Showing papers in "Journal of Applied Physics in 2018"
TL;DR: This perspective article with a focus on recent results discusses how it has been possible to efficiently create, manipulate, and destroy nanometer-size skyrmions in device-compatible materials at room-temperature by all electrical means.
Abstract: Within a decade, the field of magnetic skyrmionics has developed from a niche prediction to a huge and active research field. Not only do magnetic skyrmions—magnetic whirls with a unique topology—reveal fundamentally new physics, but they have also risen to prominence as up-and-coming candidates for next-generation high-density efficient information encoding. Within a few years, it has been possible to efficiently create, manipulate, and destroy nanometer-size skyrmions in device-compatible materials at room-temperature by all electrical means. Despite the incredibly rapid progress, several challenges still remain to obtain fully functional and competitive skyrmion devices, as discussed in this perspective article with a focus on recent results.
433 citations
TL;DR: In this article, the performance of high voltage rectifiers and enhancement-mode metal-oxide field effect transistors on Ga2O3 has been evaluated and shown to benefit from the larger critical electric field relative to either SiC or GaN.
Abstract: Gallium oxide (Ga2O3) is emerging as a viable candidate for certain classes of power electronics with capabilities beyond existing technologies due to its large bandgap, controllable doping, and the availability of large diameter, relatively inexpensive substrates. These applications include power conditioning systems, including pulsed power for avionics and electric ships, solid-state drivers for heavy electric motors, and advanced power management and control electronics. Wide bandgap (WBG) power devices offer potential savings in both energy and cost. However, converters powered by WBG devices require innovation at all levels, entailing changes to system design, circuit architecture, qualification metrics, and even market models. The performance of high voltage rectifiers and enhancement-mode metal-oxide field effect transistors benefits from the larger critical electric field of β-Ga2O3 relative to either SiC or GaN. Reverse breakdown voltages of over 2 kV for β-Ga2O3 have been reported, either with or without edge termination and over 3 kV for a lateral field-plated Ga2O3 Schottky diode on sapphire. The metal-oxide-semiconductor field-effect transistors fabricated on Ga2O3 to date have predominantly been depletion (d-mode) devices, with a few demonstrations of enhancement (e-mode) operation. While these results are promising, what are the limitations of this technology and what needs to occur for it to play a role alongside the more mature SiC and GaN power device technologies? The low thermal conductivity might be mitigated by transferring devices to another substrate or thinning down the substrate and using a heatsink as well as top-side heat extraction. We give a perspective on the materials’ properties and physics of transport, thermal conduction, doping capabilities, and device design that summarizes the current limitations and future areas of development. A key requirement is continued interest from military electronics development agencies. The history of the power electronics device field has shown that new technologies appear roughly every 10-12 years, with a cycle of performance evolution and optimization. The older technologies, however, survive long into the marketplace, for various reasons. Ga2O3 may supplement SiC and GaN, but is not expected to replace them.
348 citations
TL;DR: This tutorial explains how THz-TDS measurements can be used to identify materials, determine complex refractive indices (phase delay and absorption), and extract conductivity and explores the basic concepts of TDS.
Abstract: Terahertz time-domain spectroscopy (THz-TDS) is a powerful technique for material’s characterization and process control. It has been used for contact-free conductivity measurements of metals, semiconductors, 2D materials, and superconductors. Furthermore, THz-TDS has been used to identify chemical components such as amino acids, peptides, pharmaceuticals, and explosives, which makes it particularly valuable for fundamental science, security, and medical applications. This tutorial is intended for a reader completely new to the field of THz-TDS and presents a basic understanding of THz-TDS. Hundreds of articles and many books can be consulted after reading this tutorial. We explore the basic concepts of TDS and discuss the relationship between temporal and frequency domain information. We illustrate how THz radiation can be generated and detected, and we discuss common noise sources and limitations for THz-TDS. This tutorial concludes by discussing some common experimental scenarios and explains how THz-TDS measurements can be used to identify materials, determine complex refractive indices (phase delay and absorption), and extract conductivity.
292 citations
TL;DR: In this article, the temperature averaged entropy change is introduced as a suitable early indicator of the material's utility for magnetocaloric cooling applications, and its adoption by the caloric community is recommended.
Abstract: The efficient use of reversible thermal effects in magnetocaloric, electrocaloric, and elastocaloric materials is a promising avenue that can lead to a substantially increased efficiency of refrigeration and heat pumping devices, most importantly, those used in household and commercial cooling applications near ambient temperature. A proliferation in caloric material research has resulted in a wide array of materials where only the isothermal change in entropy in response to a handful of different field strengths over a limited range of temperatures has been evaluated and reported. Given the abundance of such data, there is a clear need for a simple and reliable figure of merit enabling fast screening and down-selection to justify further detailed characterization of those material systems that hold the greatest promise. Based on the analysis of several well-known materials that exhibit vastly different magnetocaloric effects, the Temperature averaged Entropy Change is introduced as a suitable early indicator of the material's utility for magnetocaloric cooling applications, and its adoption by the caloric community is recommended.
