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

作者：Gu Dan Ming^*; Shen Xiao Dong; Cui Sheng

来源：Materials Science and Technology, 2011, 19(6): 22-27.

• Average particle size
• BP neural networks
• Brunauer emmett tellers
• Combustion temperatures
• Combustion time
• Field emission scanning electron microscopy
• High-purity
• Major factors
• Mathematic model
• Nano-silica
• Narrow pores
• Orthogonal experiment
• Pore diameters
• Preparation parameters
• Relative errors
• Rice husk
• Specific areas

To reduce the cost, high-purity nanosilica was obtained by combustion of rice husks pretreated using hydrochloric acid. Major factors affecting the purity of SiO2 were determined by orthogonal experiment and BP neural network. The SiO2 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 SiO2 was 99.45%, while the model value of SiO2 was 99.58%, the relative error was only 0.13%. The SiO2 made from rice husk is amorphous with an average particle size of 80 nm, high specific area of 243 m2/g, narrow pore size distribution of 2~10 nm and an average pore diameter of 5.60 nm.

• 出版日期2011
• 单位南京大学