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Author: Fomin, Vladimir M. × End date: 2019 × Start date: 2010 × DDC: 540 × Version: publishedVersion × WGL Institute: IFWD ×

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    Three-Dimensional Superconducting Nanohelices Grown by He+-Focused-Ion-Beam Direct Writing
    (Washington, DC : ACS Publ., 2019) Córdoba, Rosa; Mailly, Dominique; Rezaev, Roman O.; Smirnova, Ekaterina I.; Schmidt, Oliver G.; Fomin, Vladimir M.; Zeitler, Uli; Guillamón, Isabel; Suderow, Hermann; De Teresa, José María
    Novel schemes based on the design of complex three-dimensional (3D) nanoscale architectures are required for the development of the next generation of advanced electronic components. He+ focused-ion-beam (FIB) microscopy in combination with a precursor gas allows one to fabricate 3D nanostructures with an extreme resolution and a considerably higher aspect ratio than FIB-based methods, such as Ga+ FIB-induced deposition, or other additive manufacturing technologies. In this work, we report the fabrication of 3D tungsten carbide nanohelices with on-demand geometries via controlling key deposition parameters. Our results show the smallest and highest-densely packed nanohelix ever fabricated so far, with dimensions of 100 nm in diameter and aspect ratio up to 65. These nanohelices become superconducting at 7 K and show a large critical magnetic field and critical current density. In addition, given its helical 3D geometry, fingerprints of vortex and phase-slip patterns are experimentally identified and supported by numerical simulations based on the time-dependent Ginzburg-Landau equation. These results can be understood by the helical geometry that induces specific superconducting properties and paves the way for future electronic components, such as sensors, energy storage elements, and nanoantennas, based on 3D compact nanosuperconductors. © 2019 American Chemical Society.
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    Supervised discriminant analysis for droplet micro-magnetofluidics
    (Heidelberg : Springer, 2015) Lin, Gungun; Fomin, Vladimir M.; Makarov, Denys; Schmidt, Oliver G.
    We apply the technique of supervised discriminant analysis (SDA) for in-flow detection in droplet-based magnetofluidics. Based on the SDA, we successfully discriminate bivariant droplets of different volumes containing different encapsulated magnetic content produced by a GMR-based lab-on-chip platform. We demonstrate that the accuracy of discrimination is superior when the correlation of variables for data training is included to the case when the spatial distribution of variables is considered. Droplets produced with differences in ferrofluid concentration of 2.5 mg/ml and volume of 200 pl have been identified with high accuracy (98 %), indicating the significance of SDA for e.g. the discrimination in magnetic immuno-agglutination assays. Furthermore, the results open the way for the development of a unique magnetofluidic platform for future applications in multiplexed droplet-based barcoding assays and screening.