Hydrothermal synthesis of zeolite production from coal fly ash: A heuristic approach and its optimization for system identification of conversion

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13 Citations (Scopus)

Abstract

Commercialization of synthetic zeolites has given considerable impetus to optimization of its production routes. The preferred production route involves hydrothermal treatment of coal fly ash in a strong alkali solution. The process involves several parameters, such as reaction temperature, time, the concentration and amount of alkali solution, and silica content in the fly ash, all of which strongly and non-monotonically affect the conversion. We herein perform several experiments with the Kazakhstani fly ash, and obtained a highest conversion of zeolites of 78% using 3 M NaOH at 110 °C. Further, we propose a conversion model using zero-order Takagi-Sugeno fuzzy system to analyze the effect of individual process parameters on conversion, and thereby, the reaction mechanism(s) of zeolite formation. The model is designed and developed, using the data, both from literature and our experiments on Kazakhstani fly ash. The obtained results clearly illustrate that the model accurately predict the conversion percentage of zeolite for a given set of reaction parameters. The model is further optimized to provide accurate inferences and an average deviation between the model predictions and experimental values for zeolite yield is observed to be less than 5%.

Original languageEnglish
Pages (from-to)616-623
Number of pages8
JournalJournal of Cleaner Production
Volume182
DOIs
Publication statusPublished - May 1 2018

Fingerprint

Hydrothermal synthesis
heuristics
Fly ash
fly ash
zeolite
Identification (control systems)
Coal
coal
Zeolites
commercialization
Fuzzy systems
silica
experiment
Experiments
Silica
System identification
Heuristics
prediction
parameter
temperature

Keywords

  • Coal fly ash
  • Heuristic methods
  • Hydrothermal production
  • Zeolites

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Environmental Science(all)
  • Strategy and Management
  • Industrial and Manufacturing Engineering

Cite this

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title = "Hydrothermal synthesis of zeolite production from coal fly ash: A heuristic approach and its optimization for system identification of conversion",
abstract = "Commercialization of synthetic zeolites has given considerable impetus to optimization of its production routes. The preferred production route involves hydrothermal treatment of coal fly ash in a strong alkali solution. The process involves several parameters, such as reaction temperature, time, the concentration and amount of alkali solution, and silica content in the fly ash, all of which strongly and non-monotonically affect the conversion. We herein perform several experiments with the Kazakhstani fly ash, and obtained a highest conversion of zeolites of 78{\%} using 3 M NaOH at 110 °C. Further, we propose a conversion model using zero-order Takagi-Sugeno fuzzy system to analyze the effect of individual process parameters on conversion, and thereby, the reaction mechanism(s) of zeolite formation. The model is designed and developed, using the data, both from literature and our experiments on Kazakhstani fly ash. The obtained results clearly illustrate that the model accurately predict the conversion percentage of zeolite for a given set of reaction parameters. The model is further optimized to provide accurate inferences and an average deviation between the model predictions and experimental values for zeolite yield is observed to be less than 5{\%}.",
keywords = "Coal fly ash, Heuristic methods, Hydrothermal production, Zeolites",
author = "Zhandos Tauanov and Dhawal Shah and Vassilis Inglezakis and Jamwal, {Prashant K.}",
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AU - Tauanov, Zhandos

AU - Shah, Dhawal

AU - Inglezakis, Vassilis

AU - Jamwal, Prashant K.

PY - 2018/5/1

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N2 - Commercialization of synthetic zeolites has given considerable impetus to optimization of its production routes. The preferred production route involves hydrothermal treatment of coal fly ash in a strong alkali solution. The process involves several parameters, such as reaction temperature, time, the concentration and amount of alkali solution, and silica content in the fly ash, all of which strongly and non-monotonically affect the conversion. We herein perform several experiments with the Kazakhstani fly ash, and obtained a highest conversion of zeolites of 78% using 3 M NaOH at 110 °C. Further, we propose a conversion model using zero-order Takagi-Sugeno fuzzy system to analyze the effect of individual process parameters on conversion, and thereby, the reaction mechanism(s) of zeolite formation. The model is designed and developed, using the data, both from literature and our experiments on Kazakhstani fly ash. The obtained results clearly illustrate that the model accurately predict the conversion percentage of zeolite for a given set of reaction parameters. The model is further optimized to provide accurate inferences and an average deviation between the model predictions and experimental values for zeolite yield is observed to be less than 5%.

AB - Commercialization of synthetic zeolites has given considerable impetus to optimization of its production routes. The preferred production route involves hydrothermal treatment of coal fly ash in a strong alkali solution. The process involves several parameters, such as reaction temperature, time, the concentration and amount of alkali solution, and silica content in the fly ash, all of which strongly and non-monotonically affect the conversion. We herein perform several experiments with the Kazakhstani fly ash, and obtained a highest conversion of zeolites of 78% using 3 M NaOH at 110 °C. Further, we propose a conversion model using zero-order Takagi-Sugeno fuzzy system to analyze the effect of individual process parameters on conversion, and thereby, the reaction mechanism(s) of zeolite formation. The model is designed and developed, using the data, both from literature and our experiments on Kazakhstani fly ash. The obtained results clearly illustrate that the model accurately predict the conversion percentage of zeolite for a given set of reaction parameters. The model is further optimized to provide accurate inferences and an average deviation between the model predictions and experimental values for zeolite yield is observed to be less than 5%.

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