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Articles by Marco Cantoni in JoVE

Other articles by Marco Cantoni on PubMed

Shear Mode Coupling and Tilted Grain Growth of A1N Thin Films in BAW Resonators

Polycrystalline A1N thin films were deposited by RF reactive magnetron sputtering on Pt(111)/Ti electrode films. The substrates were tilted by an angle ranging from 40 degrees to 70 degrees with respect to the target normal. A low deposition temperature and a high sputter gas pressure were found ideal for tilted growth. The resulting grain tilt angle amounts to about half the substrate tilt angle. For coupling evaluation, 5 GHz solidly mounted resonator structures have been realized. The tilted grain A1N films exhibited a permittivity in the 9.5-10.5 range and loss tangent of 0.3%. Two shear modes as well as the longitudinal mode could be clearly identified. The coupling coefficient k2(eff) of the fundamental thickness shear mode (TS0) was found to be about 0.5%, which is compatible with a c-axis tilt of about 6 degrees.

Borosilicate Nanoparticles Prepared by Exothermic Phase Separation

Nanoparticles play an important role in chemical and biological sciences due to their ability to bind and concentrate many molecules on their surface. Polymers and silica are widely used to make nanoparticles, but efforts to make nanoparticles from borosilicate glass--which exhibits high tolerance to chemicals and solvents, combined with excellent mechanical and thermal stability--have proved unsuccessful. Here we show that borosilicate nanoparticles (100-500 nm in size) can be synthesized by simply mixing a silicon-boron binary oxide solution, prepared using non-aqueous organic solvents, with water. This induces a vigorous exothermic phase separation in which borosilicate nanoparticles burst out of a silica phase. In addition to potential applications in the life sciences, monodisperse borosilicate particles could also have applications in the production of photonic bandgap devices with high optical contrast, contrast agents for ultrasonic microscopy or chemical filtration membranes.

Automated Detection and Segmentation of Synaptic Contacts in Nearly Isotropic Serial Electron Microscopy Images

We describe a protocol for fully automated detection and segmentation of asymmetric, presumed excitatory, synapses in serial electron microscopy images of the adult mammalian cerebral cortex, taken with the focused ion beam, scanning electron microscope (FIB/SEM). The procedure is based on interactive machine learning and only requires a few labeled synapses for training. The statistical learning is performed on geometrical features of 3D neighborhoods of each voxel and can fully exploit the high z-resolution of the data. On a quantitative validation dataset of 111 synapses in 409 images of 1948×1342 pixels with manual annotations by three independent experts the error rate of the algorithm was found to be comparable to that of the experts (0.92 recall at 0.89 precision). Our software offers a convenient interface for labeling the training data and the possibility to visualize and proofread the results in 3D. The source code, the test dataset and the ground truth annotation are freely available on the website http://www.ilastik.org/synapse-detection.

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