208 citations
IBM1
TL;DR: There is a significant need to build efficient non-von Neumann computing systems for highly data-centric artificial intelligence related applications and, in particular, phase-change memory (PCM), arguably the most advanced emerging non-volatile memory technology.
Abstract: There is a significant need to build efficient non-von Neumann computing systems for highly data-centric artificial intelligence related applications. Brain-inspired computing is one such approach that shows significant promise. Memory is expected to play a key role in this form of computing and, in particular, phase-change memory (PCM), arguably the most advanced emerging non-volatile memory technology. Given a lack of comprehensive understanding of the working principles of the brain, brain-inspired computing is likely to be realized in multiple levels of inspiration. In the first level of inspiration, the idea would be to build computing units where memory and processing co-exist in some form. Computational memory is an example where the physical attributes and the state dynamics of memory devices are exploited to perform certain computational tasks in the memory itself with very high areal and energy efficiency. In a second level of brain-inspired computing using PCM devices, one could design a co-processor comprising multiple cross-bar arrays of PCM devices to accelerate the training of deep neural networks. PCM technology could also play a key role in the space of specialized computing substrates for spiking neural networks, and this can be viewed as the third level of brain-inspired computing using these devices.
188 citations
TL;DR: In this article, the authors discuss the basics of the ultrafast laser-based time-domain thermoreflectance (TDTR) technique and its applications in the thermal characterization of a variety of materials.
Abstract: Measuring thermal properties of materials is not only of fundamental importance in understanding the transport processes of energy carriers (electrons and phonons in solids) but also of practical interest in developing novel materials with desired thermal properties for applications in energy conversion and storage, electronics, and photonic systems. Over the past two decades, ultrafast laser-based time-domain thermoreflectance (TDTR) has emerged and evolved as a reliable, powerful, and versatile technique to measure the thermal properties of a wide range of bulk and thin film materials and their interfaces. This tutorial discusses the basics as well as the recent advances of the TDTR technique and its applications in the thermal characterization of a variety of materials. The tutorial begins with the fundamentals of the TDTR technique, serving as a guideline for understanding the basic principles of this technique. Several variations of the TDTR technique that function similarly as the standard TDTR but with their own unique features are introduced, followed by introducing different advanced TDTR configurations that were developed to meet different measurement conditions. This tutorial closes with a summary that discusses the current limitations and proposes some directions for future development.
168 citations
TL;DR: In this article, the status of memristor-based neuromorphic computation was analyzed on the basis of papers and patents to identify the competitiveness of the Memristor properties by reviewing industrial trends and academic pursuits.
Abstract: Neuromorphic computation is one of the axes of parallel distributed processing, and memristor-based synaptic weight is considered as a key component of this type of computation. However, the material properties of memristors, including material related physics, are not yet matured. In parallel with memristors, CMOS based Graphics Processing Unit, Field Programmable Gate Array, and Application Specific Integrated Circuit are also being developed as dedicated artificial intelligence (AI) chips for fast computation. Therefore, it is necessary to analyze the competitiveness of the memristor-based neuromorphic device in order to position the memristor in the appropriate position of the future AI ecosystem. In this article, the status of memristor-based neuromorphic computation was analyzed on the basis of papers and patents to identify the competitiveness of the memristor properties by reviewing industrial trends and academic pursuits. In addition, material issues and challenges are discussed for implementing the memristor-based neural processor.
151 citations
TL;DR: This tutorial describes challenges and possible avenues for the implementation of the components of a solid-state system, which emulates a biological brain, and compares the main differences between a conventional computational machine, based on the Turing-von Neumann paradigm, and a neuromorphic machine, which tries to emulate important functionalities of a Biological brain.
Abstract: This tutorial describes challenges and possible avenues for the implementation of the components of a solid-state system, which emulates a biological brain. The tutorial is devoted mostly to a charge-based (i.e. electric controlled) implementation using transition metal oxide materials, which exhibit unique properties that emulate key functionalities needed for this application. In Sec. I, we compare the main differences between a conventional computational machine, based on the Turing-von Neumann paradigm, and a neuromorphic machine, which tries to emulate important functionalities of a biological brain. We also describe the main electrical properties of biological systems, which would be useful to implement in a charge-based system. In Sec. II, we describe the main components of a possible solid-state implementation. In Sec. III, we describe a variety of Resistive Switching phenomena, which may serve as the functional basis for the implementation of key devices for neuromorphic computing. In Sec. IV, we describe why transition metal oxides are promising materials for future neuromorphic machines. Theoretical models describing different resistive switching mechanisms are discussed in Sec. V, while existing implementations are described in Sec. VI. Section VII presents applications to practical problems. We list in Sec. VIII important basic research challenges and open issues. We discuss issues related to specific implementations, novel materials, devices, and phenomena. The development of reliable, fault tolerant, energy efficient devices, their scaling, and integration into a neuromorphic computer may bring us closer to the development of a machine that rivals the brain.
