Neuromorphic Functions in PEDOT:PSS Organic Electrochemical Transistors

Conductive MeCbl/PEDOT:PSS/HA hydrogels with electrical stimulation for enhanced peripheral nerve regeneration

Peripheral nerve regeneration (PNR) represents a substantial challenge in the medical field, primarily due to the limited regenerative capacity of the peripheral nerve system (PNS). Current research efforts are focused on developing advanced medical polymer materials to enhance nerve recovery. Despite significant progress, several critical issues remain unresolved, including biocompatibility, stability, mechanical strength, controlled degradation rates, and sustained release of therapeutic agents. This study examines the utilization of hyaluronic acid hydrogels, doped with mecobalamin (MeCbl) and conductive poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS), in combination with exogenous electrical stimulation (ES) for PNR of rats. The strategy utilizes the MeCbl hydrogel to create a regenerative microenvironment and provide nutritional support for nerve cells, while PEDOT:PSS facilitates enhanced electrical signal conduction. ES has been shown to promote PNR and functional recovery, thereby demonstrating considerable potential. This study aims to comprehensively analyze the synergistic effects and potential value of this combined therapeutic approach, providing novel insights and pathways for the effective PNR.

Responsive Molecules for Organic Neuromorphic Devices: Harnessing Memory Diversification

In the brain, both the recording and decaying of memory information following external stimulus spikes are fundamental learning rules that determine human behaviors. The former is essential to acquire new knowledge and update the database, while the latter filters noise and autorefresh cache data to reduce energy consumption. To execute these functions, the brain relies on different neuromorphic transmitters possessing various memory kinetics, which can be classified as nonvolatile and volatile memory. Inspired by the human brain, nonvolatile and volatile memory electronic devices have been employed to realize artificial neural networks and spiking neural networks, respectively, which have emerged as essential tools in machine learning. Molecular switches, capable of responding to electrical, optical, electrochemical, and magnetic stimuli, display a disruptive potential for emulating information storage in memory devices. This Review highlights recent developments on responsive molecules, their interfacing with low-dimensional nanostructures and nanomaterials, and their integration into electronic devices. By capitalizing on these concepts, a unique account of neurotransmitter-transfer electronic devices based on responsive molecules with ad hoc memory kinetics is provided. Finally, future directions, challenges, and opportunities are discussed on the use of these devices to engineer more complex logic operations and computing functions at the hardware level.

Stretchable all-gel organic electrochemical transistors

Stretchable organic electrochemical transistors (OECTs) are promising for flexible electronics. However, the balance between stretchability and electrical properties is a great challenge for OECTs. Here, high-performance stretchable all-gel OECTs based on semiconducting polymer gel active layers and poly(ionic liquid) ionogel electrolytes are developed. The all-gel network structures effectively promote ion penetration/transport and endows the OECTs with high stretchability. The resulting OECTs exhibit an excellent combination of ultra-high transconductance of 86.4 mS, on/off ratio of 1.2 × 105, stretchability up to 50%, and high stretching stability up to 10000 cycles under 30% strain. We demonstrate that the all-gel OECTs can be used as stretchable pressure-sensitive electronic skins with a low detection limit for tactile perception of robotic hands. In addition, the all-gel OECTs can be applied as stretchable artificial synapses for neuromorphic simulation and highly sensitive stretchable gas sensors for simulating olfactory perception process and monitoring food quality. This work provides a general all-gel strategy toward high-performance flexible electronics.

Organic electrochemical transistors based on a conjugated diketopyrrolopyrrole-dialkoxybithiazole copolymer

Organic electrochemical transistors (OECTs) are promising for bioelectronics due to their ability to amplify signals by converting ionic signals into electronic signals. The performance of OECTs relies heavily on the interaction between electrolyte ions and organic mixed ionic-electronic conductors (OMIECs). We examined how different aqueous electrolytes affect OECTs based on an ethylene glycol-substituted diketopyrrolopyrrole-dialkoxybithiazole copolymer (PDPP-TEG-2Tz), which is primarily p-type and electrochemically doped with anions. Our findings show that compared to the small, highly hydrated chloride anion (Cl-), the larger hexafluorophosphate (PF6-) and bis(trifluoromethanesulfonyl)imide (TFSI-) anions result in a lower threshold voltage and a faster transient response. Cations like Li+, Na+, and K+ have little impact on OECT performance. Additionally, we created a complementary inverter using p-type PDPP-TEG-2Tz with an n-type naphthalene diimide-bithiophene copolymer (PNDI2C8TEG-2T), achieving a maximum voltage gain of 22.6 at a supply voltage of 0.7 V.

Compact Artificial Synapse-Neuron Module with Chemically Mediated Spiking Behaviors

Neuromorphic electronic devices mimicking the structure and functionality of biological counterparts have shown promising applications in biorealistic computing and bioelectronic interfaces. However, current neuromorphic systems comprising synapses and neurons typically exhibit complex integrated structures and lack chemically mediated characteristics, hindering them from direct biointerfacing. Here, we report a compact artificial synapse-neuron module (ASNM) by seamlessly integrating an organic electrochemical synaptic transistor and a niobium dioxide Mott memristor, showing the chemically mediated synaptic plasticity and highly stable spiking characteristics (>1010 cycles). Sodium ions and dopamine neurotransmitter induce the short-term and long-term plasticity of synaptic transistors, respectively, thus enabling temporary and long-term modulation of the ASNM's firing frequency in a bioplausible range (0-100 Hz). Furthermore, we construct a chemically mediated artificial neuromuscular system based on the ASNM, which could replicate the learning processes of a shooting basketball. These results demonstrate that our ASNM could achieve multiple biorealistic functionalities including sensing, synaptic plasticity, and spiking in a compact structure, providing a promising way for direct biointerfacing.

Thermal Processing Creates Water-Stable PEDOT:PSS Films for Bioelectronics

Organic mixed ionic-electronic conductors have emerged as a key material for the development of bioelectronic devices due to their soft mechanical properties, biocompatibility, and high volumetric capacitance. In particular, PEDOT:PSS has become a choice material because it is highly conductive, easily processible, and commercially available. However, PEDOT:PSS is dispersible in water, leading to delamination of films when exposed to biological environments. For this reason, chemical cross-linking agents such as (3-glycidyloxypropyl)trimethoxysilane (GOPS) are used to stabilize PEDOT:PSS films in water, but at the cost of decreased electrical performance. Here, it is shown that PEDOT:PSS thin films become water-stable by simply baking at high temperatures (>150 °C) for a short time (≈ 2 min). It is shown that heat-treated PEDOT:PSS films are as stable as their chemically-cross-linked counterparts, with their performance maintained for >20 days both in vitro and in vivo. The heat-treated films eliminate electrically insulating cross-linkers, resulting in a 3× increase in volumetric capacitance. Applying thermal energy using a focused femtosecond laser enables direct patterning of 3D PEDOT:PSS microstructures. The thermal treatment method is compatible with a wide range of substrates and is readily substituted into existing workflows for manufacturing devices, enabling its rapid adoption in the field of bioelectronics.

