Effect of deposition temperature on dielectric properties of PECVD Ta2O5 thin film

Tantalum oxide film formation by plasma-enhanced chemical vapour deposition (PECVD) using TaCl₅ as a source material was examined. The effects of deposition temperature on the formation, structure and electric properties of the Ta₂O₅ film were investigated for Al/Ta₂O₅/ p-Si (MTS) capacitors. The deposition rate and refractive index increased with increasing deposition temperature. It was found that the structure of Ta₂O₅ deposited by PECVD was amorphous as-deposited. However, crystalline -Ta₂O₅ of hexagonal structure was formed by a 700 °C, 1 h heat treatment in argon. Capacitance and relative dielectric constant of the PECVD Ta₂O₅ were found to be 2.54 fF m^–2 and 23.5, respectively. The PECVD films obtained in this study have higher dielectric constants and remarkably better general film characteristics than those obtained by other deposition methods.     

Preparation of PbTiO3 thin films using an alkoxide-alkanolamine sol-gel system

The stable range of PbTiO₃ sol and the processing conditions of uniform thin films were investigated using a solution of titanium isopropoxide, three kinds of alkanolamines (monoethanolamine, diethanolamine, triethanolamine), lead acetate trihydrate and isopropanol. Depending on the sol state with various alkanolamine/alkoxide molar ratios, diethanolamine (DEA) was very effective in preparing uniform and dense oxide films through room-temperature reaction, owing to its superior stability during the hydrolysis and condensation reaction. Perovskite PbTiO₃ thin films were obtained on oxidized silicon wafer above 550 °C and completely pure films were obtained at 650 °C using DEA as a complexing agent. The dielectric constant and loss tangent of these thin films fired at 650 °C for 30 min were found to be 240 and 0.01 at 1 kHz, respectively.     

Correlated Quantum Phenomena of Spin–Orbit Coupled Perovskite Oxide Heterostructures: Cases of SrRuO3 and SrIrO3 Based Artificial Superlattices

Unexpected, yet useful functionalities emerge when two or more materials merge coherently. Artificial oxide superlattices realize atomic and crystal structures that are not available in nature, thus providing controllable correlated quantum phenomena. This review focuses on 4d and 5d perovskite oxide superlattices, in which the spin–orbit coupling plays a significant role compared with conventional 3d oxide superlattices. Modulations in crystal structures with octahedral distortion, phonon engineering, electronic structures, spin orderings, and dimensionality control are discussed for 4d oxide superlattices. Atomic and magnetic structures, J_eff = 1/2 pseudospin and charge fluctuations, and the integration of topology and correlation are discussed for 5d oxide superlattices. This review provides insights into how correlated quantum phenomena arise from the deliberate design of superlattice structures that give birth to novel functionalities.     

Room-Temperature-Processable Highly Reliable Resistive Switching Memory with Reconfigurability for Neuromorphic Computing and Ultrasonic Tissue Classification

Reversible metal-filamentary mechanism has been widely investigated to design an analog resistive switching memory (RSM) for neuromorphic hardware-implementation. However, uncontrollable filament-formation, inducing its reliability issues, has been a fundamental challenge. Here, an analog RSM with 3D ion transport channels that can provide unprecedentedly high reliability and robustness is demonstrated. This architecture is realized by a laser-assisted photo-thermochemical process, compatible with the back-end-of-line process and even applicable to a flexible format. These superior characteristics also lead to the proposal of a practical adaptive learning rule for hardware neural networks that can significantly simplify the voltage pulse application methodology even with high computing accuracy. A neural network, which can perform the biological tissue classification task using the ultrasound signals, is designed, and the simulation results confirm that this practical adaptive learning rule is efficient enough to classify these weak and complicated signals with high accuracy (97%). Furthermore, the proposed RSM can work as a diffusive-memristor at the opposite voltage polarity, exhibiting extremely stable threshold switching characteristics. In this mode, several crucial operations in biological nervous systems, such as Ca²⁺ dynamics and nonlinear integrate-and-fire functions of neurons, are successfully emulated. This reconfigurability is also exceedingly beneficial for decreasing the complexity of systems—requiring both drift- and diffusive-memristors.     

Rational Design and Synthesis of Extremely Efficient Macroporous CoSe2–CNT Composite Microspheres for Hydrogen Evolution Reaction

Uniquely structured CoSe₂–carbon nanotube (CNT) composite microspheres with optimized morphology for the hydrogen‐evolution reaction (HER) are prepared by spray pyrolysis and subsequent selenization. The ultrafine CoSe₂ nanocrystals uniformly decorate the entire macroporous CNT backbone in CoSe₂–CNT composite microspheres. The macroporous CNT backbone strongly improves the electrocatalytic activity of CoSe₂ by improving the electrical conductivity and minimizing the growth of CoSe₂ nanocrystals during the synthesis process. In addition, the macroporous structure resulting from the CNT backbone improves the electrocatalytic activity of the CoSe₂–CNT microspheres by increasing the removal rate of generated H₂ and minimizing the polarization of the electrode during HER. The CoSe₂–CNT composite microspheres demonstrate excellent catalytic activity for HER in an acidic medium (10 mA cm^?2 at an overpotential of ≈174 mV). The bare CoSe₂ powders exhibit moderate HER activity, with an overpotential of 226 mV at 10 mA cm^?2. The Tafel slopes for the CoSe₂–CNT composite and bare CoSe₂ powders are 37.8 and 58.9 mV dec^?1, respectively. The CoSe₂–CNT composite microspheres have a slightly larger Tafel slope than that of commercial carbon‐supported platinum nanoparticles, which is 30.2 mV dec^–1.     

Designing Metallic and Insulating Nanocrystal Heterostructures to Fabricate Highly Sensitive and Solution Processed Strain Gauges for Wearable Sensors

All‐solution processed, high‐performance wearable strain sensors are demonstrated using heterostructure nanocrystal (NC) solids. By incorporating insulating artificial atoms of CdSe quantum dot NCs into metallic artificial atoms of Au NC thin film matrix, metal–insulator heterostructures are designed. This hybrid structure results in a shift close to the percolation threshold, modifying the charge transport mechanism and enhancing sensitivity in accordance with the site percolation theory. The number of electrical pathways is also manipulated by creating nanocracks to further increase its sensitivity, inspired from the bond percolation theory. The combination of the two strategies achieves gauge factor up to 5045, the highest sensitivity recorded among NC‐based strain gauges. These strain sensors show high reliability, durability, frequency stability, and negligible hysteresis. The fundamental charge transport behavior of these NC solids is investigated and the combined site and bond percolation theory is developed to illuminate the origin of their enhanced sensitivity. Finally, all NC‐based and solution‐processed strain gauge sensor arrays are fabricated, which effectively measure the motion of each finger joint, the pulse of heart rate, and the movement of vocal cords of human. This work provides a pathway for designing low‐cost and high‐performance electronic skin or wearable devices.     

Error estimation for the automated multi‐level substructuring method

In this study, we propose an effective method to estimate the reliability of finite element models reduced by the automated multi‐level substructuring (AMLS) method. The proposed error estimation method can accurately predict relative eigenvalue errors in reduced finite element models. A new, enhanced transformation matrix for the AMLS method is derived from the original transformation matrix by properly considering the contribution of residual substructural modes. The enhanced transformation matrix is an important prerequisite to develop the error estimation method. Adopting the basic concept of the error estimation method recently developed for the Craig–Bampton method, an error estimation method is developed for the AMLS method. Through various numerical examples, we demonstrate the accuracy of the proposed error estimation method and explore its computational efficiency. Copyright © 2015 John Wiley & Sons, Ltd.