Browsing by Author "Arat, A. B."

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Embargo
A machine learning approach for the estimation of photocatalytic activity of ALD ZnO thin films on fabric substrates
(Elsevier, 2024-02-01) Akyıldız, Halil I.; Yiğit, E.; Arat, A. B.; Islam, S.
Research in the field of photocatalytic wastewater treatment is striving to enhance catalyst materials to achieve high-performance systems. A promising approach to this goal has been immobilizing photocatalytic materials on fibrous substrates via atomic layer deposition (ALD). Nevertheless, both the ALD process and the assessment of photocatalytic performance involve a multitude of parameters necessitating thorough investigation. In this study, we employ popular machine-learning algorithms, including Support Vector Regression (SVR) and Artificial Neural Networks (ANN), to predict the photocatalytic activity of ALD-coated textiles. The photocatalytic activity is evaluated through methylene blue and methyl orange degradation tests. Machine learning algorithms are tested and trained using the k-fold cross-validation technique. The findings demonstrate that the ANN and SVR methods utilized in this research can predict catalytic activity with mean absolute percentage errors (MAPE) of 2.35 and 3.25, respectively. This study illuminates that, within the defined range of process parameters, the photocatalytic activity of ALD-coated textiles can be precisely estimated with suitable machine-learning algorithms.
Open Access
A mechanistic approach to determine the relationship between film structure, electronic properties, and photocatalytic activity of ALD ZnO thin films on glass gibers
(Springer, 2024-06-04) Arat, A. B.; Akyıldız, Halil I.
Atomic layer deposition (ALD), a high-conformality thin-film deposition technique, offers the opportunity to immobilize photocatalytic materials on high surface area substrates. Textile substrates are inexpensive, easily accessible materials with a fibrous nature, making them high surface area scaffolds for photocatalytic applications. This study applied ZnO thin-film coatings to fabric structures with different numbers of ALD cycles. The effect of coating thickness on the surface and electronic properties of the films and their photocatalytic properties were investigated. SEM, XRD, PL, and UV-Vis were used to examine the surface morphology, crystal structure, defects, and optical properties of the ZnO thin films. As the film thickness increased, the crystal sizes and the number of defects in the structure increased. Contact angle and Hall Effect measurements revealed that these structural defects are present on the surface of the films. Optimum wettability, mobility, and photocatalytic efficiency values were observed in the 15-nm coated samples, resulting in the highest photocatalytic activity and a turning point.