Facile Synthesis of Ultrasmooth Au Nanospheres into Macroscopic 3D Supercrystals for Machine-Learning-Driven Analysis of Thiram in Soil

verified by FDTD simulation results. Furthermore, integrating a convolutional neural network (CNN) model with the ultrasensitive 3D superlattice SERS platform, the precise and wide-range concentration prediction of the pesticide thiram in soil was successfully demonstrated, breaking the limitation of high-concentration saturation in the conventional concentration-intensity fitting curve. Consequently, this innovative Au NS 3D supercrystal facilitates the fabrication of novel nanoassemblies with ideal plasmonic functions for extensive applications in the fields of food safety, environment, medicine, and biology.