Crystal violet removal using ZIF-60: Batch adsorption studies, mechanistic & machine learning modeling

Usman M. Ismail, Sagheer A. Onaizi, Muhammad S. Vohra*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

This study, for the first time, reported the utilization of ZIF-60 for the adsorptive removal of organic pollutant from contaminated water. Characterization techniques were used to confirm the synthesis of ZIF-60 adsorbent which was then used to study the uptake of crystal violet (CV) from the aqueous system. A remarkably high experimental uptake (in excess of 7000 mg/g) of CV onto ZIF-60 was noted which was due to the careful selection of process parameters while conducting the batch adsorption studies. Response surface methodology technique was utilized as the tool for response optimization and for studying the effect of varying adsorption process parameters. Temperature had the most significant influence on CV adsorption followed by CV concentration, ZIF-60 dose and pH. Adsorption kinetics and isotherm investigations were conducted based on the optimized adsorption conditions, and the obtained good data fitting with more than one model suggests an intricate adsorption process. On the other hand, the thermodynamic studies revealed a highly endothermic and spontaneous process. The post adsorption analysis revealed π-π stacking interaction as the dominant force driving the uptake of CV onto ZIF-60. Additionally, several machine learning models that were based on distinct algorithms were utilized for the prediction of CV adsorption onto ZIF-60. An ensemble model that was based on the combination of several optimized models was created using the voting technique; this model proved to be the most accurate in predicting the CV uptake by ZIF-60 as suggested by its superior value for several evaluation metrics.

Original languageEnglish
Article number103456
JournalEnvironmental Technology and Innovation
Volume33
DOIs
StatePublished - Feb 2024

Bibliographical note

Publisher Copyright:
© 2023 The Authors

Keywords

  • Crystal violet (CV) dye adsorption
  • Machine learning (ML)
  • Response surface methodology (RSM)
  • Wastewater treatment
  • Zeolitic imidazolate framework-60 (ZIF-60)

ASJC Scopus subject areas

  • General Environmental Science
  • Soil Science
  • Plant Science

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