Preparation and Characterization of Covalently Binding of Rat Anti-human IgG Monolayer on Thiol-Modified Gold Surface

The 16-mercaptohexadecanoic acid (MHA) film and rat anti-human IgG protein monolayer were fabricated on gold substrates using self-assembled monolayer (SAM) method. The surface properties of the bare gold substrate, the MHA film and the protein monolayer were characterized by contact angle measurements, atomic force microscopy (AFM), grazing incidence X-ray diffraction (GIXRD) method and X-ray photoelectron spectroscopy, respectively. The contact angles of the MHA film and the protein monolayer were 18° and 12°, respectively, all being hydrophilic. AFM images show dissimilar topographic nanostructures between different surfaces, and the thickness of the MHA film and the protein monolayer was estimated to be 1.51 and 5.53 nm, respectively. The GIXRD 2θ degrees of the MHA film and the protein monolayer ranged from 0° to 15°, significantly smaller than that of the bare gold surface, but the MHA film and the protein monolayer displayed very different profiles and distributions of their diffraction peaks. Moreover, the spectra of binding energy measured from these different surfaces could be well fitted with either Au4f, S2p or N1s, respectively. Taken together, these results indicate that MHA film and protein monolayer were successfully formed with homogeneous surfaces, and thus demonstrate that the SAM method is a reliable technique for fabricating protein monolayer

Directional fractal signature analysis of self-structured surface textures

Currently available directional fractal signature (DFS) methods are not suited for self-structured surface textures since they base on the assumption of Brownian fractal or they do not use the entire image data in calculation. To address these difficulties, two new DFS methods were developed in this study, i.e., an augmented blanket with rotating grid (ABRG) method and a blanket with shearing image (BSI) method. The performance of these methods in measuring surface roughness and directionality, the capacity for quantifying multi-patterned textures, and the ability to detect differences between textures of self-structured surfaces were evaluated. The methods were compared against a blanket with rotating grid (BRG) method. Computer-generated images of self-structured surface textures with different roughness, directions and patterns, and atomic force microscope images of real self-structured surfaces were used. The computer texture images were generated using a specially developed motif-based texture generator. Results obtained showed that the ABRG method is more accurate and reliable than the BRG and BSI methods