Nanotechnology has reached a level of maturity that allows them to take advantage of the computer-aided design. The inverse problem methodologies can help to achieve this by exceeding the simple explanation of phenomena and the direct optimization of devices. The only condition is that the scientific community takes ownership of these methods and considers them to be effective development tools.
Nanotechnology, Inverse Problem, Propagation of Uncertainties, Tolerance in Engineering Processes, Abacus, Plasmonics
A. Kildishev, U. Chettiar, Z. Liu, V. Shalaev, D. Kwon, Z. Bayraktar, and D. Werner, "Stochastic optimization of low-loss optical negative-index metamaterial," J. Opt. Soc. Am. B 24, A34-A39 (2007) - A. van Rhijn, H. Offerhaus, P. van der Walle, J. Herek, and A. Jafarpour, Exploring, tailoring, and traversing the solution landscape of a phase-shaped CARS process, Opt. Express 18, 2695-2709 (2010) - A. Mayer, L. Gaouyat, D. Nicolay, T. Carletti, and O. Deparis, "Multi-objective genetic algorithm for the optimization of a flat-plate solar thermal collector," Opt. Express 22, A1641-A1649 (2014).
British Museum, The Lycurgus Cup, http://www.britishmuseum.org/explore/highlights/highlight_objects/pe_mla/t/the_lycurgus_cup.aspx (2015).
A. Ruivo, C. Gomes, A. Lima, M. L. Botelho, R. Melo, and A. B. A. Pires de Matos: Gold nanoparticles in ancient and contemporary ruby glass, J. Cult. Heritage 9, e134–e137 (2008).
J. Lafait, S. Berthier, C. Andraud, V. Reillon, and J. Boulenguez: Physical colors in cultural heritage: surface plasmons in glass, C.R. Phys. 10, 649–659 (2009).
G. Mie, Beiträge zur Optik trüber Medien speziell kolloidaler Metallösungen (Contributions to the optics of turbid media, especially colloidal metal solutions), Ann. Phys. 330, 377 – 445 (1908) - W. J. Wiscombe, Improved Mie scattering algorithms, Appl. Opt. 19, 1505 – 1509 (1980).
T. Grosges and D. Barchiesi, Numerical Study of Plasmonic Efficiency of Gold Nanostripes for Molecule Detection, Sci. World J. 2015, art. no. 724123, (2015).
D. Barchiesi, Improved method based on S matrix for the optimization of SPR biosensors, Opt. Commun. 286, 23-29 (2012).
G. Hoffmann, CIE color space, http://docs-hoffmann.de/ciexyz29082000.pdf (2013).
J. Kennedy and R. Eberhart, Particle swarm optimization, in IEEE International Conference on Neural Networks, Perth, Australi, Vol. IV, pp. 1942 – 1948 (1995).
T. Turbadar, Complete absorption of light by thin metal films, Proc. Phys. Soc. London 73, 40 – 44 (1959).
D. Barchiesi, Numerical retrieval of thin aluminum layer properties from SPR experimental data, Opt. Express 20, 9064 – 9078 (2012).
J. Salvi and D. Barchiesi, Measurement of thicknesses and optical properties of thin films from surface plasmon resonance (SPR), Appl. Phys. A 115, 245–255 (2014).
D. Barchiesi, Lycurgus Cup: inverse problem using photographs for characterization of matter, J. Opt. Soc. Am. A 32, 1544-1555 (2015).
D. Barchiesi, S. Kessentini, N. Guillot, M. Lamy de la Chapelle and T. Grosges, Localized surface plasmon resonance in arrays of nano-gold cylinders: inverse problem and propagation of uncertainties, Opt. Express 21, 2245-2262 (2013).
T. Grosges, D. Barchiesi, S. Kessentini, G. Grehan and M. Lamy de la Chapelle, Nanoshells for photothermal therapy: a Monte-Carlo based numerical study of their design tolerance, Biomed. Opt. Express 2, 1584-1596 (2011).
L. M. Liz-Marzán, Nanometals: formation and color, Mater. Today 7, 26-31 (2004).
T. Grosges, D. Barchiesi, T. Toury and G. Grehan, Design of nanostructures for imaging and biomedical applications by plasmonic optimization, Opt. Lett. 33, 2812-2814 (2008).
D. Pejchang, S. Coëtmellec, G. Gréhan, M. Brunel, D. Lebrun, A. Chaari, T. Grosges, and D. Barchiesi, Recovering the size of nanoparticles by digital in-line holography, Opt. Express 23, 18351-18360 (2015).