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

We investigate the growth mechanisms and structures of hydrogenated amorphous silicon carbide (a-Si_xC_yH_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_xC_yH_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_xC_yH_z on a macroscopic scale, we develop a ST model for a-Si_xC_yH_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.