Characterization of a perfect sinusoidal grating profile using an artificial neural network for plasmonic-based sensors.

In this paper, we present a system intended to detect a targeted perfect sinusoidal profile of a diffraction grating during its manufactured process. Indeed, the sinusoidal nature of the periodic structure is essential to ensure optimal efficiency of specific applications as plasmonic sensors (surface plasmon resonance -based sensors). A neural network is implemented to characterize the geometrical shape of the structure under testing at the end of the laser interference lithography process. This decision tool operates in classifier mode prior to further processing. Then, the geometrical parameters of the structure can be reliably determined if necessary. Two solutions can be considered: the detection of a fixed geometrical shape operating on a binary mode and the identification of a geometrical shape from a limited number of profiles. These methods are validated in the context of plasmonic sensors on experimental sinusoidal grating structures with a grating period of 627 nm.

Influence of the Micro-Nanostructuring of Titanium Dioxide Films on the Photocatalytic Degradation of Formic Acid under UV Illumination.

Surface micro-nanostructuring can provide new functionalities and properties to coatings. For example, it can improve the absorption efficiency, hydrophobicity and/or tribology properties. In this context, we studied the influence of micro-nanostructuring on the photocatalytic efficiency of sol-gel TiO2 coatings during formic acid degradation under UV illumination. The micro-nanostructuring was performed using the UV illumination of microspheres deposited on a photopatternable sol-gel layer, leading to a hexagonal arrangement of micropillars after development. The structures and coatings were characterized using Raman spectroscopy, ellipsometry, atomic force microscopy and scanning electron microscopy. When the sol-gel TiO2 films were unstructured and untreated at 500 °C, their effect on formic acid's degradation under UV light was negligible. However, when the films were annealed at 500 °C, they crystallized in the anatase phase and affected the degradation of formic acid under UV light, also depending on the thickness of the layer. Finally, we demonstrated that surface micro-nanostructuring in the form of nanopillars can significantly increase the photocatalytic efficiency of a coating during the degradation of formic acid under UV light.

Impact of γ-rays Irradiation on Hybrid TiO2-SiO2 Sol-Gel Films Doped with RHODAMINE 6G.

In the present paper, we investigate how the optical and structural properties, in particular the observed photoluminescence (PL) of photocurable and organic-inorganic TiO2-SiO2 sol-gel films doped with Rhodamine 6G (R6G) are affected by γ-rays. For this, four luminescent films, firstly polymerized with UV photons (365 nm), were submitted to different accumulated doses of 50 kGy, 200 kGy, 500 kGy and 1 MGy while one sample was kept as a reference and unirradiated. The PL, recorded under excitations at 365 nm, 442 nm and 488 nm clearly evidences that a strong signal peaking at 564 nm is still largely present in the γ-irradiated samples. In addition, M-lines and Fourier-transform infrared (FTIR) spectroscopies are used to quantify the radiation induced refractive index variation and the chemical changes, respectively. Results show that a refractive index decrease of 7 × 10-3 at 633 nm is achieved at a 1 MGy accumulated dose while a photo-induced polymerization occurs, related to the consumption of CH=C, Si-OH and Si-O-CH3 groups to form Ti-O and Si-O bonds. All these results confirm that the host matrix (TiO2-SiO2) and R6G fluorophores successfully withstand the hard γ-ray exposure, opening the way to the use of this material for sensing applications in radiation-rich environments.

Experimental identification of a grating profile using neural network classifiers in optical scatterometry.

In this paper, we develop a new technique, to the best of our knowledge, of grating characterization based on two separate steps. First, an artificial neural network (ANN) is implemented in a classifier mode to identify the shape of the geometrical profile from a measured optical signature. Then, a second ANN is used in a regression mode to determine the geometrical parameters corresponding to the selected geometrical model. The advantage of this approach is highlighted by discussions and studies involving the error criterion that is used widely in scatterometry. In addition, experimental tests are provided on diffraction grating structures with a period of 500 and 750 nm.

Comparison between the UV and X-ray Photosensitivities of Hybrid TiO2-SiO2 Thin Layers.