147 citations
TL;DR: In this paper, the authors describe the structure, operation, and characterization of organic field effect transistor (OFET) and highlight several measurements involving OFETs that allow access to fundamental properties of organic semiconductors and the mechanism of charge transport.
Abstract: Chemical versatility and compatibility with a vast array of processing techniques has led to the incorporation of organic semiconductors in various electronic and opto-electronic devices. One such device is the organic field-effect transistor (OFET). In this tutorial, we describe the structure, operation, and characterization of OFETs. Following a short historical perspective, we introduce the architectures possible for OFETs and then describe the device physics and the methods for extracting relevant device parameters. We then provide a brief overview of the myriad organic semiconductors and deposition methods that were adopted for OFETs in the past decades. Non-ideal device characteristics, including contact resistance, are then discussed along with their effects on electrical performance and on the accuracy of extracting device parameters. Finally, we highlight several measurements involving OFETs that allow access to fundamental properties of organic semiconductors and the mechanism of charge transport in these materials.
119 citations
TL;DR: In this paper, the authors examine the interfaces between components of water systems and the water-based fluids themselves and survey opportunities for scientists and engineers to reveal new insights into their function and to design novel technologies for next-generation solutions to our collective energy-water challenges.
Abstract: Energy and water are deeply interconnected, and each sector is both central to society and under increasing stress. Innovations in materials will be a powerful tool in efforts to overcome these challenges by providing sustainable solutions to treating water and rendering it fit-for-purpose with minimal expenditure of energy and other resources. Interfaces between components of water systems and the water-based fluids themselves govern the performance of the vast majority of water treatment and conveyance processes. This perspective examines many of these interfaces, ranging from those in sorbents and sensors to membranes and catalysts, and surveys opportunities for scientists and engineers to reveal new insights into their function and, thereby, to design novel technologies for next-generation solutions to our collective energy-water challenges.
110 citations
TL;DR: The most relevant aspects of Artificial Neural Networks and delay systems are introduced, the seminal experimental demonstrations of Reservoir Computing in photonic delay systems, plus the most recent and advanced realizations are explained.
Abstract: Photonic delay systems have revolutionized the hardware implementation of Recurrent Neural Networks and Reservoir Computing in particular. The fundamental principles of Reservoir Computing strongly facilitate a realization in such complex analog systems. Especially delay systems, which potentially provide large numbers of degrees of freedom even in simple architectures, can efficiently be exploited for information processing. The numerous demonstrations of their performance led to a revival of photonic Artificial Neural Network. Today, an astonishing variety of physical substrates, implementation techniques as well as network architectures based on this approach have been successfully employed. Important fundamental aspects of analog hardware Artificial Neural Networks have been investigated, and multiple high-performance applications have been demonstrated. Here, we introduce and explain the most relevant aspects of Artificial Neural Networks and delay systems, the seminal experimental demonstrations of Reservoir Computing in photonic delay systems, plus the most recent and advanced realizations.
TL;DR: The delay-coupled electromechanical system performed well on time series classification tasks, with error rates below 0.1% for the 1st, 2nd, and 3rd order parity benchmarks and an accuracy of 78 ± 2 for the TI-46 spoken word recognition benchmark.
Abstract: Reservoir computing was achieved by constructing a network of virtual nodes multiplexed in time and sharing a single silicon beam exhibiting a classical Duffing non-linearity as the source of nonlinearity. The delay-coupled electromechanical system performed well on time series classification tasks, with error rates below 0.1% for the 1st, 2nd, and 3rd order parity benchmarks and an accuracy of ( 78 ± 2 ) % for the TI-46 spoken word recognition benchmark. As a first demonstration of reservoir computing using a non-linear mass-spring system in MEMS, this result paves the way to the creation of a new class of compact devices combining the functions of sensing and computing.
TL;DR: In this article, the authors compared the near-band-edge emission in various quality GaN samples, in order to identify the origin and to determine the capture-cross-section of the major intrinsic nonradiative recombination centers (NRCs).
