Monolithically Integrated Complementary Ferroelectric FET XNOR Synapse for the Binary Neural Network.

Neuromorphic computing, which mimics the structure and principles of the human brain, has the potential to facilitate the hardware implementation of next-generation artificial intelligence systems and process large amounts of data with very low power consumption. Among them, the XNOR synapse-based Binary Neural Network (BNN) has been attracting attention due to its compact neural network parameter size and low hardware cost. The previous XNOR synapse has drawbacks, such as a trade-off between cell density and accuracy. In this work, we show nonvolatile XNOR synapses with high density and accuracy using a monolithically stacked complementary ferroelectric field-effect transistor (C-FeFET) composed of a p-type Si MFMIS-FeFET at the bottom and a 3D stackable n-type Al:IZTO MFS-FeTFT, achieving 60F2 per cell (2C-FeFET). For adjusting the threshold voltage and improving the switching speed (100 ns) of n-type ferroelectric TFT, we employed a dual-gate configuration and a unique operation scheme, making it comparable to those of Si-based FeFETs. We performed array-level simulation with a 512 × 512 subarray size and a 3-bit flash ADC, demonstrating that the image recognition accuracies using the MNIST and CIFAR-10 data sets were increased by 3.17 and 14.07%, respectively, in comparison to other nonvolatile XNOR synapses. In addition, we performed system-level analysis on a 512 × 512 XNOR C-FeFET, exhibiting an outstanding throughput of 717.37 GOPS and an energy efficiency of 196.7 TOPS/W. We expect that our approach would contribute to the high-density memory systems, logic-in-memory technology, and hardware implementation of neural networks.

Physics, Structures, and Applications of Fluorite-Structured Ferroelectric Tunnel Junctions.

The interest in ferroelectric tunnel junctions (FTJ) has been revitalized by the discovery of ferroelectricity in fluorite-structured oxides such as HfO2 and ZrO2 . In terms of thickness scaling, CMOS compatibility, and 3D integration, these fluorite-structured FTJs provide a number of benefits over conventional perovskite-based FTJs. Here, recent developments involving all FTJ devices with fluorite structures are examined. The transport mechanism of fluorite-structured FTJs is explored and contrasted with perovskite-based FTJs and other 2-terminal resistive switching devices starting with the operation principle and essential parameters of the tunneling electroresistance effect. The applications of FTJs, such as neuromorphic devices, logic-in-memory, and physically unclonable function, are then discussed, along with several structural approaches to fluorite-structure FTJs. Finally, the materials and device integration difficulties related to fluorite-structure FTJ devices are reviewed. The purpose of this review is to outline the theories, physics, fabrication processes, applications, and current difficulties associated with fluorite-structure FTJs while also describing potential future possibilities for optimization.

Ferroelectric Hafnia-Based M3D FeTFTs Annealed at Extremely Low Temperatures and TCAM Cells for Computing-in-Memory Applications.

In order to overcome the bottleneck between the central processor unit and memory as well as the issue of energy consumption, computing-in-memory (CIM) is becoming more popular as an alternative to the traditional von Neumann structure. However, as artificial intelligence advances, the networks require CIM devices to store billions of parameters in order to handle huge data traffic demands. Monolithic three-dimensional (M3D) stacked ferroelectric thin-film transistors (FeTFTs) are one of the promising techniques for realizing high-density CIM devices that can store billions of parameters. In particular, oxide channel-based FeTFTs are well suited for these applications due to low-temperature processes, nonvolatility, and 3D integration capability. Nevertheless, the M3D-integrated CIM devices including hafnia ferroelectric films need the high-temperature annealing process to crystallize the ferroelectric layer, making M3D integration difficult. When the FeTFTs are fabricated with an M3D structure, the high-temperature process causes thermal issues in the underlying devices. Here, we present the focused microwave annealed (FMA) oxide FeTFTs with M3D integration at a low temperature of 250 °C. We confirmed that the FeTFTs with metal-ferroelectric-metal-insulator-semiconductor structure exhibited a large memory window of 3.2 V, good endurance over 106 cycles, and a long retention time of 105 s. To understand the different electrical characteristics of FeTFTs in the top and bottom layers, we experimentally analyzed the density of the state of the oxide channel and ferroelectric properties of the ferroelectric gate insulator by using multifrequency capacitance-voltage measurement and nucleation-limited-switching model analysis, respectively. With our approach, we demonstrate for the first time a vertical stacked FeTFTs-based ternary-content-addressable memory (TCAM) cell for CIM application. We believe that the proposed M3D-stacked TCAM cells composed of FeTFTs can be used in high-density memory, energy-efficient memory, and CIM technology.

