Origin of Chemical Order in a-Si_xC_yH_z: Density-Functional Tight-Binding Molecular Dynamics and Statistical Thermodynamics Calculations

Abstract

We investigate the growth mechanisms and structures of hydrogenated amorphous silicon carbide (a-Si x C y H z ) during chemical vapor deposition (CVD) by using density-functional tight-binding molecular dynamics (DFTB MD) and statistical thermodynamics (ST) calculations. Our multiscale modeling from an atomic to an experimental scale allows us to bridge the gap between micro- and macroscopic knowledge. As in any compound, the degree of chemical order in a-Si x C y H z is of practical importance. However, the origin of chemical order and effects of composition on the degree of chemical order remain unknown. First, CVD simulations are performed by the impingement of CH3 and SiH3 radicals on a Si(001)-(2 × 1):H surface with DFTB MD. The initial growth process consists of an abstraction-adsorption mechanism, where a CH3 or SiH3 radical abstracts a H atom and forms a dangling bond (DB) on the surface, and a subsequent CH3 or SiH3 radical is adsorbed on the DB. A surface-adsorbed CH2 species with a DB is inserted into a neighboring Si–Si bond converting it to a Si–C bond. The bond rearrangement simultaneously transfers the DB from the C to Si atoms. A CH3 radical is then adsorbed on the Si atom, forming a Si–C bond. The absence of DBs on C atoms reduces the opportunity for forming C–C bonds. Therefore, the bond-rearrangement and DB transfer mechanism explain why Si–C bonds are preferentially formed instead of Si–Si and C–C bonds. Second, to model CVD growth of a-Si x C y H z on a macroscopic scale, we develop a ST model for a-Si x C y H z , calculating the bonding fractions. Importantly, we show that the degree of chemical order depends on the H atom fraction. The bonding fractions obtained by ST results show excellent agreement with those obtained by DFTB MD calculations. Our DFTB MD and ST models predict the relationship between the composition and the degree of chemical order, and bridge a gap between micro- and macroscopic observations. The models can be used for designing materials for other covalent and ionic compounds at micro- to macroscales.

Construction of a Bridging Network Structure by Citric Acid for Environmental Heavy Metal Extraction

“…In addition, the schematic diagram of citric acid leaching of heavy metal ions Cu and Cr is shown in Scheme . With the development of quantum mechanics, density functional tightness binding (DFTB) has been applied to thermodynamics, dynamics, , charge density, and other fields, providing a new strategy for process simulation. − Figure a showed the ball-and-stick model of copper­(II) citrate, and Figure b indicated the three-dimensional cell model of copper­(II) citrate. In the Forcite Tools module, the non-binding energy and the total energy force remain essentially stable with an increasing simulation time, which verifies the energy conservation law of the system.…”

Molecular Dynamics Simulation for Thiolated Poly(ethylene glycol) at Low‐Temperature Based on the Density Functional Tight‐Binding Method

“…[33,34] However, a combination of computational priors and density functional based tight binding (DFTB) has emerged for problems encountered in traditional quantification modules, such as reaction kinetic processes that require a lot of time and computational resources from the researchers. [35,36] DFTB has been applied to thermodynamics, [37] kinetics, [38] noncovalent interactions, [39] voltammetric curves, [40] electron migration, [41] charge density, [42] and transmission functions. [43] DFTB brings the unique advantage of being able to simulate thousands of atomic systems, providing a new approach to problems related to complex systems and processes.…”