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

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 optical...

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Bibliographic Details
Published in:Environmental science and pollution research international 2022-06, Vol.29 (26), p.39486-39499
Main Authors: Ataeefard, Maryam, Tilebon, Seyyed Mohamad Sadati, Etezad, Seyed Masoud, Mahdavi, Saeed
Format: Article
Language:English
Subjects:
Aquatic Pollution
Artificial intelligence
Atmospheric Protection/Air Quality Control/Air Pollution
Deinking
Dosage
Earth and Environmental Science
Ecotoxicology
Environment
Environment models
Environmental Chemistry
Environmental Health
Environmental science
Enzymes
Fibers
Mechanical properties
Multiple objective analysis
Optical properties
Optimization
Pulp & paper industry
Research Article
Waste Water Technology
Water Management
Water Pollution Control
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Summary: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). Graphical abstract
ISSN:0944-1344
1614-7499
DOI:10.1007/s11356-021-15622-7