Bioinspired Electrolyte-Gated Organic Synaptic Transistors: From Fundamental Requirements to Applications

Rapid development of artificial intelligence requires the implementation of hardware systems with bioinspired parallel information processing and presentation and energy efficiency. Electrolyte-gated organic transistors (EGOTs) offer significant advantages as neuromorphic devices due to their ultra-low operation voltages, minimal hardwired connectivity, and similar operation environment as electrophysiology. Meanwhile, ionic-electronic coupling and the relatively low elastic moduli of organic channel materials make EGOTs suitable for interfacing with biology. This review presents an overview of the device architectures based on organic electrochemical transistors and organic field-effect transistors. Furthermore, we review the requirements of low energy consumption and tunable synaptic plasticity of EGOTs in emulating biological synapses and how they are affected by the organic materials, electrolyte, architecture, and operation mechanism. In addition, we summarize the basic operation principle of biological sensory systems and the recent progress of EGOTs as a building block in artificial systems. Finally, the current challenges and future development of the organic neuromorphic devices are discussed.

Organic Synaptic Transistors Based on C8-BTBT/PMMA/PbS QDs for UV to NIR Face Recognition Systems

Developing optoelectronic synaptic devices with low power consumption, broadband response, and biological compatibility is crucial to simulate the functions of optic nerve. Here, an organic synapse transistor based on C8-BTBT/PMMA/PbS quantum dots (PbS QDs) is fabricated, which has good stability, low power consumption (as low as 0.49 fJ per event under 800 nm near-infrared optical pulse), and broadband response from ultraviolet to near-infrared wavelengths. Based on the trap and release of photogenerated carriers by PbS QDs, a series of synaptic behaviors are simulated by the device. Furthermore, we use artificial neural network as the model to realize the recognition of facial feature image in the broad spectral range; the recognition rate reached 96.25% (350 nm ultraviolet), 92.14% (580 nm visible), and 90.03% (800 nm near-infrared). This work is beneficial for advancing the development of future artificial intelligence vision sensing.

Ion-Gel Gated Perovskite Field-Effect Transistors with Low Power Consumption and High Stability for Neuromorphic Applications

Ruddlesden-Popper (RP) tin halide perovskites (THPs), exemplified by PEA2SnI4, are promising two-dimensional semiconductors for optoelectronic applications, yet their field-effect transistors (FETs) often suffer from high operating voltages and stability issues. Addressing these challenges, we developed a novel approach for integrating ion gel dielectrics composed of PVDF-HFP and [EMIM+][TFSI-] with PEA2SnI4, achieving FETs with record-low operating voltages as low as 2 V. Additionally, by substituting PEA+ with BA+ in BA2SnI4 FETs, we achieve enhanced device stability, with these devices exhibiting prolonged functionality exceeding 100 days. Uniform performance was also observed across 30 randomly tested devices fabricated on a 2 inch silicon wafer. These FETs also demonstrated synaptic behavior with ultralow energy consumption (5 × 10-11 J per operation). Leveraging these advancements, we constructed artificial neural networks for item classification, achieving high accuracy (97%). Moreover, the energy consumption for a single training process based on ion-gel gated BA2SnI4 FETs is approximately 2 orders of magnitude lower than that of similar networks based on the NVIDIA GeForce RTX 4060 GPU. Our results highlight the potential of ion-gel gated BA2SnI4 FETs for low-power, high-stability applications, paving the way for the next generation of perovskite-based electronic and neuromorphic devices.

Mechano-gated iontronic piezomemristor for temporal-tactile neuromorphic plasticity

In bioneuronal systems, the synergistic interaction between mechanosensitive piezo channels and neuronal synapses can convert and transmit pressure signals into complex temporal plastic pulses with excitatory and inhibitory features. However, existing artificial tactile neuromorphic systems struggle to replicate the elaborate temporal plasticity observed between excitatory and inhibitory features in biological systems, which is critical for the biomimetic processing and memorizing of tactile information. Here we demonstrate a mechano-gated iontronic piezomemristor with programmable temporal-tactile plasticity. This system utilizes a bicontinuous phase-transition heterogel as a stiffness-governed iontronic mechanogate to achieve bidirectional piezoresistive signals, resulting in wide-span dynamic tactile sensing. By micro-integrating the mechanogate with an oscillatory iontronic memristor, it exhibits stiffness-induced bipolarized excitatory and inhibitory neuromorphics, thereby enabling the activation of temporal-tactile memory and learning functions (e.g., Bienenstock-Cooper-Munro and Hebbian learning rules). Owing to dynamic covalent bond network and iontronic features, reconfigurable tactile plasticity can be achieved. Importantly, bridging to bioneuronal interfaces, these systems possess the capacity to construct a biohybrid perception-actuation circuit. We anticipate that such temporal plastic piezomemristor devices for abiotic-biotic interfaces can serve as promising hardware systems for interfacing dynamic tactile behaviors into diverse neuromodulations.

Target-induced enzymatic cleavage cycle amplification reaction-gated organic photoelectrochemical transistor biosensor for rapid detection of okadaic acid

Okadaic acid (OA), a predominant toxic entity in Diarrhetic Shellfish Poisoning (DSP), carries substantial significance for both marine ecosystems and human well-being. The nascent organic photoelectrochemical transistor (OPECT) biosensor has emerged as a promising biometric methodology, poised to offer a fresh realm for the detection of marine biotoxins. In this work, a biosensor utilizing signal amplification based on Cd0.5Zn0.5S/ZnIn2S4 quantum dots (CZS/ZIS QDs) in OPECT was proposed for OA detection, where ZIS QDs were labeled on aptamer and a substantial quantity of QDs were generated via cyclic shearing facilitated through target-induced Exo I enzyme. Owing to the sensitizing influence of ZIS QDs on CZS, the photoelectric conversion efficiency was augmented, culminating in a notable anodic photocurrent upon exposure to light, thereby inducing a transformation in the channel state of the polymer poly(3,4-ethylenedioxythiophene): poly(styrene sulfonate) and consequently producing a remarkable modification in the channel current. The detection limit of the biosensor as low as 12.5 pM and a superior stability and specificity was confirmed, which also showed commendable outcomes in actual samples testing. Consequently, this study not only introduces a novel pathway for swift OA detection, but unveils a novel perspective for future expedited and convenient on-site detection of marine biotoxins.

Microscale droplet assembly enables biocompatible multifunctional modular iontronics

Hydrogel iontronic devices can emulate biological functions and communicate with living matter. But the fabrication of miniature, soft iontronic devices according to modular designs has not been achieved. In this work, we report the use of surfactant-supported assembly of freestanding microscale hydrogel droplets to construct various iontronic modules, circuits, and biointerfaces. Chemical modifications of silk fibroin produced a pair of oppositely charged hydrogels. Microscale assembly of various combinations of hydrogel droplets produced iontronic diodes, npn- and pnp-type transistors, and diverse reconfigurable logic gates. Through the incorporation of poly(amino acid)s, we have demonstrated a droplet-based synthetic synapse with ionic polymer-mediated long-term plasticity. Further, our iontronic transistor can serve as a biocompatible sensor to record electrophysiological signals from sheets of human cardiomyocytes, paving a way to the building of miniature bioiontronic systems.

