Open Access
Mode transition during deposition of nanoscale ITO coatings on tilted fiber Bragg gratings
(Optica Publishing Group, 2022) Imas González, José Javier; Albert, Jacques; Del Villar, Ignacio; Ozcariz Celaya, Aritz; Ruiz Zamarreño, Carlos; Matías Maestro, Ignacio; Ingeniería Eléctrica, Electrónica y de Comunicación; Institute of Smart Cities - ISC; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
The mode transition phenomenon is experimentally demonstrated in tilted fiber Bragg gratings (TFBG) through the deposition of an indium tin oxide (ITO) thin film employing a DC sputtering machine.
Open Access
Twin lossy mode resonance on a single D-shaped optical fiber
(Optica, 2021) Imas González, José Javier; Ruiz Zamarreño, Carlos; Del Villar, Ignacio; Pérez Escudero, José Manuel; Matías Maestro, Ignacio; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación
This letter presents the fabrication of dual lossy mode resonance (LMR) refractometers based on titanium dioxide (TiO2) and tin oxide (SnO2) thin films deposited on a single side-polished D-shaped optical fiber. For the first time, to the best of our knowledge, two independent LMRs are obtained in the same D-shaped optical fiber, by using a step-shaped nanostructure consisting of a first section of TiO2 with a thickness of 120 nm and a second section with a thickness of 140 nm (120 nm of TiO2 and 20 nm of SnO2). Each section is responsible for generating a first-order LMR with TM-polarized light (LMRTM). TiO2 is deposited by atomic layer deposition and SnO2 by electron-beam deposition. The theoretical results show that the depth of each of the resonances of the dual LMR depends on the length of the corresponding section. Two experimental devices were fabricated with sections of different lengths, and their sensitivities were studied, achieving values ∼ 4000 nm/refractive index unit (RIU) with a maximum of 4506 nm/RIU for values of the SRI between 1.3327 and 1.3485.
Open Access
Route towards a label-free optical waveguide sensing platform based on lossy mode resonances
(IFSA Publishing, 2019) Ruiz Zamarreño, Carlos; Zubiate Orzanco, Pablo; Ozcariz Celaya, Aritz; Elosúa Aguado, César; Socorro Leránoz, Abián Bentor; Urrutia Azcona, Aitor; López Torres, Diego; Acha Morrás, Nerea de; Ascorbe Muruzabal, Joaquín; Vitoria Pascual, Ignacio; Imas González, José Javier; Corres Sanz, Jesús María; Díaz Lucas, Silvia; Hernáez Sáenz de Zaitigui, Miguel; Goicoechea Fernández, Javier; Arregui San Martín, Francisco Javier; Matías Maestro, Ignacio; Del Villar, Ignacio; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación; Gobierno de Navarra / Nafarroako Gobernua,0011-1365-2017- 000117; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, PJUPNA26
According to recent market studies of the North American company Allied Market Research, the field of photonic sensors is an emerging strategic field for the following years and it is expected to garner $18 billion by 2021. The integration of micro and nanofabrication technologies in the field of sensors has allowed the development of new technological concepts such as lab-on-a-chip which have achieved extraordinary advances in terms of detection and applicability, for example in the field of biosensors. This continuous development has allowed that equipment consisting of many complex devices that occupied a whole room a few years ago, at present it is possible to handle them in the palm of the hand; that formerly long duration processes are carried out in a matter of milliseconds and that a technology previously dedicated solely to military or scientific uses is available to the vast majority of consumers. The adequate combination of micro and nanostructured coatings with optical fiber sensors has permitted us to develop novel sensing technologies, such as the first experimental demonstration of lossy mode resonances (LMRs) for sensing applications, with more than one hundred citations and related publications in high rank journals and top conferences. In fact, fiber optic LMR-based devices have been proven as devices with one of the highest sensitivity for refractometric applications. Refractive index sensitivity is an indirect and simple indicator of how sensitive the device is to chemical and biological species, topic where this proposal is focused. Consequently, the utilization of these devices for chemical and biosensing applications is a clear opportunity that could open novel and interesting research lines and applications as well as simplify current analytical methodologies. As a result, on the basis of our previous experience with LMR based sensors to attain very high sensitivities, the objective of this paper is presenting the route for the development of label-free optical waveguide sensing platform based on LMRs that enable to explore the limits of this technology for bio-chemosensing applications.
