Abstract
It is believed by some that the key to a successful industrial heterogeneous catalyst is a complex dynamical behavior, in which the catalyst is more than just a provider of catalytic sites. With the help of machine learning-driven molecular dynamics simulations, we show that this is indeed the case for the thermally activated synthesis of ammonia catalysed by BaH2. This system has recently been experimentally investigated and shown to act as a highly efficient catalyst for ammonia synthesis, if and only if it is alternately exposed first to N2 and then to H2 in a chemical looping process. Our simulations reveal that when first exposed to N2, BaH2 undergoes a profound change and it is transformed into a superionic mixed compound, BaH(2-2x)(NH)x, characterized by a high mobility of both hydrides and imides. This transformation is not limited to the surface but involves the entire catalyst. When this compound is exposed to H2 in the second step of the looping process, the ammonia is readily formed and released, a process greatly facilitated by the high ionic mobility. Once all the nitrogen hydrides are hydrogenated, the system reverts to its initial state and it is ready for the next looping process.
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