Monomer-mixed hole transport layers for improving hole injection of quantum dot light-emitting diodes.

Quantum-dot light-emitting diodes (QLEDs) are promising components for next-generation displays and related applications. However, their performance is critically limited by inherent hole-injection barrier caused by deep highest-occupied molecular orbital levels of quantum dots. Herein, we present an effective method for enhancing the performance of QLEDs by incorporating a monomer (TCTA or mCP) into hole-transport layers (HTL). The impact of different monomer concentrations on the characteristics of QLEDs were investigated. The results indicate that sufficient monomer concentrations improve the current efficiency and power efficiency. The increased hole current using monomer-mixed HTL suggests that our method holds considerable potential for high-performance QLEDs.

Photoresponse Analysis of All-Inkjet-Printed Single-Walled Carbon Nanotube Thin-Film Transistors for Flexible Light-Insensitive Transparent Circuit Applications.

We report daylight-stable, transparent, and flexible single-walled carbon nanotube thin-film transistors (SWCNT TFTs) using an all-inkjet printing process. Although most of the previous reports classified SWCNT TFTs as photodetectors, we demonstrated that SWCNT films actually show two different types of photoresponses depending on the power levels of light sources. The electrical characteristics of SWCNT TFTs show no significant change under daily illumination conditions such as halogen lamps and sunlight, while under high-power laser illumination, they change as reported in the previous results. In addition, the low-temperature solution process of the SWCNT with its one-dimensional nature allows us to realize highly transparent and flexible TFTs and logic circuits on plastic substrates. Our result will provide new insights into utilizing SWCNT TFTs for light-insensitive transparent and flexible electronic applications.

Crack-inducing Strain Sensor Array using Inkjet-Printed Silver Thin Film for Underplate and Off-centered Force Sensing Applications.

The change in resistance upon bending in metal films as thick as 1 mm used for underpanel force touch applications is limited by the low sensitivity, thus requiring high-performance readout circuitry. In this paper, we report inkjet-printed silver thin films having crack-inducing underlayers, which further increases the sensitivity of their resistance changes under deformation. This allows for detecting weak vertical forces even through the plates (force-receiving layer), such as 0.4 or 1.2 mm thick polyethylene terephthalate or 0.4 mm thick glass. The underplate sensors will detect a force level as low as 10 gf, which corresponds to the amount of force required for fingerprint recognition. Furthermore, such highly sensitive strain sensors can potentially solve the inaccuracy issue of wearable devices, which can occur when misplaced sensors detect relatively weak biosignals, such as heart rate and blood pressure. The sensor detects the accurate pulse patterns of the wrist artery even though it is off-centered from the artery by 6 mm or larger. The crack-based strain sensor and its usage as a hidden underplate force sensing device will create various wearable and user-machine interface applications.

Nonpatterned Soft Piezoresistive Films with Filamentous Conduction Paths for Mimicking Multiple-Resolution Receptors of Human Skin.

Soft pressure sensors play key roles as input devices of electronic skin (E-skin) to imitate real human skin. For efficient data acquisition according to stimulus types such as detailed pressure images or macroscopic strength of stimuli, soft pressure sensors can have variable spatial resolution, just like the uneven spatial distribution of pressure-sensing receptors on the human body. However, previous methods on soft pressure sensors cannot achieve such tunability of spatial resolution because their sensor materials and read-out electrodes need to be elaborately patterned for a specific sensor density. Here, we report a universal soft pressure-sensitive platform based on anisotropically self-assembled ferromagnetic particles embedded in elastomer matrices whose spatial resolution can be facilely tuned. Various spatial densities of pressure-sensing receptors of human body parts can be implemented by simply sandwiching the film between soft electrodes with different pitches. Since the anisotropically aligned nickel particles form independent filamentous conductive paths, the pressure sensors show spatial sensing ability without crosstalk, whose spatial resolution up to 100 dpi can be achieved from a single platform. The sensor array shows a wide dynamic range capable of detecting various pressure levels, such as liquid drops (∼30 Pa) and plantar (∼300 kPa) pressures. Our universal soft pressure-sensing platform would be a key enabling technology for actually imitating the receptor systems of human skin in robot and biomedical applications.

