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A novel technique based on diffuse reflectance near-infrared spectrometry and back-propagation artificial neural network for estimation of particle size in TiO2 nano particle samples |
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| Authors: | Mohammadreza Khanmohammadi Amir Bagheri Garmarudi Nafiseh Khoddami Keyvan Shabani Mohammadreza Khanlari |
| Institution: | aChemistry Department, Faculty of Science, IKIU, Qazvin, Iran;bDepartment of Chemistry & Polymer Laboratories, Engineering Research Institute, Tehran, Iran;cNanotechnology Research Department, Engineering Research Institute, Tehran, Iran;dPhysics Department, Faculty of Science, IKIU, Qazvin, Iran |
| Abstract: | Determination of particle size is one of the critical parameters in nanotechnology. 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 the 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. |
| Keywords: | Nano TiO2 Particle size DR-FTNIR spectrometry Artificial neural network Chemometrics |
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