Ultrathin All-Solid-State MoS2-Based Electrolyte Gated Synaptic Transistor with Tunable Organic-Inorganic Hybrid Film.

Electrolyte-gated synaptic transistors (EGSTs) have attracted considerable attention as synaptic devices owing to their adjustable conductance, low power consumption, and multi-state storage capabilities. To demonstrate high-density EGST arrays, 2D materials are recommended owing to their excellent electrical properties and ultrathin profile. However, widespread implementation of 2D-based EGSTs has challenges in achieving large-area channel growth and finding compatible nanoscale solid electrolytes. This study demonstrates large-scale process-compatible, all-solid-state EGSTs utilizing molybdenum disulfide (MoS2) channels grown through chemical vapor deposition (CVD) and sub-30 nm organic-inorganic hybrid electrolyte polymers synthesized via initiated chemical vapor deposition (iCVD). The iCVD technique enables precise modulation of the hydroxyl group density in the hybrid matrix, allowing the modulation of proton conduction, resulting in adjustable synaptic performance. By leveraging the tunable iCVD-based hybrid electrolyte, the fabricated EGSTs achieve remarkable attributes: a wide on/off ratio of 109, state retention exceeding 103, and linear conductance updates. Additionally, the device exhibits endurance surpassing 5 × 104 cycles, while maintaining a low energy consumption of 200 fJ/spike. To evaluate the practicality of these EGSTs, a subset of devices is employed in system-level simulations of MNIST handwritten digit recognition, yielding a recognition rate of 93.2%.

Flash-Thermal Shock Synthesis of Single Atoms in Ambient Air.

Single-atom catalysts feature interesting catalytic activity toward applications that rely on surface reactions such as electrochemical energy storage, catalysis, and gas sensors. However, conventional synthetic approaches for such catalysts require extended periods of high-temperature annealing in vacuum systems, limiting their throughput and increasing their production cost. Herein, we report an ultrafast flash-thermal shock (FTS)-induced annealing technique (temperature > 2850 °C, <10 ms duration, and ramping/cooling rates of ∼105 K/s) that operates in an ambient-air environment to prepare single-atom-stabilized N-doped graphene. Melamine is utilized as an N-doping source to provide thermodynamically favorable metal-nitrogen bonding sites, resulting in a uniform and high-density atomic distribution of single metal atoms. To demonstrate the practical utility of the single-atom-stabilized N-doped graphene produced by the FTS method, we showcased their chemiresistive gas sensing capabilities and electrocatalytic activities. Overall, the air-ambient, ultrafast, and versatile (e.g., Co, Ni, Pt, and Co-Ni dual metal) FTS method provides a general route for high-throughput, large area, and vacuum-free manufacturing of single-atom catalysts.

Flash-Thermal Shock Synthesis of High-Entropy Alloys Toward High-Performance Water Splitting.

High-entropy alloys (HEAs) provide unprecedented physicochemical properties over unary nanoparticles (NPs). According to the conventional alloying guideline (Hume-Rothery rule), however, only size-and-structure similar elements can be mixed, limiting the possible combinations of alloying elements. Recently, it has been reported that based on carbon thermal shocks (CTS) in a vacuum atmosphere at high temperature, ultrafast heating/cooling rates and high-entropy environment play a critical role in the synthesis of HEAs, ruling out the possibility of phase separation. Since the CTS requires conducting supports, the Joule-heating efficiencies rely on the carbon qualities, featuring difficulties in uniform heating along the large area. This work proposes a photo-thermal approach as an alternative and innovative synthetic method that is compatible with ambient air, large-area, remote process, and free of materials selection. Single flash irradiation on carbon nanofibers induced momentary high-temperature annealing (>1800 °C within 20 ms duration, and ramping/cooling rates >104 K s-1 ) to successfully decorate HEA NPs up to nine elements with excellent compatibility for large-scale synthesis (6.0 × 6.0 cm2 of carbon nanofiber paper). To demonstrate their feasibility toward applications, senary HEA NPs (PtIrFeNiCoCe) are designed and screened, showing high activity (ηoverall = 777 mV) and excellent stability (>5000 cycles) at the water splitting, including hydrogen evolution reactions and oxygen evolution reactions.

Imidazole-based artificial synapses for neuromorphic computing: a cluster-type conductive filament via controllable nanocluster nucleation.