Power-Delay Area-Efficient Processing-In-Memory Based on Nanocrystalline Hafnia Ferroelectric Field-Effect Transistors.

Ferroelectric field-effect transistors (FeFETs) have attracted enormous attention for low-power and high-density nonvolatile memory devices in processing-in-memory (PIM). However, their small memory window (MW) and limited endurance severely degrade the area efficiency and reliability of PIM devices. Herein, we overcome such challenges using key approaches covering from the material to the device and array architecture. High ferroelectricity was successfully demonstrated considering the thermodynamics and kinetics, even in a relatively thick (≥30 nm) ferroelectric material that was unexplored so far. Moreover, we employed a metal-ferroelectric-metal-insulator-semiconductor architecture that enabled desirable voltage division between the ferroelectric and the metal-oxide-semiconductor FET, leading to a large MW (∼11 V), fast operation speed (<20 ns), and high endurance (∼1011 cycles) characteristics. Subsequently, reliable and energy-efficient multiply-and-accumulation (MAC) operations were verified using a fabricated FeFET-PIM array. Furthermore, a system-level simulation demonstrated the high energy efficiency of the FeFET-PIM array, which was attributed to charge-domain computing. Finally, the proposed signed weight MAC computation achieved high accuracy on the CIFAR-10 dataset using the VGG-8 network.

Steep-Slope Transistor with an Imprinted Antiferroelectric Film.

The effect of negative capacitance (NC), which can internally boost the voltage applied to a transistor, has been considered to overcome the fundamental Boltzmann limit of a transistor. To stabilize the NC effect, the dielectric (DE) must be integrated into a heterostructure with a ferroelectric (FE) film. However, in a multidomain hafnia, the charge boosting effect is reduced owing to a lowering of the depolarization field originating from the stray field at each domain, and simultaneously, the operating voltage increases owing to the voltage division at the DE. Here, we demonstrate core approaches to the gate stack of energy-efficient device technology using a transient NC. Electrical measurements of the transistor with imprinted antiferroelectric and high CDE/CFE structures exhibit low subthreshold slopes below 20 mV/dec, a low voltage operation of 0.5 V, a fast operation of 20 ns, hysteresis-free Id-Vg, and high endurance characteristics of 1012 cycles. We expect that this will lead to the rapid implementation of the NC effect in high-speed switching device applications with significantly improved energy efficiency.

A review on morphotropic phase boundary in fluorite-structure hafnia towards DRAM technology.

In the present hyper-scaling era, memory technology is advancing owing to the demand for high-performance computing and storage devices. As a result, continuous work on conventional semiconductor-process-compatible ferroelectric memory devices such as ferroelectric field-effect transistors, ferroelectric random-access memory, and dynamic random-access memory (DRAM) cell capacitors is ongoing. To operate high-performance computing devices, high-density, high-speed, and reliable memory devices such as DRAMs are required. Consequently, considerable attention has been devoted to the enhanced high dielectric constant and reduced equivalent oxide thickness (EOT) of DRAM cell capacitors. The advancement of ferroelectric hafnia has enabled the development of various devices, such as ferroelectric memories, piezoelectric sensors, and energy harvesters. Therefore, in this review, we focus the morphotropic phase boundary (MPB) between ferroelectric orthorhombic and tetragonal phases, where we can achieve a high dielectric constant and thereby reduce the EOT. We also present the role of the MPB in perovskite and fluorite structures as well as the history of the MPB phase. We also address the different approaches for achieving the MPB phase in a hafnia material system. Subsequently, we review the critical issues in DRAM technology using hafnia materials. Finally, we present various applications of the hafnia material system near the MPB, such as memory, sensors, and energy harvesters.

