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The phase transition from graphite to diamond is an appealing object of study because of many fundamental and also, practical reasons. The out-of-plane distortions required for the transition are a good tool to understand the collective behaviour of layered materials (graphene, graphite) and the van der Waals forces. As today, two basic processes have been successfully tested to drive this transition: strong shocks and high energy femtolaser excitation. They induce it by increasing either pressure or temperature on graphite. In this work, we report a third method consisting in the irradiation of graphite with ultraviolet photons of energies above 4.4 eV. We show high resolution electron microscopy images of pyrolytic carbon evidencing the dislocation of the superficial graphitic layers after irradiation and the formation of crystallite islands within them. Electron energy loss spectroscopy of the islands show that the sp 2 to sp 3 hybridation transition is a surface effect. High sensitivity X-ray diffraction experiments and Raman spectroscopy confirm the formation of diamond within the islands.

Several diseases have threatened tomato production in Florida, resulting in large losses, especially in fresh markets. In this study, a high-resolution portable spectral sensor was used to investigate the feasibility of detecting multi-diseased tomato leaves in different stages, including early or asymptomatic stages. One healthy leaf and three diseased tomato leaves (late blight, target and bacterial spots) were defined into four stages (healthy, asymptomatic, early stage and late stage) and collected from a field. Fifty-seven spectral vegetation indices (SVIs) were calculated in accordance with methods published in previous studies and established in this study. Principal component analysis was conducted to evaluate SVIs. Results revealed six principal components (PCs) whose eigenvalues were greater than 1. SVIs with weight coefficients ranking from 1 to 30 in each selected PC were applied to a K-nearest neighbour for classification. Amongst the examined leaves, the healthy ones had the highest accuracy (100%) and the lowest error rate (0) because of their uniform tissues. Late stage leaves could be distinguished more easily than the two other disease categories caused by similar symptoms on the multi-diseased leaves. Further work may incorporate the proposed technique into an image system that can be operated to monitor multi-diseased tomato plants in fields.