Single-step synthesis of carbon nanotubes/iron/iron oxide composite films through inert-ambient CVD using ferric acetylacetonate as a precursor

RSC Advances ◽  
2015 ◽  
Vol 5 (73) ◽  
pp. 59463-59471 ◽  
Author(s):  
Pallavi Arod ◽  
S. A. Shivashankar

Fe–Fe3O4–CNT composite thin film was obtained by single step chemical vapor deposition process using Fe(acac)3 as the sole precursor. By changing the deposition pressure, the form of carbon deposited could be changed from amorphous to CNTs.

2015 ◽  
Vol 7 (2) ◽  
pp. 779-786 ◽  
Author(s):  
S. Ramakrishnan ◽  
K. R. Pradeep ◽  
A. Raghul ◽  
R. Senthilkumar ◽  
Murali Rangarajan ◽  
...  

Platinum nanoparticle-decorated graphene and carbon nanotube (Pt-Gr-CNT) nanocomposites synthesized by a single step chemical vapor deposition process, serve as a promising platform for the simultaneous electrochemical sensing of dopamine, uric acid and ascorbic acid.


Author(s):  
D.W. Susnitzky ◽  
S.R. Summerfelt ◽  
C.B. Carter

Solid-state reactions have traditionally been studied in the form of diffusion couples. This ‘bulk’ approach has been modified, for the specific case of the reaction between NiO and Al2O3, by growing NiAl2O4 (spinel) from electron-transparent Al2O3 TEM foils which had been exposed to NiO vapor at 1415°C. This latter ‘thin-film’ approach has been used to characterize the initial stage of spinel formation and to produce clean phase boundaries since further TEM preparation is not required after the reaction is completed. The present study demonstrates that chemical-vapor deposition (CVD) can be used to deposit NiO particles, with controlled size and spatial distributions, onto Al2O3 TEM specimens. Chemical reactions do not occur during the deposition process, since CVD is a relatively low-temperature technique, and thus the NiO-Al2O3 interface can be characterized. Moreover, a series of annealing treatments can be performed on the same sample which allows both Ni0-NiAl2O4 and NiAl2O4-Al2O3 interfaces to be characterized and which therefore makes this technique amenable to kinetics studies of thin-film reactions.


2012 ◽  
Vol 1 (1) ◽  
pp. 46 ◽  
Author(s):  
Amir Mahyar Khorasani ◽  
Mohammad Reza Solymany yazdi ◽  
Mehdi Faraji ◽  
Alex Kootsookos

Thin-film coating plays a prominent role on the manufacture of many industrial devices. Coating can increase material performance due to the deposition process. Having adequate and precise model that can predict the hardness of PVD and CVD processes is so helpful for manufacturers and engineers to choose suitable parameters in order to obtain the best hardness and decreasing cost and time of industrial productions. This paper proposes the estimation of hardness of titanium thin-film layers as protective industrial tools by using multi-layer perceptron (MLP) neural network. Based on the experimental data that was obtained during the process of chemical vapor deposition (CVD) and physical vapor deposition (PVD), the modeling of the coating variables for predicting hardness of titanium thin-film layers, is performed. Then, the obtained results are experimentally verified and very accurate outcomes had been attained.


Carbon ◽  
2014 ◽  
Vol 68 ◽  
pp. 399-405 ◽  
Author(s):  
Yun Liu ◽  
Minghan Xu ◽  
Xingzhong Zhu ◽  
Minmin Xie ◽  
Yanjie Su ◽  
...  

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