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Intelligent modeling and optimization of environmentally friendly green enzymatic deinking of printed paper

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Abstract

Nowadays, the paper industry supplies its required fibers either from primary fibers, including wood and plants, or waste papers, called secondary fibers. One of the most challenging recycling processes is deinking of papers digitally printed with electrophotographic ink. In order to produce optically high-quality paper from recycled waste papers, deinking step is required at the desired levels. In this work, the environmentally friendly green enzymatic deinking of printed paper was modeled and optimized via an innovative approach called artificial intelligence method. The effect of treatment temperature, treatment time, and enzyme dosage on mechanical properties (tensile and burst strengths) as well as optical properties (whiteness and brightness) of handsheet was investigated. The developed code can appropriately learn the non-linear behavior of deinking process, and make decisions according to the pattern constructed intelligently. Finally, multi-objective optimization at the specified treatment temperature, treatment time, and enzyme dosage was performed to identify the best conditions for enzyme-deinked handsheet (maximized mechanical and optical properties).

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Authors and Affiliations

  1. Department of Printing Science and Technology, Institute for Color Science and Technology, Tehran, Iran

    Maryam Ataeefard

  2. School of Chemical, Petroleum, and Gas Engineering, Iran University of Science and Technology, Narmak, Tehran, Iran

    Seyyed Mohamad Sadati Tilebon

  3. Department of Environmental Research, Institute for Color Science and Technology, Tehran, Iran

    Seyed Masoud Etezad

  4. Wood and Forest Products Division, Research Institute of Forest and Rangelands, Agricultural Research Education and Extension Organization (AREEO), Tehran, Iran

    Saeed Mahdavi

Authors
  1. Maryam Ataeefard
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  2. Seyyed Mohamad Sadati Tilebon
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  3. Seyed Masoud Etezad
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  4. Saeed Mahdavi
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Contributions

B.G.H. performed the analyses. M.A. is the corresponding author and wrote the manuscript. S.M.S.T. performed the ANN and contributed to the writing of the manuscript. S.M.E. and S.M. performed the analyses. All the authors read and approved the final manuscript.

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Correspondence to Maryam Ataeefard.

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Ataeefard, M., Tilebon, S.M.S., Etezad, S.M. et al. Intelligent modeling and optimization of environmentally friendly green enzymatic deinking of printed paper. Environ Sci Pollut Res 29, 39486–39499 (2022). https://doi.org/10.1007/s11356-021-15622-7

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  • DOI: https://doi.org/10.1007/s11356-021-15622-7

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