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Water decontamination by metal–organic framework: experimental and statistical optimization

  • Laís Weber AguiarEmail author
  • Everton da Costa
  • Andressa dos Santos
  • Andrelson Wellington Rinaldi
  • Wagner André dos Santos Conceição
  • Silvia Luciana Fávaro
  • Terezinha Aparecida Guedes
  • Vanderly Janeiro
Original Article
  • 7 Downloads

Abstract

In the current work, the adsorption of bisphenol A (BPA) was investigated using a metal–organic framework (MIL-100). MIL-100 was prepared using a homemade microwave oven and characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD) analysis, and physisorption analysis based on the Brunauer–Emmett–Teller BET surface area. Response surface methodology (RSM) was used to optimize the adsorption conditions, i.e., pH and the initial concentrations of BPA and the adsorbent; the BPA adsorption was considered the response. Using a central composite design (CCD), we obtained an experimental model validated by ANOVA and the interaction of two significant factors using RSM to the response. The laboratory experiments using MIL-100 revealed excellent adsorption activity toward BPA in water. The optimum conditions for BPA removal were 1.0 mg MIL-100 concentration and 200 mg/L initial BPA concentration. Under these conditions, the maximum adsorption of 1400 mg/g, which was higher than that previously reported, was obtained due to the favorable physicochemical properties of the adsorbent, such as large surface area, high porosity, and high stability. These results showed that MIL-100 can be an effective adsorbent for water decontamination by BPA removal; furthermore, statistical analysis can be used for adsorption tests, thereby reducing the number of experiments and making the analysis environmentally friendly.

Keywords

Adsorption Bisphenol A Aqueous solution Response surface methodology 

Notes

Acknowledgements

The authors are grateful to CAPES (Process 1782317 and 88882.315857/2019-01) and CNPQ for their financial support and to COMCAP-UEM and the postgraduate programs: biostatistics, mechanical engineer and chemistry for experimental support.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Laís Weber Aguiar
    • 1
    • 2
    Email author
  • Everton da Costa
    • 1
  • Andressa dos Santos
    • 2
  • Andrelson Wellington Rinaldi
    • 3
  • Wagner André dos Santos Conceição
    • 2
  • Silvia Luciana Fávaro
    • 2
  • Terezinha Aparecida Guedes
    • 1
  • Vanderly Janeiro
    • 1
  1. 1.Department of StatisticsState University of MaringáMaringáBrazil
  2. 2.Department of Mechanical EngineeringState University of MaringáMaringáBrazil
  3. 3.Rinaldi Research GroupState University of MaringáMaringáBrazil

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