New model dielectric function and exchange-correlation potential for semiconductors and insulators

Levine, Zachary H.; Louie, Steven G.

doi:10.1103/physrevb.25.6310

Cited by 262 publications

(128 citation statements)

References 26 publications

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“…We have therefore found that the solution of the BSE, when the screening of the Coulomb interaction is explicitly calculated at the RPA level rather than obtained from model dielectric functions [19,[41][42][43], is able to reproduce and explain the NRIXS data. This is confirmed by the direct comparison between the calculated and experimental spectra (see Appendix).…”

Section: Resultsmentioning

confidence: 99%

Exciton energy-momentum map of hexagonal boron nitride

et al. 2015

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Understanding and controlling the way excitons propagate in solids is a key for tailoring materials with improved optoelectronic properties. A fundamental step in this direction is the determination of the exciton energy-momentum dispersion. Here, thanks to the solution of the parameter-free Bethe-Salpeter equation (BSE), we draw and explain the exciton energy-momentum map of hexagonal boron nitride (h-BN) in the first three Brillouin zones. We show that h-BN displays strong excitonic effects not only in the optical spectra at vanishing momentum q, as previously reported, but also at large q. We validate our theoretical predictions by assessing the calculated exciton map by means of an inelastic x-ray scattering (IXS) experiment. Moreover, we solve the discrepancies between previous experimental data and calculations, proving then that the BSE is highly accurate through the whole momentum range. Therefore, these results put forward the combination BSE and IXS as the tool of choice for addressing the exciton dynamics in complex materials.

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Section: Resultsmentioning

confidence: 99%

Exciton energy-momentum map of hexagonal boron nitride

et al. 2015

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“…• The model dielectric function (Levine and Louie, 1982;Hybertsen and Louie, 1988;Bechstedt, Del Sole, et al, 1992). These approaches allow one to considerably reduce the computational effort or even to avoid completely the ab initio calculation of .…”

Section: A Evaluation Of the Green's Function Gmentioning

confidence: 99%

Electronic excitations: density-functional versus many-body Green’s-function approaches

2002

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Electronic excitations lie at the origin of most of the commonly measured spectra. However, the first-principles computation of excited states requires a larger effort than ground-state calculations, which can be very efficiently carried out within density-functional theory. On the other hand, two theoretical and computational tools have come to prominence for the description of electronic excitations. One of them, many-body perturbation theory, is based on a set of Green's-function equations, starting with a one-electron propagator and considering the electron-hole Green's function for the response. Key ingredients are the electron's self-energy ⌺ and the electron-hole interaction. A good approximation for ⌺ is obtained with Hedin's GW approach, using density-functional theory as a zero-order solution. First-principles GW calculations for real systems have been successfully carried out since the 1980s. Similarly, the electron-hole interaction is well described by the Bethe-Salpeter equation, via a functional derivative of ⌺. An alternative approach to calculating electronic excitations is the time-dependent density-functional theory (TDDFT), which offers the important practical advantage of a dependence on density rather than on multivariable Green's functions. This approach leads to a screening equation similar to the Bethe-Salpeter one, but with a two-point, rather than a four-point, interaction kernel. At present, the simple adiabatic local-density approximation has given promising results for finite systems, but has significant deficiencies in the description of absorption spectra in solids, leading to wrong excitation energies, the absence of bound excitonic states, and appreciable distortions of the spectral line shapes. The search for improved TDDFT potentials and kernels is hence a subject of increasing interest. It can be addressed within the framework of many-body perturbation theory: in fact, both the Green's functions and the TDDFT approaches profit from mutual insight. This review compares the theoretical and practical aspects of the two approaches and their specific numerical implementations, and presents an overview of accomplishments and work in progress. CONTENTS

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“…This process is critical for example in the avalanche breakdown of semiconductor junctions, and is a detrimental effect in short channel MOS devices in terms of excess substrate current and decreased reliability. The ionization rate of valence electrons by energetic conduction band electrons is usually described by Fermi's rule in which a screened Coulomb interaction is assumed between the two particles, where screening is described by an appropriate dielectric function such as that proposed by Levine and Louie [48]. In general, the impact ionization rate should be a function of the wavevector of the incident electron, hence of the direction of an electric field in the crystal, although there is still some debate as to the experimental and theoretical evidence.…”

Section: Band To Band Impact Ionizationmentioning

confidence: 99%

Monte Carlo Device Simulations

2017

Handbook of Optoelectronic Device Modeling and Simulation

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Applications of Monte Carlo Method in Science and Engineering 386 materials are given to completely specify the collision integral in the BTE. A discussion followed with the presentation of a generic flow-chart for implementing bulk Monte Carlo code is presented. Note that bulk Monte Carlo approach is suitable for the characterization of materials, but in order to study behavior of semiconductor devices coupling of the Monte Carlo transport kernel with a Poisson equation solver which gives the self-consistent field that moves the carriers around is needed. Important ingredients in describing particle-based device simulators are the particle-mesh coupling, treatment of the Ohmic contacts and calculation of the current. A generic flowchart of a particle-based device simulator is provided. The prospects of the Monte Carlo method for the solution of the Boltzmann transport equation, in the context of device simulations of nanoscale structures and of solar cells and power devices, are discussed at the end of the book chapter.2. Importance of MC particle-based device simulations 2.1 Industry trends and the need for modeling and simulation As semiconductor feature sizes shrink into the nanometer scale regime, even conventional device behavior becomes increasingly complicated as new physical phenomena at short dimensions occur, and limitations in material properties are reached [1]. In addition to the problems related to the understanding of actual operation of ultra-small devices, the reduced feature sizes require more complicated and time-consuming manufacturing processes. This fact signifies that a pure trial-and-error approach to device optimization will become impossible since it is both too time consuming and too expensive. Since computers are considerably cheaper resources, simulation is becoming an indispensable tool for the device engineer. Besides offering the possibility to test hypothetical devices which have not (or could not) yet been manufactured, simulation offers unique insight into device behavior by allowing the observation of phenomena that can not be measured on real devices. Computational Electronics [2,3,4] in this context refers to the physical simulation of semiconductor devices in terms of charge transport and the corresponding electrical behavior. It is related to, but usually separate from process simulation, which deals with various physical processes such as material growth, oxidation, impurity diffusion, etching, and metal deposition inherent in device fabrication [5] leading to integrated circuits. Device simulation can be thought of as one component of technology for computer-aided design (TCAD), which provides a basis for device modeling, which deals with compact behavioral models for devices and sub-circuits relevant for circuit simulation in commercial packages such as SPICE [6]. The relationship between various simulation design steps that have to be followed to achieve certain customer need is illustrated in Figure 1.

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New model dielectric function and exchange-correlation potential for semiconductors and insulators

Cited by 262 publications

References 26 publications

Exciton energy-momentum map of hexagonal boron nitride

Exciton energy-momentum map of hexagonal boron nitride

Electronic excitations: density-functional versus many-body Green’s-function approaches

Monte Carlo Device Simulations

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