Determining zeolite structures with a domain-dependent genetic algorithm

Nowadays, the synthesis and characterization of novel zeolites is a significant area in which chemical engineers are working on. The zeolite structure determination is crucial for designing and understanding these materials so as to use them as adsorbents and catalysts. Modern diffraction techniques can normally obtain the cell parameters of zeolites, but they are not capable of solving the location of their atoms, especially for complex zeolites. Here, we propose a novel approach for determining the zeolite structure based on Genetic Algorithms of artificial intelligence area. This proposal takes into account the specific features of the problem domain for designing a suitable fitness function. Moreover, unlike typical genetic algorithm applications, our approach also includes these specific features of the problem when generating the initial generation and when applying the crossover operator, with relevant results. With this proposal, some representative zeolite structures have been found.