Silent Speech Recognition with Strain Sensors and Deep Learning Analysis of Directional Facial Muscle Movement.

Silent communication based on biosignals from facial muscle requires accurate detection of its directional movement and thus optimally positioning minimum numbers of sensors for higher accuracy of speech recognition with a minimal person-to-person variation. So far, previous approaches based on electromyogram or pressure sensors are ineffective in detecting the directional movement of facial muscles. Therefore, in this study, high-performance strain sensors are used for separately detecting x- and y-axis strain. Directional strain distribution data of facial muscle is obtained by applying three-dimensional digital image correlation. Deep learning analysis is utilized for identifying optimal positions of directional strain sensors. The recognition system with four directional strain sensors conformably attached to the face shows silent vowel recognition with 85.24% accuracy and even 76.95% for completely nonobserved subjects. These results show that detection of the directional strain distribution at the optimal facial points will be the key enabling technology for highly accurate silent speech recognition.

Recent progress in strain-engineered elastic platforms for stretchable thin-film devices.

Strain-engineered elastic platforms that can efficiently distribute mechanical stress under deformation offer adjustable mechanical compliance for stretchable electronic systems. By fully exploiting strain-free regions that are favourable for fabricating thin-film devices and interconnecting with reliably stretchable conductors, various electronic systems can be integrated onto stretchable platforms with the assistance of strain engineering strategies. Over the last decade, applications of multifunctional stretchable thin-film devices simultaneously exhibiting superior electrical and mechanical performance have been demonstrated, shedding light on the realization of further reliable human-machine interfaces. This review highlights recent developments in enabling technologies for strain-engineered elastic platforms. In particular, representative approaches to realize strain-engineered substrates and stretchable interconnects in island-bridge configurations are introduced from the perspective of the material homogeneity and structural design of the substrate. State-of-the-art achievements in sophisticated stretchable electronic devices on strain-engineered elastic platforms are also presented, such as stretchable sensors, energy devices, thin-film transistors, and displays, and then, the challenges and outlook are discussed.

Electronic Skin Based on a Cellulose/Carbon Nanotube Fiber Network for Large-Area 3D Touch and Real-Time 3D Surface Scanning.

Electronic skin (E-skin) based on tactile sensors has great significance in next-generation electronics such as biomedical application and artificial intelligence that requires interaction with humans. To mimic the properties of human skin, high flexibility, excellent sensing capability, and sufficient spatial resolution through high-level sensor integration are required. Here, we report a highly sensitive pressure sensor matrix based on a piezoresistive cellulose/single-walled carbon nanotube-entangled fiber network, which forms its own porous structure enabling a superior pressure sensor with a high sensitivity (9.097 kPa-1), a fast response speed (<2 ms), and orders of magnitude detection range with a detection limit of 1 Pa. Furthermore, the remarkable device expandability based on the ease of patterning and scalability allows easy implementation of a large-area pressure sensor matrix which has 2304 (48 × 48) pixels. Combined with a real-time pressure distribution monitoring system, a flexible 3D touch sensor that simultaneously displays plane coordinates and pressure information and a scanning device that detects the morphology of the soft body 3D surface are successfully demonstrated.

Wafer-scale carbon nanotube network transistors.

Highly purified, preseparated semiconducting carbon nanotubes (CNTs) hold great potential for high-performance CNT network transistors due to their high electrical conductivity, high mechanical strength, and room-temperature processing compatibility. In this paper, we report our recent progress on CNT network transistors integrated on an 8-inch wafer. We observe that the key device performance parameters of CNT network transistors at various locations on an 8-inch wafer are highly uniform and that the device yield is impressive. Therefore, this work validates a promising path toward mass production and will make a significant contribution to the future field of wafer-scale CNT electronics.

Directly drawn top-gate semiconducting carbon nanotube thin-film transistors and complementary inverters.

