In the present work, a comparative study of the mechanical behavior of two series of elastomeric composites, based on carboxylated styrene butadiene rubber (X-SBR) and reinforced with rice bran carbon (RBC) and graphite, is reported. Hybrid composites of X-SBR filled with RBC-graphite were also investigated in terms of the cure characteristics, hardness, tensile properties, abrasion resistance, and swelling. It was observed that the cure times decreased with the incorporation of a carbon filler whereas the torque difference, tensile strength, tensile modulus, hardness, and swelling resistance increased compared to the neat X-SBR revealing a favorable characteristic of crosslinking. Dynamic rheological analysis showed that the G' values of the composites, upon the addition of RBC-graphite, were changed to some extent. This demonstrates that the presence of a strongly developed network of fillers will ensure a reinforcing characteristic in a polymer matrix.

Many advanced ground-based solar telescopes improve the spatial resolution of observation images using an adaptive optics (AO) system. As any AO correction remains only partial, it is necessary to use post-processing image reconstruction techniques such as speckle masking or shift-and-add (SAA) to reconstruct a high-spatial-resolution image from atmospherically degraded solar images. In the New Vacuum Solar Telescope (NVST), the spatial resolution in solar images is improved by frame selection and SAA. In order to overcome the burden of massive speckle data processing, we investigate the possibility of using the speckle reconstruction program in a real-time application at the telescope site. The code has been written in the C programming language and optimized for parallel processing in a multi-processor environment. We analyze the scalability of the code to identify possible bottlenecks, and we conclude that the presented code is capable of being run in real-time reconstruction applications at NVST and future large aperture solar telescopes if care is taken that the multi-processor environment has low latencies between the computation nodes.