45
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Study of molecular mechanism and extraction performance evaluation for separation of phenolics from alkaline wastewater through synergistic extraction

, , , , , & show all
Pages 2180-2196 | Received 26 Jun 2023, Accepted 06 Dec 2023, Published online: 23 Jan 2024
 

ABSTRACT

Phenols were a kind of pollutant in coal chemical wastewater with high concentration and difficult to decompose and have a significant impact on the subsequent biochemical treatment of the wastewater. In addition, phenols were a kind of weak electrolytes that partially dissociation oxidation under weakly alkaline conditions, making recovery more difficult. In order to solve this problem, phenols were extracted from weak alkaline wastewater with a synergistic solvent. First, the interaction between solvents and phenols and the solvent effect of solvents were calculated by quantum chemistry and the synergistic extractant cyclohexanone/1-pentanol was determined to have significant advantages. Moreover, the synergistic extractant was further analyzed through independent gradient model based on Hirshfeld partition analysis, atoms in molecule topology analysis, electrostatic potential analysis. Results indicated that the synergistic extract can provide multiple hydrogen bond interactions with phenol due to the double action sites of the C=O group of ketone and the -OH group of alcohol. In addition, the efficacy of the extractant was validated by multistage extraction, indicating partial dissociation oxidation of hydroquinone to benzoquinone under weakly alkaline conditions, with removal rates of 99.5% and 99.2% for phenol and hydroquinone, respectively. In general, the synergistic extractant can effectively remove phenols.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/15567036.2023.2298005.

Additional information

Notes on contributors

Xuehui Zhang

Xuehui Zhang received his master’s degree from Qingdao University of Science and Technology in 2024. His research focuses on process simulation and optimization and molecular simulation.

Hong Liu

Hong Liu received his master’s degree from Qingdao University of Science and Technology in 2023. Her research mainly focuses on process system engineering and quantum chemical calculations.

Xiaochong Liu

Xiaochong Liu received his master’s degree from Qingdao University of Science and Technology in 2023. His research mainly focuses on the resource utilization of sludge and the safe management and disposal of hazardous waste.

Qingrui Zhang

Qingrui Zhang received her doctoral degree in Biochemical Engineering from Dalian University of Technology in2008. Currently, she has been promoted to Associate Professor with a professional technical title, and mainly engages in research in the fields of process systems engineering and biocatalytic transformation.

Siyuan Zhang

Siyuan Zhang received his master’s degree from Qingdao University of Science and Technology in 2024. His research mainly focused on molecular design and extraction mechanism analysis.

Kang Liu

Kang Liu received his master’s degree from Qingdao University of Science and Technology in 2024. His research mainly focuses on industrial process optimization and design.

Jianbo Liu

Jianbo Liu received a doctorate in environmental management from Yokohama National University in 2011. At present, he has been promoted to associate professor with professional and technical titles. He is mainly engaged in the development of microbial remediation technology for soil water environment and the regulation of microbial enzyme activity expression.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.