Wafer-Scale Ag2S-Based Memristive Crossbar Arrays with Ultra-Low Switching-Energies Reaching Biological Synapses

Memristive crossbar arrays (MCAs) offer parallel data storage and processing for energy-efficient neuromorphic computing. However, most wafer-scale MCAs that are compatible with complementary metal-oxide-semiconductor (CMOS) technology still suffer from substantially larger energy consumption than biological synapses, due to the slow kinetics of forming conductive paths inside the memristive units. Here we report wafer-scale Ag2S-based MCAs realized using CMOS-compatible processes at temperatures below 160 °C. Ag2S electrolytes supply highly mobile Ag+ ions, and provide the Ag/Ag2S interface with low silver nucleation barrier to form silver filaments at low energy costs. By further enhancing Ag+ migration in Ag2S electrolytes via microstructure modulation, the integrated memristors exhibit a record low threshold of approximately - 0.1 V, and demonstrate ultra-low switching-energies reaching femtojoule values as observed in biological synapses. The low-temperature process also enables MCA integration on polyimide substrates for applications in flexible electronics. Moreover, the intrinsic nonidealities of the memristive units for deep learning can be compensated by employing an advanced training algorithm. An impressive accuracy of 92.6% in image recognition simulations is demonstrated with the MCAs after the compensation. The demonstrated MCAs provide a promising device option for neuromorphic computing with ultra-high energy-efficiency.

High-Endurance Long-Term Potentiation in Neuromorphic Organic Electrochemical Transistors by PEDOT:PSS Electrochemical Polymerization on the Gate Electrode

The brain exhibits extraordinary information processing capabilities thanks to neural networks that can operate in parallel with minimal energy consumption. Memory and learning require the creation of new neural networks through the long-term modification of the structure of the synapses, a phenomenon called long-term plasticity. Here, we use an organic electrochemical transistor to simulate long-term potentiation and depotentiation processes. Similarly to what happens in a synapse, the polymerization of the 3,4-ethylenedioxythiophene (EDOT) on the gate electrode modifies the structure of the device and boosts the ability of the gate potential to modify the conductivity of the channel. Operando AFM measurements were carried out to demonstrate the correlation between neuromorphic behavior and modification of the gate electrode. Long-term enhancement depends on both the number of pulses used and the gate potential, which generates long-term potentiation when a threshold of +0.7 V is overcome. Long-term depotentiation occurs by applying a +3.0 V potential and exploits the overoxidation of the deposited PEDOT:PSS. The induced states are stable for at least 2 months. The developed device shows very interesting characteristics in the field of neuromorphic electronics.

Open-shell Poly(3,4-dioxythiophene) Radical for Highly Efficient Photothermal Conversion

Open-shell organic radical semiconductor materials have received increasing attention in recent years due to their distinctive properties compared to the traditional materials with closed-shell singlet ground state. However, their poor chemical and photothermal stability in ambient conditions remains a significant challenge, primarily owing to their high reactivity with oxygen. Herein, a novel open-shell poly(3,4-dioxythiophene) radical PTTO2 is designed and readily synthesized for the first time using low-cost raw material via a straightforward BBr3-demethylation of the copolymer PTTOMe2 precursor. The open-shell character of PTTO2 is carefully studied and confirmed via the signal-silent 1H nuclear magnetic resonance spectrum, highly enhanced electron spin resonance signal compared with PTTOMe2, as well as the ultra-wide ultraviolet-visible-near nfraredUV-vis-NIR absorption and other technologies. Interestingly, the powder of PTTO2 exhibits an extraordinary absorption range spanning from 300 to 2500 nm and can reach 274 °C under the irradiation of 1.2 W cm-2, substantially higher than the 108 °C achieved by PTTOMe2. The low-cost PTTO2 stands as one of the best photothermal conversion materials among the pure organic photothermal materials and provides a new scaffold for the design of stable non-doped open-shell polymers.

Exploiting Spatial Ionic Dynamics in Solid-State Organic Electrochemical Transistors for Multi-Tactile Sensing and Processing

The human nervous system inspires the next generation of sensory and communication systems for robotics, human-machine interfaces (HMIs), biomedical applications, and artificial intelligence. Neuromorphic approaches address processing challenges; however, the vast number of sensors and their large-scale distribution complicate analog data manipulation. Conventional digital multiplexers are limited by complex circuit architecture and high supply voltage. Large sensory arrays further complicate wiring. An 'in-electrolyte computing' platform is presented by integrating organic electrochemical transistors (OECTs) with a solid-state polymer electrolyte. These devices use synapse-like signal transport and spatially dependent bulk ionic doping, achieving over 400 times modulation in channel conductance, allowing discrimination of locally random-access events without peripheral circuitry or address assignment. It demonstrates information processing from 12 tactile sensors with a single OECT output, showing clear advantages in circuit simplicity over existing all-electronic, all-digital implementations. This self-multiplexer platform offers exciting prospects for circuit-free integration with sensory arrays for high-quality, large-volume analog signal processing.

All-Inorganic CsPbBr3 Perovskite Planar-Type Memristors as Optoelectronic Synapses

Mimicking fundamental synaptic working principles with memristors contributes an essential step toward constructing brain-inspired, high-efficiency neuromorphic systems that surpass von Neumann system computers. Here, an electroforming-free planar-type memristor based on a CsPbBr3 single crystal is proposed and exhibits excellent resistive switching (RS) behaviors including stable endurance, ultralow power consumption, and fast switching speed. Furthermore, an optically tunable RS performance is demonstrated by manipulating irradiation intensity and wavelength. Optical analysis techniques such as steady-state photoluminescence and time-resolved photoluminescence are employed to investigate the distribution of Br ions and vacancies before and after quantitative polarization, describing migration dynamic processes to elucidate the RS mechanism. Importantly, a CsPbBr3 single crystal, as the optoelectronic synapse, shows unique potential to emulate photoenhanced synaptic functions such as excitatory postsynaptic current, paired-pulse facilitation, long-term potentiation/depression, spike-timing-dependent plasticity, spike-voltage-dependent plasticity, and learning-forgetting-relearning process with ultralow per synapse event energy consumption. A classical Pavlov's dog experiment is simulated with a combination of optical and electrical stimulation. Finally, pattern recognition with simulated artificial neural networks based on our synapse reached an accuracy of 93.11%. The special strategy and superior RS characteristics of optoelectronic synapses provide a pathway toward high-performance, energy-efficient neuromorphic electronics.

PEDOT:PSS-Based Prolonged Long-Term Decay Synaptic OECT with Proton-Permeable Material, Nafion

Poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS), a conductive polymer, has gained popularity as the channel layer in organic electrochemical transistors (OECTs) due to its high conductivity and straightforward processing. However, difficulties arise in controlling its conductivity through gate voltage, presenting a challenge. To address this issue, aromatic amidine base, diazabicyclo[4.3.0]non-5-ene (DBN), is used to stabilize the doping state of the PEDOT chain through a reliable chemical de-doping process. Furthermore, the addition of the proton-penetrable material Nafion to the PEDOT:PSS channel layer induces phase separation between the substances. By utilizing a solution containing both PEDOT:PSS and Nafion as the channel layer of OECTs, the efficiency of ion movement into the channel from the electrolyte is enhanced, resulting in improved OECT performance. The inclusion of Nafion in the OECTs' channel layer modifies ion movement dynamics, allowing for the adjustment of synaptic properties such as pulse-paired facilitation, memory level, short-term plasticity, and long-term plasticity. This research aims to introduce new possibilities in the field of neuromorphic computing and contribute to biomimetic technology through the enhancement of electronic component performance.

