Hong Quan, Yaxing Zhang, Can Can Lv, Yimin Deng, Helei Liu
Abstract A biphasic aqueous solvent of 25% aminoethylethanolamine (AEEA)/50% diethylethanolamine (DEEA) has attracted much attention because of its cheap raw material, fast CO 2 absorption rate and low adsorption/desorption energy consumption. In this work, the mass transfer model of CO 2 absorption into biphasic solvent of DEEA–AEEA in structured packed columns was investigated. The influence of operating parameters on K G a v in a regular packed column is investigated and discussed. Meanwhile, mass transfer mechanism of CO 2 absorption into biphasic solvent of DEEA–AEEA was comprehensively examcned. In addition, the prediction model of K G a v is constructed by introducing the phase separation volume, and the error of the empirical correlation is 7%. On this basis, three machine learning algorithms, that is, backpropagation neural network (BPNN), radial basis function neural network (RBFNN) and random forest (RF) algorithms, were used to construct the K G a v model, and the AAD of the models was less than 3%.