Noise-Robust Multimodal Audio-Visual Speech Recognition System for Speech-Based Interaction Applications.

Speech is a commonly used interaction-recognition technique in edutainment-based systems and is a key technology for smooth educational learning and user-system interaction. However, its application to real environments is limited owing to the various noise disruptions in real environments. In this study, an audio and visual information-based multimode interaction system is proposed that enables virtual aquarium systems that use speech to interact to be robust to ambient noise. For audio-based speech recognition, a list of words recognized by a speech API is expressed as word vectors using a pretrained model. Meanwhile, vision-based speech recognition uses a composite end-to-end deep neural network. Subsequently, the vectors derived from the API and vision are classified after concatenation. The signal-to-noise ratio of the proposed system was determined based on data from four types of noise environments. Furthermore, it was tested for accuracy and efficiency against existing single-mode strategies for extracting visual features and audio speech recognition. Its average recognition rate was 91.42% when only speech was used, and improved by 6.7% to 98.12% when audio and visual information were combined. This method can be helpful in various real-world settings where speech recognition is regularly utilized, such as cafés, museums, music halls, and kiosks.

Novel Approach to High κ (∼59) and Low EOT (∼3.8 Å) near the Morphotrophic Phase Boundary with AFE/FE (ZrO2/HZO) Bilayer Heterostructures and High-Pressure Annealing.

We present herewith a novel approach of equally thick AFE/FE (ZrO2/HZO) bilayer stack heterostructure films for achieving an equivalent oxide thickness (EOT) of 4.1 Å with a dielectric constant (κ) of 56 in complementary metal-oxide semiconductor (CMOS) compatible metal-ferroelectric-metal (MFM) capacitors using a high-pressure annealing (HPA) technique. The low EOT and high κ values were achieved by careful optimization of AFE/FE film thicknesses and HPA conditions near the morphotropic phase boundary (MPB) after field cycling effects. Stable leakage current density (J < 10-7 A/cm2 at ±0.8 V) was found at 3/3 nm bilayer stack films (κ = 56 and EOT = 4.1 Å) measured at room temperature. In comparison with previous work, our remarkable achievement stems from the interfacial coupling between FE and AFE films as well as a high-quality crystalline structure formed by HPA. Kinetically stabilized hafnia films result in a small grain size in bilayer films, leading to reducing the leakage current density. Further, a higher κ value of 59 and lower EOT of 3.4 Å were found at 333 K. However, stable leakage current density was found at 273 K with a high κ value of 53 and EOT of 3.85 Å with J < 10-7 A/cm2. This is the lowest recorded EOT employing hafnia and TiN electrodes that are compatible with CMOS, and it has important implications for future dynamic random access memory (DRAM) technology.

End-to-End Sentence-Level Multi-View Lipreading Architecture with Spatial Attention Module Integrated Multiple CNNs and Cascaded Local Self-Attention-CTC.

Concomitant with the recent advances in deep learning, automatic speech recognition and visual speech recognition (VSR) have received considerable attention. However, although VSR systems must identify speech from both frontal and profile faces in real-world scenarios, most VSR studies have focused solely on frontal face pictures. To address this issue, we propose an end-to-end sentence-level multi-view VSR architecture for faces captured from four different perspectives (frontal, 30°, 45°, and 60°). The encoder uses multiple convolutional neural networks with a spatial attention module to detect minor changes in the mouth patterns of similarly pronounced words, and the decoder uses cascaded local self-attention connectionist temporal classification to collect the details of local contextual information in the immediate vicinity, which results in a substantial performance boost and speedy convergence. To compare the performance of the proposed model for experiments on the OuluVS2 dataset, the dataset was divided into four different perspectives, and the obtained performance improvement was 3.31% (0°), 4.79% (30°), 5.51% (45°), 6.18% (60°), and 4.95% (mean), respectively, compared with the existing state-of-the-art performance, and the average performance improved by 9.1% compared with the baseline. Thus, the suggested design enhances the performance of multi-view VSR and boosts its usefulness in real-world applications.

