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Mechanisms beyond energetics revealed by multiscale kinetic modeling of 2D‐material growth and nanocatalysis

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Abstract Entanglement of spatial and/or temporal scales proposes great challenges to unravel mechanisms of complex chemical systems for their rational design. Multiscale modeling and calculations combining theoretical methods and algorithms at different scales provide powerful tools to address such problems. It has been conventionally known that energetics such as the reaction barrier plays an essential role in complex systems involving chemical reactions, in this review, we focus on recent progress of mechanisms beyond energetics revealed by multiscale kinetic modeling to emphasize the variety of underlying mechanism for such systems, and highlights the importance of kinetics in multiscale modeling and calculations for practical applications. Several interesting mechanisms as well as the corresponding concepts of multiscale kinetic modeling are described in detail, ranging from effects of geometry, micro‐orientation, or reactant flux on 2D material epitaxial growth, to diffusion, directional mass transfer, or confinement enhanced electrocatalysis on nanocatalysts. This article is categorized under: Theoretical and Physical Chemistry > Reaction Dynamics and Kinetics
(a) Heterogeneous growth of carbon monomers on a zigzag Ir R0 ribbon. The attachment is thermodynamically favorable to occupy a top site (the left panel) and unfavorable to occupy a hollow one (the right panel). (b) Schematic diagram of the KMC model standing on the graphene growth front. The dependence of growth exponent γ on effective carbon‐substrate interaction strength α for (c) R0 and (d) R30 orientation. Insets show the lattice‐mismatch for R0 and R30, respectively. (Figure adapted with permissions from References 57 and 58. Copyright 2012 American Chemical Society and 2013 American Physics Society)
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(a) The concentration distributions of CO (left), C2(middle), C3(right). (b) The morphology structures of solid, cavity I, cavity II and fragment (left) in experiments. The simulation results of the C3/C2 product selectivity on different catalysts show a good agreement with experimental ones (right). (c) Computed concentration and distribution of species. CO2, C1, C2, and C3 concentrations on the multihollow structure. (Figure adapted with permissions from References 96 and 94. Copyright 2020 American Chemical Society and 2018 Springer Nature)
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(a) The kinetic model for electrocatalytic reduction of CO2 near a tip on electrode surface. SP denotes side products rather than CO. Insets show the experimental setup in Reference 14 (top left) and the numerical simulation setup (top right). Optimal performance depending on (b) the energetic barrier, (c) the interaction strength between adsorbed CO2 and the locally induced electric field, and (d) the effective adsorption rate for CO2 on the electrode surface. Where R*, v*, and e* are the tip size, CO producing rate, and efficiency when the optimal performance is achieved. (Figure adapted with permission from Reference 15. Copyright 2017 John Wiley and Sons)
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(a) Schematic of a spherical particle sitting upon a supporting planar surface (left) and the grid used for discretization of the sphere (right). (b) Simulated concentration profile around the spherical particle at scan rate δ = 0.1,1,10,100,1000, respectively. (c) Simulated voltammetry for a reversible electrode transfer at δ = 0.001,1,1000, respectively. (Figure adapted with permissions from Reference 10. Copyright 2007 American Chemical Society)
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(a) Schematic of controlled synthesis procedure for TMDC nanoribbons. (b) Flow field distribution within the tube and space‐confined region. (c) The KMC simulated growth morphologies of monolayer WS2 under diverse experiment conditions. (Figure adapted from Reference 77 with permissions and from Reference 78 under the terms of the Creative Commons CC BY license for open access articles. Copyright 2020 Elsevier.)
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(a) Schematic of MoS2 grain growth model. (b) Kink nucleation and propagation at a MoS2 zigzag edge. (c) Grain boundary formation in KMC simulations. The overall growth orientation of the grain boundary (vb) is the composition of kink propagation vectors at the two edges (v1 and v2). (d) Formation kinetics of (bi–biii) smooth BC grain boundary and (ci‐ciii) rough CD grain boundary during two‐grain growth in KMC simulations. High‐resolution STEM image of (biv) smooth and (civ) rough grain boundaries. Scale bars are 1 nm. (Figure adapted with permissions from Reference 67. Copyright 2019 American Chemical Society)
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