As the emerging demand for electronic devices that are simple, cost effective and capable of rapid fabrication has increased, novel fabrication techniques for designing and manufacturing such devices have attracted remarkable research interest. One method for prototyping these electronic devices is to draw them using a handwriting tool that is commonly available. In this work, we demonstrate a transistor and complementary logic inverter that are directly drawn using a brush and that are based on solution-based materials such as semiconducting carbon nanotubes (CNTs), silver ink and paste, and cross-linked poly(4-vinylphenol) (cPVP). The directly drawn CNT thin-film transistor (TFT) has p-type behavior due to the adsorption of oxygen and moisture, a high current on/off ratio (approximately 103), and a low operating voltage. By employing a solution-based chemical doping treatment with an amine-rich polymer, polyethyleneimine (PEI), that has strong electron-donating ability, the drawn p-type CNT-TFT is successfully converted to an n-type CNT-TFT. Therefore, we fabricate a drawn complementary logic inverter consisting of the p-type CNT-TFT and PEI-treated n-type CNT-TFT and evaluate its electrical performance.

Binarized Neural Network with Silicon Nanosheet Synaptic Transistors for Supervised Pattern Classification.

In the biological neural network, the learning process is achieved through massively parallel synaptic connections between neurons that can be adjusted in an analog manner. Recent developments in emerging synaptic devices and their networks can emulate the functionality of a biological neural network, which will be the fundamental building block for a neuromorphic computing architecture. However, on-chip implementation of a large-scale artificial neural network is still very challenging due to unreliable analog weight modulation in current synaptic device technology. Here, we demonstrate a binarized neural network (BNN) based on a gate-all-around silicon nanosheet synaptic transistor, where reliable digital-type weight modulation can contribute to improve the sustainability of the entire network. BNN is applied to three proof-of-concept examples: (1) handwritten digit classification (MNIST dataset), (2) face image classification (Yale dataset), and (3) experimental 3 × 3 binary pattern classifications using an integrated synaptic transistor network (total 9 × 9 × 2 162 cells) through a supervised online training procedure. The results consolidate the feasibility of binarized neural networks and pave the way toward building a reliable and large-scale artificial neural network by using more advanced conventional digital device technologies.

Flexible carbon nanotube Schottky diode and its integrated circuit applications.

Carbon nanotubes (CNTs), a low-dimensional material currently popular in industry and academia, are promising candidates for addressing the limits of existing semiconductors. In particular, CNTs are attractive candidates for flexible electronic materials due to their excellent flexibility and potential applications. In this work, we demonstrate a flexible CNT Schottky diode based on highly purified, preseparated, solution-processed 99% semiconducting CNTs and an integrated circuit application using the CNT Schottky diodes. Notably, the fabricated flexible CNT diode can greatly modulate the properties of the contact formed between the semiconducting CNT and the anode electrode via the control gate bias, exhibiting a high rectification ratio of up to 2.5 × 105. In addition, we confirm that the electrical performance of the CNT Schottky diodes does not significantly change after a few thousand bending/releasing cycles of the flexible substrate. Finally, integrated circuit (IC) applications of logic circuits (OR and AND gates) and an analog circuit (a half-wave rectifier) were presented through the use of flexible CNT Schottky diode combinations. The correct output responses are successfully achieved from the circuit applications; hence, we expect that our findings will provide a promising basis for electronic circuit applications based on CNTs.

Three-Dimensional Printed Poly(vinyl alcohol) Substrate with Controlled On-Demand Degradation for Transient Electronics.

Electronics that degrade after stable operation for a desired operating time, called transient electronics, are of great interest in many fields, including biomedical implants, secure memory devices, and environmental sensors. Thus, the development of transient materials is critical for the advancement of transient electronics and their applications. However, previous reports have mostly relied on achieving transience in aqueous solutions, where the transience time is largely predetermined based on the materials initially selected at the beginning of the fabrication. Therefore, accurate control of the transience time is difficult, thereby limiting their application. In this work, we demonstrate transient electronics based on a water-soluble poly(vinyl alcohol) (PVA) substrate on which carbon nanotube (CNT)-based field-effect transistors were fabricated. We regulated the structural parameters of the PVA substrate using a three-dimensional (3D) printer to accurately control and program the transience time of the PVA substrate in water. The 3D printing technology can produce complex objects directly, thus enabling the efficient fabrication of a transient substrate with a prescribed and controlled transience time. In addition, the 3D printer was used to develop a facile method for the selective and partial destruction of electronics.

