Computer-aided blended extractant design and screening for co-extracting phenolic, polycyclic aromatic hydrocarbons and nitrogen heterocyclic compounds pollutants from coal chemical wastewater

Abstract

An innovative design and screening methodology of blended extractants was proposed, for co-extracting phenolic, polycyclic aromatic hydrocarbons (PAHs) and nitrogen heterocyclic compounds (NHCs) pollutants from coal chemical wastewater. The methodology includes two major issues, generating single-component candidate extractants and screening optimal binary extractants. In this work, two single-component extractant candidate sets, which present the potential to be good extractants of phenolic and PAHs/NHCs pollutants respectively, were generated by data searching of the Existing Commercial Compound Database (ECCD). The binary extractant candidate set was generated by traversal inter-combination between these two single-component candidate sets. To screen the target blended extractants from the generated candidates, a series of non-linear programming (NLP) models were set up and solved via special tailored strategy. Pseudo-component was introduced to represent various pollutants in coal chemical wastewater which reducing the size and complexity of NLP problems. Miscibility constraints of blended extractants and grid parallel computing method were adopted to reduce the time cost. Case study showed that the selected binary extractants can achieve co-extracting phenolic and PAHs/NHCs pollutants. It will benefit the sustainable development of coal chemical industry in China.