Toward a Brain-Neuromorphics Interface

Brain-computer interfaces (BCIs) that enable human-machine interaction have immense potential in restoring or augmenting human capabilities. Traditional BCIs are realized based on complementary metal-oxide-semiconductor (CMOS) technologies with complex, bulky, and low biocompatible circuits, and suffer with the low energy efficiency of the von Neumann architecture. The brain-neuromorphics interface (BNI) would offer a promising solution to advance the BCI technologies and shape the interactions with machineries. Neuromorphic devices and systems are able to provide substantial computation power with extremely high energy-efficiency by implementing in-materia computing such as in situ vector-matrix multiplication (VMM) and physical reservoir computing. Recent progresses on integrating neuromorphic components with sensing and/or actuating modules, give birth to the neuromorphic afferent nerve, efferent nerve, sensorimotor loop, and so on, which has advanced the technologies for future neurorobotics by achieving sophisticated sensorimotor capabilities as the biological system. With the development on the compact artificial spiking neuron and bioelectronic interfaces, the seamless communication between a BNI and a bioentity is reasonably expectable. In this review, the upcoming BNIs are profiled by introducing the brief history of neuromorphics, reviewing the recent progresses on related areas, and discussing the future advances and challenges that lie ahead.

Bioinspired iontronic synapse fibers for ultralow-power multiplexing neuromorphic sensorimotor textiles

Artificial neuromorphic devices can emulate dendric integration, axonal parallel transmission, along with superior energy efficiency in facilitating efficient information processing, offering enormous potential for wearable electronics. However, integrating such circuits into textiles to achieve biomimetic information perception, processing, and control motion feedback remains a formidable challenge. Here, we engineer a quasi-solid-state iontronic synapse fiber (ISF) comprising photoresponsive TiO2, ion storage Co-MoS2, and an ion transport layer. The resulting ISF achieves inherent short-term synaptic plasticity, femtojoule-range energy consumption, and the ability to transduce chemical/optical signals. Multiple ISFs are interwoven into a synthetic neural fabric, allowing the simultaneous propagation of distinct optical signals for transmitting parallel information. Importantly, IFSs with multiple input electrodes exhibit spatiotemporal information integration. As a proof of concept, a textile-based multiplexing neuromorphic sensorimotor system is constructed to connect synaptic fibers with artificial fiber muscles, enabling preneuronal sensing information integration, parallel transmission, and postneuronal information output to control the coordinated motor of fiber muscles. The proposed fiber system holds enormous promise in wearable electronics, soft robotics, and biomedical engineering.

Highly Stable Flexible Organic Electrochemical Transistors with Natural Rubber Latex Additives

Organic electrochemical transistors (OECTs) have attracted considerable interest in the context of wearable and implantable biosensors due to their remarkable signal amplification combined with seamless integration into biological systems. These properties underlie OECTs' potential utility across a range of bioelectronic applications. One of the main challenges to their practical applications is the mechanical limitation of PEDOT:PSS, the most typical conductive polymer used as a channel layer, when the OECTs are applied to implantable and stretchable bioelectronics. In this work, we address this critical issue by employing natural rubber latex (NRL) as an additive in PEDOT:PSS to improve flexibility and stretchability of the OECT channels. Although the inclusion of NRL leads to a decrease in transconductance, mainly due to a reduced carrier mobility from 0.3 to 0.1 cm2/V·s, the OECTs maintain satisfactory transconductance, exceeding 5 mS. Furthermore, it is demonstrated that the OECTs exhibit excellent mechanical stability while maintaining their performance even after 100 repetitive bending cycles. This work, therefore, suggests that the NRL/PEDOT:PSS composite film can be deployed for wearable/implantable applications, where high mechanical stability is needed. This finding opens up new avenues for practical use of OECTs in more robust and versatile wearable and implantable biosensors.

Bistable organic electrochemical transistors: enthalpy vs. entropy

Organic electrochemical transistors (OECTs) underpin a range of emerging technologies, from bioelectronics to neuromorphic computing, owing to their unique coupling of electronic and ionic charge carriers. In this context, various OECT systems exhibit significant hysteresis in their transfer curve, which is frequently leveraged to achieve non-volatility. Meanwhile, a general understanding of its physical origin is missing. Here, we introduce a thermodynamic framework that readily explains the emergence of bistable OECT operation via the interplay of enthalpy and entropy. We validate this model through temperature-resolved characterizations, material manipulation, and thermal imaging. Further, we reveal deviations from Boltzmann statistics for the subthreshold swing and reinterpret existing literature. Capitalizing on these findings, we finally demonstrate a single-OECT Schmitt trigger, thus compacting a multi-component circuit into a single device. These insights provide a fundamental advance for OECT physics and its application in non-conventional computing, where symmetry-breaking phenomena are pivotal to unlock new paradigms of information processing.

Recent Progress in Organic Electrochemical Transistor-Structured Biosensors

The continued advancement of organic electronic technology will establish organic electrochemical transistors as pivotal instruments in the field of biological detection. Here, we present a comprehensive review of the state-of-the-art technology and advancements in the use of organic electrochemical transistors as biosensors. This review provides an in-depth analysis of the diverse modification materials, methods, and mechanisms utilized in organic electrochemical transistor-structured biosensors (OETBs) for the selective detection of a wide range of target analyte encompassing electroactive species, electro-inactive species, and cancer cells. Recent advances in OETBs for use in sensing systems and wearable and implantable applications are also briefly introduced. Finally, challenges and opportunities in the field are discussed.

Advanced Neuromorphic Applications Enabled by Synaptic Ion-Gating Vertical Transistors

Bioinspired synaptic devices have shown great potential in artificial intelligence and neuromorphic electronics. Low energy consumption, multi-modal sensing and recording, and multifunctional integration are critical aspects limiting their applications. Recently, a new synaptic device architecture, the ion-gating vertical transistor (IGVT), has been successfully realized and timely applied to perform brain-like perception, such as artificial vision, touch, taste, and hearing. In this short time, IGVTs have already achieved faster data processing speeds and more promising memory capabilities than many conventional neuromorphic devices, even while operating at lower voltages and consuming less power. This work focuses on the cutting-edge progress of IGVT technology, from outstanding fabrication strategies to the design and realization of low-voltage multi-sensing IGVTs for artificial-synapse applications. The fundamental concepts of artificial synaptic IGVTs, such as signal processing, transduction, plasticity, and multi-stimulus perception are discussed comprehensively. The contribution draws special attention to the development and optimization of multi-modal flexible sensor technologies and presents a roadmap for future high-end theoretical and experimental advancements in neuromorphic research that are mostly achievable by the synaptic IGVTs.

