Development of Electrical Conductivity Estimation Method Based on Tight-Binding Quantum Chemical Molecular Dynamics Simulation

Abstract

In the development of materials for nano-scale devices, particularly those including impurities, defects, surfaces, and hetero-interfaces, estimation of their electrical conductivity based on quantum chemistry provides important information. Existing quantum mechanics-based methods for theoretically estimating the electrical conductivity require huge computational cost, which prohibit their applications to complex systems. We have already succeeded in the development of our original tight-binding quantum chemical molecular dynamics program “Colors”, which realizes a calculation speed over 5000 times faster than the conventional first principles molecular dynamics methods. Here we present a novel electrical conductivity estimation method based on “Colors” combined with Monte Carlo algorithm for estimating the value corresponding to the carrier mobility. We have applied the developed method to systems of C, Si, Ge, and Sn. Calculated results quantitatively agree with experimental data, which indicates the validity of the developed method. We have also applied the developed method to the study of Si surface.

Electronic structure and electrical conductivity of MgO protecting layer in plasma‐display panels: A tight‐binding quantum chemical study

“…A more-detailed description of the procedure of our electrical conductivity simulator is given in our previous paper. 14 As depicted in Fig. 2(a 3…”

“…In the electrical-conductivity simulation 14 based on Colors, the following procedures were performed to calculate the electron mobility µ: (1) information on the molecular orbitals of a system is obtained by using the Colors program, (2) the three-dimensional mesh model for the system is constructed, (3) the probability density distribution of the electrons of the system calculated from the information of molecular orbitals are assigned to a three-dimensional mesh model constructed during procedure (2), (4) the probability of movement of an electron to an adjacent mesh point is assumed to be proportional to the probability density of electrons, (5) an electron is moved by using the Monte Carlo method according to the assumption described in procedure (4), and (6) the number of electrons reaching the goal plane as an input condition was determined. This scheme is schematically represented in Fig.…”

“…However, such a procedure has not been reported experimentally to the best of our knowledge. Recently, we have successfully developed a novel electrical conductivity program 14 based on Colors and validated its accuracy. In this study, as a first step in the theoretical study of the relationship of the electronic structure and the electrical conductivity in the MgO-protectinglayer materials, we attempted to estimate the electrical conductivities of the MgO model with and without an oxygen defect using our novel electrical conductivity simulator.…”

Development of a Multi-Scale Electromigration Simulator Based on a Combination of Ultra Accelerated Quantum Chemical Molecular Dynamics and Kinetic Monte Carlo Methods Application to Cu Interconnects Lifetime Simulation

“…The details of this parameterization process, based on first-principles methods, have been published elsewhere. 22) Next, for evaluation of the micro-scale spatial distribution of the electron wind force caused by the electron flow density, an electrical conductivity simulator, 16) also developed in our laboratories, was used. This simulator, based on a KMC method, has been developed considering that the carrier movement follows the conceptual principle that the region with large electron density value defines the pathway for the carrier movement.…”

“…The first is a KMC method to evaluate the lifetime of the interconnects by formation of voids, while the second is an atomic scale simulator that can simulate the movement of a vacancy of a metal atom in a lattice. The latter combines our originally developed electrical conductivity simulator 16) and ultra accelerated quantum chemical molecular dynamics (UA-QCMD) methods. 17) The electrical conductivity simulator was used to evaluate the electron wind force using our original tight-binding quantum chemical (TBQC) program ''Colors''.…”