Open Access
Micro sized interdigital capacitor for humidity detection based on agarose coating
(2021) Vitoria Pascual, Ignacio; Armas, Dayron; Coronel Camones, Carlos Manuel; 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
A micro sized interdigital capacitor has been proposed for the detection of relative humidity. The photolithography technique enables the fabrication of fingers with a size of 10x500 um. A thin film of agarose functionalizes the sensor for humidity sensing, which improves its performance by 155 times, obtaining a sensitivity of 32.98 pF/%RH.
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.
Open Access
Air bubble detection in water flow by means of ai-assisted infrared reflection system
(IEEE, 2024-06-26) 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
This letter introduces an innovative, cost-effective solution for detecting air bubbles in water flow systems using an AI-assisted infrared reflection system. In industries, such as chemical, mechanical, oil, and nuclear, the presence of air bubbles in fluids can compromise both product quality and process efficiency. Our research develops a system that combines infrared optical sensors with machine learning algorithms to detect and quantify bubble presence effectively. The system’s design utilizes infrared emitters and photodetectors arranged around a pipe to capture detailed data on bubble characteristics, which is then analyzed using a support vector machine (SVM) model to predict bubble concentrations. Experimental results demonstrate the system’s ability to accurately identify different levels of bubble presence, offering significant improvements over existing methods. Key performance metrics include a mean squared error of 0.0694, a root mean squared error of 0.2634, and a coefficient of determination of 0.9765, indicating high accuracy and reliability. This approach not only enhances operational reliability and safety but also provides a scalable solution adaptable to various industrial settings.
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
Gas detection using LMR-based optical fiber sensors
(MDPI, 2018) Dreyer, Uilian José; Ozcariz Celaya, Aritz; Ascorbe Muruzabal, Joaquín; Zubiate Orzanco, Pablo; Vitoria Pascual, Ignacio; Martelli, Cicero; Cardozo da Silva, Jean Carlos; Ruiz Zamarreño, Carlos; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación
This work presents a first approach to the utilization of Lossy Mode Resonance (LMR) based optical fiber sensors for gas detection. The optical sensor is based on a SnO2 thin-film fabricated onto the core of cladding removed multimode fibers (MMF). The time response of the device to four different gases (NH3, NO, CO2 and O2) was monitored obtaining the best sensitivity for NO whereas the response to NH3 revealed the best repeatability.
Open Access
Micro sized interdigital capacitor for gases detection based on graphene oxide coating
(Springer, 2023) Vitoria Pascual, Ignacio; Armas, Dayron; Coronel Camones, Carlos Manuel; Algarra González, Manuel; Ruiz Zamarreño, Carlos; Matías Maestro, Ignacio; Mukhopadhyay, Subhas C.; Institute for Advanced Materials and Mathematics - INAMAT2; Institute of Smart Cities - ISC
A micro sized interdigital capacitor sensible to CO2 and NO is studied in this work. The photolithography technique enables to obtain fingers with dimensions of 10 × 500 µm and separated 7 µm between them. The deposition of a film composed of graphene oxide particles as the dielectrics of the capacitor allows to measure the gas concentration of CO2 and NO mixed with N2. The sensors were characterized in a gas chamber with a constant flow, obtaining promising results in changes of capacitance at 100 Hz. The sensors have a good linearity and sensitivity with a R2 = 0.996 and 5.026·10-1 pF/ % v/v for CO2 and R2=0.972 and 1.433·10-1 pF/ppb for NO.
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
A comprehensive study of optical resonances in metals, dielectrics, and excitonic materials in double interface structures
(Elsevier, 2025-02-01) Imas González, José Javier; Matías Maestro, Ignacio; Del Villar, Ignacio; Ozcariz Celaya, Aritz; Vitoria Pascual, Ignacio; Ruiz Zamarreño, Carlos; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza; Institute of Smart Cities - ISC
From an optical perspective, depending on the relationship between the real (n) and imaginary (k) parts of its refractive index, three broad categories of materials can be distinguished: metals (k ¿ n), dielectrics (n ¿ k), and materials in which n ¿ k (termed here excitonic materials). The modes and optical resonances that appear in a thin film bounded by two dielectrics with similar refractive index, what we call here a double interface structure, have been widely studied in the case of metals, but not for dielectrics, or materials with n ¿ k. In this work, we propose a new approach, based on employing the phase matching condition to correlate the resonances that appear in the wavelength versus incident angle color maps of the reflected power with the modal analysis of the cross section of the structure. This analysis is performed, using an attenuated total reflection (ATR) setup, for thin film materials that belong to each of the mentioned categories: a metal (gold, Au), a dielectric (titanium dioxide, TiO2), and a material with n ¿ k (chromium, Cr). The theoretical analysis is supported with experimental results. It is demonstrated that this method enables to identify any resonance at any wavelength or incident angle, being valid for all three types of materials. Therefore, it is considered the suggested approach will help the research in these materials and in the double interface structure in the optics and photonics field.
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
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).