transition-metal carbides and nitrides (MXenes) to diverse application fields such as energy storage and harvesters, catalysts, sensors, optoelectronics, electromagnetic interference shielding and antennas since its first discovery in 2011 is clearly evident. Their intrinsic high conductivity limits the development of MXenes in photodetectors that rely on the semiconducting properties of active materials, while the abundant functional groups on the surface of MXenes provide opportunities for using MXenes as sensing materials in the fabrication of flexible photodetectors. Considerable studies on MXene based photodetectors have been carried out, but the main obstacles include seeking novel semiconducting materials in MXene families, the manufacturing technology, etc. This review highlights the progress, challenges and opportunities in MXene based flexible photodetectors and discusses novel materials, architectures, and approaches that capitalize on our growing understanding of MXenes.

Fused-Ring Electron-Acceptor Single Crystals with Chiral 2D Supramolecular Organization for Anisotropic Chiral Optoelectronic Devices

Supramolecular chiral organization gives π-conjugated molecules access to fascinating specific interactions with circularly polarized light (CPL). Such a feature enables the fabrication of high-performance chiral organic electronic devices that detect or emit CPL directly. Herein, it is shown that chiral fused-ring electron-acceptor BTP-4F single-crystal-based phototransistors demonstrate distinguished CPL discrimination capability with current dissymmetry factor exceeding 1.4, one of the highest values among state-of-the-art direct CPL detectors. Theoretical calculations prove that the chirality at the supramolecular level in these enantiomeric single crystals originates from chiral exciton coupling of a unique quasi-2D supramolecular organization consisting of interlaced molecules with opposite helical conformation. Impressively, such supramolecular organization produces a higher dissymmetry factor along the preferred growth direction of the chiral single crystals in comparison to that of the short axis direction. Furthermore, the amplified, inverted, and also anisotropic current dissymmetry compared to optical dissymmetry is studied by finite element simulations. Therefore, a unique chiral supramolecular organization that is responsible for the excellent chiroptical response and anisotropic electronic properties is developed, which not only enables the construction of high-performance CPL detection devices but also allows a better understanding of the structure-property relationships in chiral organic optoelectronics.

Porous crystalline materials for memories and neuromorphic computing systems

Porous crystalline materials usually include metal-organic frameworks (MOFs), covalent organic frameworks (COFs), hydrogen-bonded organic frameworks (HOFs) and zeolites, which exhibit exceptional porosity and structural/composition designability, promoting the increasing attention in memory and neuromorphic computing systems in the last decade. From both the perspective of materials and devices, it is crucial to provide a comprehensive and timely summary of the applications of porous crystalline materials in memory and neuromorphic computing systems to guide future research endeavors. Moreover, the utilization of porous crystalline materials in electronics necessitates a shift from powder synthesis to high-quality film preparation to ensure high device performance. This review highlights the strategies for preparing porous crystalline materials films and discusses their advancements in memory and neuromorphic electronics. It also provides a detailed comparative analysis and presents the existing challenges and future research directions, which can attract the experts from various fields (e.g., materials scientists, chemists, and engineers) with the aim of promoting the applications of porous crystalline materials in memory and neuromorphic computing systems.

First principles insights into stability of defected MXenes in water

Two-dimensional transition metal carbides and nitrides, known as MXenes, have demonstrated remarkable performance in electrochemical energy storage and various other applications. Despite their potential, MXenes exhibit instability in aqueous solutions, and the role of defects in their aqueous stability is unclear. In this study, we report on the interfacial chemistry between water and defected Ti3C2O2 MXene at room temperature using first principles molecular dynamics simulations. We investigate how defects such as O vacancy, Ti vacancy, F terminal groups, and Ti-O vacancy pair influence the chemical interaction of water molecules with the basal plane of Ti3C2O2. Our results show that water molecules can repair the surface O vacancies, by dissociating to hydroxide and hydronium. On the other hand, F terminal groups cannot effectively block water chemisorption on the surface Ti, while Ti vacancies behave as a spectator species on the surface with respect to interaction with water. Ti3C2O2 with a Ti-O vacancy pair is found to behave like Ti3C2O2 with an O vacancy where a water molecule dissociates and refills the vacancy. These findings enrich our understanding of water interaction with defects on the MXene surfaces.

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.

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.

