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Byung-Chul Jeon

Bio: Byung-Chul Jeon is an academic researcher from Seoul National University. The author has contributed to research in topics: Thyristor & Insulated-gate bipolar transistor. The author has an hindex of 13, co-authored 47 publications receiving 702 citations.

Papers
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Journal ArticleDOI
TL;DR: Flexoelectricity can play an important role in the reversal of the self-polarization direction in epitaxial BiFeO3 thin films.
Abstract: Flexoelectricity can play an important role in the reversal of the self-polarization direction in epitaxial BiFeO3 thin films. The flexoelectric and interfacial effects compete with each other to determine the self-polarization state. In Region I, the self-polarization is downward because the interfacial effect is more dominant than the flexoelectric effect. In Region II, the self-polarization is upward, because the flexoelectric effect becomes more dominant than the interfacial effect.

126 citations

Journal ArticleDOI
TL;DR: Multilevel non-volatile memory for high-density date storage is achieved by using the deterministic control of ferroelectric polarization, which can be used to triple or quadruple the memory density, even at existing feature scales.
Abstract: Multilevel non-volatile memory for high-density date storage is achieved by using the deterministic control of ferroelectric polarization. In a real ferroelectric thin-film system, eight stable and reproducible polarization states are realized (i.e., 3-bit data storage) by adjusting the displacement current. This approach can be used to triple or quadruple the memory density, even at existing feature scales.

125 citations

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TL;DR: A scalable and unsupervised feature engineering method that uses vibration imaging and deep learning that can substantially increase the applicability of the fault diagnosis method while maintaining good accuracy is proposed.
Abstract: This paper proposes a scalable and unsupervised feature engineering method that uses vibration imaging and deep learning. For scalability, a vibration imaging approach is devised that incorporates data from systems with various scales, such as small testbeds and real field-deployed systems. Moreover, a deep learning approach is proposed for unsupervised feature engineering. The overall procedure includes three key steps: 1) vibration image generation; 2) unsupervised feature extraction; and 3) fault classifier design. To demonstrate the validity of the proposed approach, three case studies are conducted using an RK4 rotor kit and a power plant journal bearing system. By incorporating smaller-system data as well as real-system data, the proposed approach can substantially increase the applicability of the fault diagnosis method while maintaining good accuracy. Moreover, the time and effort needed to develop a diagnostic approach for other rotor systems can be reduced considerably.

104 citations

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TL;DR: This study provides novel insight into defect engineering, as well as allows a pathway to design defect configuration and associated electronic function.
Abstract: Flexoelectric control of defect formation and associated electronic function is demonstrated in ferroelectric BiFeO3 thin films. An intriguing, so far never demonstrated, effect of internal electric field (Eint ) on defect formation is explored by a means of flexoelectricity. Our study provides novel insight into defect engineering, as well as allows a pathway to design defect configuration and associated electronic function.

87 citations

Journal ArticleDOI
TL;DR: The unique functionality of the defect dipole to control ferroelectric switching is visualized and can provide a foundation for novel ferro electric applications, such as high-density multilevel data storage.
Abstract: Active control of defect structures and associated polarization switching in a ferroelectric material is achieved without compromising its ferroelectric properties. Based on dipolar interaction between defect dipole and polarization, the unique functionality of the defect dipole to control ferroelectric switching is visualized. This approach can provide a foundation for novel ferroelectric applications, such as high-density multilevel data storage.

72 citations


Cited by
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Journal ArticleDOI
TL;DR: The applications of deep learning in machine health monitoring systems are reviewed mainly from the following aspects: Auto-encoder and its variants, Restricted Boltzmann Machines, Convolutional Neural Networks, and Recurrent Neural Networks.

1,569 citations

Journal ArticleDOI
TL;DR: Ferroelectric tunnel junctions represent a promising and flexible device design that is able to retain its information even when switched off, and to miniaturize such devices to the size of a few nanometres.
Abstract: Computer memory based on ferroelectric polarization is a promising alternative to technologies based, for example, on magnetism. Here, Garcia and Bibes review how ferroelectric tunnel junctions, where ferroelectric polarization controls electrical resistance, could improve the performance of these devices.

