S. Balamurali1,2,R. Chandramohan2, M. Karunakaran2

and T. Mahalingam3

 

1. Research Scholar, Department of Physics, Manonmaniam Sundaranar   University, Tirunelveli -627 012, India.

2. Annamalai Chettiar Research Centre, Physics Department, Sree Sevugan Annamalai College, Devakottai- 630303, India

3. Department of Physics, Karunya University, Coimbatore-641114, India.

Stability under normal environmental conditions over a long period of time is crucial for sustainable thin-film device performance. Co doped ZnO films with thicknesses in the 140 - 450 nm range were deposited on to amorphous glass microscope slides by Successive Ionic layer growth by Adsorption Reaction (SILAR) method. The results of the hardness measurements performed in this work for various Co doped ZnO films annealed at different temperatures cannot be explained simply in terms of the residual stress relaxation phenomenon or the grain size effect.Hardness of the film is increased by thermal annealing or aging. However, annealing does not appear as a viable option for durable Co doped ZnO thin film coatings. During the annealing processes hardness increased and unwanted changes in the microstructure occur concurrently. The fact that the hardness increased with annealing temperature above 300° C suggested that crystallinity of the film was the dominant factor in affecting the hardness. The decrease in hardness was due to the residual stress relaxed by the annealing process. An interesting point to note from the hardness results was that the hardness of the Co doped ZnO film increased with annealing temperature higher than 300° C. The hardness was Sh.N for the films annealed at 300° C, 400° C and 450° C, respectively.

 

[1] S. Kuriki, T. Kawashima, Thin Solid Films 515 (2007)  8594.

 

 

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    I suggest creating a Knowledge Base of you experimental result. Under the Knowledge Base, I mean an information and calculation tool, containing all relationships between all variables of nano object, allowing to calculate a value of one variable by means of others as well as allowing a solving of direct and inverse problems, allowing a predicting of characteristics of nano objects which have not been investigated yet as well as a predicting a technology parameters that provide the required characteristics of nano object. I have a large experience for the Knowledge Base creation by means of Data Mining.

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