Abstract: The nonradiative lifetime (τNR) of the near-band-edge emission in various quality GaN samples is compared with the results of positron annihilation measurement, in order to identify the origin and to determine the capture-cross-section of the major intrinsic nonradiative recombination centers (NRCs). The room-temperature τNR of various n-type GaN samples increased with decreasing the concentration of divacancies composed of a Ga vacancy (VGa) and a N vacancy (VN), namely, VGaVN. The τNR value also increased with increasing the diffusion length of positrons, which is almost proportional to the inverse third root of the gross concentration of all point defects. The results indicate that major intrinsic NRC in n-type GaN is VGaVN. From the relationship between its concentration and τNR, its hole capture-cross-section is estimated to be about 7 × 10−14 cm2. Different from the case of 4H-SiC, the major NRCs in p-type and n-type GaN are different: the major NRCs in Mg-doped p-type GaN epilayers are assigned to ...
TL;DR: In this paper, an elastic metasurface for splitting SV- and P-waves is designed and demonstrated using full wave finite element simulations, which is capable of modulating the phase change of SV-wave while keeping the phase of P-wave unchanged.
Abstract: Although recent advances have made it possible to manipulate electromagnetic and acoustic wavefronts with sub-wavelength metasurface slabs, the design of elastodynamic counterparts remains challenging. We introduce a novel but simple design approach to control SV-waves in elastic solids. The proposed metasurface can be fabricated by cutting an array of aligned parallel cracks in a solid such that the materials between the cracks act as plate-like waveguides in the background medium. The plate array is capable of modulating the phase change of SV-wave while keeping the phase of P-wave unchanged. An analytical model for SV-wave incidence is established to calculate the transmission coefficient and the transmitted phase through the plate-like waveguide explicitly. A complete 2π range of phase delay is achieved by selecting different thicknesses for the plates. An elastic metasurface for splitting SV- and P-waves is designed and demonstrated using full wave finite element simulations. Two metasurfaces for focusing plane and cylindrical SV-waves are also presented.
TL;DR: In this article, the challenges of attaining red luminescence from GaN under current injection and the methods that have been developed to circumvent them are addressed and a large emphasis is placed on the recent developments of doping GaN with Eu3+ to achieve an efficient red GaN-based LED.
Abstract: While InGaN/GaN blue and green light-emitting diodes (LEDs) are commercially available, the search for an efficient red LED based on GaN is ongoing. The realization of this LED is crucial for the monolithic integration of the three primary colors and the development of nitride-based full-color high-resolution displays. In this perspective, we will address the challenges of attaining red luminescence from GaN under current injection and the methods that have been developed to circumvent them. While several approaches will be mentioned, a large emphasis will be placed on the recent developments of doping GaN with Eu3+ to achieve an efficient red GaN-based LED. Finally, we will provide an outlook to the future of this material as a candidate for small scale displays such as mobile device screens or micro-LED displays.
TL;DR: In this article, a deep-subwavelength absorber based on the concept of coiled-up space was investigated and it was found that the resonance frequency of the absorber is easily tuned and near-total absorption is acquired under a fixed deep subwavelength thickness.
Abstract: This paper presents a theoretical, numerical, and experimental investigation of a deep-subwavelength absorber based on the concept of coiled-up space. By adjusting a partition panel in the cavity to form an unequal-section channel, it is found that the resonance frequency of the absorber is easily tuned and near-total absorption is acquired under a fixed deep-subwavelength thickness. The absorption mechanism induced by nearly critical coupling is revealed by graphically analyzing the reflection coefficient in the complex plane. In contrast to conventional techniques, near-total absorption can be adjusted over a wider frequency range. To further enhance the absorption, we demonstrate a broadband absorber with a relative bandwidth up to 33.3%.
TL;DR: In this article, the authors review the basic principles of magnetometry and present a representative discussion of artifacts which can occur in studying samples like soft magnetic materials as well as low moment samples.
Abstract: In the field of nanomagnetism and spintronics, integral magnetometry is nowadays challenged by samples with low magnetic moments and/or low coercive fields. Commercial superconducting quantum interference device magnetometers are versatile experimental tools to magnetically characterize samples with ultimate sensitivity as well as with a high degree of automation. For realistic experimental conditions, the as-recorded magnetic signal contains several artifacts, especially if small signals are measured on top of a large magnetic background or low magnetic fields are required. In this Tutorial, we will briefly review the basic principles of magnetometry and present a representative discussion of artifacts which can occur in studying samples like soft magnetic materials as well as low moment samples. It turns out that special attention is needed to quantify and correct the residual fields of the superconducting magnet to derive useful information from integral magnetometry while pushing the limits of detection and to avoid erroneous conclusions.
TL;DR: In this article, the authors study the manifestations of ion migration in frequency-domain small-signal measurements, focusing on the popular technique of Electrical Impedance Spectroscopy (EIS).
