Juan Antonio Martinez-Rojas

The increasing integration of acoustic and electromagnetic phenomena in modern sensing systems poses a significant challenge for material selection, as optimal performance in one domain may conflict with requirements in another. This study proposes a unified multicriteria framework for material selection in multiphysics sensing environments, based on the combined analysis of acoustic impedance, electromagnetic properties, and practical engineering constraints. The methodology integrates the Analytic Hierarchy Process (AHP) for criteria weighting with multiple multicriteria decision-making (MCDM) methods, including COPRAS, VIKOR, TOPSIS, PROMETHEE, and WASPAS, applied to a heterogeneous dataset of materials spanning metals, polymers, composites, porous absorbers, and textiles. In addition to physical descriptors, the framework incorporates economic (cost) and safety-related criteria, enabling a more realistic and application-oriented evaluation. The results consistently identify highly absorptive materials, such as melamine and polyurethane foams, as the most suitable candidates under acoustically driven conditions. Composite materials emerge as robust compromise solutions, while materials with balanced profiles, such as textiles and common polymers, improve their relative position when practical constraints are considered. In contrast, highly specialized materials exhibit reduced performance due to imbalances across criteria. The consistency of the obtained rankings is assessed through Spearman rank correlation analysis, revealing a high level of agreement among the evaluated MCDM methods. Showing a very high level of agreement among methods (ρ = 0.95–1.00). Identical rankings are obtained for VIKOR, TOPSIS, and PROMETHEE (ρ = 1.00), while minor deviations observed in COPRAS and WASPAS reflect differences in aggregation behavior rather than inconsistencies in the decision problem. Overall, the proposed framework demonstrates that material selection in multiphysics systems should be approached as a scenario-based decision problem rather than a deterministic optimization task. By enabling the exploration of trade-offs between competing physical and engineering criteria, the methodology provides a transparent and extensible decision-support tool with potential applications in hybrid sensing platforms, non-destructive evaluation, and advanced wave-based systems.

This paper presents the design and tests of a miniaturized flat Archimedean spiral antenna. The antenna has two gold Archimedean spiral arms on the surface of a thick alumina cylinder. This cylindrical substrate has an outer diameter of 1.1 mm and a thickness of 0.52 mm. These reduced dimensions make the presented antenna at least an order of magnitude smaller than any previous planar Archimedean spiral antenna reported in the literature. This small antenna can be used for communication in small devices, wireless power transmission for implantable sensors, microrobots and other micro applications. Despite its reduced size, the antenna has a relatively low resonant frequency, which was measured at 4.9 GHz. The characteristic length of the antenna can be reported as only 0.018λ. The design and simulations of the fundamental parameters of the antenna are presented, showing a uniform radiation pattern. Also, the manufacturing process is described. Seven prototypes of the antenna have been manufactured and their reflection coefficient was measured. The tests showed good agreement with simulations. The repeatability of the measurements and the reliability of the fabrication process are demonstrated.

This work presents the results of the characterization of two 1 × 5 mm² miniaturized rectennas developed for medical applications. They have been designed for relatively high voltage and high-power applications, given the size of the rectennas. Both rectennas were tested in open-air conditions and surrounded by pork fat and muscle tissues, whose properties are similar to those of the human body. The resonant frequencies of the rectennas were found, and the incident electric field on the rectennas tests was increased. The first chip showed a maximum output voltage of 5.29 V and a maximum output power of 0.056 mW, at 1.446 GHz, under an incident field on the rectenna of 340 V/m, and the second chip, 4.62 V and 4.27 mW, at 1.175 GHz, under 535 V/m. The second rectenna can provide an output power greater than 5 mW. The rectennas presented in this article are beyond the state of the art, as they can deliver about three times more power and voltage than those of similar dimensions reported in the literature. Based on the test results, the efficiency of the rectennas was analyzed at different locations of the human body, considering different thicknesses of tissues with high and low water content. Finally, potential applications are described in which the rectennas could power implantable medical devices or microsurgery tools, for example, pulmonary artery pressure monitors.

This study presents the measurements of exposure to electromagnetic fields, carried out comparatively following standard methods from fixed sites using a broadband meter and using a smartphone on which an App designed for this purpose has been installed. The results of two measurement campaigns carried out on the campus of the University of Alcalá over an area of 1.9 km² are presented. To characterize the exposure, 20 fixed points were measured in the first case and 860 points along the route made with a bicycle in the last case. The results obtained indicate that there is proportionality between the two methods, making it possible to use the smartphone for comparative measurements. The presented methodology makes it possible to characterize the exposure in the area under study in four times less time than that required with the traditional methodology.

