利用BP网络建立稻壳制备高纯纳米SiO2数学模型

为降低纳米SiO2的制备成本,以稻壳为原料,经盐酸预处理、高温燃烧,成功制得了高纯纳米SiO2.通过正交实验和BP神经网络系统研究盐酸体积分数、燃烧温度和燃烧时间的变化对SiO2纯度的影响规律,并采用XRD、FT-IR、BET及FE-SEM对所得到的SiO2样品进行表征.研究表明:影响SiO2纯度的主次因素依次为燃烧温...

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 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 ℃ 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.