Memristive synapses based on conductive bridging RAMs (CBRAMs) utilize a switching layer having low binding energy with active metals for excellent analog conductance modulation, but the resulting unstable conductive filaments cause fluctuation and drift of the conductance. This tunability-stability dilemma makes it difficult to implement practical neuromorphic computing. A novel method is proposed to enhance the stability and controllability of conductive filaments by introducing imidazole groups that boost the nucleation of Cu nanoclusters in the ultrathin polymer switching layer through the initiated chemical vapor deposition (iCVD) process. It is confirmed that conductive filaments based on nanoclusters with specific gaps are generated in the copolymer medium using this method. Furthermore, by modulating the tunneling gaps, an ultra-wide conductance range of analog tunable conductive filaments is achieved from several hundreds of nS to a few mS with a sub-1 V driving voltage. Through this, both reliable and stable analog switching are achieved with low cycle-to-cycle and device-to-device weight update variations and separable state retention with 32 states. This approach paves the way for the extension of state availability in synaptic devices to overcome the tunability-stability dilemma, which is essential for the synaptic elements in neuromorphic systems.

A Highly Reliable Molybdenum Disulfide-Based Synaptic Memristor Using a Copper Migration-Controlled Structure.

Memristors are drawing attention as neuromorphic hardware components because of their non-volatility and analog programmability. In particular, electrochemical metallization (ECM) memristors are extensively researched because of their linear conductance controllability. Two-dimensional materials as switching medium of ECM memristors give advantages of fast speed, low power consumption, and high switching uniformity. However, the multistate retention in the switching conductance range for the long-term reliable neuromorphic system has not been achieved using two-dimensional materials-based ECM memristors. In this study, the copper migration-controlled ECM memristor showing excellent multistate retention characteristics in the switching conductance range using molybdenum disulfide (MoS2 ) and aluminum oxide (Al2 O3 ) is proposed. The fabricated device exhibits gradual resistive switching with low switching voltage (<0.5 V), uniform switching (σ/µ âˆ¼ 0.07), and a wide switching range (>12). Importantly, excellent reliabilities with robustness to cycling stress and retention over 104 s for more than 5-bit states in the switching conductance range are achieved. Moreover, the contribution of the Al2 O3 layer to the retention characteristic is investigated through filament morphology observation using transmission electron microscopy (TEM) and copper migration component analysis. This study provides a practical approach to developing highly reliable memristors with exceptional switching performance.

Preventing Vanishing Gradient Problem of Hardware Neuromorphic System by Implementing Imidazole-Based Memristive ReLU Activation Neuron.

With advances in artificial intelligent services, brain-inspired neuromorphic systems with synaptic devices are recently attracting significant interest to circumvent the von Neumann bottleneck. However, the increasing trend of deep neural network parameters causes huge power consumption and large area overhead of a nonlinear neuron electronic circuit, and it incurs a vanishing gradient problem. Here, a memristor-based compact and energy-efficient neuron device is presented to implement a rectifying linear unit (ReLU) activation function. To emulate the volatile and gradual switching of the ReLU function, a copolymer memristor with a hybrid structure is proposed using a copolymer/inorganic bilayer. The functional copolymer film developed by introducing imidazole functional groups enables the formation of nanocluster-type pseudo-conductive filaments by boosting the nucleation of Cu nanoclusters, causing gradual switching. The ReLU neuron device is successfully demonstrated by integrating the memristor with amorphous InGaZnO thin-film transistors, and achieves 0.5 pJ of energy consumption based on sub-10 µA operation current and high-speed switching of 650 ns. Furthermore, device-to-system-level simulation using neuron devices on the MNIST dataset demonstrates that the vanishing gradient problem is effectively resolved by five-layer deep neural networks. The proposed neuron device will enable the implementation of high-density and energy-efficient hardware neuromorphic systems.

Ultrafast Ambient-Air Exsolution on Metal Oxide via Momentary Photothermal Effect.

