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Titanium-Pillared Clay: Preparation Optimization,Characterization, and Artificial Neural Network Modeling
Authors:Seyed Heydar Mosavi Mirak  Seyedmehdi Sharifian  Fatemeh Esmaeili Khalil Saraei  Neda Asasian-Kolur  Bahram Haddadi  Christian Jordan  Michael Harasek
Affiliation:1.Fouman Faculty of Engineering, College of Engineering, University of Tehran, Fouman 43516-66456, Iran; (S.H.M.M.); (S.S.); (F.E.K.S.);2.Institute of Chemical, Environmental and Bioscience Engineering, Technische Universität Wien, Getreidemarkt 9/166, A-1060 Vienna, Austria; (B.H.); (C.J.); (M.H.)
Abstract:Titanium-pillared clay (Ti-PILC), as one of the most suitable types of porous adsorbents/(photo)catalysts, was prepared from a local type of Iranian clay and titanium isopropoxide. The production process was optimized by changing three operating parameters, including the clay suspension concentration (in the range of 0.5–10% w/v), the H+/Ti ratio (2–8 mol/mol), and the calcination temperature (300–700 °C). The largest specific surface area for the Ti-PILC was about 164 m2/g under the clay suspension of 0.5% w/v, H+/Ti = 6, with a surface area 273% larger than that of the raw clay. The surface areas obtained from more concentrated clay suspensions were, however, comparable (159 m2/g for 3% w/v clay and H+/Ti = 4). An increase in the calcination temperature has a negative effect on the porous texture of Ti-PILC, but based on modeling with artificial neural networks, its contribution was only 7%. Clay suspension and H+/Ti ratio play a role of 56 and 37% of the specific surface area. The presence of rutile phase, and in some cases anatase phase of TiO2 crystals was detected. FTIR and SEM investigations of Ti-PILCs produced under different operating parameters were analyzed.
Keywords:pillared clay   intercalation   titanium   characterization   artificial neural network
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