amorphous carbon

In this article, the growth kinetic and optical property of amorphous carbon (a-C) nanolayers deposited by ion beam sputtering deposition technique on glass substrates are investigated. The atomic force microscopy is used to measure the variation of surface roughness versus deposition time. According to the calculations, the roughness of thin films increases during the growth process as a fractal scaling law. The Hurst exponent (α) has a value higher than 0.5, and the growth exponent (β) changes in the range of 0.02 to 0.22. These fractal exponents predict that the growth process of amorphous carbon nanolayers obeys the rules of the Wolf-Villain model belonging to the Edwards-Wilkinson universality class, in which the relaxation and surface diffusion happen during the growth process. The results indicate that the optical band gap decreases by reducing the surface roughness, Hurst exponent and the correlation length during thin film growth which is the first observation of this trend.

Surface grafting of nanocarriers could modulate their properties and characteristics. As carbon nanotubes synthesis is a very tricky process and requires high-end methods, hence the present investigation was aimed to develop an eco-friendly method for synthesis carbon nanotubes (CNTs) and subsequent surface grafting for enhanced drug delivery application. The present study elaborates two-step chemical modifications; wherein the first step is catalytic cleavage of natural precursor in the presence of ferrocene and the second step involve chemical grafting of Acyclovir (ACV) as a model drug to understand the drug release behaviour. The catalytic cleavage of sugarcane cubes (natural precursor) was carried out in a closed copper tube, which prevents oxidation and results in a conversion of tubular nanostructures to amorphous carbon. The covalent attachment of ACV on purified CNTs (fCNTs) was done using carbodiimide chemistry. The preliminary Uv-Vis absorbance spectra defined at 260 nm was arised due to π-π* stacking of aromatic C-C bonds. The Fourier Transforms Infrared Spectroscopy (FTIR) indicated the hydroxyl stretch at 3300 cm-1 while amide I bond formation was observed at 1672 cm-1. The XRD spectra confirmed successful synthesis of CNTs. The calculated average crystallite size (Scherer equation) of synthesized CNTs was found to be 42.84 and 44.45 nm; it was also in accordance with the morphological observation as confirmed simultaneously using SEM analysis. The covalently attached ACV was released up to 80% during 8h of in vitro drug release study. The surface grafting potential of CNTs was found to be promising compared to other nanomaterials.

One of the main methods for the synthesis of amorphous and nanostructured carbon is the mechanical milling of graphite. However, calculation and anticipation of the amorphous phase during the mechanical milling of graphite still is a major challenge due to a lot of important parameters. The main aim of this study is to mass-produce amorphous carbon and predict the crystallite size of graphite. For this purpose, ball-milling of graphite powder was carried out at different times of milling. Then, the destruction of crystal structure and changes in phases were studied by XRD, TEM, AFM, SEM, and Zeta Seizer. The results of theMAUD analysis showed that 91% and 93% of the unmilled graphite were converted to amorphous carbon at 250 and 330 hours of ball-milling, respectively. In order to predict the crystallite size of carbon during the high energy ball-milling, the effective variables in the ball-milling process along with the initial crystallite size of carbon were determined as the input of the artificial neural network (ANN). Moreover, the final crystallite size of carbon was considered as the output of the network. The designed network with a root mean square error (RMSE) of 4% was able to predict the crystallite size of carbon during the process. Finally, by comparing the experimental results and the designed model, it was shown that the predicted results were very close to the experimental outcomes. Accordingly, the presented model can be used for predicting the crystallite size of carbon during the mechanical milling of graphite.