Planar Microwave Sensors E-Book

Ferran Martin

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Serie: Wiley - IEEE
• Sprache: Englisch

Seitenzahl: 1073

Veröffentlichungsjahr: 2022

Beschreibung

Comprehensive resource detailing the latest advances in microwave and wireless sensors implemented in planar technology Planar Microwave Sensors is an authoritative resource on the subject, discussing the main relevant sensing strategies, working principles, and applications on the basis of the authors' own experience and background, while also highlighting the most relevant contributions to the topic reported by international research groups. The authors provide an overview of planar microwave sensors grouped by chapters according to their working principle. In each chapter, the working principle is explained in detail and the specific sensor design strategies are discussed, including validation examples at both simulation and experimental level. The most suited applications in each case are also reported. The necessary theory and analysis for sensor design are further provided, with special emphasis on performance improvement (i.e., sensitivity and resolution optimization, dynamic range, etc.). Lastly, the work covers a number of applications, from material characterization to biosensing, including motion control sensors, microfluidic sensors, industrial sensors, and more. Sample topics covered in the work include: * Non-resonant and resonant sensors, reflective-mode and transmission-mode sensors, single-ended and differential sensors, and contact and contactless sensors * Design guidelines for sensor performance optimization and analytical methods to retrieve the variables of interest from the measured sensor responses * Radiofrequency identification (RFID) sensor types, prospective applications, and materials/technologies towards "green sensors" implementation * Comparisons between different technologies for sensing and the advantages and limitations of microwave sensors, particularly planar sensors Engineers and qualified professionals involved in sensor technologies, along with undergraduate and graduate students in related programs of study, can harness the valuable information inside Planar Microwave Sensors to gain complete foundational knowledge on the subject and stay up to date on the latest research and developments in the field.

Leseprobe

Planar Microwave Sensors

Ferran MartínParis VélezJonathan Muñoz‐EnanoLijuan Su

Universitat Autònoma de Barcelona

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Library of Congress Cataloging-in-Publication DataNames: Martín, Ferran, 1965- author. | Vélez, Paris, author. | Muñoz‐Enano, Jonathan, author. | Su, Lijuan, author.Title: Planar microwave sensors / Ferran Martín, Paris Vélez, Jonathan Muñoz-Enano, Lijuan Su.Description: Hoboken, New Jersey : Wiley-IEEE Press, [2023]Identifiers: LCCN 2022017876 (print) | LCCN 2022017877 (ebook) | ISBN 9781119811039 (cloth) | ISBN 9781119811046 (adobe pdf) | ISBN 9781119811053 (epub)Subjects: LCSH: Microwave detectors.Classification: LCC TK7876 .M22 2022 (print) | LCC TK7876 (ebook) | DDC 621.381/3–dc23/eng/20220622LC record available at https://lccn.loc.gov/2022017876LC ebook record available at https://lccn.loc.gov/2022017877

Cover Design: WileyCover Image: Courtesy of Ferran Marté­n, Paris Vélez, Jonathan Muñoz-Enano, Lijuan Su

To Anna, Alba, and ArnauTo Pedro, Ana, Julia, Miguel, Arantxa, and IraiTo Claudio, Loli, Adrian, Antonia, and RaquelTo Gerard and OscarAnd to the memory of Prof. Tatsuo Itoh, a Mentor and a Guide, awarded the Honoris Causa Doctorate by the Universitat Autònoma de Barcelona in 2015, among many other distinctions and honors.

Preface

Perseverance, humility and courage are necessary qualities in a good scientist, more than wisdom, curiosity, and intelligence. Generosity is probably the highest virtue of a great person.

Someone, somewhere, sometime

In today's society, there is an increasing need to sense multitude of variables of different types. Data collection from the environment, or, in general, from a certain system, is a fundamental requirement in order to gain insight on the state of such system, and thus take appropriate decisions and actions, either through human intervention or autonomously, when necessary. The subject of analysis of the system can be as diverse as large‐scale (macro) systems, medium‐sized systems, or microsystems. Examples include the space, the atmosphere, a forest, a city, a crop field, a civil infrastructure, a factory, industrial machinery, the home, a specific indoor/outdoor area, daily objects, persons, animals, food, a biological sample, etc. In certain cases, retrieving information of the system is the main, and sometimes unique, objective, without any further active action that modifies the system, or represents any kind of control over it. For example, weather forecasting is based on the measurement of ambient variables such as temperature, atmospheric pressure, relative humidity, wind velocity, etc., and the information provided by weather forecasters (inferred from such environmental data using complex meteorological models) is very useful for citizens and administrations for obvious reasons (in particular, when extreme meteorological conditions are predicted). However, obtaining these environmental variables has an informative intention (i.e. the weather forecast), exclusively. There are other macro systems, for instance, a region in the Earth susceptible to seismic action, where the sensed data (seismic variables, in this particular case) are not used to generate preventive actions (earthquakes cannot be avoided) but to make useful predictions (that avoid major catastrophes or, at least, protect the population).