Organic Mixed Ionic-Electronic Conductors for Bioelectronic Sensors: Materials and Operation Mechanisms

The field of organic mixed ionic-electronic conductors (OMIECs) has gained significant attention due to their ability to transport both electrons and ions, making them promising candidates for various applications. Initially focused on inorganic materials, the exploration of mixed conduction has expanded to organic materials, especially polymers, owing to their advantages such as solution processability, flexibility, and property tunability. OMIECs, particularly in the form of polymers, possess both electronic and ionic transport functionalities. This review provides an overview of OMIECs in various aspects covering mechanisms of charge transport including electronic transport, ionic transport, and ionic-electronic coupling, as well as conducting/semiconducting conjugated polymers and their applications in organic bioelectronics, including (multi)sensors, neuromorphic devices, and electrochromic devices. OMIECs show promise in organic bioelectronics due to their compatibility with biological systems and the ability to modulate electronic conduction and ionic transport, resembling the principles of biological systems. Organic electrochemical transistors (OECTs) based on OMIECs offer significant potential for bioelectronic applications, responding to external stimuli through modulation of ionic transport. An in-depth review of recent research achievements in organic bioelectronic applications using OMIECs, categorized based on physical and chemical stimuli as well as neuromorphic devices and circuit applications, is presented.

Predicting Blood Glucose Levels with Organic Neuromorphic Micro-Networks

Accurate glucose prediction is vital for diabetes management. Artificial intelligence and artificial neural networks (ANNs) are showing promising results for reliable glucose predictions, offering timely warnings for glucose fluctuations. The translation of these software-based ANNs into dedicated computing hardware opens a route toward automated insulin delivery systems ultimately enhancing the quality of life for diabetic patients. ANNs are transforming this field, potentially leading to implantable smart prediction devices and ultimately to a fully artificial pancreas. However, this transition presents several challenges, including the need for specialized, compact, lightweight, and low-power hardware. Organic polymer-based electronics are a promising solution as they have the ability to implement the behavior of neural networks, operate at low voltage, and possess key attributes like flexibility, stretchability, and biocompatibility. Here, the study focuses on implementing software-based neural networks for glucose prediction into hardware systems. How to minimize network requirements, downscale the architecture, and integrate the neural network with electrochemical neuromorphic organic devices, meeting the strict demands of smart implants for in-body computation of glucose prediction is investigated.

An organic brain-inspired platform with neurotransmitter closed-loop control, actuation and reinforcement learning

Organic neuromorphic platforms have recently received growing interest for the implementation and integration of artificial and hybrid neuronal networks. Here, achieving closed-loop and learning/training processes as in the human brain is still a major challenge especially exploiting time-dependent biosignalling such as neurotransmitter release. Here, we present an integrated organic platform capable of cooperating with standard silicon technologies, to achieve brain-inspired computing via adaptive synaptic potentiation and depression, in a closed-loop fashion. The microfabricated platform could be interfaced and control a robotic hand which ultimately was able to learn the grasping of differently sized objects, autonomously.

Air-Stable Perylene Diimide Trimer Material for N-Type Organic Electrochemical Transistors

A new method is reported to make air-stable n-type organic mixed ionic-electronic conductor (OMIEC) films for organic electrochemical transistors (OECTs) using a solution-processable small molecule helical perylene diimide trimer, hPDI[3]-C11. Alkyl side chains are attached to the conjugated core for processability and film making, which are then cleaved via thermal annealing. After the sidechains are removed, the hPDI[3] film becomes less hydrophobic, more ordered, and has a deeper lowest unoccupied molecular orbital (LUMO). These features provide improved ionic transport, greater electronic mobility, and increased stability in air and in aqueous solution. Subsequently, hPDI[3]-H is used as the active material in OECTs and a device with a transconductance of 44 mS, volumetric capacitance of ≈250 F cm-3, µC* value of 1 F cm-1 V-1 s-1, and excellent stability (> 5 weeks) is demonstrated. As proof of their practical applications, a hPDI[3]-H-based OECTs as a glucose sensor and electrochemical inverter is utilized. The approach of side chain removal after film formation charts a path to a wide range of molecular semiconductors to be used as stable, mixed ionic-electronic conductors.

Graphene-Based Artificial Dendrites for Bio-Inspired Learning in Spiking Neuromorphic Systems

Analog neuromorphic computing systems emulate the parallelism and connectivity of the human brain, promising greater expressivity and energy efficiency compared to those of digital systems. Though many devices have emerged as candidates for artificial neurons and artificial synapses, there have been few device candidates for artificial dendrites. In this work, we report on biocompatible graphene-based artificial dendrites (GrADs) that can implement dendritic processing. By using a dual side-gate configuration, current applied through a Nafion membrane can be used to control device conductance across a trilayer graphene channel, showing spatiotemporal responses of leaky recurrent, alpha, and Gaussian dendritic potentials. The devices can be variably connected to enable higher-order neuronal responses, and we show through data-driven spiking neural network simulations that spiking activity is reduced by ≤15% without accuracy loss while low-frequency operation is stabilized. This positions the GrADs as strong candidates for energy efficient bio-interfaced spiking neural networks.

Aerosol Doping System for Microscale Seamless p-n Patterning of Carbon Nanotube Films

Carbon nanotube (CNT) films are extensively researched as a promising material for wearable thermoelectric generators (TEGs) owing to their good flexibility and high thermoelectric conversion ability. Miniaturizing a pair of p- and n-type thermocouples and increasing the number of repeating elements can effectively increase the power of TEGs. However, conventional p-n patterning methods, such as dipping and printing, have a coarse resolution at the submillimeter level, thereby limiting the miniaturization rate. This study developed an aerosol doping system as a fine n-doping method. A dopant aerosol with a <3 μm diameter was formed through ultrasonic nebulization and air separation, while n-doping was achieved by exposing the CNT film to the dopant aerosol. Microscale p-n patterning of 1 μm was achieved through exposure using small-sized aerosols at an exceptionally slow rate of 3 Å/min. This resolution is 100 times higher than those of conventional p-n patterning methods. The developed aerosol doping system for CNTs can also be used on organic semiconductor materials, such as PEDOT/PSS and perovskite materials. Therefore, it has the potential to significantly impact the realization of Internet of Things (IoT) terminals, such as flexible TEGs, transistors, and solar cells.

One-Shot Remote Integration of Macromolecular Synaptic Elements on a Chip for Ultrathin Flexible Neural Network System

The field of biomimetic electronics that mimic synaptic functions has expanded significantly to overcome the limitations of the von Neumann bottleneck. However, the scaling down of the technology has led to an increasingly intricate manufacturing process. To address the issue, this work presents a one-shot integrable electropolymerization (OSIEP) method with remote controllability for the deposition of synaptic elements on a chip by exploiting bipolar electrochemistry. Condensing synthesis, deposition, and patterning into a single fabrication step is achieved by combining alternating-current voltage superimposed on direct-current voltage-bipolar electropolymerization and a specially designed dual source/drain bipolar electrodes. As a result, uniform 6 × 5 arrays of poly(3,4-ethylenedioxythiophene) channels are successfully fabricated on flexible ultrathin parylene substrates in one-shot process. The channels exhibited highly uniform characteristics and are directly used as electrochemical synaptic transistor with synaptic plasticity over 100 s. The synaptic transistors have demonstrated promising performance in an artificial neural network (NN) simulation, achieving a high recognition accuracy of 95.20%. Additionally, the array of synaptic transistor is easily reconfigured to a multi-gate synaptic circuit to implement the principles of operant conditioning. These results provide a compelling fabrication strategy for realizing cost-effective and disposable NN systems with high integration density.

