A. C. Grillet’s research while affiliated with Laboratoire Optimisation de la Conception et Ingénierie de l'Environnement and other places

In the present study, Spartium junceum (SJ) fibers were chemically treated with different concentrations of two coupling agents, silane N [-3 Trimethoxysilyl propyl] ethylene diamine (Z-6020) and stearic acid, in order to improve the mechanical properties of polypropylene/Spartium junceum fibers (PP/SJ) composites. The chemical modification efficiency was verified by FTIR analysis which showed the appearance of bands around 1260 and 1100 cm attributed to asymmetric stretching of Si-O-Si linkage and Si-O-Cellulose for (Z-6020) modified SJ fibers. The mechanical properties of the composites prepared from chemically treated Spartium junceum fibers are found to increase substantially compared to those with untreated ones.

The composites investigated in this article were polypropylene reinforced with Spanish broom (Spartium junceum) fibers. These fibers were modified with N[-3 Trimethoxysilyl propyl] ethylene diamine (Z6020) or stearic acid, which work as coupling agents between fibers and matrix. This work studied the thermal (differential scanning calorimetry) and thermomechanical (dynamic mechanical thermal) analysis. The surfaces of the composites were characterized by electron microscopy. It was found that silane-treated fiber composites show superior properties compared with the specimens made of pure polypropylene. Microscopic observations correlate with these results.

Image analysis is currently used to study the structure of materials. In this paper, classical techniques of signal analysis such as power spectrum and autocorrelation functions are applied for this purpose. These techniques allow the detection of hidden features in complex images such as fracture surfaces, before highlighting them using spatial filtering. For that, the power spectrum allows us to locate the range of scales of peculiar texture, present but invisible to the naked eye. Thus, this study deals with the homogeneity of epoxy networks. Another way to use the method concerns aggregation phenomena. Indeed, the method allows us to assimilate several images of different magnifications, in order to characterize the aggregation on a large range of scales from the size of the particle or fibre to the full size of the sample. Then, the peculiar morphology of thermoplastic composites made from commingled fibres can be studied. The autocorrelation function method is also used to highlight features in the images of such composite materials.