Mathematic model for preparing high-purity nanosilica from rice husk with BP neural network

To reduce the cost, high-purity nanosilica was obtained by combustion of rice husks pretreated using hydrochloric acid. Major factors affecting the purity of SiO ₂ were determined by orthogonal experiment and BP neural network. The SiO ₂ was characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), Brunauer-Emmett-Teller (BET) and field emission scanning electron microscopy (FE-SEM). The results showed that the order of major factors was combustion temperature, HCl volume fraction and combustion time, and the optimal preparation parameters were HCl volume fraction of 4.5%, combustion temperature of 697°C and combustion time of 5 h, under which conditions, the content of SiO ₂ was 99.45%, while the model value of SiO ₂ was 99.58%, the relative error was only 0.13%. The SiO ₂ made from rice husk is amorphous with an average particle size of 80 nm, high specific area of 243 m ²/g, narrow pore size distribution of 2~10 nm and an average pore diameter of 5.60 nm.