Kinetic Monte Carlo Simulations in Heterogeneous Catalysis

Kinetic Monte Carlo (kMC) simulations offer a stochastic framework for modelling the dynamics of surface reactions on heterogeneous catalysts. By discretising a catalyst’s surface into a lattice of adsorption sites and assigning rate constants to elementary events—adsorption, diffusion, reaction and desorption—kMC tracks the temporal evolution of surface species under realistic conditions. Inputs for these simulations are typically drawn from first-principles calculations, which supply adsorption energies, activation barriers and lateral interaction parameters. In this way kMC bridges the gap between atomistic energetics and macroscopic observables such as turnover frequency and selectivity. The method inherently accounts for spatial correlations, fluctuations and coverage-dependent phenomena that escape mean-field approaches, enabling predictions of reaction pathways, surface phase behaviour and the influence of support effects or nanoscale strain. Applications range from CO oxidation and steam reforming to CO₂ hydrogenation and ammonia synthesis, supporting rational catalyst design by revealing rate-determining processes, the role of surface heterogeneity and strategies for performance optimisation under industrially relevant temperatures and pressures.

Research from Nature Portfolio

High-resolution transmission electron microscopy combined with first-principles kMC has elucidated how atomic-scale strain at the interface of metal nanoparticles and oxide supports modulates catalytic turnover. By mapping strain distributions on platinum nanoparticles and feeding the resulting site-specific energetics into kMC models of CO oxidation, researchers demonstrated that even modest compressive or tensile distortions of surface atoms significantly alter local reaction rates. These findings quantify the link between mechanical strain and catalytic activity, illustrating that tailored interface engineering can be exploited to optimise catalyst performance. The work establishes strain as a design parameter alongside composition and morphology for next-generation heterogeneous catalysts.

Kinetic Monte Carlo Simulations in Heterogeneous Catalysis publication trend

The graph below shows the total number of articles in kinetic monte carlo simulations in heterogeneous catalysis across all publications each year (not limited to Nature Index journals).

Technical terms

Kinetic Monte Carlo simulation: A computational method that uses stochastic sampling of discrete elementary events on a lattice to simulate reaction kinetics over extended timescales.

First-principles calculations: Quantum-mechanical computations, often based on density functional theory, that provide energetic and structural data for elementary processes without empirical parameters.

Eley–Rideal reaction: A surface mechanism in which a gas-phase species reacts directly with an adsorbed species without first equilibrating on the surface.

Turnover frequency: The number of product molecules formed per active site per unit time under steady-state conditions.

Transition state: A high-energy configuration along a reaction coordinate corresponding to the saddle point on the potential energy surface.

Lateral interactions: Energetic influences between adsorbates on neighbouring sites that affect adsorption energies and activation barriers.

References

1. A Practical Guide to Surface Kinetic Monte Carlo Simulations. Frontiers in Chemistry (2019).
2. Influence of atomic site-specific strain on catalytic activity of supported nanoparticles. Nature Communications (2018).
3. Comprehensive Density Functional and Kinetic Monte Carlo Study of CO2 Hydrogenation on a Well-Defined Ni/CeO2 Model Catalyst: Role of Eley–Rideal Reactions. ACS Catalysis (2024).
4. Automatic Process Exploration through Machine Learning Assisted Transition State Searches. Physical Review Letters (2025).
5. Kinetic Monte Carlo simulations for heterogeneous catalysis: Fundamentals, current status, and challenges. The Journal of Chemical Physics (2022).