10.57647/jnsc.2025.1502.07

Developing a New Model for Optimizing Response in Design of Experiments Considering Consumable Factors: Removal of Pollutant from Wastewater with Fe3O4/graphene Nano-sorbent

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  • Jieying Liu1,
  • Yong Go1,
  • Ali Behmaneshfar2,
  • Abdolhossein Sadrnia3,
  • Zhifang Zhang1,
  • Rui Dang1,
  1. School of Chemistry and Chemical Engineering Yulin University; Yulin, 719000, China
  2. Department of Industrial Engineering, Na.C., Islamic Azad University, Najafabad, Iran
  3. Department of Industrial Engineering, Faculty of Engineering Science, Quchan University of Technology, Quchan, Iran
Developing a New Model for Optimizing Response in Design of Experiments Considering Consumable Factors: Removal of Pollutant from Wastewater with Fe3O4/graphene Nano-sorbent

Received: 04-03-2025

Revised: 30-03-2025

Accepted: 29-04-2025

Published in Issue 30-04-2025

Copyright (c) 2025 Jieying Liu, Yong Go, Ali Behmaneshfar, Abdolhossein Sadrnia, Zhifang Zhang, Rui Dang (Author)

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Liu, J., Go, Y., Behmaneshfar, A., Sadrnia, A., Zhang, Z., & Dang, R. (2025). Developing a New Model for Optimizing Response in Design of Experiments Considering Consumable Factors: Removal of Pollutant from Wastewater with Fe3O4/graphene Nano-sorbent. Journal of Nanostructure in Chemistry, 15(2 (April 2025). https://doi.org/10.57647/jnsc.2025.1502.07
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Abstract

Removing toxic pollutants, especially colored compounds, from water samples and surface wastewater is one of the most significant and challenging issues in the environmental field. This paper aims to develop a new model for optimizing responses in the Design of Experiments (DoE) by dividing the process into different stages. The process is broken down into several stages based on consumable factors such as time and adsorbent weight. The number of stages increases until the stopping criteria are met. These criteria include restrictions on the cost of adding a new stage and obtaining an unsatisfactory response in the subsequent stage. In this regard, Fe3O4/graphene adsorbent was synthesized using a chemical precipitation strategy and characterized by FESEM, XRD, EDS, and mapping analysis methods. The presence of (220); (400); (422); (511); (440) and (533) layers in XRD pattern confirm Fe3O4 nanoparticle with high purity and crystallinity structure and particle size 45 nm. The removal of Sudan I by the Fe3O4/graphene adsorbent was optimized using Response Surface Methodology (RSM) based on the Box-Behnken design. The four effective factors are the weight of the adsorbent, time (both consumable factors), pH, and temperature. The proposed model increased the removal percentage significantly, from 65.4% in a single-stage process to 88.67% in a four-stage process. Therefore, it can be concluded that the pollutant removal in this study is much more efficient than the existing method at the same factor levels. It is important to note that increasing the process duration and adsorbent weight will result in higher costs. However, in this model, the high levels of factors remain unchanged due to the increased number of stages. As a result, the costs associated with establishing these factors remain constant. The results show a recovery percentage between 84.1% and 87.5%, for groundwater (well water) and drinking removal that confirming the effectiveness of both the adsorbent and the method for real-world applications.

Keywords

  • Fe3O4/graphene adsorbent,
  • Sudan I,
  • Removal,
  • Response Surface Methodology,
  • Design of Experiments,
  • Consumable Factors
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