Abstract: The research study was based on an evaluation of the
ability of glued test samples to pass the criterion of sufficient
bondline adhesion under the exposure conditions defined in EN 302-
1. Additionally, an infrared spectroscopic analysis of the evaluated
adhesives (phenol-resorcinol-formaldehyde PRF and melamine-ureaformaldehyde
MUF) with different mix ratios was carried out to
evaluate the possible effects of a faulty technological process.
Abstract: Simultaneous determination of multicomponents of phenol, resorcinol and catechol with a chemometric technique a PCranking artificial neural network (PCranking-ANN) algorithm is reported in this study. Based on the data correlation coefficient method, 3 representative PCs are selected from the scores of original UV spectral data (35 PCs) as the original input patterns for ANN to build a neural network model. The results obtained by iterating 8000 .The RMSEP for phenol, resorcinol and catechol with PCranking- ANN were 0.6680, 0.0766 and 0.1033, respectively. Calibration matrices were 0.50-21.0, 0.50-15.1 and 0.50-20.0 μg ml-1 for phenol, resorcinol and catechol, respectively. The proposed method was successfully applied for the determination of phenol, resorcinol and catechol in synthetic and water samples.