2018
DOI: 10.1021/acs.jpca.8b09797
|View full text |Cite
|
Sign up to set email alerts
|

Tuning Hydrogenated Silicon, Germanium, and SiGe Nanocluster Properties Using Theoretical Calculations and a Machine Learning Approach

Abstract: There are limited studies available that predict the properties of hydrogenated silicon–germanium (SiGe) clusters. For this purpose, we conducted a computational study of 46 hydrogenated SiGe clusters (Si x Ge y H z , 1 < X + Y ≤ 6) to predict the structural, thermochemical, and electronic properties. The optimized geometries of the Si x Ge y H z clusters were investigated using quantum chemical calculations and statistical thermodynamics. The clusters contained 6 to 9 fused Si–Si, Ge–Ge, or Si–Ge bonds, i.e.… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
8
0

Year Published

2019
2019
2023
2023

Publication Types

Select...
6

Relationship

2
4

Authors

Journals

citations
Cited by 9 publications
(8 citation statements)
references
References 74 publications
0
8
0
Order By: Relevance
“…The single-event parameters of the Arrhenius relationship, logIJA) and E A were obtained by fitting lnIJk) versus T −1 over the temperature range 298-1500 K. This procedure was performed automatically using a modified version of the CalcK script previously employed by our group for reaction kinetics analysis. [29][30][31][32][33][34][35][36][37][38][39][40] Through linear regression analysis, we determined Arrhenius behavior was obeyed well for all reactions. The solvation impact of liquid phase kinetics is beyond the scope of this work but will be addressed in future studies following the work of Jalan et al, which computes liquid-phase kinetics in relation to both the solute and the solvent.…”
Section: Reaction Chemistry and Engineering Papermentioning
confidence: 99%
“…The single-event parameters of the Arrhenius relationship, logIJA) and E A were obtained by fitting lnIJk) versus T −1 over the temperature range 298-1500 K. This procedure was performed automatically using a modified version of the CalcK script previously employed by our group for reaction kinetics analysis. [29][30][31][32][33][34][35][36][37][38][39][40] Through linear regression analysis, we determined Arrhenius behavior was obeyed well for all reactions. The solvation impact of liquid phase kinetics is beyond the scope of this work but will be addressed in future studies following the work of Jalan et al, which computes liquid-phase kinetics in relation to both the solute and the solvent.…”
Section: Reaction Chemistry and Engineering Papermentioning
confidence: 99%
“…With an average absolute deviation of 18.1 kJ mol −1 from experimental measurements, the G3//B3LYP composite method was the most accurate for the standard enthalpy of formation prediction of ammonia, disilane, trisilane, and the silicon‐nitride diatomic molecule. Among experimental and calculated values for standard enthalpy of formation, the greatest deviations were seen for the nitrogen‐containing species ammonia and silicon‐nitride diatomic molecule; however, there is insufficient experimental data available to regress bond additivity corrections as we had done in our previous works [31,32] . The G3//B3LYP method was more accurate for calculating standard enthalpy of formation values than the B3LYP functional alone for ammonia and silicon‐nitride diatomic molecule which can be ascribed to the higher‐level corrections incorporated in the composite method.…”
Section: Resultsmentioning
confidence: 88%
“…Extensive details regarding the computational methodology for calculation of optimized electronic structures and statistical thermodynamics, including corrections for vibrational anharmonicity, have been discussed elsewhere [31,32] and are provided in the Supporting Information for convenience. The quantum chemical values have been used in our data-driven approach to assess cluster reactivity which is presented here.…”
Section: Computational Methodologymentioning
confidence: 99%
See 2 more Smart Citations