In our previous studies, structure determination of MgCl2 nanoplates capped with TiCl4 molecules was performed by combining a genetic algorithm (GA) for global search and DFT for local geometry optimization, while a parallel work, where high-dimensional neural network potentials were used to accelerate the structure determination, allowed the exploration of structures with size and coverage comparable to the real system. These results showed the interdependence between the structure and adsorption: The adsorption preference and quantity of TiCl4 directly affected the exposed surfaces of MgCl2. Moreover, it significantly diversified the energetically accessible structures, thereby introducing the active site distribution. The current paper delivers our next step towards the realistic modelling of the ZN catalyst, in which our non-empirical structure determination method was extended to a ternary system, comprising MgCl2, TiCl4, and ID with the objective of studying ID-guided nanostructure formation at an atomic level, thus not only advancing ZN catalyst research, but also ab initio structure determination of heterogeneous catalysts.