Optimization of cellulose phosphate synthesis from oil palmlignocellulosics using wavelet neural networks

Abstract

Cellulose phosphate was synthesized from microcrystalline cellulose derived from oil palm lignocellu-losics via the H3PO4/P2O5/Et3PO4/hexanol method. The influence of process variables (viz. temperature,reaction time, and the H3PO4/Et3PO4ratio) on the properties of the resulting cellulose phosphate wasinvestigated using a wavelet neural network model with the goals of ascertaining which factors werecritical and of determining optimized reaction parameters for this synthesis. The experimental resultscorroborated the good fit of the wavelet neural network model. The prediction errors were quite small(less than 7%), and the regression values (R2greater than 0.99) were also satisfactory