The process of exsolution for the synthesis of strongly anchored metal nanoparticles (NPs) on host oxide lattices has been proposed as a promising strategy for designing robust catalyst-support composite systems. However, because conventional exsolution processes occur in harsh reducing environments at high temperatures for long periods of time, the choice of support materials and dopant metals are limited to those with inherently high thermal and chemical stability. Herein, we report the exsolution of a series of noble metal catalysts (Pt, Rh, and Ir) from metal oxide nanofibers (WO3 NFs) supports in an entirely ambient environment induced by intense pulsed light (IPL)-derived momentary photothermal treatment (>1000 °C). Since the exsolution process spans an extremely short period of time (<20 ms), unwanted structural artifacts such as decreased surface area and phase transition of the support materials are effectively suppressed. At the same time, exsolved NPs (<5 nm) with uniform size distributions could successfully be formed. To prove the practical utility of exsolved catalytic NPs functionalized on WO3 NFs, the chemiresistive gas sensing characteristics of exsolved Pt-decorated WO3 NFs were analyzed, exhibiting high durability (>200 cyclic exposures), enhanced response (Rair/Rgas > 800 @ 1 ppm/350 °C), and selectivity toward H2S target gas. Altogether, we successfully demonstrated that ultrafast exsolution within a few milliseconds could be induced in ambient conditions using the IPL-derived momentary photothermal treatment and contributed to expanding the practical viability of the exsolution-based synthetic approaches for the production of highly stable catalyst systems.

Spatially isolated neutral excitons via clusters on trilayer MoS2.

In spite of having a large exciton binding energy, two-dimensional (2D) transition metal dichalcogenides (TMDs) are limited as light-emitting materials because the spectral weight of neutral excitons decreases exponentially with increasing the excitation density. That is, neutral excitons easily transfer to trions, and exciton-exciton annihilation (EEA) occurs due to the strengthening of exciton kinetic energy in the layered structure. In here, we come up with an isolated neutral exciton system, maintaining its high spectral weight when the carrier density increased, which is achieved via MoS2 clusters on a MoS2 trilayer directly synthesized by metal-organic chemical vapor deposition (MOCVD). While increasing the excitation density, trions are decomposed by spatial confinement at the saturation level of its full width at half maximum (FWHM), and simultaneously the spectral weight of neutral excitons restarts to increase. Furthermore, we reveal the causality relationship between trions and B excitons, providing a keen insight into organic interactions among radiative recombination processes in 2D TMDs.

Colorimetric Dye-Loaded Nanofiber Yarn: Eye-Readable and Weavable Gas Sensing Platform.

The colorimetric gas sensor offers an opportunity for the simple and rapid detection of toxic gaseous substances based on visually discernible changes in the color of the sensing material. In particular, the accurate detection of trace amounts of certain biomarkers in a patient's breath provides substantial clues regarding specific diseases, for example, hydrogen sulfide (H2S) for halitosis and ammonia (NH3) for kidney disorder. However, conventional colorimetric sensors often lack the sensitivity, selectivity, detection limit, and mass-productivity, impeding their commercialization. Herein, we report an inexpensive route for the meter-scale synthesis of a colorimetric sensor based on a composite nanofiber yarn that is chemically functionalized with an ionic liquid as an effective H2S adsorbent and lead acetate as a colorimetric dye. As an eye-readable and weavable sensing platform, the single-strand yarn exhibits enhanced sensitivity supported by its high surface area and well-developed porosity to detect the breath biomarker (1 ppm of H2S). Alternatively, the yarn loaded with lead iodide dyes could reversibly detect NH3 gas molecules in the ppm-level, demonstrating the facile extensibility. Finally, we demonstrated that the freestanding yarns could be sewn into patterned textiles for the fabrication of a wearable toxic gas alarm system with a visual output.

Conductive-bridging random-access memories for emerging neuromorphic computing.

With the increasing utilisation of artificial intelligence, there is a renewed demand for the development of novel neuromorphic computing owing to the drawbacks of the existing computing paradigm based on the von Neumann architecture. Extensive studies have been performed on memristors as their electrical nature is similar to those of biological synapses and neurons. However, most hardware-based artificial neural networks (ANNs) have been developed with oxide-based memristors owing to their high compatibility with mature complementary metal-oxide-semiconductor (CMOS) processes. Considering the advantages of conductive-bridging random-access memories (CBRAMs), such as their high scalability, high on-off current with a wide dynamic range, and low off-current, over oxide-based memristors, extensive studies on CBRAMs are required. In this review, the basics of operation of CBRAMs are examined in detail, from the formation of metal nanoclusters to filament bridging. Additionally, state-of-the-art experimental demonstrations of CBRAM-based artificial synapses and neurons are presented. Finally, CBRAM-based ANNs are discussed, including deep neural networks and spiking neural networks, along with other emerging computing applications. This review is expected to pave the way toward further development of large-scale CBRAM array systems.

Low-Thermal-Budget Doping of 2D Materials in Ambient Air Exemplified by Synthesis of Boron-Doped Reduced Graphene Oxide.