Abstract: Perovskite solar cells are notorious for exhibiting transient behavior not seen in conventional inorganic semiconductor devices. Significant inroads have been made into understanding this fact in terms of rapid ion migration, now a well-established property of the prototype photovoltaic perovskite MAPbI 3 and strongly implicated in the newer mixed compositions. Here, we study the manifestations of ion migration in frequency-domain small-signal measurements, focusing on the popular technique of Electrical Impedance Spectroscopy (EIS). We provide new interpretations for a variety of previously puzzling features, including giant photoinduced low-frequency capacitance and negative capacitance in a variety of forms. We show that these apparently strange measurements can be rationalized by the splitting of AC current into two components, one associated with charge-storage and the other with the quasi-steady-state recombination current of electrons and holes. The latter contribution to the capacitance can take either a positive or a negative sign and is potentially very large when slow, voltage-sensitive processes such as ion migration are at play. Using numerical drift-diffusion semiconductor models, we show that giant photoinduced capacitance, inductive loop features, and low-frequency negative capacitance all emerge naturally as consequences of ion migration via its coupling to quasi-steady-state electron and hole currents. In doing so, we unify the understanding of EIS measurements with the comparably well-developed theory of rate dependent current-voltage (I-V) measurements in perovskite cells. Comparing the two techniques, we argue that EIS is more suitable for quantifying I-V hysteresis than conventional methods based on I-V sweeps and demonstrate this application on a variety of cell types.
TL;DR: A statistical model is developed that describes both the cumulative conductance evolution and conductance drift and is used to simulate the supervised training of both spiking and non-spiking artificial neuronal networks.
Abstract: Phase-change memory (PCM) is an emerging non-volatile memory technology that is based on the reversible and rapid phase transition between the amorphous and crystalline phases of certain phase-change materials. The ability to alter the conductance levels in a controllable way makes PCM devices particularly well-suited for synaptic realizations in neuromorphic computing. A key attribute that enables this application is the progressive crystallization of the phase-change material and subsequent increase in device conductance by the successive application of appropriate electrical pulses. There is significant inter- and intra-device randomness associated with this cumulative conductance evolution, and it is essential to develop a statistical model to capture this. PCM also exhibits a temporal evolution of the conductance values (drift), which could also influence applications in neuromorphic computing. In this paper, we have developed a statistical model that describes both the cumulative conductance evolution and conductance drift. This model is based on extensive characterization work on 10 000 memory devices. Finally, the model is used to simulate the supervised training of both spiking and non-spiking artificial neuronal networks.
TL;DR: In this article, the most widely used junction spectroscopy approaches for characterizing deep-level defects in semiconductors and present some of the early work on which the principles of today's methodology are based.
Abstract: The term junction spectroscopy embraces a wide range of techniques used to explore the properties of semiconductor materials and semiconductor devices. In this tutorial review, we describe the most widely used junction spectroscopy approaches for characterizing deep-level defects in semiconductors and present some of the early work on which the principles of today's methodology are based. We outline ab-initio calculations of defect properties and give examples of how density functional theory in conjunction with formation energy and marker methods can be used to guide the interpretation of experimental results. We review recombination, generation, and trapping of charge carriers associated with defects. We consider thermally driven emission and capture and describe the techniques of Deep Level Transient Spectroscopy (DLTS), high resolution Laplace DLTS, admittance spectroscopy, and scanning DLTS. For the study of minority carrier related processes and wide gap materials, we consider Minority Carrier Trans...
TL;DR: In this paper, the authors studied the charge carrier transport and electroluminescence (EL) in thin-film polycrystalline (poly-) GaN/c-Si heterojunction diodes realized using a plasma enhanced atomic layer deposition process.
Abstract: In this work, we study the charge carrier transport and electroluminescence (EL) in thin-film polycrystalline (poly-) GaN/c-Si heterojunction diodes realized using a plasma enhanced atomic layer deposition process. The fabricated poly-GaN/p-Si diode with a native oxide at the interface showed a rectifying behavior (Ion/Ioff ratio ∼ 103 at ±3 V) with current-voltage characteristics reaching an ideality factor n of ∼5.17. The areal (Ja) and peripheral (Jp) components of the current density were extracted, and their temperature dependencies were studied. The space charge limited current (SCLC) in the presence of traps is identified as the dominant carrier transport mechanism for Ja in forward bias. An effective trap density of 4.6 × 1017/cm3 at a trap energy level of 0.13 eV below the GaN conduction band minimum was estimated by analyzing Ja. Other basic electrical properties of the material such as the free carrier concentration, effective density of states in the conduction band, electron mobility, and dielectric relaxation time were also determined from the current-voltage analysis in the SCLC regime. Further, infrared EL corresponding to the Si bandgap was observed from the fabricated diodes. The observed EL intensity from the GaN/p-Si heterojunction diode is ∼3 orders of magnitude higher as compared to the conventional Si only counterpart. The enhanced infrared light emission is attributed to the improved injector efficiency of the GaN/Si diode because of the wide bandgap of the poly-GaN layer and the resulting band discontinuity at the GaN/Si interface.In this work, we study the charge carrier transport and electroluminescence (EL) in thin-film polycrystalline (poly-) GaN/c-Si heterojunction diodes realized using a plasma enhanced atomic layer deposition process. The fabricated poly-GaN/p-Si diode with a native oxide at the interface showed a rectifying behavior (Ion/Ioff ratio ∼ 103 at ±3 V) with current-voltage characteristics reaching an ideality factor n of ∼5.17. The areal (Ja) and peripheral (Jp) components of the current density were extracted, and their temperature dependencies were studied. The space charge limited current (SCLC) in the presence of traps is identified as the dominant carrier transport mechanism for Ja in forward bias. An effective trap density of 4.6 × 1017/cm3 at a trap energy level of 0.13 eV below the GaN conduction band minimum was estimated by analyzing Ja. Other basic electrical properties of the material such as the free carrier concentration, effective density of states in the conduction band, electron mobility, and die...
