Analysis and pathway exploration of high-boiling residues for methyl-chlorosilane-monomers production.

[Display omitted] • Machine learning analysis identifies catalyst's key role in Me 2 SiCl 2 selectivity. • MeSiCl 2 -SiCl 2 Me and MeSiCl 2 -SiClMe 2 are main compositions of industrial HBRs. • MeSiCl 2 -SiClMe 2 prefers to produce MeSiCl 3 and Me 2 SiHCl based upon DFT insights. • Challenges & suggestions for upgrading HBRs to Me 2 SiHCl has been analyzed. Recently, the growing capacity of silicone monomers directly lead to a large accumulation of associated high-boiling residues (HBRs), which has become an urgent issue for limiting the sustainably development in industry. Dimethyldichlorosilane (M2) is an essential intermediate in silicone industry, which have been extensively applied in kinds of fields like architecture, electronics, new energy, medicine, transportation and plastic rubber. Consequently, the catalytic cracking of HBRs to produce value-added M2 is considered a promising strategy. However, most cracking catalysts exhibit low M2 selectivity in batch reactors. In this perspective, we initially provide an overview of the HBRs current cracking system. Moreover, the influence factors of M2 selectivity during HBRs-catalytic cracking system through machine learning (ML) methods are systematically calculated and analyzed. The latest findings regarding the actual components of HBRs feeding and their effluxes of HBRs-tri-n-butylamine cracking system are presented, as well as their distribution of final products. Finally, the existing challenges and suggestions for HBRs to M2, are given with the aim of providing novel research ideas and stimulating inspiration to drive toward a sustainable development for minimizing pollution and enhancing cost-effectiveness. [ABSTRACT FROM AUTHOR]