Electromagnetic Interference and Compatibility (EMI–EMC) are a serious problem in Microelectromechanical Systems (MEMS), and specially in powered by wireless energy transfer MEMS. Most MEMS have dimensions in the order of 1 mm or less, thus, most of the suitable electromagnetic radiation sources have wavelengths larger than this, making isolation of electromagnetic effects very difficult. Model‐Based Systems Engineering (MBSE) can be an excellent tool to deal with EMI—EMC in MEMS during early design phases. In this work, we present a problem‐solving procedure and integration of EMI—EMC in MEMS from a Model‐Based Systems Engineering perspective. This approach is described in detail by a real example using a procedure based on nine steps fully integrated with the proposed systems engineering methodology. For example, the use of context diagrams (IBDs) and N SQUARE charts to describe EMC interactions is explained in detail. The system is formed by a Wireless Power Transfer (WPT) subsystem working near 2.45 or 4.5 GHz coupled to an electromagnetic micromotor. This micromotor contains copper microcoils which can receive electromagnetic radiation directly at the same time that the WPT subsystem. The greatest difficulty is, then, to power the WPT while isolating the micromotor, and optimizing the coupling interface. A summary of the most important EMC concepts and tools are reviewed from the systems engineer perspective and possible problems during the design and testing phases are discussed in detail using the example.

A miniaturized helical antenna is presented in this work. The antenna is flexible, it is 6100 μm long and it has a diameter of 352 μm. This antenna has such a small cross-section, that permits to be implanted in the human body with fine syringes and minimally invasive surgeries. The antenna can be used to receive power and/or send information in medical devices. The antenna is made of biocompatible materials: polytetrafluoroethylene (PFTE) and copper. The fundamental parameters of the antenna have been simulated and experimentally measured in animal human-like tissues, showing good agreement. The resonant frequency of the antenna is 4.7 GHz, with a reflection coefficient of -25.1 dB, and a gain of -4.7 dBi. As expected, the resonant frequency decreases inside biological tissues comparing to the free-space open-air measurement. Reducing the resonant frequency is an advantage because power signals can penetrate deeper into body tissues.

Acoustic analysis of materials is a common non-destructive technique, but most efforts are focused on the ultrasonic range. In the audible range, such studies are generally devoted to audio engineering applications. Ultrasonic sound has evident advantages, but also severe limitations, like penetration depth and the use of coupling gels. We propose a biomimetic approach in the audible range to overcome some of these limitations. A total of 364 samples of water and fructose solutions with 28 concentrations between 0 g/L and 9 g/L have been analyzed inside an anechoic chamber using audible sound configurations. The spectral information from the scattered sound is used to identify and discriminate the concentration with the help of an improved grouping genetic algorithm that extracts a set of frequencies as a classifier. The fitness function of the optimization algorithm implements an extreme learning machine. The classifier obtained with this new technique is composed only by nine frequencies in the (3–15) kHz range. The results have been obtained over 20,000 independent random iterations, achieving an average classification accuracy of 98.65% for concentrations with a difference of ±0.01 g/L.

Decision-making is an important part of human life and particularly in any engineering process related to a complex product. New sensors and actuators based on MEMS technologies are increasingly complex and quickly evolving into products. New biomedical implanted devices may benefit from system engineering approaches, previously reserved to very large projects, and it is expected that this need will increase in the future. Here, we propose the application of Model Based Systems Engineering (MBSE) to systematize and optimize the trade-off analysis process. The criteria, their utility functions and the weighting factors are applied in a systematic way for the selection of the best alternative. Combining trade-off with MBSE allow us to identify the more suitable technology to be implemented to transfer energy to an implanted biomedical micro device.

In recent years, the study and design of wearable antennas have been empowered given the success of Wireless Body Area Networks (WBAN) for healthcare and medical purposes. This work analyses a flexible textile antenna whose performance can be optimised by the careful selection of the substrate thickness of the textile material, and by varying the antenna’s geometrical shape. After considering these parameters, several arrangements of antennas were simulated using the Computer Simulation Technology software (CST). The results of the simulations were compared to the experimental prototypes manufactured on a flexible felt material for a range of thicknesses and curvatures of the antenna substrate. Such antenna designs can be utilised in off-body communications and ISM applications.