TL;DR: In this paper, the impact of Al, Y, and La dopants on the stabilization of the ferroelectric Pca21 phase in HfO2 was investigated in a comprehensive first-principles study.
Abstract: III-valent dopants have shown to be most effective in stabilizing the ferroelectric, crystalline phase in atomic layer deposited, polycrystalline HfO2 thin films. On the other hand, such dopants are commonly used for tetragonal and cubic phase stabilization in ceramic HfO2. This difference in the impact has not been elucidated so far. The prospect is a suitable doping to produce ferroelectric HfO2 ceramics with a technological impact. In this paper, we investigate the impact of Al, Y, and La doping, which have experimentally proven to stabilize the ferroelectric Pca21 phase in HfO2, in a comprehensive first-principles study. Density functional theory calculations reveal the structure, formation energy, and total energy of various defects in HfO2. Most relevant are substitutional electronically compensated defects without oxygen vacancy, substitutional mixed compensated defects paired with a vacancy, and ionically compensated defect complexes containing two substitutional dopants paired with a vacancy. The...
TL;DR: In this article, the authors discuss how to employ one such property, memory (time non-locality), in a novel physics-based approach to computation, and focus on digital memcomputing machines (DMMs) that are scalable.
Abstract: It is well known that physical phenomena may be of great help in computing some difficult problems efficiently. A typical example is prime factorization that may be solved in polynomial time by exploiting quantum entanglement on a quantum computer. There are, however, other types of (non-quantum) physical properties that one may leverage to compute efficiently a wide range of hard problems. In this perspective, we discuss how to employ one such property, memory (time non-locality), in a novel physics-based approach to computation: Memcomputing. In particular, we focus on digital memcomputing machines (DMMs) that are scalable. DMMs can be realized with non-linear dynamical systems with memory. The latter property allows the realization of a new type of Boolean logic, one that is self-organizing. Self-organizing logic gates are “terminal-agnostic,” namely, they do not distinguish between the input and output terminals. When appropriately assembled to represent a given combinatorial/optimization problem, the corresponding self-organizing circuit converges to the equilibrium points that express the solutions of the problem at hand. In doing so, DMMs take advantage of the long-range order that develops during the transient dynamics. This collective dynamical behavior, reminiscent of a phase transition, or even the “edge of chaos,” is mediated by families of classical trajectories (instantons) that connect critical points of increasing stability in the system's phase space. The topological character of the solution search renders DMMs robust against noise and structural disorder. Since DMMs are non-quantum systems described by ordinary differential equations, not only can they be built in hardware with the available technology, they can also be simulated efficiently on modern classical computers. As an example, we will show the polynomial-time solution of the subset-sum problem for the worst cases, and point to other types of hard problems where simulations of DMMs' equations of motion on classical computers have already demonstrated substantial advantages over traditional approaches. We conclude this article by outlining further directions of study.
TL;DR: In this paper, an alternate explanation for the negative capacitance (NC) effect in ferroelectrics (FE) has been proposed, in which the steady state polarization strictly increases with the voltage across the FE and show that despite the inherent positive FE capacitance, reduction in FE voltage with the increase in its charge is possible in a R-FE network as well as in a ferroelectric-dielectric (FE-DE) stack.