End-to-End Lip-Reading Open Cloud-Based Speech Architecture.

Deep learning technology has encouraged research on noise-robust automatic speech recognition (ASR). The combination of cloud computing technologies and artificial intelligence has significantly improved the performance of open cloud-based speech recognition application programming interfaces (OCSR APIs). Noise-robust ASRs for application in different environments are being developed. This study proposes noise-robust OCSR APIs based on an end-to-end lip-reading architecture for practical applications in various environments. Several OCSR APIs, including Google, Microsoft, Amazon, and Naver, were evaluated using the Google Voice Command Dataset v2 to obtain the optimum performance. Based on performance, the Microsoft API was integrated with Google's trained word2vec model to enhance the keywords with more complete semantic information. The extracted word vector was integrated with the proposed lip-reading architecture for audio-visual speech recognition. Three forms of convolutional neural networks (3D CNN, 3D dense connection CNN, and multilayer 3D CNN) were used in the proposed lip-reading architecture. Vectors extracted from API and vision were classified after concatenation. The proposed architecture enhanced the OCSR API average accuracy rate by 14.42% using standard ASR evaluation measures along with the signal-to-noise ratio. The proposed model exhibits improved performance in various noise settings, increasing the dependability of OCSR APIs for practical applications.

Flexible Ferroelectric Hafnia-Based Synaptic Transistor by Focused-Microwave Annealing.

Hafnia-based ferroelectric memory devices with excellent ferroelectricity, low power consumption, and fast operation speed have attracted considerable interest with the ever-growing desire for nonvolatile memory in flexible electronics. However, hafnia films are required to perform a high temperature (>500 °C) annealing process for crystallization into the ferroelectric orthorhombic phase. It can hinder the integration of hafnia ferroelectric films on flexible substrates including plastic and polymer, which are not endurable at high temperatures above 300 °C. Here, we propose the extremely low-temperature (∼250 °C) process for crystallization of Hf0.5Zr0.5O2 (HZO) thin films by applying a focused-microwave induced annealing method. HZO thin films on a flexible mica substrate exhibits robust remnant polarization (2Pr ∼ 50 µC/cm2), which is negligibly changed under bending tests. In addition, the electrical characteristics of a HZO capacitor on the mica substrate were evaluated, and ferroelectric thin film transistors (Fe-TFTs), using a HZO gate insulator, were fabricated on mica substrates for flexible synapse applications. Symmetric potentiation and depression characteristics are successfully demonstrated in the Fe-TFT memory devices, and the synaptic devices result in high recognition accuracy of 91.44%. The low-temperature annealing method used in this work are promising for forming hafnia-based Fe-TFT memory devices as a building block on a flexible platform.

Positive Correlation of Triacylglycerols with Increased Chain Length and Unsaturation with ω-O-Acylceramide and Ceramide-NP as Well as Acidic pH in the Skin Surface of Healthy Korean Adults.