Open Access
Surface exciton polariton resonances (SEPR)-based sensors
(Elsevier, 2023) Vitoria Pascual, Ignacio; Ruiz Zamarreño, Carlos; Ozcariz Celaya, Aritz; Imas González, José Javier; Del Villar, Ignacio; Matías Maestro, Ignacio; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación
A new type of resonance in the development of sensors using long-range surface exciton polariton (LRSEP) phenomena has been coined: surface exciton plasmon resonance (SEPR). The resonance was obtained in the reflected spectrum of a Kretschmann-Raether setup with a two-coupled-interface structure composed of 412 nm magnesium fluoride and 50 nm chromium thin films. The roles of different parameters such as thicknesses of the films and the incidence angles have been simulated. Some preliminary experimental results show a promising performance with a shift of the resonance central wavelength with changes in the incidence angle of -136.52 nm/° and a sensitivity of 23,221 nm/refractive index unit.
Open Access
Rheumatoid arthritis miRNA biomarker detection by means of LMR based fiber-optic biosensor
(IEEE, 2020) Imas González, José Javier; Ruiz Zamarreño, Carlos; Zubiate Orzanco, Pablo; Campión, J.; Sánchez-Martín, L.; Matías Maestro, Ignacio; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, PJUPNA26
Development of miRNA optical biosensors for disease diagnosis and monitoring has acquired relevance in recent years, due to the clinical importance of miRNA and the inherent advantages of optical sensors. Here, we present the utilization of a fiber optic sensor based on Lossy Mode Resonance (LMR) for the detection of miRNA hsa-miR-223, a promising biomarker for the diagnosis of rheumatoid arthritis (RA).
Open Access
Beyond near-infrared lossy mode resonances with fluoride glass optical fiber
(Optica, 2021) Vitoria Pascual, Ignacio; Ruiz Zamarreño, Carlos; Ozcariz Celaya, Aritz; Imas González, José Javier; Matías Maestro, Ignacio; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
The objective of this Letter consists of the exploration of the lossy mode resonance (LMR) phenomenon beyond the nearinfrared region and specifically in the short wave infrared region (SWIR) and medium wave infrared region (MWIR). The experimental and theoretical results show for the first time, to the best of our knowledge, not only LMRs in these regions, but also the utilization of fluoride glass optical fiber associated with this phenomenon. The fabricated devices consist of a nanometric thin-film of titanium dioxide used as LMR generating material, which probed extraordinary sensitivities to external refractive index (RI) variations. RI sensitivity was studied in the SWIR and MWIR under different conditions, such as the LMR wavelength range or the order of resonance, showing a tremendous potential for the detection of minute concentrations of gaseous or biological compounds in different media.
Open Access
Data augmentation techniques for machine learning applied to optical spectroscopy datasets in agrifood applications: a comprehensive review
(MDPI, 2023) Gracia Moisés, Ander; Vitoria Pascual, Ignacio; Imas González, José Javier; Ruiz Zamarreño, Carlos; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza; Institute of Smart Cities - ISC
Machine learning (ML) and deep learning (DL) have achieved great success in different tasks. These include computer vision, image segmentation, natural language processing, predicting classification, evaluating time series, and predicting values based on a series of variables. As artificial intelligence progresses, new techniques are being applied to areas like optical spectroscopy and its uses in specific fields, such as the agrifood industry. The performance of ML and DL techniques generally improves with the amount of data available. However, it is not always possible to obtain all the necessary data for creating a robust dataset. In the particular case of agrifood applications, dataset collection is generally constrained to specific periods. Weather conditions can also reduce the possibility to cover the entire range of classifications with the consequent generation of imbalanced datasets. To address this issue, data augmentation (DA) techniques are employed to expand the dataset by adding slightly modified copies of existing data. This leads to a dataset that includes values from laboratory tests, as well as a collection of synthetic data based on the real data. This review work will present the application of DA techniques to optical spectroscopy datasets obtained from real agrifood industry applications. The reviewed methods will describe the use of simple DA techniques, such as duplicating samples with slight changes, as well as the utilization of more complex algorithms based on deep learning generative adversarial networks (GANs), and semi-supervised generative adversarial networks (SGANs).
