Wireless ThermochromicPlatform Based on Au/SiO₂ Photonic Crystals for <i>Operando</i> Monitoringof Catalyst Sintering with Machine Learning

<i>Operando</i> 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, SiO₂ photonic crystals were endowed with a distinct color change from the inherent blue hue of SiO₂ 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/SiO₂ 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/SiO₂ 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/SiO₂ 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 catalysts and offers further insight into the chemical engineering process.