Understanding asymmetric switching times in accumulation mode organic electrochemical transistors

Understanding the factors underpinning device switching times is crucial for the implementation of organic electrochemical transistors in neuromorphic computing, bioelectronics and real-time sensing applications. Existing models of device operation cannot explain the experimental observations that turn-off times are generally much faster than turn-on times in accumulation mode organic electrochemical transistors. Here, using operando optical microscopy, we image the local doping level of the transistor channel and show that turn-on occurs in two stages-propagation of a doping front, followed by uniform doping-while turn-off occurs in one stage. We attribute the faster turn-off to a combination of engineering as well as physical and chemical factors including channel geometry, differences in doping and dedoping kinetics and the phenomena of carrier-density-dependent mobility. We show that ion transport limits the operation speed in our devices. Our study provides insights into the kinetics of organic electrochemical transistors and guidelines for engineering faster organic electrochemical transistors.

All-Photolithography Fabrication of Ion-Gated Flexible Organic Transistor Array for Multimode Neuromorphic Computing

Organic ion-gated transistors (OIGTs) demonstrate commendable performance for versatile neuromorphic systems. However, due to the fragility of organic materials to organic solvents, efficient and reliable all-photolithography methods for scalable manufacturing of high-density OIGT arrays with multimode neuromorphic functions are still missing, especially when all active layers are patterned in high-density. Here, a flexible high-density (9662 devices per cm2) OIGT array with high yield and minimal device-to-device variation is fabricated by a modified all-photolithography method. The unencapsulated flexible array can withstand 1000 times' bending at a radius of 1 mm, and 3 months' storage test in air, without obvious performance degradation. More interesting, the OIGTs can be configured between volatile and nonvolatile modes, suitable for constructing reservoir computing systems to achieve high accuracy in classifying handwritten digits with low training costs. This work proposes a promising design of organic and flexible electronics for affordable neuromorphic systems, encompassing both array and algorithm aspects.

Graphene oxide-DNA/graphene oxide-PDDA sandwiched membranes with neuromorphic function

The behavior of polyelectrolytes in confined spaces has direct relevance to the protein mediated ion transport in living organisms. In this paper, we govern lithium chloride transport by the interface provided by polyelectrolytes, polycation, poly(diallyldimethylammonium chloride) (PDDA) and, polyanion, double stranded deoxyribonucleic acid (dsDNA), in confined graphene oxide (GO) membranes. Polyelectrolyte-GO interfaces demonstrate neuromorphic functions that were successfully applied with nanochannel ion interactions contributed, resulting in ion memory effects. Excitatory and inhibitory post-synaptic currents were tuned continuously as the number of pulses applied increased accordingly, increasing decay times. Furthermore, we demonstrated the short-term memory of a trained vs untrained device in computation. On account of its simple and safe production along with its robustness and stability, we anticipate our device to be a low dimensional building block for arrays to embed artificial neural networks in hardware for neuromorphic computing. Additionally, incorporating such devices with sensing and actuating parts for a complete feedback loop produces robotics with its own ability to learn by modifying actuation based on sensing data.

Oxide Ionic Neuro-Transistors for Bio-inspired Computing

Current computing systems rely on Boolean logic and von Neumann architecture, where computing cells are based on high-speed electron-conducting complementary metal-oxide-semiconductor (CMOS) transistors. In contrast, ions play an essential role in biological neural computing. Compared with CMOS units, the synapse/neuron computing speed is much lower, but the human brain performs much better in many tasks such as pattern recognition and decision-making. Recently, ionic dynamics in oxide electrolyte-gated transistors have attracted increasing attention in the field of neuromorphic computing, which is more similar to the computing modality in the biological brain. In this review article, we start with the introduction of some ionic processes in biological brain computing. Then, electrolyte-gated ionic transistors, especially oxide ionic transistors, are briefly introduced. Later, we review the state-of-the-art progress in oxide electrolyte-gated transistors for ionic neuromorphic computing including dynamic synaptic plasticity emulation, spatiotemporal information processing, and artificial sensory neuron function implementation. Finally, we will address the current challenges and offer recommendations along with potential research directions.

Spiers Memorial Lecture: Challenges and prospects in organic photonics and electronics

While a substantial amount of research activity has been conducted in fields related to organic photonics and electronics, including the development of devices such as organic field-effect transistors, organic photovoltaics, and organic light-emitting diodes for applications encompassing organic thermoelectrics, organic batteries, excitonic organic materials for photochemical and optoelectronic applications, and organic thermoelectrics, this perspective review will primarily concentrate on the emerging and rapidly expanding domain of organic bioelectronics and neuromorphics. Here we present the most recent research findings on organic transistors capable of sensing biological biomarkers down at the single-molecule level (i.e., oncoproteins, genomes, etc.) for the early diagnosis of pathological states and to mimic biological synapses, paving the way to neuromorphic applications that surpass the limitations of the traditional von Neumann computing architecture. Both organic bioelectronics and neuromorphics exhibit several challenges but will revolutionize human life, considering the development of artificial synapses to counteract neurodegenerative disorders and the development of ultrasensitive biosensors for the early diagnosis of cancer to prevent its development. Moreover, organic bioelectronics for sensing applications have also triggered the development of several wearable, flexible and stretchable biodevices for continuous biomarker monitoring.

Technology and Integration Roadmap for Optoelectronic Memristor

Optoelectronic memristors (OMs) have emerged as a promising optoelectronic Neuromorphic computing paradigm, opening up new opportunities for neurosynaptic devices and optoelectronic systems. These OMs possess a range of desirable features including minimal crosstalk, high bandwidth, low power consumption, zero latency, and the ability to replicate crucial neurological functions such as vision and optical memory. By incorporating large-scale parallel synaptic structures, OMs are anticipated to greatly enhance high-performance and low-power in-memory computing, effectively overcoming the limitations of the von Neumann bottleneck. However, progress in this field necessitates a comprehensive understanding of suitable structures and techniques for integrating low-dimensional materials into optoelectronic integrated circuit platforms. This review aims to offer a comprehensive overview of the fundamental performance, mechanisms, design of structures, applications, and integration roadmap of optoelectronic synaptic memristors. By establishing connections between materials, multilayer optoelectronic memristor units, and monolithic optoelectronic integrated circuits, this review seeks to provide insights into emerging technologies and future prospects that are expected to drive innovation and widespread adoption in the near future.

