Chemometric assessment of mechano-chemically activated zeolites for application in the construction composites

Abstract

Natural zeolites of clinoptilolite type from seven deposits were submitted to mechano-chemical activation in a Retsch ultra -centrifugal mill. The zeolite types and activation parameters were altered during the experiment with an aim to determine the optimal combination that would produce powder with adequate physico-chemical and microstructural properties for application as a binder replacement and an ion -exchanger in the construction composites. The effects of input variables (chemical composition of the samples) and process parameters (the rotor velocity and the activation period) on the efficiency of zeolite activation were investigated in terms of dependent parameters such as: specific surface area, grain size distribution, cation exchange capacity, melting point, compression strength, shrinking, water absorption and apparent porosity. Cluster analysis, Principal component analysis and Standard score analysis were applied in the assessment of the acquired product quality. Artificial neural networks (ANN) were developed in mathematical modeling of observed responses. Subsequently the ANN was compared to experimental results and the developed second order polynomial models. Developed models showed r(2) values in the 0.822-0.998 range, meaning that they were able to predict the observed responses in a wide range of processing parameters. ANN models performed high prediction accuracy (0.975-0.993) and can be considered as precise and very useful for response variables prediction. The combination of the conducted mathematical analyses isolated Z5 zeolite as a preferable type, and 20000 rpm and 30 min as an optimal activation set of parameters. Mathematically derived conclusions were confirmed by results of instrumental analyses (XRD, DTA/TG, SEM).