Near infrared spectrometric analysis of titanium dioxide nano particles for size classification

Determination of nano particle size is substantial since the nano particle size exerts a significant effect on various properties of nano materials. Proposing non-destructive, accurate and rapid techniques for analytical aims is of high interest. In this research the relationship between particle size and diffuse reflectance (DR) spectra in near infrared region has been applied to introduce a method for estimation of particle size. Back propagation artificial neural network (BP-ANN) as a nonlinear model was applied to estimate average particle size based on near infrared diffuse reflectance spectra. Thirty five different nano TiO2 samples with different particle size were analyzed by DR-FTNIR spectrometry and the obtained data were processed by BP- ANN. The network was trained by 30 samples and was evaluated by remaining 5 samples. In order to establish whether the new method is applicable for estimation of particle size of nano structured samples, the optimized model was applied to analyze 44 nano TiO2 samples. It was observed that ANN using the back-propagation algorithm is capable of generalization and could correctly predict the average particle size of nano-sized particles.