Coatings of Na-aluminosilicate zeolites prepared using predictions from an artificial neural network method

Tatlıer, Melkon; Cıǧızoǧlu, K. Barış; Ciğizoğlu, H. Kerem; Erdem-Şenatalar, Ayşe

doi:10.1007/s10934-006-9085-z

Cited by 7 publications

(5 citation statements)

References 18 publications

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“…The presence of amorphous material with some zeolite P may be mainly observed from the pattern. This contradicts the result (zeolite X) obtained previously on stainless steel plates under the same synthesis conditions (Tatlier et al, 2008). Thermogravimetric analyses were also performed for the samples prepared from composition C1 and it was observed that the desorption capacities obtained after the initial TG measurements (0.20-0.24 g/g hydrated coating) decreased to about 0.05-0.06 g/g hydrated coating in the second run for all the samples prepared after 18-42 h of synthesis.…”

Section: Resultscontrasting

confidence: 99%

“…As the Si/Al ratio of the reaction mixture was decreased further, pure zeolite X could be crystallized on soda-lime type glass plates from composition C3 after different periods of synthesis (18 h, 24 h and 32 h), as confirmed by XRD and TG measurements. This result was similar to that obtained employing the same composition on stainless steel substrates (Tatlier et al, 2008). The XRD pattern of the sample prepared after 24 h of synthesis is shown in Figure 3(c).…”

Section: Resultssupporting

confidence: 86%

“…Hydrothermal synthesis was performed in an oven kept at 80 °C for 6-42 h. Clear reaction mixtures with molar compositions of 70 Na2O:Al2O3:26 SiO2:2100 H2O (C1), 70 Na2O:Al2O3:18 SiO2:2100 H2O (C2) and 70 Na2O:Al2O3:15 SiO2:2100 H2O (C3), in the composition range previously shown to yield zeolite X on stainless steel (Tatlier et al, 2008), were selected. The glass plates had a 5x5 cm 2 surface area and were about 3.5 mm in thickness.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Preparation of Zeolite X Coatings on Soda-Lime Type Glass Plates

Tatlıer

Atalay-Oral

2017

Braz. J. Chem. Eng.

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-The dissolution of glass in highly alkaline reaction mixtures and the impact of this phenomenon on zeolite coating formation were investigated. Coating samples were prepared and characterized by X-ray diffraction (XRD), field emission gun scanning electron microscopy (FEGSEM) and thermogravimetry (TG). It was demonstrated that zeolite X coatings might be prepared on soda-lime glass. Glass dissolved to some degree, up to 2% of its original mass, in the reaction mixtures for the conditions investigated. This dissolution affected the zeolite synthesis taking place on the glass surface, resulting in phases different from those obtained on inert metal surfaces in some cases, especially for the use of reaction mixtures with relatively high Si/Al ratios. The percentage of dissolution of glass plates increased with their decreasing thickness, indicating a surface phenomenon for the dissolution. The stabilities of the coatings, which varied with the synthesis conditions, benefited from the addition of extra thin layers of polyacrylic acid.

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Section: Resultscontrasting

confidence: 99%

Section: Resultssupporting

confidence: 86%

Section: Methodsmentioning

confidence: 99%

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Preparation of Zeolite X Coatings on Soda-Lime Type Glass Plates

Tatlıer

Atalay-Oral

2017

Braz. J. Chem. Eng.

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“…In this study, the Generalized Regression Neural Network (GRNN) method was used to relate the XRD data to the properties of the crystal structures of zeolites. The basics of the GRNN can be found in the literature [10,11]. The GRNN method does not require an iterative training procedure but instead estimates any arbitrary function between input and output vectors, drawing the function estimate directly from the training data.…”

Section: Artificial Neural Networkmentioning

confidence: 99%

Investigation of the Use of an Artificial Neural Network Method for the Prediction of Crystal Structures of Zeolites from XRD Data

Tatlıer¹,

Ciğizoğlu²

2009

Proceedings of the 5th International Workshop on Artificial Neural Networks and Intelligent Information Processing

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The possibility of using artificial neural network methods for the prediction of zeolite crystal structures, such as pore size and unit cell dimensions, from X-ray diffraction patterns was investigated. The Generalized Regression Neural Network method and X-ray diffraction data obtained from literature were utilized in these investigations. The predictions made by using this neural network method were, in general, more reliable than those performed by regression. The best predictions were achieved for the estimation of the pore size, while the neural network method improved significantly the very poor results obtained by regression for the unit cell dimensions.

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“…The best predictions of the Si molar contents (per mole of Al) of the zeolites that would be obtained from a given starting reaction mixture were made by the GRNN method. A few initial experimental verifications were also made which resulted in the syntheses of zeolites X and P from previously unknown compositions [12].…”

Section: Introductionmentioning

confidence: 99%

Artificial neural network methods for the prediction of framework crystal structures of zeolites from XRD data

Tatlıer

2010

Neural Comput & Applic

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Extracting information about the structures of zeolites and other crystalline materials from X-ray diffraction (XRD) data simply by using statistical methods may provide an impetus for the discovery and identification of unknown materials. In this study, the possibility of using artificial neural network methods for relating framework crystal structures to XRD data reported in literature was investigated. Generalized Regression Neural Networks and Radial Basis Function-Based Neural Networks were utilized in the investigations. The results obtained by neural networks, using fivefold cross validation technique, were compared to the actual values as well as to those determined by multilinear regression. The predictions made by these neural network methods were, in general, more reliable than those performed by regression. The best predictions were achieved for the estimation of the framework densities of zeolites, which provided quite small deviations from the actual values.

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Coatings of Na-aluminosilicate zeolites prepared using predictions from an artificial neural network method

Cited by 7 publications

References 18 publications

Preparation of Zeolite X Coatings on Soda-Lime Type Glass Plates

Preparation of Zeolite X Coatings on Soda-Lime Type Glass Plates

Investigation of the Use of an Artificial Neural Network Method for the Prediction of Crystal Structures of Zeolites from XRD Data

Artificial neural network methods for the prediction of framework crystal structures of zeolites from XRD data

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