Elektrokimyasal Anotlama Yöntemiyle ZnO Nanotellerin Üretilmesi ve Fotokatalitik Aktiviteleri

Aykaç, Ahmet

doi:10.21205/deufmd.2019216107

deufmd

2019

DOI: 10.21205/deufmd.2019216107

|View full text |Cite

Elektrokimyasal Anotlama Yöntemiyle ZnO Nanotellerin Üretilmesi ve Fotokatalitik Aktiviteleri

Ahmet Aykaç¹

Abstract: Öz Bu çalışmada ZnO nanoteller Zn plakalar üzerine elektrokimyasal anotlama yöntemi ile iki farklı voltaj (5V-10V) kullanılarak büyütülmüştür. Büyütme işleminin ardından kristalin çinko oksit fazı oluşturmak amacıyla hava ortamında 300 °C 'de 1 saat süreyle ısıl işleme tabi tutulmuştur. Elde edilen yapıların morfolojik ve yapısal özellikleri sırasıyla taramalı elektron mikroskobu (SEM) ve Xışınları kırınım difraktometresi (XRD) ile tespit edilmiştir. Son olarak ZnO nanotellerin fotokatalitik performansı sulu m… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Mathematical modeling and optimum design of zinc oxide nanostructures modified carbon fiber reinforced polymethylmethacrylate-based bone cement composite using machine learning methods

Savran,

Aydin,

et al. 2024

Proceedings of the Institution of Mechanical Engineers, Part C:

View full text Add to dashboard Cite

A novel design-modeling strategy is proposed to enhance the mechanical properties of a medical polymethylmethacrylate (PMMA) bone cement (BC) under compressive and flexural loading conditions by considering the ratio of carbon fiber (CF), zinc (Zn)-coated carbon fiber (CF/Zn), and nanostructured zinc-oxide (ZnO) coated CF as design variables. A detailed study was carried out on multiple nonlinear neuro-regression analyses and revealed the advantages of the proposed method compared to Artificial Neural Networks (ANN). Polynomial, trigonometric and hybrid mathematical models are used to define the experimental process accurately. The boundedness of the candidate models is checked after the calculation of R2training and R2testing values to reveal whether the model is realistic or not. The results show that hybrid models are the most successful when the strength and strain are considered objective functions; the fourth-order polynomial model should be preferred when the module is considered objective. Also, it is seen that the most significant advantage of the Neuro-regression approach compared to artificial neural networks is that the mathematical models can be used directly without needing any transformation. This is not possible in neural networks and, therefore, significantly limits and complicates the use of models obtained using ANN.

show abstract

Mathematical modeling and optimum design of zinc oxide nanostructures modified carbon fiber reinforced polymethylmethacrylate-based bone cement composite using machine learning methods

Savran,

Aydin,

et al. 2024

Proceedings of the Institution of Mechanical Engineers, Part C:

View full text Add to dashboard Cite

show abstract

Electrodeposited ZnO Nanostructures on ITO Surfaces: Exploring Their Efficacy for Cholesterol Biosensing Applications

Erol,

Aykaç,

Dikici

et al. 2024

Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen Ve Mühendislik Dergisi

View full text Add to dashboard Cite

In this study, ZnO nanostructures were prepared by electrochemical anodization of electrodeposited Zn on ITO/glass substrates for cholesterol detection. The efficiency of the developed ZnO nanostructures in the detection of the Cholesterol oxidase (ChOx) enzyme was determined by the cyclic voltammetry method. The XRD and SEM results confirmed the synthesis of ZnO nanostructures prepared by the anodization method with various parameters. The effect of electrodeposition and anodization time on the morphology was observed. Cyclic voltammetry of ZnO/Zn/ITO/glass and Pt/ZnO/Zn/ITO/glass electrodes in electrolytes with various cholesterol concentrations was performed. The detection limit of the obtained Pt/ZnO/Zn/ITO/glass structured electrode was calculated as 0.965x10-3M. The resulting material with a layered structure may have potential applications in electrochemical sensors and biosensors in biomedical applications. In addition to biosensing performance, this study proposes a new approach for the development of ZnO-based biosensors that does not require expensive infrastructure and raw material costs, making it possible to develop high-sensitivity biosensor electrodes with lower detection limits with improvements to be made in future studies.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Elektrokimyasal Anotlama Yöntemiyle ZnO Nanotellerin Üretilmesi ve Fotokatalitik Aktiviteleri

Cited by 2 publications

References 13 publications

Mathematical modeling and optimum design of zinc oxide nanostructures modified carbon fiber reinforced polymethylmethacrylate-based bone cement composite using machine learning methods

Mathematical modeling and optimum design of zinc oxide nanostructures modified carbon fiber reinforced polymethylmethacrylate-based bone cement composite using machine learning methods

Electrodeposited ZnO Nanostructures on ITO Surfaces: Exploring Their Efficacy for Cholesterol Biosensing Applications

Contact Info

Product

Resources

About