However, in most systems, sensing is necessary as a first step to generate actions that modify, or perturb, it according to certain requirements. For example, any motion control system, present in many industrial scenarios (e.g. elevators, conveyor belts, and servomotors), is equipped with sensors that measure motion variables, such as position, velocity, etc., and such variables are used by system actuators to generate correcting actions, if needed. Another clear example is the autonomous and intelligent vehicle, where a set of sensors of different types continuously collects data, which are used not only to assist the driver (if it is present) but also to autonomously take decisions (the so‐called unmanned vehicle is another paradigmatic example). In healthcare, smart systems able to monitor vital constants, to measure variables of medical interest, e.g. glucose content in blood, or to detect unexpected body movements (e.g. in disabled or elderly people), indicative of potential dangerous events (such as lipothymia or ictus), are of the highest interest. Naturally, such systems need sensors to collect these data, but the main relevant and distinctive feature of smart healthcare systems is their ability (not always present) to generate specific actions from the retrieved data. For example, in the event of a sudden increase of glucose in blood above a certain threshold, detected by a dedicated real‐time glucose‐monitoring sensor, an alert indicative of hyperglycemia should be activated, in order to prevent the patient from dramatic irreversible effects. Alternatively, in hospital environment, a smart system should be able to automatically inoculate insulin to the patient, in a controlled way, in order to compensate for the excess of sugar in blood.

The three examples reported in the previous paragraph (motion control, the autonomous vehicle, and smart systems for healthcare) are representative of three sectors where system intelligence is penetrating significantly and are thereby experiencing a considerable (digital) transformation, namely, the Smart Industry (intimately related to the fourth industrial revolution, also called Industry 4.0), the Intelligent Car, and the Smart Healthcare. Nevertheless, there are many other sectors, which are nowadays in the process of transformation toward the digital world (or Smart World), including agriculture, packaging, food industry, city management and sustainability, and civil engineering (e.g. structural health monitoring), to cite some of them. Thus, terms such as Smart Agriculture, Smart Packaging, Smart Cities, or Ambient Intelligence, among others, are becoming progressively more familiar within our society.

To make the Smart World concept a reality, or, at least, to achieve further levels of intelligence within the above‐cited fields, efforts at different levels are needed. At system level, enabling technologies for the so‐called Internet of Things (IoT), e.g. radiofrequency identification (RFID), near‐field communications (NFC), wireless sensor networks (WSN), energy harvesting, cloud computing, big data analysis, communication protocols, and embedded systems, is the subject of an intensive research activity, and the progress in such technologies is fundamental to envisage a future interconnected and intelligent world. Nevertheless, one key factor for the deployment of IoT and related applications is the recent implantation of the fifth generation of mobile networks (5G), with higher capacity, connectivity, and broader bandwidths (among other advantages) as compared to 4G. At device level, the key components in smart sensing systems are sensors. The research activity in the sensors domain has experienced a very significant growth in recent years. There are many types of sensors, exploiting different technologies, e.g. optical sensors, acoustic sensors, and magnetic sensors, but the sensors that are expected to play a key role in future smart systems are microwave sensors, and particularly planar sensors, the subject of this book. Their low cost, small size, and low profile, as well as the possibility of sensor implementation in flexible and organic substrates (by either subtractive or additive processes) are important attributes of planar microwave sensors. Other important aspects of microwave technologies are low‐cost generation and detection systems, microwave interaction with the materials at different scales (i.e. through the near field or the far field), wave propagation (and penetration) in many different types of materials, and system functionality in hostile and harsh environments, e.g. with pollution and dirtiness (encountered in many industrial scenarios), or under adverse meteorological conditions. Planar microwave sensors can be implemented in combination with other technologies, such as microfluidics, micromachining, lab‐on‐a‐chip, textiles, etc., and, inherently, exhibit a potentially wireless connectivity. Moreover, the sensor substrate can integrate the associated sensor electronics, needed for signal generation, post‐processing, and (eventually) communication purposes, representing a reduction in system complexity and cost. Versatility is another relevant characteristic of planar microwave sensors. Despite the fact that such devices are (canonically) permittivity sensors, able to detect changes in the dielectric properties of the immediate environment, it is possible to use these sensors to determine material composition or to detect defects or anomalies in samples or targets, in both cases related to permittivity changes. Nevertheless, it is also possible to use planar microwave sensors to measure many other parameters, including physical and chemical variables (e.g. temperature, humidity, motion, concentration of certain substances in samples, and gas detection) or to perform biological analysis (e.g. bacterial growth and presence of certain analytes in biosamples). In some cases, smart materials (i.e. functional materials with dielectric properties highly sensitive to the measurand), reagents (i.e. chemical agents able to activate a chemical reaction), or bioreceptors (i.e. biological elements that bind to a specific analyte) are needed in order to boost up sensor sensitivity, a key performance parameter. Finally, let us mention that by using biodegradable substrates and organic inks, planar microwave sensors are potential candidates for the implementation of “green” sensing systems (for instance, RFID sensors with battery‐free and chipless sensing tags). Nevertheless, there are many challenging aspects, mainly related to performance degradation inherent to the use of eco‐friendly materials, that should be addressed to make “green sensing” a reality.

