Evolution of structural topology of forming nanocrystalline silicon film by atomic-scale-mechanism-driven model based on realistic network
Source abstract
Abstract
To establish a description of realistic structural evolution of a growth film, we propose a local definite continuous-random-network (CRN) structure combined with a kinetic Monte Carlo (KMC) method based on an atomic-scale mechanism from first-principles density-functional-theory computations and molecular-dynamics computations. The proposed CRN-KMC method elucidates the evolution of elaborate topological structure and the transformation from amorphous phase to nanocrystalline phase of Si films, which is essentially attributed to the atomic interactive behavior of film growth. The method further predicts the realistic structural networks of a growing film at various temperatures based on various atomic-scale mechanisms competing with each other, mechanisms that not only essentially drive the radical from physisorption to chemisorption with the film surface, but also decidedly influence the film-surface chemical composition. In particular, we find the evolution of topological structure’s critical dependence on the compositions of the film surface and H-induced crystallization mechanism, which provide the important information for the strategy for determining optimized deposition conditions for local crystal formation. The results of the evolution of the structural network indicate that the structure of film is similar the CRN model’s representation at relative lower temperature, and is in full agreement with the inhomogeneous crystalline model at relative higher temperature without an abrupt phase change from polycrystalline to amorphous. Our CRN-KMC realistic structure model has significance for exploring the relation of various atomic-scale mechanisms to the phase transformation of growing films.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Thin-Film Transistor Technologies · Machine Learning in Materials Science · Theoretical and Computational Physics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Physics, State Key Laboratory of Optoelectronic Materials and Technologies, Sun Yat-sen University 1 , Guangzhou 510275, People’s Republic of China
Department of Physics and Electrical Engineering, Hanshan Normal University 2 , Chaozhou 521041, People’s Republic of China
Funding
the Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund · National Natural Science Foundation of China
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