Nuclear quantum effects on zeolite proton hopping kinetics explored with machine learning potentials and path integral molecular dynamics

Proton hopping is a key reactive process within zeolite catalysis. However, the accurate determination of its kinetics poses major challenges both for theoreticians and experimentalists. Nuclear quantum effects (NQEs) are known to influence the structure and dynamics of protons, but their rigorous inclusion through the path integral molecular dynamics (PIMD) formalism was so far beyond reach for zeolite catalyzed processes due to the excessive computational cost of evaluating all forces and energies at the Density Functional Theory (DFT) level. Herein, we overcome this limitation by training first a reactive machine learning potential (MLP) that can reproduce with high fidelity the DFT potential energy surface of proton hopping around the first Al coordination sphere in the H-CHA zeolite. The MLP offers an immense computational speedup, enabling us to derive accurate reaction kinetics beyond standard transition state theory for the proton hopping reaction. Overall, more than 0.6 mu s of simulation time was needed, which is far beyond reach of any standard DFT approach. NQEs are found to significantly impact the proton hopping kinetics up to similar to 473 K. Moreover, PIMD simulations with deuterium can be performed without any additional training to compute kinetic isotope effects over a broad range of temperatures.

Automated summary

Proton hopping is a crucial process in zeolite catalysis, but accurately determining its kinetics is challenging. In this study, a machine learning potential (MLP) was trained to accurately reproduce the potential energy surface of proton hopping in H-CHA zeolite at the Density Functional Theory (DFT) level. The MLP significantly speeds up computations and allows for accurate determination of reaction kinetics beyond standard transition state theory. Nuclear quantum effects (NQEs) were found to have a significant impact on proton hopping kinetics, and kinetic isotope effects can be computed without additional training using PIMD simulations with deuterium.