A hybrid transistor with transcriptionally controlled computation and plasticity

Organic electrochemical transistors (OECTs) are ideal devices for translating biological signals into electrical readouts and have applications in bioelectronics, biosensing, and neuromorphic computing. Despite their potential, developing programmable and modular methods for living systems to interface with OECTs has proven challenging. Here we describe hybrid OECTs containing the model electroactive bacterium Shewanella oneidensis that enable the transduction of biological computations to electrical responses. Specifically, we fabricated planar p-type OECTs and demonstrated that channel de-doping is driven by extracellular electron transfer (EET) from S. oneidensis. Leveraging this mechanistic understanding and our ability to control EET flux via transcriptional regulation, we used plasmid-based Boolean logic gates to translate biological computation into current changes within the OECT. Finally, we demonstrated EET-driven changes to OECT synaptic plasticity. This work enables fundamental EET studies and OECT-based biosensing and biocomputing systems with genetically controllable and modular design elements.

2D MXene electrochemical transistors

The solid-state field-effect transistor, FET, and its theories were paramount in the discovery and studies of graphene. In the past two decades another transistor based on conducting polymers, called organic electrochemical transistor (ECT), has been developed and largely studied. The main difference between organic ECTs and FETs is the mode and extent of channel doping; while in FETs the channel only has surface doping through dipoles, the mixed ionic-electronic conductivity of the channel material in organic ECTs enables bulk electrochemical doping. As a result, organic ECTs maximize conductance modulation at the expense of speed. To date ECTs have been based on conducting polymers, but here we show that MXenes, a class of 2D materials beyond graphene, enable the realization of electrochemical transistors (ECTs). We show that the formulas for organic ECTs can be applied to these 2D ECTs and used to extract parameters like mobility. These MXene ECTs have high transconductance values but low on-off ratios. We further show that conductance switching data measured using ECT, in combination with other in situ-ex situ electrochemical measurements, is a powerful tool for correlating the change in conductance to that of the redox state, to our knowledge, this is the first report of this important correlation for MXene films. 2D ECTs can draw great inspiration and theoretical tools from the field of organic ECTs and have the potential to considerably extend the capabilities of transistors beyond those of conducting polymer ECTs, with added properties such as extreme heat resistance, tolerance for solvents, and higher conductivity for both electrons and ions than conducting polymers.

Wearable and Implantable Cortisol-Sensing Electronics for Stress Monitoring

Cortisol is a steroid hormone that is released from the body in response to stress. Although a moderate level of cortisol secretion can help the body maintain homeostasis, excessive secretion can cause various diseases, such as depression and anxiety. Conventional methods for cortisol measurement undergo procedures that limit continuous monitoring, typically collecting samples of bodily fluids, followed by separate analysis in a laboratory setting that takes several hours. Thus, recent studies demonstrate wearable, miniaturized sensors integrated with electronic modules that enable wireless real-time analysis. Here, the primary focus is on wearable and implantable electronic devices that continuously measure cortisol concentration. Diverse types of cortisol-sensing techniques, such as antibody-, DNA-aptamer-, and molecularly imprinted polymer-based sensors, as well as wearable and implantable devices that aim to continuously monitor cortisol in a minimally invasive fashion are discussed. In addition to the cortisol monitors that directly measure stress levels, other schemes that indirectly measure stress, such as electrophysiological signals and sweat are also summarized. Finally, the challenges and future directions in stress monitoring and management electronics are reviewed.

Selenophene Substitution Enabled High-Performance n-Type Polymeric Mixed Ionic-Electronic Conductors for Organic Electrochemical Transistors and Glucose Sensors

High-performance n-type polymeric mixed ionic-electronic conductors (PMIECs) are essential for realizing organic electrochemical transistors (OECTs)-based low-power complementary circuits and biosensors, but their development still remains a great challenge. Herein, by devising two novel n-type polymers (f-BTI2g-SVSCN and f-BSeI2g-SVSCN) containing varying selenophene contents together with their thiophene-based counterpart as the control, it is demonstrated that gradually increasing selenophene loading in polymer backbones can simultaneously yield lowered lowest unoccupied molecular orbital levels, boosted charge-transport properties, and improved ion-uptake capabilities. Therefore, a remarkable volumetric capacitance (C*) of 387.2 F cm-3 and a state-of-the-art OECT electron mobility (µe,OECT ) of 0.48 cm2 V-1 s-1 are synchronously achieved for f-BSeI2g-SVSCN having the highest selenophene content, yielding an unprecedented geometry-normalized transconductance (gm,norm ) of 71.4 S cm-1 and record figure of merit (µC*) value of 191.2 F cm-1 V-1 s-1 for n-type OECTs. Thanks to such excellent performance of f-BSeI2g-SVSCN-based OECTs, a glucose sensor with a remarkably low detection limit of 10 nMm and decent selectivity is further implemented, demonstrating the power of selenophene substitution strategy in enabling high-performance n-type PMIECs for biosensing applications.

Two-Dimensional Conjugated Polymers: a New Choice For Organic Thin-Film Transistors

Organic thin-film transistors (OTFTs) as a vital component among transistors have shown great potential in smart sensing, flexible displays, and bionics due to their flexibility, biocompatibility and customizable chemical structures. Even though linear conjugated polymer semiconductors are common for constructing channel materials of OTFTs, advanced materials with high charge carrier mobility, tunable band structure, robust stability, and clear structure-property relationship are indispensable for propelling the evolution of OTFTs. Two-dimensional conjugated polymers (2DCPs), featured with conjugated lattice, tailorable skeletons, and functional porous structures, match aforementioned criteria closely. In this review, we firstly introduce the synthesis of 2DCP thin films, focusing on their characteristics compatible with the channels of OTFTs. Subsequently, the physics and operating mechanisms of OTFTs and the applications of 2DCPs in OTFTs are summarized in detail. Finally, the outlook and perspective in the field of OTFTs using 2DCPs are provided as well.

Chameleon-Inspired Colorimetric Sensors for Real-Time Detections with Humidity

In recent decades, vapor sensors have gained substantial attention for their crucial roles in environmental monitoring and pharmaceutical applications. Herein, we introduce a chameleon-inspired colorimetric (CIC) sensor, detailing its design, fabrication, and versatile applications. The sensor seamlessly combines a PEDOT:PSS vapor sensor with a colorimetric display, using thermochromic liquid crystal (TLC). We further explore the electrical characteristics of the CIC sensor when doped with ethylene glycol (EG) and polyvinyl alcohol (PVA). Comparative analyses of resistance change rates for different weight ratios of EG and PVA provide insights into fine-tuning the sensor's responsiveness to varying humidity levels. The CIC sensor's proficiency in measuring ambient humidity is investigated under a voltage input as small as 2.6 V, capturing resistance change rates and colorimetric shifts at relative humidity (RH) levels ranging from 20% to 90%. Notably, the sensor exhibits distinct resistance sensitivities of 9.7 mΩ (0.02% ∆R/R0)/%RH, 0.5 Ω (0.86% ∆R/R0)/%RH, and 5.7 Ω (9.68% ∆R/R0)/%RH at RH 20% to 30%, RH 30% to 80%, and RH 80% to 90%, respectively. Additionally, a linear temperature change is observed with a sensitivity of -0.04 °C/%RH. The sensor also demonstrates a colorimetric temperature sensitivity of -82,036 K/%RH at RH 20% to 30% and -514 K/%RH at RH 30% to 90%, per captured image. Furthermore, real-time measurements of ethanol vapor with varying concentrations showcase the sensor's applicability in gas sensing applications. Overall, we present a comprehensive exploration of the CIC sensor, emphasizing its design flexibility, electrical characteristics, and diverse sensing capabilities. The sensor's potential applications extend to real-time environmental monitoring, highlighting its promising role in various gas sensing fields.

