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Computational Study of Structure Sensitivity in Methylcyclohexane Dehydrogenation on Platinum
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陈
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DOI：10.1021/acscatal.6c04610.png)
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Abstract
En 中文
For liquid organic hydrogen carriers (LOHCs), developing efficient hydrogen release strategies is crucial to advancing storage technologies. The methylcyclohexane (MCH)-toluene (TOL) system holds promise, yet its practical use remains limited by high dehydrogenation temperature, by-product formation, and catalyst deactivation. Here, machine-learning-assisted transition-state exploration, density functional theory calculations, and microkinetic simulations are combined to unravel the complex MCH dehydrogenation network, revealing the atomic-scale origin of structure sensitivity on platinum (Pt) catalysts. Pt(111) exhibits high selectivity toward TOL but limited activity due to its weak C−H activation capability at terrace sites; Pt(110), exposed with low-coordinated step sites, facilitate efficient C−H bond cleavage, yet Pt(110) strongly binds TOL, which drives its conversion into benzene (BZ) and promotes carbon production, thus impairing TOL selectivity; in contrast, Pt(211) achieves a balance between activity and selectivity, attributed to its moderate interaction with TOL through the cooperative effect of both terrace and step sites. Furthermore, we elucidate the influence of reaction conditions: elevating the temperature accelerates dehydrogenation kinetics, enhances product desorption, and alleviates coke and carbon deposition, while co-feeding hydrogen introduces surface *H species that suppress the accumulation of carbon intermediate, thereby improving product selectivity and extending catalyst durability. Collectively, these insights deepen the mechanistic understanding of LOHC dehydrogenation and provide guidance for the rational design of Pt-based catalysts.
Keywords:
hydrogen carrier
methylcyclohexane dehydrogenation
platinum
machine-learning potential
density functional theory
Journal
IF:
13.1
Papers:
1.6W
Citations:
15.0W
Organization
Cited Papers