An Evolvable Organic Electrochemical Transistor for Neuromorphic Applications

Porous Semiconducting Polymers Enable High-Performance Electrochemical Transistors

Organic polymer electrochemical transistors (OECTs) are of great interest for flexible electronics and bioelectronics applications owing to their high transconductance and low operating voltage. However, efficient OECT operation must delicately balance the seemingly incompatible materials optimizations of redox chemistry, active layer electronic transport, and ion penetration/transport. The latter characteristics are particularly challenging since most high-mobility semiconducting polymers are hydrophobic, which hinders efficient ion penetration, hence limiting OECT performance. Here, the properties and OECT response of a series of dense and porous semiconducting polymer films are compared, the latter fabricated via a facile breath figure approach. This methodology enables fast ion doping, high transconductance (up to 364 S cm^-1 ), and a low subthreshold swing for the hydrophobic polymers DPPDTT and P3HT, rivalling or exceeding the metrics of the relatively hydrophilic polymer, Pg2T-T. Furthermore, the porous morphology also enhances the transconductance of hydrophilic polymers, offering a general strategy for fabricating high-performance electrochemical transistors.

Polaron Delocalization in Donor-Acceptor Polymers and its Impact on Organic Electrochemical Transistor Performance

Donor-acceptor (D-A) polymers are promising materials for organic electrochemical transistors (OECTs), as they minimize detrimental faradaic side-reactions during OECT operation, yet their steady-state OECT performance still lags far behind their all-donor counterparts. We report three D-A polymers based on the diketopyrrolopyrrole unit that afford OECT performances similar to those of all-donor polymers, hence representing a significant improvement to the previously developed D-A copolymers. In addition to improved OECT performance, DFT simulations of the polymers and their respective hole polarons also reveal a positive correlation between hole polaron delocalization and steady-state OECT performance, providing new insights into the design of OECT materials. Importantly, we demonstrate how polaron delocalization can be tuned directly at the molecular level by selection of the building blocks comprising the polymers' conjugated backbone, thus paving the way for the development of even higher performing OECT polymers.

Influence of Side Chains on the n-Type Organic Electrochemical Transistor Performance

n-Type (electron transporting) polymers can make suitable interfaces to transduce biological events that involve the generation of electrons. However, n-type polymers that are stable when electrochemically doped in aqueous media are relatively scarce, and the performance of the existing ones lags behind their p-type (hole conducting) counterparts. Here, we report a new family of donor-acceptor-type polymers based on a naphthalene-1,4,5,8-tetracarboxylic-diimide-bi-thiophene (NDI-T2) backbone where the NDI unit always bears an ethylene glycol (EG) side chain. We study how small variations in the side chains tethered to the acceptor as well as the donor unit affect the performance of the polymer films in the state-of-the-art bioelectronic device, the organic electrochemical transistor (OECT). First, we find that substitution of the T2 core with an electron-withdrawing group (i.e., methoxy) or an EG side chain leads to ambipolar charge transport properties and causes significant changes in film microstructure, which overall impairs the n-type OECT performance. We thus show that the best n-type OECT performer is the polymer that has no substitution on the T2 unit. Next, we evaluate the distance of the oxygen from the NDI unit as a design parameter by varying the length of the carbon spacer placed between the EG unit and the backbone. We find that the distance of the EG from the backbone affects the film order and crystallinity, and thus, the electron mobility. Consequently, our work reports the best-performing NDI-T2-based n-type OECT material to date, i.e., the polymer without the T2 substitution and bearing a six-carbon spacer between the EG and the NDI units. Our work provides new guidelines for the side-chain engineering of n-type polymers for OECTs and insights on the structure-performance relationships for mixed ionic-electronic conductors, crucial for devices where the film operates at the aqueous electrolyte interface.

Competing memristors for brain-inspired computing

The expeditious development of information technology has led to the rise of artificial intelligence (AI). However, conventional computing systems are prone to volatility, high power consumption, and even delay between the processor and memory, which is referred to as the von Neumann bottleneck, in implementing AI. To address these issues, memristor-based neuromorphic computing systems inspired by the human brain have been proposed. A memristor can store numerous values by changing its resistance and emulate artificial synapses in brain-inspired computing. Here, we introduce six types of memristors classified according to their operation mechanisms: ionic migration, phase change, spin, ferroelectricity, intercalation, and ionic gating. We review how memristor-based neuromorphic computing can learn, infer, and even create, using various artificial neural networks. Finally, the challenges and perspectives in the competing memristor technology for neuromorphic computing systems are discussed.

