Xiliang Yan

DFT-driven multitask deep learning for sulfur gas sensing and removal by transition metal phthalocyanines

Accurate prediction of both gas sensitivity and adsorption capacity is essential for developing high-performance sensing and purification materials for sulfur-based toxic gases. However, these two targets are governed by multiple interrelated physicochemical factors originating from both the sensing material and gas mo...

AI in Chemistry: A Data-Driven Framework for Managing Domino Effects

Abstract The recent innovation of AI-powered autonomous labs and plants holds immense potential in chemical engineering – but it also raises urgent questions about ecological risks. The breakneck speed of AI-driven design and synthesis of chemicals outpaces our ability to assess its ecological implications, widening th...

Boronate-mediated antibody orientation: a molecular simulation-guided strategy for ultra-sensitive lateral flow immunoassays