Application of genetic-fuzzy approach for estimation of nano ZSM-5 crystallinity

Soltanali, Saeed; Halladj, Rouein; Tayyebi, Shokoufe; Rashidi, Alimorad

doi:10.1016/j.matlet.2015.02.132

Cited by 8 publications

(3 citation statements)

References 12 publications

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“…Chem-ZSM-5 was selected as the reference sample for calculation of the relative crystallinity (C %) of bio-ZSM-5. 35 The crystallinity of the synthesized bio-ZSM-5 samples was calculated based on eq 1:…”

Section: ■ Experimental Methodsmentioning

confidence: 99%

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Hydrogenation of CO₂ to Dimethyl Ether over Tandem Catalysts Based on Biotemplated Hierarchical ZSM-5 and Pd/ZnO

Wang

Zhan

et al. 2020

ACS Sustainable Chem. Eng.

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The chemical transformation of CO 2 to valueadded chemicals and fuels remains a daunting research challenge, requiring the development of more efficient catalysts. The present work offers highly active integrated nanocatalysts for CO 2 hydrogenation to dimethyl ether (DME) through tandem catalysis, that is, Pd/ZnO converts CO 2 to methanol, and bio-ZSM-5 further catalyzes methanol dehydration to DME. Notably, the hierarchically porous bio-ZSM-5 with high pore connectivity was prepared by using low-cost rice husk and luffa sponge as biotemplates. The formation of bio-ZSM-5 involved three consecutive steps, including (i) diffusion of precursor species, (ii) confined crystal growth, and (iii) calcination treatment to remove the residual biomass. Interestingly, the obtained bio-ZSM-5 possesses abundant hierarchical porosity, including the intrinsic micropores from ZSM-5 frameworks, the mesopores from intracrystalline void space or pinholes in the intergrown zeolite layers, and the macroscopic channels from the original biomass architecture. It was found that the tetrapropylammonium hydroxide amount and Si/Al ratio were two critical factors affecting the crystallinity and porosity of the bio-ZSM-5. The silicon content in biomass (8.3 wt % in rice husk and 0.016 wt % in luffa sponge) also played a crucial role in the synthesis of bio-ZSM-5. Different spatial configurations of Pd/ZnO and bio-ZSM-5 significantly affected the DME yield, wherein spatial distances between the bio-ZSM-5 and Pd/ZnO components were adjusted by controlling the size of Pd/ZnO or the integration manners. The current results indicated that the closest proximity of the bifunctional catalyst was unfavorable for DME production (selectivity < 3%), because of which low-valent Zn cations from Pd/ZnO could displace the Brønsted acid sites on bio-ZSM-5 by ion exchange, and the powder mixing in the mortar was the best combination configuration of Pd/ZnO and bio-ZSM-5, promoting the CO 2 conversion (10.8%) with a DME selectivity of 31% under the reaction of 300 °C and 30 bar. Furthermore, as compared to the traditional ZSM-5 based catalyst, the obtained Pd/ZnO/bio-ZSM-5 bifunctional catalysts showed excellent longterm stability in 60 h on stream with a less amount of coke formed in the spent catalysts.

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Section: ■ Experimental Methodsmentioning

confidence: 99%

“…Chem-ZSM-5 was selected as the reference sample for calculation of the relative crystallinity ( C %) of bio-ZSM-5 . The crystallinity of the synthesized bio-ZSM-5 samples was calculated based on eq : wherein, A p is the total peak area of the bio-ZSM-5 product in the XRD pattern, and A R is the total area of the reference sample.…”

Section: Experimental Methodsmentioning

confidence: 99%

Hydrogenation of CO₂ to Dimethyl Ether over Tandem Catalysts Based on Biotemplated Hierarchical ZSM-5 and Pd/ZnO

Wang

Zhan

et al. 2020

ACS Sustainable Chem. Eng.

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“…The most common methods of AI for modeling purposes in chemical engineering are ANN and fuzzy logic, which sometimes are hybridized with evolutionary algorithms [4][5][6][7]. In addition to ANN and fuzzy logic methods, their hybrid scheme named adaptive-network-based fuzzy inference system (ANFIS) which is actually a fuzzy inference system implemented in the framework of adaptive networks has also been applied for modeling purposes in chemical engineering.…”

Section: Application Of Ai In Chemical Process Modelingmentioning

confidence: 99%

Application of AI in Chemical Engineering

Hajjar¹,

Tayyebi²,

EghbalAhmadi³

2018

Artificial Intelligence - Emerging Trends and Applications

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A major shortcoming of traditional strategies is the fact that solving chemical engineering problems due to the highly nonlinear behavior of chemical processes is often impossible or very difficult. Today, artificial intelligence (AI) techniques are becoming useful due to simple implementation, easy designing, generality, robustness and flexibility. The AI includes various branches, namely, artificial neural network, fuzzy logic, genetic algorithm, expert systems and hybrid systems. They have been widely used in various applications of the chemical engineering field including modeling, process control, classification, fault detection and diagnosis. In this chapter, the capabilities of AI are investigated in various chemical engineering fields.

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Modeling of PEO Coatings by Coupling an Artificial Neural Network and Taguchi Design of Experiment

Shahri

Allahkaram

Soltani

et al. 2023

J. of Materi Eng and Perform

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Application of genetic-fuzzy approach for estimation of nano ZSM-5 crystallinity

Cited by 8 publications

References 12 publications

Hydrogenation of CO₂ to Dimethyl Ether over Tandem Catalysts Based on Biotemplated Hierarchical ZSM-5 and Pd/ZnO

Hydrogenation of CO₂ to Dimethyl Ether over Tandem Catalysts Based on Biotemplated Hierarchical ZSM-5 and Pd/ZnO

Application of AI in Chemical Engineering

Modeling of PEO Coatings by Coupling an Artificial Neural Network and Taguchi Design of Experiment

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Application of genetic-fuzzy approach for estimation of nano ZSM-5 crystallinity

Cited by 8 publications

References 12 publications

Hydrogenation of CO2 to Dimethyl Ether over Tandem Catalysts Based on Biotemplated Hierarchical ZSM-5 and Pd/ZnO

Hydrogenation of CO2 to Dimethyl Ether over Tandem Catalysts Based on Biotemplated Hierarchical ZSM-5 and Pd/ZnO

Application of AI in Chemical Engineering

Modeling of PEO Coatings by Coupling an Artificial Neural Network and Taguchi Design of Experiment

Contact Info

Product

Resources

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Hydrogenation of CO₂ to Dimethyl Ether over Tandem Catalysts Based on Biotemplated Hierarchical ZSM-5 and Pd/ZnO

Hydrogenation of CO₂ to Dimethyl Ether over Tandem Catalysts Based on Biotemplated Hierarchical ZSM-5 and Pd/ZnO