587 citations

Journal ArticleDOI
TL;DR: In this article, the authors focus on thin-film ferroelectric materials and, in particular, on the possibility of controlling their properties through the application of strain engineering in conventional and unconventional ways, and discuss several exciting possibilities for the development of new devices, including those in electronic, thermal, photovoltaic applications, and transduction sensors and actuators.
Abstract: Ferroelectric materials, because of their robust spontaneous electrical polarization, are widely used in various applications. Recent advances in modelling, synthesis and characterization techniques are spurring unprecedented advances in the study of these materials. In this Review, we focus on thin-film ferroelectric materials and, in particular, on the possibility of controlling their properties through the application of strain engineering in conventional and unconventional ways. We explore how the study of ferroelectric materials has expanded our understanding of fundamental effects, enabled the discovery of novel phases and physics, and allowed unprecedented control of materials properties. We discuss several exciting possibilities for the development of new devices, including those in electronic, thermal and photovoltaic applications, and transduction sensors and actuators. We conclude with a brief survey of the different directions that the field may expand to over the coming years. Strain engineering can be used to control the properties of thin-film ferroelectric materials, which are promising for electronic, thermal, photovoltaic and transduction applications. This Review addresses fundamental aspects, novel ways to control materials properties and the development of new ferroelectric-based devices.

533 citations

Journal ArticleDOI
TL;DR: In this paper, the thermodynamic and kinetic origins of the formation and stabilization of the frequently observed secondary, nonperovskite phases, such as Bi25FeO39 and Bi2Fe4O9, are discussed.
Abstract: Bismuth ferrite (BiFeO3), a perovskite material, rich in properties and with wide functionality, has had a marked impact on the field of multiferroics, as evidenced by the hundreds of articles published annually over the past 10 years. Studies from the very early stages and particularly those on polycrystalline BiFeO3 ceramics have been faced with difficulties in the preparation of the perovskite free of secondary phases. In this review, we begin by summarizing the major processing issues and clarifying the thermodynamic and kinetic origins of the formation and stabilization of the frequently observed secondary, nonperovskite phases, such as Bi25FeO39 and Bi2Fe4O9. The second part then focuses on the electrical and electromechanical properties of BiFeO3, including the electrical conductivity, dielectric permittivity, high-field polarization, and strain response, as well as the weak-field piezoelectric properties. We attempt to establish a link between these properties and address, in particular, the macroscopic response of the ceramics under an external field in terms of the dynamic interaction between the pinning centers (e.g., charged defects) and the ferroelectric/ferroelastic domain walls.

355 citations

Journal Article
TL;DR: Noh et al. as mentioned in this paper proposed a percolation model based on a network of circuit breakers with two switchable metastable states to explain the reversible resistance switching behavior in polycrystalline TiO2 thin capacitors.
Abstract: The existence of reversible resistance switching (RS) behaviors induced by electric stimulus has been known for some time, and these intriguing physical phenomena have been observed in numerous materials, including oxides. As conventional charge-based random access memory is expected to face a size limit in the near future, a surge of renewed interest has been developed in RS phenomena for possible applications in small nonvolatile memory devices called resistance random access memory (RRAM). Of particular interest is unipolar RS, which shows the RS at two values of applied voltage of the same polarity. The unipolar RS exhibits a much larger resistance change than other RS phenomena, and this greatly simplifies the process of reading the memory state. When fabricated with oxide p-n diodes, memory cells using unipolar RS can be stacked vertically, which has the potential for dramatically increasing memory density. Therefore, unipolar RRAM may be a good candidate for multi-stacked, high density, nonvolatile memory. The most important scientific and technical issues concerning unipolar RS are how it works and the identification of its controlling parameters. Some studies have reported that unipolar RS comes from a homogeneous/inhomogeneous transition of current distribution, while others maintain that it comes from the formation and rupture of conducting filaments. Even with recent extensive studies on unipolar RS, its basic origin is still far from being understood. In addition, no model exists that actually explains how the reversible switching can occur at two values of applied voltage. This lack of a quantitative model poses a major barrier for unipolar RRAM applications. In this study, we describe RS behavior in polycrystalline TiO2 film. To explain the basic mechanism of unipolar RS behavior, we propose a new percolation model based on a network of ‘‘circuit breakers’’ with two switchable metastable states. The random circuit breaker (RCB) network model can explain the long-standing material issue of how unipolar RS occurs. This simple percolation model is different from the conventional percolation models, which have dealt only with static or irreversible dynamic processes. In addition, the RCB network model provides an indication of how to overcome the substantial distribution of switching voltages, which is currently considered the most serious obstacle to practical unipolar RRAM applications. The unipolar RS phenomenon can be explained by the current (I)-voltage (V) curves in Figure 1a, which are derived from measurements of our polycrystalline TiO2 thin capacitors. At the pristine state (green dot), they are in an insulating state. As the external voltage Vext increases from zero and reaches a threshold voltage Vforming, a sudden increase occurs in the current. If the current is not limited to a certain value, here called the compliance current Icomp, the TiO2 capacitor would experience a dielectric breakdown and be destroyed. However, [*] Prof. T. W. Noh, S. C. Chae, S. B. Lee, S. H Chang, Dr. C. Liu ReCOE & FPRD, Department of Physics and Astronomy Seoul National University Seoul 151-747 (Korea) E-mail: twnoh@snu.ac.kr

302 citations