Graphene oxide (GO) doping and reduction allow for physicochemical property modification to suit practical application needs. Herein, the challenge of simultaneous low-thermal-budget heteroatom doping of GO and its reduction in ambient air is addressed through the synthesis of B-doped reduced GO (B@rGO) by flash irradiation of boric acid loaded onto a GO support with intense pulsed light (IPL). The effects of light power and number of shots on the in-depth sequential doping and reduction mechanisms are investigated by ex situ X-ray photoelectron spectroscopy and direct millisecond-scale temperature measurements (temperature >1600 °C, < 10-millisecond duration, ramping rate of 5.3 × 105 °C s-1). Single-flash IPL allows the large-scale synthesis of substantially doped B@rGO (≈3.60 at% B) to be realized with a thermal budget 106-fold lower than that of conventional thermal methods, and the prepared material with abundant B active sites is employed for highly sensitive and selective room-temperature NO2 sensing. Thus, this work showcases the great potential of optical annealing for millisecond-scale ultrafast reduction and heteroatom doping of GO in ambient air, which allows the tuning of multiple physicochemical GO properties.

TFT Channel Materials for Display Applications: From Amorphous Silicon to Transition Metal Dichalcogenides.

As the need for super-high-resolution displays with various form factors has increased, it has become necessary to produce high-performance thin-film transistors (TFTs) that enable faster switching and higher current driving of each pixel in the display. Over the past few decades, hydrogenated amorphous silicon (a-Si:H) has been widely utilized as a TFT channel material. More recently, to meet the requirement of new types of displays such as organic light-emitting diode displays, and also to overcome the performance and reliability issues of a-Si:H, low-temperature polycrystalline silicon and amorphous oxide semiconductors have partly replaced a-Si:H channel materials. Basic material properties and device structures of TFTs in commercial displays are explored, and then the potential of atomically thin layered transition metal dichalcogenides as next-generation channel materials is discussed.

Polymer Analog Memristive Synapse with Atomic-Scale Conductive Filament for Flexible Neuromorphic Computing System.

With the advent of artificial intelligence (AI), memristors have received significant interest as a synaptic building block for neuromorphic systems, where each synaptic memristor should operate in an analog fashion, exhibiting multilevel accessible conductance states. Here, we demonstrate that the transition of the operation mode in poly(1,3,5-trivinyl-1,3,5-trimethyl cyclotrisiloxane) (pV3D3)-based flexible memristor from conventional binary to synaptic analog switching can be achieved simply by reducing the size of the formed filament. With the quantized conductance states observed in the flexible pV3D3 memristor, analog potentiation and depression characteristics of the memristive synapse are obtained through the growth of atomically thin Cu filament and lateral dissolution of the filament via dominant electric field effect, respectively. The face classification capability of our memristor is evaluated via simulation using an artificial neural network consisting of pV3D3 memristor synapses. These results will encourage the development of soft neuromorphic intelligent systems.

Sub-Parts-per-Million Hydrogen Sulfide Colorimetric Sensor: Lead Acetate Anchored Nanofibers toward Halitosis Diagnosis.

Lead(II) acetate [Pb(Ac)2] reacts with hydrogen sulfide to form colored brownish precipitates of lead sulfide. Thus far, in order to detect leakage of H2S gas in industrial sectors, Pb(Ac)2 has been used as an indicator in the form of test papers with a detection limit only as low as 5 ppm. Diagnosis of halitosis by exhaled breath needs sensors able to detect down to 1 ppm of H2S gas. In this work, high surface area and porous Pb(Ac)2 anchored nanofibers (NFs) that overcome limitations of the conventional Pb(Ac)2-based H2S sensor are successfully achieved. First, lead(II) acetate, which melts at 75 °C, and polyacrylonitrile (PAN) polymer are mixed and stirred in dimethylformamide (DMF) solvent at 85 °C, enabling uniform dispersion of fine liquid droplets in the electrospinning solution. During the subsequent electrospinning, Pb(Ac)2 anchored NFs are obtained, providing an ideal nanostructure with high thermal stability against particle aggregation, numerous reactions sites, and enhanced diffusion of H2S into the three-dimensional (3D)-networked NF web. This newly obtained sensing material can detect down to 400 ppb of H2S at a relative humidity of 90%, exhibiting high potential feasibility as a high-performance colorimetric sensor platform for diagnosis of halitosis.