Three-Dimensionally Printed Micro-electromechanical Switches.

Three-dimensional (3D) printers have attracted considerable attention from both industry and academia and especially in recent years because of their ability to overcome the limitations of two-dimensional (2D) processes and to enable large-scale facile integration techniques. With 3D printing technologies, complex structures can be created using only a computer-aided design file as a reference; consequently, complex shapes can be manufactured in a single step with little dependence on manufacturer technologies. In this work, we provide a first demonstration of the facile and time-saving 3D printing of two-terminal micro-electromechanical (MEM) switches. Two widely used thermoplastic materials were used to form 3D-printed MEM switches; freely suspended and fixed electrodes were printed from conductive polylactic acid, and a water-soluble sacrificial layer for air-gap formation was printed from poly(vinyl alcohol). Our 3D-printed MEM switches exhibit excellent electromechanical properties, with abrupt switching characteristics and an excellent on/off current ratio value exceeding 106. Therefore, we believe that our study makes an innovative contribution with implications for the development of a broader range of 3D printer applications (e.g., the manufacturing of various MEM devices and sensors), and the work highlights a uniquely attractive path toward the realization of 3D-printed electronics.

Determination of individual contact interfaces in carbon nanotube network-based transistors.

Carbon nanotubes (CNTs) used as semiconducting channels induce high mobility, thermal conductivity, mechanical flexibility, and chemical stability in field-effect, thin-film transistors (TFTs). However, the contact interfaces in CNT-TFTs have contact resistances that are difficult to reduce; this contact resistance can eventually limit the overall performance of CNT-TFTs. The contact interface between the source/drain electrodes and CNTs, especially for those CNT-TFTs in which the channel comprises randomly networked CNTs, plays a particularly dominant role in determining the performance and degree of variability in CNT-TFTs. However, no studies have reported a determination method that individually extracts each contact resistance at the source/drain electrodes. The present work presents an efficient method for directly determining the contact interfaces in CNT-TFTs by extracting each contact resistance produced at the source (R S ) and drain (R D ) electrodes. Moreover, we comprehensively simulated the randomly networked CNTs using an in-depth Monte-Carlo method, which provides an efficient method for visualizing the uniformity of a CNT network with various controllable CNT parameters. The proposed method provides guidance and a means for optimizing the design of the CNT network channel in CNT-TFTs and additional insights into improving the performance of CNT-TFTs.

Transparent, Flexible Strain Sensor Based on a Solution-Processed Carbon Nanotube Network.

The demands for transparent, flexible electronic devices are continuously increasing due to their potential applications to the human body. In particular, skin-like, transparent, flexible strain sensors have been developed to realize multifunctional human-machine interfaces. Here, we report a sandwich-like structured strain sensor with excellent optical transparency based on highly purified, solution-processed, 99% metallic CNT-polydimethylsiloxane (PDMS) composite thin films. Our CNT-PDMS composite strain sensors are mechanically compliant, physically robust, and easily fabricated. The fabricated strain sensors exhibit a high optical transparency of over 92% in the visible range with acceptable sensing performances in terms of sensitivity, hysteresis, linearity, and drift. We also found that the sensitivity and linearity of the strain sensors can be controlled by the number of CNT sprays; hence, our sensor can be applied and controlled based on the need of individual applications. Finally, we investigated the detections of human activities and emotions by mounting our transparent strain sensor on various spots of human skins.

Pattern Recognition Using Carbon Nanotube Synaptic Transistors with an Adjustable Weight Update Protocol.

Recent electronic applications require an efficient computing system that can perform data processing with limited energy consumption. Inspired by the massive parallelism of the human brain, a neuromorphic system (hardware neural network) may provide an efficient computing unit to perform such tasks as classification and recognition. However, the implementation of synaptic devices (i.e., the essential building blocks for emulating the functions of biological synapses) remains challenging due to their uncontrollable weight update protocol and corresponding uncertain effects on the operation of the system, which can lead to a bottleneck in the continuous design and optimization. Here, we demonstrate a synaptic transistor based on highly purified, preseparated 99% semiconducting carbon nanotubes, which can provide adjustable weight update linearity and variation margin. The pattern recognition efficacy is validated using a device-to-system level simulation framework. The enlarged margin rather than the linear weight update can enhance the fault tolerance of the recognition system, which improves the recognition accuracy.

