研究目的
Investigating the properties of hydrogenated silicon-germanium (SiGe) clusters to predict structural, thermochemical, and electronic properties using quantum chemical calculations and a machine learning approach.
研究成果
The study successfully predicted the structural, thermochemical, and electronic properties of hydrogenated Si, Ge, and SiGe clusters using quantum chemical calculations and a machine learning approach. A novel bond additivity correction model was developed to improve the accuracy of standard enthalpy of formation predictions. The HOMO-LUMO energy gap analysis provided insights into the electronic stability of the clusters.
研究不足
The study is limited to hydrogenated Si, Ge, and SiGe clusters with up to six Si and/or Ge atoms. The anharmonic small ring movements and torsional vibrational modes for some structures were not treated aside from the temperature-dependent scaling factor.
1:Experimental Design and Method Selection:
Quantum chemical calculations were performed with the Gaussian 16 software. All electronic energies for the hydrogenated Si, Ge, and SiGe clusters and acyclic species were calculated using the G3//B3LYP composite method, which uses B3LYP/6-31g(d) geometries and higher-level corrections based on single point energies.
2:Sample Selection and Data Sources:
A computational study of 46 hydrogenated SiGe clusters (SixGeyHz, 1<X+Y≤6) was conducted.
3:List of Experimental Equipment and Materials:
Gaussian 16 software was used for quantum chemical calculations.
4:Experimental Procedures and Operational Workflow:
Geometries and harmonic vibrational frequencies are confirmed local minima on the singlet potential energy surface. The harmonic vibrational frequencies and zero-point vibrational energy (ZPE) were linearly scaled by a temperature-dependent scaling factor of
5:98 to account for anharmonicity. Data Analysis Methods:
Enthalpy, H, and entropy, S, are calculated using standard formulas. Calculation of thermochemical properties was performed automatically using the CalcTherm script.
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