Synaptic Iontronic Devices for Brain-Mimicking Functions: Fundamentals and Applications

Inspired by the information transmission mechanism in the central nervous systems of life, synapse-mimicking devices have been designed and fabricated for the purpose of breaking the bottleneck of von Neumann architecture and realizing the construction of effective hardware-based artificial intelligence. In this case, synaptic iontronic devices, dealing with current information with ions instead of electrons, have attracted enormous scientific interests owing to their unique characteristics provided by ions, such as the designability of charge carriers and the diversity of chemical regulation. Herein, the basic conception, working mechanism, performance metrics, and advanced applications of synaptic iontronic devices based on three-terminal transistors and two-terminal memristors are systematically reviewed and comprehensively discussed. This Review provides a prospect on how to realize artificial synaptic functions based on the regulation of ions and raises a series of further challenges unsolved in this area.

Two-dimensional materials for next-generation computing technologies

Rapid digital technology advancement has resulted in a tremendous increase in computing tasks imposing stringent energy efficiency and area efficiency requirements on next-generation computing. To meet the growing data-driven demand, in-memory computing and transistor-based computing have emerged as potent technologies for the implementation of matrix and logic computing. However, to fulfil the future computing requirements new materials are urgently needed to complement the existing Si complementary metal-oxide-semiconductor technology and new technologies must be developed to enable further diversification of electronics and their applications. The abundance and rich variety of electronic properties of two-dimensional materials have endowed them with the potential to enhance computing energy efficiency while enabling continued device downscaling to a feature size below 5 nm. In this Review, from the perspective of matrix and logic computing, we discuss the opportunities, progress and challenges of integrating two-dimensional materials with in-memory computing and transistor-based computing technologies.

Water stable molecular n-doping produces organic electrochemical transistors with high transconductance and record stability

From established to emergent technologies, doping plays a crucial role in all semiconducting devices. Doping could, theoretically, be an excellent technique for improving repressively low transconductances in n-type organic electrochemical transistors – critical for advancing logic circuits for bioelectronic and neuromorphic technologies. However, the technical challenge is extreme: n-doped polymers are unstable in electrochemical transistor operating environments, air and water (electrolyte). Here, the first demonstration of doping in electron transporting organic electrochemical transistors is reported. The ammonium salt tetra-n-butylammonium fluoride is simply admixed with the conjugated polymer poly(N,N’-bis(7-glycol)-naphthalene-1,4,5,8-bis(dicarboximide)-co-2,2’-bithiophene-co-N,N’-bis(2-octyldodecyl)-naphthalene-1,4,5,8-bis(dicarboximide), and found to act as a simultaneous molecular dopant and morphology-additive. The combined effects enhance the n-type transconductance with improved channel capacitance and mobility. Furthermore, operational and shelf-life stability measurements showcase the first example of water-stable n-doping in a polymer. Overall, the results set a precedent for doping/additives to impact organic electrochemical transistors as powerfully as they have in other semiconducting devices.

Improving electron transport and stability of n-type organic electrochemical transistors (OECTs) is required to realize a commercially-viable technology for bioelectronics applications. Here, the authors report water-stable doped n-type OECTs with enhanced transconductance and record stability.

The Design of 3D-Interface Architecture in an Ultralow-Power, Electrospun Single-Fiber Synaptic Transistor for Neuromorphic Computing

Synaptic electronics is a new technology for developing functional electronic devices that can mimic the structure and functions of biological counterparts. It has broad application prospects in wearable computing chips, human-machine interfaces, and neuron prostheses. These types of applications require synaptic devices with ultralow energy consumption as the effective energy supply for wearable electronics, which is still very difficult. Here, artificial synapse emulation is demonstrated by solid-ion gated organic field-effect transistors (OFETs) with a 3D-interface conducting channel for ultralow-power synaptic simulation. The basic features of the artificial synapse, excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and high-pass filtering, are successfully realized. Furthermore, the single-fiber based artificial synapse can be operated by an ultralow presynaptic spike down to -0.5 mV with an ultralow reading voltage at -0.1 mV due to the large contact surface between the ionic electrolyte and fiber-like semiconducting channel. Therefore, the ultralow energy consumption at one spike of the artificial synapse can be realized as low as ≈3.9 fJ, which provides great potential in a low-power integrated synaptic circuit.