Open Access
Optical biosensors: a quick overview
(2021) Imas González, José Javier; Ruiz Zamarreño, Carlos; Matías Maestro, Ignacio; Ingeniería Eléctrica, Electrónica y de Comunicación; Institute of Smart Cities - ISC; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
This work aims to provide a brief overview of the latest trends in the domain of optical biosensors.
Open Access
Tunable sensitivity in long period fiber gratings during mode transition with low refractive index intermediate layer
(IEEE, 2022) Del Villar, Ignacio; Montoya-Cardona, Jorge; Imas González, José Javier; Reyes-Vera, Erick; Ruiz Zamarreño, Carlos; Matías Maestro, Ignacio; Cruz, José Luis; Ingeniería Eléctrica, Electrónica y de Comunicación; Institute of Smart Cities - ISC; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
Double-clad fibers where the second cladding has a lower refractive index than the first cladding, prove to be ideal structures for potentiating and tuning the sensitivity in long-period fiber gratings (LPFGs) operating in mode transition. When a thin film is deposited on the optical fiber, the second cladding performs acts as a barrier that initially prevents the transition to guidance in the thin film of one of the modes guided in the first cladding. Finally, the transition to guidance occurs with a sensitivity increase, in analogy to the tunnel effect observed in semiconductors. This improvement has been demonstrated both as a function of the thin film thickness and the surrounding medium refractive index, with enhancement factors of 4 and 2, respectively. This idea reinforces the performance of LPFGs, adding a new degree of freedom to the mode transition and the dispersion turning point phenomena. Moreover, the control of the variation of the effective index of cladding modes could be applied in other structures, such as tilted-fiber gratings or evanescent wave sensors.
Embargo
Optimization of optical spectroscopy classification algorithms for limited data scenarios in the food industry: tomato sauce samples case
(Elsevier, 2025-01-01) Gracia Moisés, Ander; Vitoria Pascual, Ignacio; Avedillo de la Casa, Amaia; Moreno Pérez, María; Imas González, José Javier; Ruiz Zamarreño, Carlos; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza; Institute of Smart Cities - ISC; Gobierno de Navarra / Nafarroako Gobernua; Universidad Pública de Navarra / Nafarroako Unibertistate Publikoa
This study addresses the problem of training deep learning models with limited datasets, a significant challenge in sectors like medical imaging and food quality analysis. To tackle this issue, generative adversarial networks (GANs) will be employed to augment the available data and improve model performance. An innovative approach is introduced here, integrating semi-supervised learning and generative modeling to maximize the use of small datasets in developing robust models. The method involves reversing the conventional distribution of training and testing data to focus on model evaluation and generalization from limited samples. Wasserstein GANs (WGANs) and Semi-Supervised GANs (SGANs), are utilized to supplement datasets with synthetic but realistic examples, enhancing the training process in scenarios of data scarcity. These techniques are applied in the context of visible reflectance spectroscopy to analyze tomato sauces, demonstrating the method's effectiveness in non-invasively assessing key quality parameters such as oil content, °Brix, and pH. The results show significant improvements in model performance metrics: for %Oil content, overall accuracy increased from 0.47 to 0.66; for °Bx, it rose from 0.65 to 0.71; and for pH measurement, accuracy improved from 0.43 to 0.62. These outcomes highlight the model's improved capability to generalize and maintain accuracy with limited data.