Abstract: In this paper, we describe and analytically substantiate an alternate explanation for the negative capacitance (NC) effect in ferroelectrics (FE). We claim that the NC effect previously demonstrated in resistance-ferroelectric (R-FE) networks does not necessarily validate the existence of “S” shaped relation between polarization and voltage (according to Landau theory). In fact, the NC effect can be explained without invoking the “S”-shaped behavior of FE. We employ an analytical model for FE (Miller model) in which the steady state polarization strictly increases with the voltage across the FE and show that despite the inherent positive FE capacitance, reduction in FE voltage with the increase in its charge is possible in a R-FE network as well as in a ferroelectric-dielectric (FE-DE) stack. This can be attributed to a large increase in FE capacitance near the coercive voltage coupled with the polarization lag with respect to the electric field. Under certain conditions, these two factors yield transient NC effect. We analytically derive conditions for NC effect in R-FE and FE-DE networks. We couple our analysis with extensive simulations to explain the evolution of NC effect. We also compare the trends predicted by the aforementioned Miller model with Landau-Khalatnikov (L-K) model (static negative capacitance due to “S”-shape behaviour) and highlight the differences between the two approaches. First, with an increase in external resistance in the R-FE network, NC effect shows a non-monotonic behavior according to Miller model but increases according to L-K model. Second, with the increase in ramp-rate of applied voltage in the FE-DE stack, NC effect increases according to Miller model but decreases according to L-K model. These results unveil a possible way to experimentally validate the actual reason of NC effect in FE.
TL;DR: In this paper, the authors present an overview of the hysteresis in a reactive magnetron sputtering process and the possibilities to eliminate them in a stable operative sense using phenomenological global models.
Abstract: Reactive magnetron sputtering is a well-established physical vapor technique to deposit thin compound films on different substrates, ranging from insulating glass windows over wear-resistant car parts to high-responsive touch screens. In this way, the industrial and technological relevance drives the need to understand this process on a more profound level to make optimal use of it. Notwithstanding, the basic principles of the technique can be summarized on a single sheet of paper, and truly mastering and understanding the process behavior is not a simple task. One of the main reasons is the often strong non-linear response of the reactive system to changes in the operation parameters or to small system fluctuations. This aspect of reactive sputtering is embodied by the occurrence of a hysteresis in the system observables as a function of the operation parameters. It is the existence of the hysteresis that troubles optimal deposition and process control on the one hand and gives voice to the intertwined physical and chemical complexity on the other hand. The aim of this tutorial can be considered as threefold: to acquaint the reader with an insight into the concept of the hysteresis during reactive sputtering, to touch some of the possibilities to eliminate the hysteresis, and finally, to present how to control this hysteresis in a stable operative sense. To this end, the reactive magnetron sputtering process will be formulated in practical parameters and by two discriminating phenomenological global models: the original Berg model and the reactive sputtering deposition (RSD) model. The reactive sputtering of Al in an O 2/Ar atmosphere under direct discharge current control will be used as a reference system. The models are able to describe the hysteresis effects, giving an insight into their origin and the possibilities to eliminate them. The discharge description can, in this context, be reduced to the current/voltage or I V-characteristic and its response to a changing target state. The tutorial concludes with the existence of a double hysteresis effect and an explanation based on the RSD model.
TL;DR: In this paper, the impact ionization coefficient (IIC) of a valence-band electron and an excited electron is computed from the matrix elements of a screened Coulomb operator.
Abstract: A theoretical investigation of extremely high field transport in an emerging wide-bandgap material β-Ga2O3 is reported from first principles. The signature high-field effect explored here is impact ionization. The interaction between a valence-band electron and an excited electron is computed from the matrix elements of a screened Coulomb operator. Maximally localized Wannier functions are utilized in computing the impact ionization rates. A full-band Monte Carlo simulation is carried out incorporating the impact ionization rates and electron-phonon scattering rates. This work brings out valuable insights into the impact ionization coefficient (IIC) of electrons in β-Ga2O3. The isolation of the Γ point conduction band minimum by a significantly high energy from other satellite band pockets plays a vital role in determining ionization co-efficients. IICs are calculated for electric fields ranging up to 8 MV/cm for different crystal directions. A Chynoweth fitting of the computed IICs is done to calibrate ionization models in device simulators.
TL;DR: Deep level defects were characterized in Ge-doped (010) β-Ga2O3 layers grown by plasma-assisted molecular beam epitaxy (PAMBE) using deep level optical spectroscopy (DLOS) and deep level transient spectral analysis (DLTS) as mentioned in this paper.
