Loi Quang K, Searles Debra J
Centre for Theoretical and Computational Molecular Science, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD 4072, Australia.
School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD 4072, Australia.
Langmuir. 2024 Sep 3;40(35):18430-18438. doi: 10.1021/acs.langmuir.4c01212. Epub 2024 Jul 16.
The conversion of CO to hydrocarbons using catalysts is a promising route to utilize CO and produce more valuable chemicals in a sustainable manner. Recent studies have shown that iron-based catalysts perform well for the hydrogenation of CO. While the hydrogenation reaction mechanism in the gas phase is straightforward, when catalyzed by iron it has been demonstrated to involve various chemical transformations, and the selectivity and conversion are strongly dependent on the particle size. To further investigate the dependence of the reactivity of iron catalysts on cluster size, we performed reactive molecular dynamics simulations using the ReaxFF force field (ReaxFF-MD) for iron nanoclusters of various sizes in a CO and H-rich environment. We demonstrated that the homogeneous hydrogenation of CO was correctly described by this ReaxFF model. The dissociation mechanism of CO on the Fe, Fe clusters, and the bcc(100) Fe slab agrees with previous DFT results. The ReaxFF-MD simulations suggest a strong dependence of reactivity on the cluster size, with the Fe cluster having the highest reactivity. We show that ReaxFF-MD provides a route to understand reaction mechanisms in these nonequilibrium reactive processes where fast processes and local minima are important.
使用催化剂将一氧化碳转化为碳氢化合物是一种很有前景的途径,可用于以可持续的方式利用一氧化碳并生产更有价值的化学品。最近的研究表明,铁基催化剂在一氧化碳加氢反应中表现良好。虽然气相中的加氢反应机理很简单,但在铁催化下,已证明该反应涉及各种化学转化,并且选择性和转化率强烈依赖于颗粒尺寸。为了进一步研究铁催化剂的反应活性对团簇尺寸的依赖性,我们在富含一氧化碳和氢气的环境中,使用反应分子动力学模拟(ReaxFF-MD)对各种尺寸的铁纳米团簇进行了研究。我们证明了该ReaxFF模型能够正确描述一氧化碳的均相加氢反应。一氧化碳在铁、铁团簇和体心立方(100)铁平板上的解离机理与先前的密度泛函理论(DFT)结果一致。ReaxFF-MD模拟表明反应活性强烈依赖于团簇尺寸,其中铁团簇具有最高的反应活性。我们表明,ReaxFF-MD为理解这些非平衡反应过程中的反应机理提供了一条途径,在这些过程中快速过程和局部最小值很重要。