The photo-induced effects on sol-gel-based organo TiO2-SiO2 thin layers deposited by the dip-coating technique have been investigated using two very different light sources: A light-emitting diode (LED) emitting in the UV (at 365 nm, 3.4 eV) and an X-ray tube producing 40 keV mean-energy photons. The impact of adding a photo-initiator (2,2-dimethoxy-2-phenylacetophenone-DMPA) on the sol-gel photosensitivity is characterized namely in terms of the photo-induced refractive index measured through M-line spectroscopy. Results show that both silica-titania sol-gel films with or without the photo-initiator are photosensitive to both photon sources. The induced refractive index values reveal several features where slightly higher refractive indexes are obtained for the sol-gel containing the photo-initiator. UV and X-ray-induced polymerization degrees are discussed using Fourier-transform infrared (FTIR) spectroscopy where the densification of hybrid TiO2-SiO2 layers is related to the consumption of the CH=C groups and to the decomposition of Si-OH and Si-O-CH3 bonds. X-rays are more efficient at densifying the TiO2-SiO2 inorganic and organic network with respect to the UV photons. Hard X-ray photolithography, where no cracks or damages are observed after intense exposition, can be a promising technique to design submicronic-structure patterns on TiO2-SiO2 thin layers for the building of optical sensors.

Longitudinal magneto-optical effect enhancement with high transmission through a 1D all-dielectric resonant guided mode grating.

A significant enhancement of the longitudinal magneto-optical effect is demonstrated numerically and experimentally in transmission, and for small angles of incidence, through a subwavelength resonant structure consisting of a dielectric grating on top of a magneto-optical waveguide. The enhanced polarization rotation is associated with a high transmittance. These low footprint devices may thus be suitable for applications like magnetic field sensors or in non-destructive testing.

Enhancement of Both Faraday and Kerr Effects with an All-Dielectric Grating Based on a Magneto-Optical Nanocomposite Material.

We report on the design, fabrication, and characterization of an all-dielectric one-dimensional (1D) resonant device formed by a silicon nitride grating impregnated by a low-index magneto-optical silica-type matrix. This impregnation is realized through the dipping of the 966 nm periodic template in a sol-gel solution previously doped with CoFe2O4 nanoparticles, and able to fill the grating slits. By a proper adjustment of the geometrical parameters of such a photonic crystal membrane, simultaneous excitation of transverse electric (TE) and transverse magnetic (TM) polarization resonances is nearly achieved at 1570 nm. This TE/TM phase-matching situation leads to a fivefold enhancement of the Faraday effect in the resonance area with an increased merit factor of 0.32°. Moreover, the device demonstrates its ability to enhance longitudinal and transverse Kerr effects for the other directions of the applied magnetic field. Taking benefits from the ability of the nanocomposite material to be processed on photonic platforms, and despite its quite low magneto-optical activity compared to classical magnetic materials, this work proves that an all-dielectric 1D device can produce a high magneto-optical sensitivity to every magnetic field directions.

Periodic TiO2 Nanostructures with Improved Aspect and Line/Space Ratio Realized by Colloidal Photolithography Technique.

This paper presents substantial improvements of the colloidal photolithography technique (also called microsphere lithography) with the goal of better controlling the geometry of the fabricated nano-scale structures-in this case, hexagonally arranged nanopillars-printed in a layer of directly photopatternable sol-gel TiO2. Firstly, to increase the achievable structure height the photosensitive layer underneath the microspheres is deposited on a reflective layer instead of the usual transparent substrate. Secondly, an increased width of the pillars is achieved by tilting the incident wave and using multiple exposures or substrate rotation, additionally allowing to better control the shape of the pillar's cross section. The theoretical analysis is carried out by rigorous modelling of the photonics nanojet underneath the microspheres and by optimizing the experimental conditions. Aspect ratios (structure height/lateral structure size) greater than 2 are predicted and demonstrated experimentally for structure dimensions in the sub micrometer range, as well as line/space ratios (lateral pillar size/distance between pillars) greater than 1. These nanostructures could lead for example to materials exhibiting efficient light trapping in the visible and near-infrared range, as well as improved hydrophobic or photocatalytic properties for numerous applications in environmental and photovoltaic systems.