Abstract: Deep level defects were characterized in Ge-doped (010) β-Ga2O3 layers grown by plasma-assisted molecular beam epitaxy (PAMBE) using deep level optical spectroscopy (DLOS) and deep level transient (thermal) spectroscopy (DLTS) applied to Ni/β-Ga2O3:Ge (010) Schottky diodes that displayed Schottky barrier heights of 1.50 eV. DLOS revealed states at EC − 2.00 eV, EC − 3.25 eV, and EC − 4.37 eV with concentrations on the order of 1016 cm−3, and a lower concentration level at EC − 1.27 eV. In contrast to these states within the middle and lower parts of the bandgap probed by DLOS, DLTS measurements revealed much lower concentrations of states within the upper bandgap region at EC − 0.1 – 0.2 eV and EC − 0.98 eV. There was no evidence of the commonly observed trap state at ∼EC − 0.82 eV that has been reported to dominate the DLTS spectrum in substrate materials synthesized by melt-based growth methods such as edge defined film fed growth (EFG) and Czochralski methods [Zhang et al., Appl. Phys. Lett. 108, 052105 (2016) and Irmscher et al., J. Appl. Phys. 110, 063720 (2011)]. This strong sensitivity of defect incorporation on crystal growth method and conditions is unsurprising, which for PAMBE-grown β-Ga2O3:Ge manifests as a relatively “clean” upper part of the bandgap. However, the states at ∼EC − 0.98 eV, EC − 2.00 eV, and EC − 4.37 eV are reminiscent of similar findings from these earlier results on EFG-grown materials, suggesting that possible common sources might also be present irrespective of growth method.
TL;DR: In this article, a modified metamaterial beam was proposed for simultaneous vibration suppression and energy harvesting, where local resonators were alternately coupled and each resonator was associated with a piezoelectric element for converting vibrations into electrical energy.
Abstract: The paper proposes a modified metamaterial beam for simultaneous vibration suppression and energy harvesting. Local resonators in the modified metamaterial beam are alternately coupled, and each resonator is associated with a piezoelectric element for converting vibrations into electrical energy. First, the mathematical model of the modified metamaterial beam based piezoelectric energy harvester (PEH) is developed. The vibration suppression and energy harvesting performances of this system are analysed and compared with those of a conventional metamaterial beam PEH. The analytical results predict that not only the energy harvesting performance can be massively reinforced in the low frequency range, but also the vibration suppression performance can be slightly enhanced due to the appearance of an additional band gap. Subsequently, two finite element models, Models A and B, are developed. Model A is expected to be equivalent to the analytical model for validation and the local oscillators represented by lumped parameters in the analytical model are modelled by using cantilevers with tip masses. These tip masses are alternately coupled with ideal springs. The finite element analysis results in terms of both vibration suppression and energy harvesting show good agreement with the analytical results. Finally, to propose a more practical design of the internal coupling, Model B is established. Every two neighbouring tip masses are alternately coupled by using a beam connection. The finite element analysis results show that Model B is not completely equivalent to the proposed analytical model: no significant enhancement in terms of energy harvesting but a remarkably enhanced vibration suppression performance.
TL;DR: An example of studies on an artificial synapse based on spintronics and its application to artificial neural networks is reviewed.
Abstract: While digital integrated circuits with von Neumann architectures, having exponentially evolved for half a century, are an indispensable building block of today's information society, recently growing demand on executing more complex tasks like the human brain has allowed a revisit to the architecture of information processing. Brain-inspired hardware using artificial neural networks is expected to offer a complementary approach to deal with complex problems. Since the neuron and synapse are key components of brains, most of the mathematical models of artificial neural networks require artificial neurons and synapses. Consequently, much effort has been devoted to creating artificial neurons and synapses using various solid-state systems with ferroelectric materials, phase-change materials, oxide-based memristive materials, and so on. Here, we review an example of studies on an artificial synapse based on spintronics and its application to artificial neural networks. The spintronic synapse, having analog and nonvolatile memory functionality, consists of an antiferromagnet/ferromagnet heterostructure and is operated by spin-orbit torque. After giving an overview of this field, we describe the operation principle and results of analog magnetization switching of the spintronic synapse. We then review a proof-of-concept demonstration of the artificial neural network with 36 spintronic synapses, where an associative memory operation based on the Hopfield model is performed and the learning ability of the spintronic synapses is confirmed, showing promise for low-power neuromorphic computation.
TL;DR: In this article, a water-based metamaterial absorber was proposed to achieve the broadband absorption at microwave frequencies and optical transparence simultaneously, where the water is encapsulated between the ITO backed plate and PMMA, serving as the microwave loss as well as optically transparent material.
Abstract: Naturally occurring water is a promising candidate for achieving broadband absorption. In this work, by virtue of the optically transparent character of the water, the water-based metamaterial absorbers (MAs) are proposed to achieve the broadband absorption at microwave frequencies and optical transparence simultaneously. For this purpose, the transparent indium tin oxide (ITO) and polymethyl methacrylate (PMMA) are chosen as the constitutive materials. The water is encapsulated between the ITO backed plate and PMMA, serving as the microwave loss as well as optically transparent material. Numerical simulations show that the broadband absorption with the efficiency over 90% in the frequency band of 6.4–30 GHz and highly optical transparency of about 85% in the visible region can be achieved and have been well demonstrated experimentally. Additionally, the proposed water-based MA displays a wide-angle absorption performance for both TE and TM waves and is also robust to the variations of the structure parameters, which is much desired in a practical application.