Maximization of extraction of Cadmium and Zinc during recycling of spent battery mix: An application of combined genetic programming and simulated annealing approach
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- @Article{YUN:2019:JCP,
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author = "Liu Yun and Wei Li and Akhil Garg and
Sivasriprasanna Maddila and Liang Gao and Zhun Fan and
P. Buragohain and Chin-Tsan Wang",
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title = "Maximization of extraction of Cadmium and Zinc during
recycling of spent battery mix: An application of
combined genetic programming and simulated annealing
approach",
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journal = "Journal of Cleaner Production",
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volume = "218",
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pages = "130--140",
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year = "2019",
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keywords = "genetic algorithms, genetic programming, Recycling,
Copper recovery, Waste printed circuit boards, Waste
management",
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ISSN = "0959-6526",
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DOI = "doi:10.1016/j.jclepro.2018.11.226",
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URL = "http://www.sciencedirect.com/science/article/pii/S0959652618336291",
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abstract = "There are a number of government directives and
regulations as well as many public schemes on the
recycling of batteries, in spite of this; the quantity
of batteries that are actually recycled is still very
low. Current production capacity cannot meet projected
demand of Lithium-ion batteries. To counter this, the
reclamation and repurposing of metals like cadmium,
Lithium and Zinc from used or spent batteries is the
only viable scheme. This is both environmentally
friendly and economically feasible. An alternative is
the selective chemical leaching in the presence of
Sulfuric acid and Sodium metabisulfite. In this paper,
the effect of these chemicals as well as the
solid-to-liquid ratio and time of retention is
comprehensively studied. Experiments are designed for
the recovery of Zinc and cadmium from the spend
Lithium-ion batteries mix. To maximize the recovery of
Zinc and cadmium, the combined genetic programming and
simulated annealing approach is proposed. Genetic
programming is used for the formulation of functional
relationship between recovered metals Zinc and cadmium
and the inputs (Solid/Liquid ratio, concentration of
Sulfuric acid, mass of Sodium metabisulfite and
retention time). The optimal input conditions
determined using the simulated annealing algorithm
includes Solid/Liquid ratio of 11.7percent, 0.86a M
Sulfuric acid, 0.56a g/g of Sodium metabisulfite and
45a min of retention time. Three dimensions surface
analysis reveals that a lower value of Solid/Liquid
ratio favours a better yield. The optimal conditions
are validated using experiments. This confirms the
efficacy of simulated annealing aided genetic
programming techniques as well as the optimal
conditions of the metal extraction",
- }
Genetic Programming entries for
Liu Yun
Wei Li
Akhil Garg
Sivasriprasanna Maddila
Liang Gao
Zhun Fan
P Buragohain
Chin-Tsan Wang
Citations