Modulation of Binary Neuroplasticity in a Heterojunction-Based Ambipolar Transistor

To keep pace with the upcoming big-data era, the development of a device-level neuromorphic system with highly efficient computing paradigms is underway with numerous attempts. Synaptic transistors based on an all-solution processing method have received growing interest as building blocks for neuromorphic computing based on spikes. Here, we propose and experimentally demonstrated the dual operation mode in poly{2,2-(2,5-bis(2-octyldodecyl)-3,6-dioxo-2,3,5,6-tetrahydropyrrolo[3,4-c]pyrrole-1,4-diyl)dithieno[3,2-b]thiophene-5,5-diyl-alt-thiophen-2,5-diyl}(PDPPBTT)/ZnO junction-based synaptic transistor from ambipolar charge-trapping mechanism to analog the spiking interfere with synaptic plasticity. The heterojunction formed by PDPPBTT and ZnO layers serves as the basis for hole-enhancement and electron-enhancement modes of the synaptic transistor. Distinctive synaptic responses of paired-pulse facilitation (PPF) and paired-pulse depression (PPD) were configured to achieve the training/recognition function for digit image patterns at the device-to-system level. The experimental results indicate the potential application of the ambipolar transistor in future neuromorphic intelligent systems.

Nanosystems, Edge Computing, and the Next Generation Computing Systems

It is widely recognized that nanoscience and nanotechnology and their subfields, such as nanophotonics, nanoelectronics, and nanomechanics, have had a tremendous impact on recent advances in sensing, imaging, and communication, with notable developments, including novel transistors and processor architectures. For example, in addition to being supremely fast, optical and photonic components and devices are capable of operating across multiple orders of magnitude length, power, and spectral scales, encompassing the range from macroscopic device sizes and kW energies to atomic domains and single-photon energies. The extreme versatility of the associated electromagnetic phenomena and applications, both classical and quantum, are therefore highly appealing to the rapidly evolving computing and communication realms, where innovations in both hardware and software are necessary to meet the growing speed and memory requirements. Development of all-optical components, photonic chips, interconnects, and processors will bring the speed of light, photon coherence properties, field confinement and enhancement, information-carrying capacity, and the broad spectrum of light into the high-performance computing, the internet of things, and industries related to cloud, fog, and recently edge computing. Conversely, owing to their extraordinary properties, 0D, 1D, and 2D materials are being explored as a physical basis for the next generation of logic components and processors. Carbon nanotubes, for example, have been recently used to create a new processor beyond proof of principle. These developments, in conjunction with neuromorphic and quantum computing, are envisioned to maintain the growth of computing power beyond the projected plateau for silicon technology. We survey the qualitative figures of merit of technologies of current interest for the next generation computing with an emphasis on edge computing.

On the Role of Contact Resistance and Electrode Modification in Organic Electrochemical Transistors

Contact resistance is renowned for its unfavorable impact on transistor performance. Despite its notoriety, the nature of contact resistance in organic electrochemical transistors (OECTs) remains unclear. Here, by investigating the role of contact resistance in n-type OECTs, the first demonstration of source/drain-electrode surface modification for achieving state-of-the-art n-type OECTs is reported. Specifically, thiol-based self-assembled monolayers (SAMs), 4-methylbenzenethiol (MBT) and pentafluorobenzenethiol (PFBT), are used to investigate contact resistance in n-type accumulation-mode OECTs made from the hydrophilic copolymer P-90, where the deliberate functionalization of the gold source/drain electrodes decreases and increases the energetic mismatch at the electrode/semiconductor interface, respectively. Although MBT treatment is found to increase the transconductance three-fold, contact resistance is not found to be the dominant factor governing OECT performance. Additional morphology and surface energy investigations show that increased performance comes from SAM-enhanced source/drain electrode surface energy, which improves wetting, semiconductor/metal interface quality, and semiconductor morphology at the electrode and channel. Overall, contact resistance in n-type OECTs is investigated, whilst identifying source/drain electrode treatment as a useful device engineering strategy for achieving state of the art n-type OECTs.

Reversible uptake and release of sodium ions in layered SnS2-reduced graphene oxide composites for neuromorphic devices

With the advent of brain-inspired computing for complex data processing, emerging nonvolatile memories have been widely studied to develop neuromorphic devices for pattern recognition and deep learning. However, the devices still suffer from limitations such as nonlinearity and large write noise because they adopt a stochastic switching approach. Here, we suggest a biomimetic three-terminal electrochemical artificial synapse that is operated by a conductance change in response to intercalation of sodium (Na+) ions into a layered SnS2-reduced graphene oxide (RGO) composite channel. SnS2-RGO can reversibly uptake and release Na+ ions, so the conductance of the channel in artificial synapse can be controlled effectively and thereby it can emulate essential synaptic functions including short-term plasticity, spatiotemporal signal processing, and transition from short-term to long-term plasticity. The artificial synapse also shows linear and symmetric potentiation/depression with low cycle-to-cycle variation; these responses could improve the write linearity and reduce the write noise of devices. This study demonstrates the feasibility of next-generation neuromorphic memory using ion-based electrochemical devices that can mimic biological synapses with the migration of Na+ ions.