基于傅里叶红外光谱的SiO_2基相变储湿复合材料结构分析及性能优选预测

以SiO_2为载体材料、脂肪酸为相变材料制备具有相变调温性能与储湿调湿性能的SiO_2基相变储湿复合材料。采用等温吸放湿法和步冷曲线法测试不同脂肪酸用量的SiO_2基相变储湿复合材料相变调温性能与储湿调湿性能。利用傅里叶红外光谱测试SiO_2基相变储湿复合材料的结构组成,分析SiO_2与脂肪酸的嵌合机理。以SiO_2基相变储湿复合材料的傅里叶红外光谱特征吸收峰作为输入层,以SiO_2基相变储湿复合材料的脂肪酸用量、相对湿度52.89%下SiO_2基相变储湿复合材料吸湿平衡含湿量与放湿平衡含湿量的平均值、SiO_2基相变储湿复合材料从30~15℃降温所需的时间作为输出层,以S型激活函数作为隐含层,利用BE神经网络建立结构参数与综合相变储湿性能的SiO_2基相变储湿复合材料性能优选预测模型。结果表明,SiO_2基相变储湿复合材料中SiO_2与脂肪酸仅为物理嵌合,未发生化学作用;当脂肪酸用量0.079 mol时,所制备的SiO_2基相变储湿复合材料具有最优的综合相变储湿性能,即在相对湿度52.89%下的吸湿平衡含湿量为0.132 3 g·g~(-1)、放湿平衡含湿量0.147 5 g·g~(-1)、平衡含湿量的平均值为0.139 9 g·g~(-1),从30~15℃降温所需的时间为1 305 s;SiO_2基相变储湿复合材料的性能优选预测模型吻合性较好,具有较高的精确度,其预测值与实测值的相对误差为-2.07%和2.45%,可以用于优选预测SiO_2基相变储湿复合材料的储湿调湿性能和相变调温性能。

Structural Analysis and Optimization Performance Forecast of SiO2-Based Phase Change and Humidity Storage Composite Materials with Fourier Transform Infrared Spectrum

SiO2-based phase change and humidity storage composite materials with phase change thermal control performance and humidity storage humidity control performance were made with SiO2 as the carrier and fatty acid as a phase change material. Phase change thermal control performance and humidity storage humidity control performance of SiO2-based phase change and humidity storage composite materials with different fatty acid content were tested with isothermal sorption method and cooling curve method.Composition structure of SiO2-based phase change and humidity storage composite materials were tested by Fourier transform infrared spectrum to analyze chimeric mechanism of SiO2 and fatty acid.Characteristic FTIR absorption peaks of SiO2-based phase change and humidity storage composite materials were considered as input layer;different fatty acid content of SiO2-based phase change and humidity storage composite materials,average values of absorption equilibrium moisture content and desorption equilibrium moisture content of SiO2-based phase change and humidity storage composite materials with relative humidity as 52.89%,and cooling time from 30 to 1 5 ℃ of SiO2-based phase change and humidity storage composite materials were seen as output layer respectively;S activation function was treated as hidden layer;then,optimization performance forecast model of SiO2-based phase change and humidity storage composite materials with structural parameters and phase change and hu-midity storage comprehensive performance was established by back-propagation neural network.The results showed that SiO2 and fatty acid are only physical chimeric to each other,while there is no chemical reaction between them.SiO2-based phase change and humidity storage composite materials by adding in 0.079 mol fatty acid has the best phase change and humidity stor-age comprehensive performance,that is,absorption equilibrium moisture content is 0.132 3 g · g-1 ,desorption equilibrium moisture content is 0.147 5 g·g-1 ,average value of equilibrium moisture content is 0.139 9 g·g-1 when relative humidity is 52.89%,cooling time from 30 to 1 5 ℃ is 1 305 s.Optimization performance forecast model of SiO2-based phase change and hu-midity storage composite materials are proved well with good accuracy,and the relative error of predicted data and experimental data are -2.07% and 2.45%,respectively;forecast model can be used for optimizing forecast phase change thermal control performance and humidity storage humidity control performance of SiO2-based phase change and humidity storage composite ma-terials.