Triacylglycerols (TG) play an important role in skin homeostasis including the synthesis of ω-O-acylceramides (acylCER) required for skin barrier formation by providing linoleic acid (C18:2n6). However, the overall relationships of TG species with various ceramides (CER) including CER-NP, the most abundant CER, ω-O-acylCER, and another acylCER, 1-O-acylCER in human SC, remain unclear. Therefore, we investigated these relationships and their influence on skin health status in healthy Korean adults. Twelve CER subclasses including two ω-O-acylCER and two 1-O-acylCER were identified with CER-NP consisting of approximately half of the total CER. The ω-O-acylCER species exhibited positive relationships with TG 52:4 and TG 54:2 containing C18:2, while interestingly, 1-O-acylCER containing ester-linked C14:0 and C16:0 demonstrated positive relationships with TG 46-50 including C14:0 and C16:0, respectively. In addition, CER-NP and CER-NH showed positive correlations with TG 52-54 containing C18:2 or C18:3. A lipid pattern with higher levels of CER including CER-NP and ω-O-acylCER with TG 54 and TG with 5-6 double bonds was related to good skin health status, especially with acidic skin pH. Collectively, TG with increased chain length and unsaturation seemed to improve CER content, and profiles such as higher acylCER and CER-NP improved skin health status by fortifying skin barrier structure.

Selector-less Ferroelectric Tunnel Junctions by Stress Engineering and an Imprinting Effect for High-Density Cross-Point Synapse Arrays.

In the quest for highly scalable and three-dimensional (3D) stackable memory components, ferroelectric tunnel junction (FTJ) crossbar architectures are promising technologies for nonvolatile logic and neuromorphic computing. Most FTJs, however, require additional nonlinear devices to suppress sneak-path current, limiting large-scale arrays in practical applications. Moreover, the giant tunneling electroresistance (TER) remains challenging due to their inherent weak polarization. Here, we present that the employment of a diffusion barrier layer as well as a bottom metal electrode having a significantly low thermal expansion coefficient has been identified as an important way to enhance the strain, stabilize the ferroelectricity, and manage the leakage current in ultrathin hafnia film, achieving a high TER of 100, negligible resistance changes even up to 108 cycles, and a high switching speed of a few tens of nanoseconds. Also, we demonstrate that the usage of an imprinting effect in a ferroelectric capacitor induced by an ionized oxygen vacancy near the electrode results in highly asymmetric current-voltage characteristics with a rectifying ratio of 1000. Notably, the proposed FTJ exhibits a high density array size (>4k) with a securing read margin of 10%. These findings provide a guideline for the design of high-performance and selector-free FTJ devices for large-scale crossbar arrays in neuromorphic applications.

Lipreading Architecture Based on Multiple Convolutional Neural Networks for Sentence-Level Visual Speech Recognition.

In visual speech recognition (VSR), speech is transcribed using only visual information to interpret tongue and teeth movements. Recently, deep learning has shown outstanding performance in VSR, with accuracy exceeding that of lipreaders on benchmark datasets. However, several problems still exist when using VSR systems. A major challenge is the distinction of words with similar pronunciation, called homophones; these lead to word ambiguity. Another technical limitation of traditional VSR systems is that visual information does not provide sufficient data for learning words such as "a", "an", "eight", and "bin" because their lengths are shorter than 0.02 s. This report proposes a novel lipreading architecture that combines three different convolutional neural networks (CNNs; a 3D CNN, a densely connected 3D CNN, and a multi-layer feature fusion 3D CNN), which are followed by a two-layer bi-directional gated recurrent unit. The entire network was trained using connectionist temporal classification. The results of the standard automatic speech recognition evaluation metrics show that the proposed architecture reduced the character and word error rates of the baseline model by 5.681% and 11.282%, respectively, for the unseen-speaker dataset. Our proposed architecture exhibits improved performance even when visual ambiguity arises, thereby increasing VSR reliability for practical applications.

Effect of Ga composition on mobility in a-InGaZnO thin-film transistors.

