Spectroscopic Fingerprints of MgCl2/TiCl4Nanoclusters Determined by Machine Learning and DFT

Understanding the structure and properties of MgCl2/TiCl4 nanoclusters is a key to uncovering the origin of Ziegler-Natta catalysis. In particular, vibrational spectroscopy can sensitively probe the morphology and active species of MgCl2/TiCl4. Here, we determined vibrational spectroscopic fingerprints of 50MgCl2 and 50MgCl2/3TiCl4 which were obtained by nonempirical structure determination based on an evolutionary algorithm and DFT. The adsorption of CO, TiCl4, and Ti2Cl8 dimers was also modeled on each of the coordinatively unsaturated Mg2+ sites available for binding including so-called defect sites, which are likely present at the surface of activated MgCl2 nanocrystals and plausible sites for strong TiCl4 species adsorption. The outcomes of thermodynamical and vibrational analysis were compared to results on ideal surfaces of MgCl2. Vibrational analysis (IR and Raman) on plausible models of TiCl4/ MgCl2 nanoclusters revealed that IR response is useful for distinguishing between the different ways of binding of TiCl4 on different sites of adsorption, whereas Raman response provides a clear fingerprint of supported TiCl4 species.