Ensemble Effects in Adsorbate–Adsorbate Interactions in Microkinetic Modeling

Abstract

Adsorbates on a surface experience lateral interactions that result in a distribution of adsorption energies. The adsorbate–adsorbate interactions are known to affect the kinetics of surface reactions, which motivates efforts to develop models that accurately account for the interactions. Here, we use density functional theory (DFT) calculations combined with Monte Carlo simulations to investigate how the distribution of adsorbates affects adsorption and desorption of CO from Pt(111). We find that the mean of the average adsorption energy determines the adsorption process, whereas the desorption process can be described by the low energy part of the adsorbate stability distribution. The simulated results are in very good agreement with calorimetry and temperature-programmed desorption experiments and provide a guideline of how to include adsorbate–adsorbate interactions in DFT-based mean-field kinetic models.

Accelerated Approach toward Predicting Coverage-Dependent Surface Free Energies on Transition-Metal Surfaces

“…It is also intuitively expected that the strength of these lateral interactions diminishes in magnitude as the distance between the adsorbates increases. Hence, these repulsive interactions can be mathematically represented in terms of the distance between the adsorbates, and various functional forms can be used for this purpose, including linear, polynomial, ,, exponential, , or other discrete ,,, functions. Among the various functions proposed, we consider a step function inspired by the model introduced in previous works , where the total interaction energy is derived from the summation of distance-dependent energy interaction parameters.…”

“…32,33 Although the lateral interactions between adsorbates are generally weaker than the interactions between adsorbates and surfaces, these interactions can influence the adsorption/desorption energies, 34 the stability of transition states, 35,36 and catalytic turnovers. 31,37,38 The lateral interactions between adsorbates have been captured explicitly by cluster expansion or Ising type formalisms, [31][32][33]39,40 linear, 41 polynomial, 27,42,43 exponential, 41,43 or other discrete 31,38,43,44 functions of adsorbate coverage. The DFT-parametrized lattice gas cluster expansion has been successfully applied to small adsorbates (O*, 39,45,46 H*, 47 CO*, 48 NO*, 49 H 2 O*, 50 etc.)…”

“…This average adsorbate binding energy is the chemical potential of adsorbates anchored to the surface relative to the chemical potential of a gas-phase reservoir . The average adsorbate binding energy comprises of the interaction between the adsorbate and a particular active site (binding energy of a single adsorbate) and lateral interactions between the adsorbates (differential binding energy). , Although the lateral interactions between adsorbates are generally weaker than the interactions between adsorbates and surfaces, these interactions can influence the adsorption/desorption energies, the stability of transition states, , and catalytic turnovers. ,, The lateral interactions between adsorbates have been captured explicitly by cluster expansion or Ising type formalisms, − ,, linear, polynomial, ,, exponential, , or other discrete ,,, functions of adsorbate coverage. The DFT-parametrized lattice gas cluster expansion has been successfully applied to small adsorbates (O*, ,, H*, CO*, NO*, H 2 O*, etc.)…”

Catalytic Conversion of H2S to H2: Challenges and Catalyst Limitations

“…The impact of the presence of pre-adsorbed species on the catalyst surface (termed here adsorbate–adsorbate interactions) can have important implications on the catalyst performance. − The adsorbate–adsorbate interaction typically occurs as a result of the lateral interaction between adsorbates on the catalyst surface. In this section, we focus on studying the impact of the presence of one or two pre-adsorbed species on the behavior of the catalyst surface.…”

Energy Maps of Complex Catalyst Surfaces

“…20−22 Adsorption energies calculated by DFT, primarily derived for metals, reported values comparable with experiments. 8,23,24 However, atomistic information for complex catalyst surfaces and composites is lacking. Since the structure of the adsorption complex is unclear, computational studies that address oxides or other multicomponent systems can be subject to significant uncertainties.…”