Acceleration and sensitivity analysis of lattice kinetic Monte Carlo simulations using parallel processing and rate constant rescaling
| Autor: | Marcel Nunez, T. Robie, Dionisios G. Vlachos |
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| Rok vydání: | 2017 |
| Předmět: |
Speedup
Chemistry Likelihood ratio method Monte Carlo method Finite difference General Physics and Astronomy Stiffness 02 engineering and technology 010402 general chemistry 021001 nanoscience & nanotechnology 01 natural sciences 0104 chemical sciences Reaction rate constant Lattice (order) medicine Statistical physics Kinetic Monte Carlo Physical and Theoretical Chemistry medicine.symptom 0210 nano-technology |
| Zdroj: | The Journal of chemical physics. 147(16) |
| ISSN: | 1089-7690 |
| Popis: | Kinetic Monte Carlo (KMC) simulation provides insights into catalytic reactions unobtainable with either experiments or mean-field microkinetic models. Sensitivity analysis of KMC models assesses the robustness of the predictions to parametric perturbations and identifies rate determining steps in a chemical reaction network. Stiffness in the chemical reaction network, a ubiquitous feature, demands lengthy run times for KMC models and renders efficient sensitivity analysis based on the likelihood ratio method unusable. We address the challenge of efficiently conducting KMC simulations and performing accurate sensitivity analysis in systems with unknown time scales by employing two acceleration techniques: rate constant rescaling and parallel processing. We develop statistical criteria that ensure sufficient sampling of non-equilibrium steady state conditions. Our approach provides the twofold benefit of accelerating the simulation itself and enabling likelihood ratio sensitivity analysis, which provides further speedup relative to finite difference sensitivity analysis. As a result, the likelihood ratio method can be applied to real chemistry. We apply our methodology to the water-gas shift reaction on Pt(111). |
| Databáze: | OpenAIRE |
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