Linear and Non-Linear Kinetic Modeling for Adsorption of Disperse Dye in Batch Process Article Swipe

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Sheo Prasad Shukla , Markandeya Tiwari , Ganesh Chandra Kisku ·

YOU? · · 2015 · Open Access · · DOI: https://doi.org/10.3923/rjet.2015.320.331

Removal of disperse orange 25 dye by adsorption on activated carbon was experimentally investigated in a batch process in present study which revealed that the equilibrium data fitted better in the Langmuir isotherm, indicating monolayer coverage of disperse orange 25 dye molecules at the outer surface of activated carbon.Several forms of pseudo-first and second order kinetic models were employed to determine the best-fitting form of particular model on the basis of statistical analysis.The results concluded that the non-linear form of pseudo-second order kinetic model is best suited to explain the present adsorption study as compared to linear forms.

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Adsorption Process (computing) Kinetic energy Disperse dye Batch processing Process engineering Chemistry Linear model Biological system Chromatography Computer science Mathematics Statistics Physical chemistry Physics Organic chemistry Engineering Dyeing Biology Programming language Quantum mechanics Operating system

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Type: article
Language: en
Landing Page: https://doi.org/10.3923/rjet.2015.320.331
PDF: https://scialert.net/qredirect.php?doi=rjet.2015.320.331&linkid=pdf
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Cited By: 88
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DOI: https://doi.org/10.3923/rjet.2015.320.331

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Title: Linear and Non-Linear Kinetic Modeling for Adsorption of Disperse Dye in Batch Process

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Language: en

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Publication year: 2015

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Publication date: 2015-06-01

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Authors: Sheo Prasad Shukla, Markandeya Tiwari, Ganesh Chandra Kisku

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Concepts: Adsorption, Process (computing), Kinetic energy, Disperse dye, Batch processing, Process engineering, Chemistry, Linear model, Biological system, Chromatography, Computer science, Mathematics, Statistics, Physical chemistry, Physics, Organic chemistry, Engineering, Dyeing, Biology, Programming language, Quantum mechanics, Operating system

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Cited by: 88

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citation_normalized_percentile.is_in_top_10_percent	True