Oxide semiconductor TFTs have attracted considerable attention in the recent past due to their excellent mobility, high optical transparency in the visible region, and most importantly their fabrication process at low-temperature. However, charge trapping formation in the gate dielectric and the interfaces in such oxide TFTs leads to serious issues such as their operational stability and reliability. Understanding the charge trapping mechanism is therefore of utmost importance to identify the root cause of the aforesaid problems. In this report, we present a detailed study on the charge trapping and dynamic charge transport of a-IGZO TFTs by examining microsecond fast IV (FIV), pulse IV (PIV), and transient IV measurements. The a-IGZO TFTs have designed and fabricated with various Ga compositions (0, 0.14 and 0.22). It was observed that the charge trapping in the a-IGZO TFT is reliant on the sweeping time and the carrier mobility measured using the FIV technique was found to be higher than that obtained from the conventional DC IV measurement. Mobility values ([Formula: see text]) was also measured through the PIV technique and are found to be approximately 10%, 16%, and 21% lower than the intrinsic mobility values. Temperature-dependent study reveals that the intrinsic mobility values (18.45, 16.1 and 12.03 cm2 V-1 s-1) are higher than the pulse mobility values for various Ga compositions (0, 0.14 and 0.22) at higher temperature (175 °C) probably due to the formation of free carriers. Suitable optimization of process parameters of a-IGZO TFTs can therefore enhance the device stability and reliability characteristics leading to their potential utilization in flexible and stretchable electronic devices, sensors & detectors and biomedical devices.

Excellent Reliability and High-Speed Antiferroelectric HfZrO2 Tunnel Junction by a High-Pressure Annealing Process and Built-In Bias Engineering.

Hafnia-based ferroelectric tunnel junctions (FTJs) have great potential for use in logic in nonvolatile memory because of their complementary metal-oxide-semiconductor process compatibility, low power consumption, high scalability, and nondestructive readout. However, typically, ferroelectrics have a depolarization field, resulting in poor endurance owing to the early dielectric breakdown. Herein, an outstandingly reliable and high-speed antiferroelectric HfZrO tunnel junction (AFTJ) is probed to understand whether it is a promising candidate for next-generation nonvolatile memory applications. High-reliability AFTJ can be explained by less charge injection due to the low depolarized field. The formation of two stable nonvolatile states, even with antiferroelectric materials, is possible if asymmetric work function electrodes and fixed oxide charges are employed, generating a built-in bias and shifting the polarization-voltage curve. In addition, via high-pressure annealing, a critical voltage that determines the transition from the t-phase to the o-phase is effectively reduced (22%). The AFTJ shows a higher endurance property (>109 cycles) and faster switching speed (<30 ns) than FTJ. Hence, it is proposed that with the help of internal bias modulation and high-pressure annealing, AFTJs can be employed in next-generation memory devices.

Oxygen vacancy control as a strategy to achieve highly reliable hafnia ferroelectrics using oxide electrode.

Recently, hafnia ferroelectrics with two spontaneous polarization states have attracted marked attention for non-volatile, super-steep switching devices, and neuromorphic application due to their fast switching, scalability, and CMOS compatibility. However, field cycling-induced instabilities are a serious obstacle in the practical application of various low-power electronic devices that require a settled characteristic of polarization hysteresis. In this work, a large reduction in the field cycling-induced instabilities and significantly improved ferroelectric properties were observed in a Hf0.5Zr0.5O2 (HZO) thin film with a RuO2 oxide electrode. The oxide electrode can supply additional oxygen to the HZO film, consequently minimizing the oxygen vacancies at the interface which is the origin of low reliability. From the material and electrical analysis results, we verified that HZO with the RuO2 electrode has less non-ferroelectric dead layers and fewer oxygen vacancies at the interface, resulting in excellent switching properties and improved reliability. This result suggests a beneficial method to produce high-quality hafnia thin films free from interfacial defects and with stable field cycling electrical properties for actual applications.

Broad spectral responsivity in highly photoconductive InZnO/MoS2 heterojunction phototransistor with ultrathin transparent metal electrode.

