合理设计用于甲烷活化的 OsM4 中心:气相结果神经网络模型。

IF 2.7 2区 化学 Q3 CHEMISTRY, PHYSICAL
Shihan Li, Jiaying Wang, Chao Qian, Shaodong Zhou
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引用次数: 0

摘要

利用四极杆离子阱质谱结合量子化学计算,研究了[OsBx]+(x = 1-4)与甲烷在环境温度下的气相反应。OsBx]+(x = 1-4)团簇离子可与甲烷发生脱氢反应。对[OsBx]+/CH4 (x = 1-4)体系与 Os-络合物([OsCy]+ (y = 1-3) 和 [OsOz]+ (z = 1-3))的综合分析表明,簇离子的极性大和 ETS-NOCV 中 Os 与配体之间的配对能量总和高,共同促进了簇离子活化甲烷的能力。簇的极性可诱导 C-H 键的异质裂解,碎片的对能之和可降低簇的轨道能,使之与甲烷轨道相匹配,从而提高簇的稳定性。这两个因素的协同作用可能为在凝聚相中活化甲烷提供了一种可行的方法,即通过调节活性位点的配位环境来提高稳定性,促进 C-H 键的裂解以及与甲烷轨道的匹配程度。根据 OsBmCnOlHk 单元的有限能差数据,使用非线性函数提取对能差有显著影响的二阶特征。接下来设计了一个神经网络模型,以高精度预测 OsM4+(M = C、N、O、Al、Si 或 P)转化甲烷的反应障碍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Toward the Rational Design of an OsM4 Center for Methane Activation: Gas-Phase Result-Derived Neural Network Model.

Gas-phase reactions of [OsBx]+ (x = 1-4) with methane at ambient temperature have been studied by using quadrupole-ion trap mass spectrometry combined with quantum chemical calculations. The [OsBx]+ (x = 1-4) cluster ions can undergo dehydrogenation reactions with methane. Comprehensive analysis of the [OsBx]+/CH4 (x = 1-4) system with Os-complexes ([OsCy]+ (y = 1-3) and [OsOz]+ (z = 1-3)) shows that the large polarity of the cluster and the high sum of the pair energies between Os and the ligand in the ETS-NOCV combine to promote the ability of the cluster to activate methane. Cluster polarity may induce heterolytic cleavage of the C-H bond, and the sum of the pair energies of the fragments may reduce the cluster orbital energy to match the methane orbital and improve the cluster stability. The synergistic interplay of these two factors may offer a viable approach for the activation of methane in the condensed phase, which involves modulating the coordination environment of the active sites to enhance the stability and facilitate C-H bond cleavage and the degree of matching with methane orbitals. A nonlinear function is used to extract second-order characteristic features that have a significant impact on the energy difference based on the limited energy difference data of the OsBmCnOlHk units. A neural network model is next designed to predict the reaction barrier for methane conversion by OsM4+ (M = C, N, O, Al, Si, or P) with high accuracy.

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来源期刊
The Journal of Physical Chemistry A
The Journal of Physical Chemistry A 化学-物理:原子、分子和化学物理
CiteScore
5.20
自引率
10.30%
发文量
922
审稿时长
1.3 months
期刊介绍: The Journal of Physical Chemistry A is devoted to reporting new and original experimental and theoretical basic research of interest to physical chemists, biophysical chemists, and chemical physicists.
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