Wireless Thermochromic Platform Based on Au/SiO 2 Photonic Crystals for Operando Monitoring of Catalyst Sintering with Machine Learning

作者：Mingyu Tang, Bingbing Song, Ya‐Jie Kong, Rui Ning Wang, Shujing Li, Wanlin Fu, Wu Yang, Weibing Lu, Yueming Sun, Yunqian Dai · 发表于：ACS Nano · 年份：2025 · DOI：10.1021/acsnano.4c18155 · 被引用次数：6 · 研究领域：Neural Networks and Reservoir Computing、Photonic Crystals and Applications、Distributed Control Multi-Agent Systems

Operando monitoring of the catalyst sinter-degree during reactions is essential for achieving a stable, safe, and efficient chemical engineering process. This work introduces a wireless thermochromic platform that utilizes machine learning to correlate color changes with the sinter-degree of catalysts and to identify hot spots during chemical reactions. After being decorated with sub-2 nm Au clusters, SiO 2 photonic crystals were endowed with a distinct color change from the inherent blue hue of SiO 2 photonic crystals to the distinctive red shade associated with Au clusters, due to the gradual growth of Au clusters over a wide temperature range from 25 to 900 °C. With the assistance of an artificial neural network, a robust correlation was established between the observed color change and the sinter-degree of Au species. After training, the smart Au/SiO 2 catalyst achieved self-visualization for the sinter-degree of Au species within 12.4 μm × 12.4 μm, during CO oxidation. Moreover, an intelligent noninvasive platform can be constructed by patterning Au/SiO 2 photonic crystals into quick response codes, for real-time monitoring of temperature distribution at a micro-region scale (208 μm × 208 μm) within 5 ms during chemical reactions. The Au/SiO 2 thermochromic platform enables wireless data transmission and facilitates the programmable warning of abnormal hot spots in reactors. This work serves as a technical reserve for future research on the development of advanced cataly...