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Supercritical fluids exhibit peculiar inhomogeneity, which strongly affects reaction behaviors in them. However, explanations for inhomogeneity and its effect on reactions are both ambiguous so far. Here, we provide an atomic-level understanding of inhomogeneity effects on reactions via the computational method, with the example of n-decane pyrolysis under supercritical conditions. We describe the characteristic pyrolysis behaviors through collective variable-driven hyperdynamics (CVHD) simulations and explain the inhomogeneity of supercritical n-decane as the coexistence of gas-like and liquid-like atoms by a trained machine learning classifier. Due to their specific local environment, the appearance of liquid-like atoms under supercritical conditions significantly increases the type and frequency of bimolecular reactions and eventually causes changes in product distributions. Future research with this method is expected to extend the effect of inhomogeneity on other reactions under supercritical conditions or other condensed phases.

Wang Yutong, Liu Guozhu