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A review of clinoptilolite, its photocatalytic, chemical activity, structure and properties: in time of artificial intelligence

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Abstract

Clinoptilolite belongs to the heulandite group and is one of the most abundant zeolites, possessing significant properties such as high porosity and absorbency. In this compound, the Si/Al ratio is larger than in other zeolites, which makes it stable under high temperatures and acidic conditions. Consequently, it has been used as an efficient and stable photocatalytic material in recent years. Clinoptilolite can be used individually as a self-photocatalyst, as well as with modifications such as increasing its hydrophobicity led to enhance its photocatalytic efficiency. Furthermore, clinoptilolite is applied as a support for photoactive materials that increase the photoactivity of transition metals. Due to its low cost and availability, this material is used as a high-performance natural photocatalytic material. In this article, we review and investigate the geological settings, geochemistry of clinoptilolite species, crystal structure and photocatalytic properties of natural and modified clinoptilolite. We also explore the benefits of using machine learning techniques, such as neural networks, which represent a paradigm shift in the way advancements are made in this field.

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Authors and Affiliations

  1. Department of Chemistry, University of Gonabad, Gonabad, Iran

    Roya Mohammadzadeh Kakhki

  2. Geology Department, University of Gonabad, Gonabad, Iran

    Sedigheh Zirjanizadeh

  3. Electrical and Computer Engineering Department, University of Gonabad, Gonabad, Iran

    Mojtaba Mohammadpoor

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  1. Roya Mohammadzadeh Kakhki
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  2. Sedigheh Zirjanizadeh
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  3. Mojtaba Mohammadpoor
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Contributions

The main text of article and discussions about photocatalytic application of clinoptilolite was written by R. Mohammadzadeh Kakhki. Geological settings, geochemistry of clinoptilolite species and crystal structure of clinoptilolite were added by S. Zirjanizadeh. The application, advantages and proposal of modeling using intelligent methods such as neural networks were added by M. Mohammadpoor.

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Correspondence to Roya Mohammadzadeh Kakhki.

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Mohammadzadeh Kakhki, R., Zirjanizadeh, S. & Mohammadpoor, M. A review of clinoptilolite, its photocatalytic, chemical activity, structure and properties: in time of artificial intelligence. J Mater Sci 58, 10555–10575 (2023). https://doi.org/10.1007/s10853-023-08643-9

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