van der Waals 2D transition metal dichalcogenide/organic hybridized heterostructures: recent breakthroughs and emerging prospects of the device

The near-atomic thickness and organic molecular systems, including organic semiconductors and polymer-enabled hybrid heterostructures, of two-dimensional transition metal dichalcogenides (2D-TMDs) can modulate their optoelectronic and transport properties outstandingly. In this review, the current understanding and mechanism of the most recent and significant breakthrough of novel interlayer exciton emission and its modulation by harnessing the band energy alignment between TMDs and organic semiconductors in a TMD/organic (TMDO) hybrid heterostructure are demonstrated. The review encompasses up-to-date device demonstrations, including field-effect transistors, detectors, phototransistors, and photo-switchable superlattices. An exploration of distinct traits in 2D-TMDs and organic semiconductors delves into the applications of TMDO hybrid heterostructures. This review provides insights into the synthesis of 2D-TMDs and organic layers, covering fabrication techniques and challenges. Band bending and charge transfer via band energy alignment are explored from both structural and molecular orbital perspectives. The progress in emission modulation, including charge transfer, energy transfer, doping, defect healing, and phase engineering, is presented. The recent advancements in 2D-TMDO-based optoelectronic synaptic devices, including various 2D-TMDs and organic materials for neuromorphic applications are discussed. The section assesses their compatibility for synaptic devices, revisits the operating principles, and highlights the recent device demonstrations. Existing challenges and potential solutions are discussed. Finally, the review concludes by outlining the current challenges that span from synthesis intricacies to device applications, and by offering an outlook on the evolving field of emerging TMDO heterostructures.

Hysteresis in Organic Electrochemical Transistors: Distinction of Capacitive and Inductive Effects

Organic electrochemical transistors (OECTs) are effective devices for neuromorphic applications, bioelectronics, and sensors. Numerous reports in the literature show persistent dynamical hysteresis effects in the current-voltage curves, attributed to the slow ionic charging of the channel under the applied gate voltage. Here we present a model that considers the dominant electrical and electrochemical operation aspects of the device based on a thermodynamic function of ion insertion. We identify the volume capacitance as the derivative of the thermodynamic function, associated with the chemical capacitance of the ionic-electronic film. The dynamical analysis shows that the system contains both capacitive and inductive hysteresis effects. The inductor response, which can be observed in impedance spectroscopy, is associated with ionic diffusion from the surface to fill the channel up to the equilibrium value. The model reveals the multiple dynamical features associated with specific kinetic relaxations that control the transient and impedance response of the OCET.

Artificial Neuron Devices

Efforts to design devices emulating complex cognitive abilities and response processes of biological systems have long been a coveted goal. Recent advancements in flexible electronics, mirroring human tissue's mechanical properties, hold significant promise. Artificial neuron devices, hinging on flexible artificial synapses, bioinspired sensors, and actuators, are meticulously engineered to mimic the biological systems. However, this field is in its infancy, requiring substantial groundwork to achieve autonomous systems with intelligent feedback, adaptability, and tangible problem-solving capabilities. This review provides a comprehensive overview of recent advancements in artificial neuron devices. It starts with fundamental principles of artificial synaptic devices and explores artificial sensory systems, integrating artificial synapses and bioinspired sensors to replicate all five human senses. A systematic presentation of artificial nervous systems follows, designed to emulate fundamental human nervous system functions. The review also discusses potential applications and outlines existing challenges, offering insights into future prospects. We aim for this review to illuminate the burgeoning field of artificial neuron devices, inspiring further innovation in this captivating area of research.

Stretchable, skin‐conformable neuromorphic system for tactile sensory recognizing and encoding

Expanding wearable technologies to artificial tactile perception will be of significance for intelligent human–machine interface, as neuromorphic sensing devices are promising candidates due to their low energy consumption and highly effective operating properties. Skin‐compatible and conformable features are required for the purpose of realizing wearable artificial tactile perception. Here, we report an intrinsically stretchable, skin‐integrated neuromorphic system with triboelectric nanogenerators as tactile sensing and organic electrochemical transistors as information processing. The integrated system provides desired sensing, synaptic, and mechanical characteristics, such as sensitive response (~0.04 kPa−1) to low‐pressure, short‐ and long‐term synaptic plasticity, great switching endurance (>10 000 pulses), symmetric weight update, together with high stretchability of 100% strain. With neural encoding, demonstrations are capable of recognizing, extracting, and encoding features of tactile information. This work provides a feasible approach to wearable, skin‐conformable neuromorphic sensing system with great application prospects in intelligent robotics and replacement prosthetics.

Cascade-heterogated biphasic gel iontronics for electronic-to-multi-ionic signal transmission

Currently, electronics and iontronics in abiotic-biotic systems can only use electrons and single-species ions as unitary signal carriers. Thus, a mechanism of gating transmission for multiple biosignals in such devices is needed to match and modulate complex aqueous-phase biological systems. Here we report the use of cascade-heterogated biphasic gel iontronics to achieve diverse electronic-to-multi-ionic signal transmission. The cascade-heterogated property determined the transfer free energy barriers experienced by ions and ionic hydration-dehydration states under an electric potential field, fundamentally enhancing the distinction of cross-interface transmission between different ions by several orders of magnitude. Such heterogated or chemical-heterogated iontronics with programmable features can be coupled with multi-ion cross-interface mobilities for hierarchical and selective cross-stage signal transmission. We expect that such iontronics would be ideal candidates for a variety of biotechnology applications.

Neuromorphic sensing of biomolecules covalently immobilised on polydimethyl glutarimide

Polydimethyl glutarimide (PMGI) layers with sub-micron thicknesses have been modified in a 2.5 kV Ar plasma immersion ion implantation (PIII) process to introduce free radical covalent binding sites. The surface roughness of the PMGI increased after the PIII treatment but no through-layer defects were observed. When applied to the treated PMGI, horseradish peroxidase (HRP) enzyme remained bound to the surface after extended immersion in sodium dodecyl sulfate solution (SDS). Hence, covalent binding between the activated surface and enzyme was confirmed. This covalent binding was achieved up to 24-h after the PIII process. The treated PMGI was then incorporated as a gate dielectric layer within a lateral three-terminal electrolyte-gated device. The device output characteristics resembled those of post-synaptic outputs; as successive (pre-synaptic) voltage pulses were applied to the gate, paired pulse depression and spike rate dependent plasticity were observed in the source-drain (post-synaptic) current. These characteristics were altered by the presence of HRP immobilised on the plasma-modified PMGI gate dielectric layer thus providing readout detection. These results and preliminary device characteristics show the potential for the plasma functionalized PMGI as a sensitive and reproducible biosensing technology.