An amorphous InZnO/MoS2 heterojunction-based phototransistor with excellent photoconductive gain and responsivity over the entire visible range has been demonstrated. The photogenerated current of the InZnO phototransistor at long light wavelength (>600 nm) was significantly improved by utilizing narrow bandgap MoS2 as the capping layer (1.3 eV). At lower wavelength, photocarriers are generated due to the optical absorption of both InZnO and MoS2 layers, whereas the latter ensures significant photocarrier generation even at the higher wavelength region of the visible spectrum. The photogenerated carriers subsequently transfer to the underlying InZnO layer of superior carrier mobility that has a high channel conduction of additional electrons from the optically-induced doubly positively charged oxygen vacancies (Vo++) where the gate field is screening, thereby leading to the higher photoconductive gain of the InZnO/MoS2 phototransistors. The dynamic photosensitivity behaviour of the aforesaid phototransistor reveals the presence of persistent photoconductivity (PPC) due to the oxygen vacancy associated with InZnO which can be removed by applying a reset gate pulse from -15 to +5 V. The optical properties of these phototransistors were further enhanced by replacing the opaque Ti/Au electrode by an ultrathin transparent Ti/Au electrode. Utilization of the transparent electrode results in enhanced electron injection from source to channel due to a reduced barrier height under illumination giving rise to a ten-fold improvement in the photocurrent and responsivity of the phototransistors. A position-dependent study of the photocurrent w.r.t beam position also reveals that the enhancement in photocurrent is strongly dependent on the position and is at its maximum when the beam is placed near the source region.

Transparent and Flexible Mayan-Pyramid-based Pressure Sensor using Facile-Transferred Indium tin Oxide for Bimodal Sensor Applications.

Transparent and conducting flexible electrodes have been successfully developed over the last few decades due to their potential applications in optoelectronics. However, recent developments in smart electronics, such as a direct human-machine interface, health-monitoring devices, motion-tracking sensors, and artificially electronic skin also require materials with multifunctional properties such as transparency, flexibility and good portability. In such devices, there remains room to develop transparent and flexible devices such as pressure sensors or temperature sensors. Herein, we demonstrate a fully transparent and flexible bimodal sensor using indium tin oxide (ITO), which is embedded in a plastic substrate. For the proposed pressure sensor, the embedded ITO is detached from its Mayan-pyramid-structured silicon mold by an environmentally friendly method which utilizes water-soluble sacrificial layers. The Mayan-pyramid-based pressure sensor is capable of six different pressure sensations with excellent sensitivity in the range of 100 Pa-10 kPa, high endurance of 105 cycles, and good pulse detection and tactile sensing data processing capabilities through machine learning (ML) algorithms for different surface textures. A 5 × 5-pixel pressure-temperature-based bimodal sensor array with a zigzag-shaped ITO temperature sensor on top of it is also demonstrated without a noticeable interface effect. This work demonstrates the potential to develop transparent bimodal sensors that can be employed for electronic skin (E-skin) applications.

Improved optical performance of multi-layer MoS2 phototransistor with see-through metal electrode.

In recent years, MoS2 has emerged as a prime material for photodetector as well as phototransistor applications. Usually, the higher density of state and relatively narrow bandgap of multi-layer MoS2 give it an edge over monolayer MoS2 for phototransistor applications. However, MoS2 demonstrates thickness-dependent energy bandgap properties, with multi-layer MoS2 having indirect bandgap characteristics and therefore possess inferior optical properties. Herein, we investigate the electrical as well as optical properties of single-layer and multi-layer MoS2-based phototransistors and demonstrate improved optical properties of multi-layer MoS2 phototransistor through the use of see-through metal electrode instead of the traditional global bottom gate or patterned local bottom gate structures. The see-through metal electrode utilized in this study shows transmittance of more than 70% under 532 nm visible light, thereby allowing the incident light to reach the entire active area below the source and drain electrodes. The effect of contact electrodes on the MoS2 phototransistors was investigated further by comparing the proposed electrode with conventional opaque electrodes and transparent IZO electrodes. A position-dependent photocurrent measurement was also carried out by locally illuminating the MoS2 channel at different positions in order to gain better insight into the behavior of the photocurrent mechanism of the multi-layer MoS2 phototransistor with the transparent metal. It was observed that more electrons are injected from the source when the beam is placed on the source side due to the reduced barrier height, giving rise to a significant enhancement of the photocurrent.