Scattering effects and high-spatial-frequency nanostructures on ultrafast laser irradiated surfaces of zirconium metallic alloys with nano-scaled topographies.

The origin of high-spatial-frequency laser-induced periodic surface structures (HSFL) driven by incident ultrafast laser fields, with their ability to achieve structure resolutions below λ/2, is often obscured by the overlap with regular ripples patterns at quasi-wavelength periodicities. We experimentally demonstrate here employing defined surface topographies that these structures are intrinsically related to surface roughness in the nano-scale domain. Using Zr-based bulk metallic glass (Zr-BMG) and its crystalline alloy (Zr-CA) counterpart formed by thermal annealing from its glassy precursor, we prepared surfaces showing either smooth appearances on thermoplastic BMG or high-density nano-protuberances from randomly distributed embedded nano-crystallites with average sizes below 200 nm on the recrystallized alloy. Upon ultrashort pulse irradiation employing linearly polarized 50 fs, 800 nm laser pulses, the surfaces show a range of nanoscale organized features. The change of topology was then followed under multiple pulse irradiation at fluences around and below the single pulse threshold. While the former material (Zr-BMG) shows a specific high quality arrangement of standard ripples around the laser wavelength, the latter (Zr-CA) demonstrates strong predisposition to form high spatial frequency rippled structures (HSFL). We discuss electromagnetic scenarios assisting their formation based on near-field interaction between particles and field-enhancement leading to structure linear growth. Finite-difference-time-domain simulations outline individual and collective effects of nanoparticles on electromagnetic energy modulation and the feedback processes in the formation of HSFL structures with correlation to regular ripples (LSFL).

Fabrication of Optical Multilayer Devices from Porous Silicon Coatings with Closed Porosity by Magnetron Sputtering.

The fabrication of single-material photonic-multilayer devices is explored using a new methodology to produce porous silicon layers by magnetron sputtering. Our bottom-up methodology produces highly stable amorphous porous silicon films with a controlled refractive index using magnetron sputtering and incorporating a large amount of deposition gas inside the closed pores. The influence of the substrate bias on the formation of the closed porosity was explored here for the first time when He was used as the deposition gas. We successfully simulated, designed, and characterized Bragg reflectors and an optical microcavity that integrates these porous layers. The sharp interfaces between the dense and porous layers combined with the adequate control of the refractive index and thickness allowed for excellent agreement between the simulation and the experiments. The versatility of the magnetron sputtering technique allowed for the preparation of these structures for a wide range of substrates such as polymers while also taking advantage of the oblique angle deposition to prepare Bragg reflectors with a controlled lateral gradient in the stop band wavelengths.

Demonstration of the feasibility of a complete ellipsometric characterization method based on an artificial neural network.

Ellipsometry is an optical technique that is widely used for determining optical and geometrical properties of optical thin films. These properties are in general extracted from the ellipsometric measurement by solving an inverse problem. Classical methods like the Levenberg-Marquardt algorithm are generally too long, depending on direct calculation and are very sensitive to local minima. In this way, the neural network has proved to be an efficient tool for solving these kinds of problems in a very short time. Indeed, it is rapid and less sensitive to local minima than the classical inversion method. We suggest a complete neural ellipsometric characterization method for determining the index dispersion law and the thickness of a simple SiO(2) or photoresist thin layer on Si, SiO(2), and BK7 substrates. The influence of the training couples on the artificial neural network performance is also discussed.

Accurate and rapid optical characterization of an anisotropic guided structure based on a neural method.

Optimal performances of integrated optical devices are obtained by the use of an accurate and reliable characterization method. The parameters of interest, i.e., optical indices and thickness of the waveguide structure, are calculated from effective indices by means of an inversion procedure. We demonstrate how an artificial neural network can achieve such a process. The artificial neural network used is a multilayer perceptron. The first result concerns a simulated anisotropic waveguide. The accuracy in the determination of optical indices and waveguide thickness is 5 x 10(-5) and 4 nm, respectively. Then an experimental application on a silica-titania thin film is performed. In addition, effective indices are measured by m-lines spectroscopy. Finally, a comparison with a classical optimization algorithm demonstrates the robustness of the neural method.