Three-Dimensional Fin-Structured Semiconducting Carbon Nanotube Network Transistor.

Three-dimensional (3-D) fin-structured carbon nanotube field-effect transistors (CNT-FETs) with purified 99.9% semiconducting CNTs were demonstrated on a large scale 8 in. silicon wafer. The fabricated 3-D CNT-FETs take advantage of the 3-D geometry and exhibit enhanced electrostatic gate controllability and superior charge transport. A trigated structure surrounding the randomly networked single-walled CNT channel was formed on a fin-like 3-D silicon frame, and as a result, the effective packing density increased to almost 600 CNTs/µm. Additionally, highly sensitive controllability of the threshold voltage (VTH) was achieved using a thin back gate oxide in the same silicon frame to control power consumption and enhance performance. Our results are expected to broaden the design margin of CNT-based circuit architectures for versatile applications. The proposed 3-D CNT-FETs can potentially provide a desirable alternative to silicon based nanoelectronics and a blueprint for furthering the practical use of emerging low-dimensional materials other than CNTs.

Logic circuits composed of flexible carbon nanotube thin-film transistor and ultra-thin polymer gate dielectric.

Printing electronics has become increasingly prominent in the field of electronic engineering because this method is highly efficient at producing flexible, low-cost and large-scale thin-film transistors. However, TFTs are typically constructed with rigid insulating layers consisting of oxides and nitrides that are brittle and require high processing temperatures, which can cause a number of problems when used in printed flexible TFTs. In this study, we address these issues and demonstrate a method of producing inkjet-printed TFTs that include an ultra-thin polymeric dielectric layer produced by initiated chemical vapor deposition (iCVD) at room temperature and highly purified 99.9% semiconducting carbon nanotubes. Our integrated approach enables the production of flexible logic circuits consisting of CNT-TFTs on a polyethersulfone (PES) substrate that have a high mobility (up to 9.76 cm(2) V(-1) sec(-)1), a low operating voltage (less than 4 V), a high current on/off ratio (3 × 10(4)), and a total device yield of 90%. Thus, it should be emphasized that this study delineates a guideline for the feasibility of producing flexible CNT-TFT logic circuits with high performance based on a low-cost and simple fabrication process.

Carbon Nanotube Synaptic Transistor Network for Pattern Recognition.

Inspired by the human brain, a neuromorphic system combining complementary metal-oxide semiconductor (CMOS) and adjustable synaptic devices may offer new computing paradigms by enabling massive neural-network parallelism. In particular, synaptic devices, which are capable of emulating the functions of biological synapses, are used as the essential building blocks for an information storage and processing system. However, previous synaptic devices based on two-terminal resistive devices remain challenging because of their variability and specific physical mechanisms of resistance change, which lead to a bottleneck in the implementation of a high-density synaptic device network. Here we report that a three-terminal synaptic transistor based on carbon nanotubes can provide reliable synaptic functions that encode relative timing and regulate weight change. In addition, using system-level simulations, the developed synaptic transistor network associated with CMOS circuits can perform unsupervised learning for pattern recognition using a simplified spike-timing-dependent plasticity scheme.

A Highly Responsive Silicon Nanowire/Amplifier MOSFET Hybrid Biosensor.

This study demonstrates a hybrid biosensor comprised of a silicon nanowire (SiNW) integrated with an amplifier MOSFET to improve the current response of field-effect-transistor (FET)-based biosensors. The hybrid biosensor is fabricated using conventional CMOS technology, which has the potential advantage of high density and low noise performance. The biosensor shows a current response of 5.74 decades per pH for pH detection, which is 2.5 × 10(5) times larger than that of a single SiNW sensor. In addition, we demonstrate charged polymer detection using the biosensor, with a high current change of 4.5 × 10(5) with a 500 nM concentration of poly(allylamine hydrochloride). In addition, we demonstrate a wide dynamic range can be obtained by adjusting the liquid gate voltage. We expect that this biosensor will be advantageous and practical for biosensor applications which requires lower noise, high speed, and high density.