Stretchable Transistor-Structured Artificial Synapses for Neuromorphic Electronics

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

Large-Area Metal-Semiconductor Heterojunctions Realized via MXene-Induced Two-Dimensional Surface Polarization

Direct MXene deposition on large-area 2D semiconductor surfaces can provide design versatility for the fabrication of MXene-based electronic devices (MXetronics). However, it is challenging to deposit highly uniform wafer-scale hydrophilic MXene films (e.g., Ti₃C₂T_x) on hydrophobic 2D semiconductor channel materials (e.g., MoS₂). Here, we demonstrate a modified drop-casting (MDC) process for the deposition of MXene on MoS₂ without any pretreatment, which typically degrades the quality of either MXene or MoS₂. Different from the traditional drop-casting method, which usually forms rough and thick films at the micrometer scale, our MDC method can form an ultrathin Ti₃C₂T_x film (ca. 10 nm) based on a MXene-introduced MoS₂ surface polarization phenomenon. In addition, our MDC process does not require any pretreatment, unlike MXene spray-coating that usually requires a hydrophilic pretreatment of the substrate surface before deposition. This process offers a significant advantage for Ti₃C₂T_x film deposition on UV-ozone- or O₂-plasma-sensitive surfaces. Using the MDC process, we fabricated wafer-scale n-type Ti₃C₂T_x-MoS₂ van der Waals heterojunction transistors, achieving an average effective electron mobility of ∼40 cm²·V^-1·s^-1, on/off current ratios exceeding 10⁴, and subthreshold swings of under 200 mV·dec^-1. The proposed MDC process can considerably enhance the applications of MXenes, especially the design of MXene/semiconductor nanoelectronics.

Novel Strain Engineering Combined with a Microscopic Pore Synergistic Modulated Strategy for Designing Lattice Tensile-Strained Porous V2C-MXene for High-Performance Overall Water Splitting

Transition metal carbon/nitride (MXene) holds immense potential as an innovative electrocatalyst for enhancing the overall water splitting properties. Nevertheless, the re-stacking nature induced by van der Waals force remains a significant challenge. In this work, the lattice tensile-strained porous V₂C-MXene (named as TS₍₂₄₎-P₍₅₀₎-V₂C) is successfully constructed via the rapid spray freezing method and the following hydrothermal treatment. Besides, the influence of lattice strain degree and microscopic pores on the catalytic ability is reviewed and explored systematically. The lattice tensile strain within V₂C-MXene could widen the interlayer spacing and accelerate the ion transfer. The microscopic pores could change the ion transmission path and shorten the migration distance. As a consequence, the obtained TS₍₂₄₎-P₍₅₀₎-V₂C shows extraordinary hydrogen evolution reaction and oxygen evolution reaction activity with the overpotential of 154 and 269 mV, respectively, at the current density of 10 mA/cm², which is quite remarkable compared to the MXene-based electrocatalysts. Moreover, the overall water splitting device assembled using TS₍₂₄₎-P₍₅₀₎-V₂C as both anode and cathode demonstrates a low cell voltage requirement of 1.57 V to obtain 10 mA/cm². Overall, the implementation of this work could offer an exciting avenue to overcome the re-stacking issue of V₂C-MXene, affording a high-efficiency electrocatalyst with superior catalytic activity and desirable reaction kinetics.

Large area roll-to-roll printed semiconducting carbon nanotube thin films for flexible carbon-based electronics

A universal roll-to-roll (R2R) printing approach was developed to construct large area (8 cm × 14 cm) semiconducting single-walled carbon nanotube (sc-SWCNT) thin films on flexible substrates (such as polyethylene terephthalate (PET), paper, and Al foils) at a printing speed of 8 m min^-1 using highly concentrated sc-SWCNT inks and crosslinked poly-4-vinylphenol (c-PVP) as the adhesion layer. Bottom-gated and top-gated flexible printed p-type TFTs based on R2R printed sc-SWCNT thin films exhibited good electrical properties with a carrier mobility of ∼11.9 cm² V^-1 s^-1, I_on/I_off ratios of ∼10⁶, small hysteresis, and a subthreshold swing (SS) of 70-80 mV dec^-1 at low gate operating voltages (±1 V), and excellent mechanical flexibility. Furthermore, the flexible printed complementary metal oxide semiconductor (CMOS) inverters demonstrated rail-to-rail voltage output characteristics under an operating voltage as low as V_DD = -0.2 V, a voltage gain of 10.8 at V_DD = -0.8 V, and power consumption as low as 0.056 nW at V_DD = -0.2 V. To the best of our knowledge, the electrical properties of the printed SWCNT TFTs (such as I_on/I_off ratio, mobility, operating voltage, and mechanical flexibility) and printed CMOS inverters based on the R2R printed sc-SWCNT active layer in this work are excellent compared to those of R2R printed SWCNT TFTs reported in the literature. Consequently, the universal R2R printing method reported in this work could promote the development of fully printed low-cost, large-area, high-output, and flexible carbon-based electronics.

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 J_ON of 16.6 mA cm^-2 and a high J_ON /J_OFF 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.

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

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

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

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