The previous advantageous characteristics of planar microwave sensors explain the huge efforts dedicated to their research and optimization in recent years and justify the publication of the present book. Though a planar microwave sensor in a real scenario is composed of three main blocks (the electromagnetic module, including the sensitive element, the electronics module, responsible for signal generation and post‐processing, and the communication module), and, eventually, of a mechanical part, this book is essentially focused on the electromagnetic, or microwave, block. Nevertheless, in some of the reported sensor implementations (proof‐of‐concept demonstrators), part of the electronics is also included (especially, when this is necessary to retrieve and visualize the sensing data). The book tries to emphasize the underlying physics behind the considered sensing mechanisms and provides useful guidelines for sensor design, inferred from detailed analysis of the structures under study, mainly devoted to sensitivity optimization. Most of the reported sensors in the book are focused on permittivity measurements, material characterization, and motion sensing, and mainly correspond to recent contributions by the authors. Nevertheless, there are many other prototypes (especially in the subtopic of RFID sensors) proposed by other researchers working in the field. Let us also mention that by using functional materials, many of the ideas presented in this book can be extrapolated to the implementation of sensors devoted to the measurement of a wide variety of physical, chemical, and biological/medical variables.

The book contains as many chapters as considered sensing working principles, plus an additional introductory chapter (Chapter 1) and a concluding chapter (Chapter 8). Thus, Chapter 1 is an introduction to the topic of the book, planar microwave sensors. However, a general overview of other microwave (mainly nonplanar and remote) sensors, extended also to other sensing technologies (such as optics, acoustics, magnetic, mechanical, and electric), is carried out in the chapter. The chapter proposes a general and useful categorization scheme of microwave sensors, where it is shown that planar sensors belong to the category of non‐remote sensors, in contrast to the remote counterparts, mainly RADAR sensors and radiometers. Special attention is dedicated to the classification of planar microwave sensors, the subject of interest in the book. Probably the most useful categorization criterion for such sensors is the one that obeys to their working principle (the classification adopted in this book). Chapter 1 ends with a comparison of planar microwave sensors with other sensors based on microwaves and other technologies.

Chapter 2 is devoted to frequency‐variation sensors, probably those planar microwave sensors that constitute the main subject of research in the field to date. These sensors are based on resonant structures, with resonance frequency (and magnitude) sensitive to the dielectric properties of the surrounding environment. The chapter presents a set of (planar) semi‐lumped resonators useful for sensing and includes a sensitivity analysis, based on the circuit models describing the sensor, that links the sensitivity to the characteristics of the sensor material and circuit parameters. It is shown that these sensors are useful for the dielectric characterization of solid and liquid samples. Moreover, it is demonstrated that, by considering sensor arrays and multifrequency sensing, it is possible to resolve the dielectric properties of the sample, with potential application to the detection of anomalies in organic tissues (e.g. malignant or cancerous cells). The chapter also presents a multifrequency method for the selective determination of components in complex mixtures (e.g. liquid solutions), which is based on the dispersive behavior of the permittivity of the different constitutive elements of the composite.

The working principle discussed and studied in Chapter 3 is phase variation. Such sensors are single‐frequency devices that can be implemented by means of transmission‐mode or reflective‐mode structures. Moreover, phase‐variation sensors can operate either differentially or as single‐ended devices. The phase of the transmission or the reflection coefficient is the canonical output variable, sensitive to the dielectric properties of the medium in contact (or in proximity) with the sensitive element, typically a transmission line section, or a planar resonator. It is shown that, by exploiting the highly dispersive behavior of artificial lines, high sensitivities in phase‐variation sensors based on such artificial lines can be achieved. Several examples representative of the specific approaches are included in the chapter. Nevertheless, probably the most notable contribution of Chapter 3 concerns the introduction of a sensor strategy useful to optimize the sensitivity without the need to increase the area of the sensing region (the usual procedure in phase‐variation sensors). The technique applies to reflective‐mode structures, and it is based on cascading a step‐impedance line (with quarter‐wavelength sections) to the sensing element, typically an open‐ended half‐ or quarter‐wavelength line section, or a planar resonator tuned to the operating frequency. An exhaustive analysis, useful to predict the sensitivity in these highly sensitive reflective‐mode sensors, is carried out in Chapter 3. Although most phase‐variation sensors are devoted to permittivity measurements or dielectric characterization of solids and liquids, examples of motion sensors based on phase variation are also included in Chapter 3.

Chapter 4 is dedicated to coupling‐modulation sensors, i.e. planar microwave sensors where the (variable) electromagnetic coupling between a transmission line (or a transmission line‐based structure) and a planar resonant element (or a set of resonators) is the physical sensing mechanism. Since such electromagnetic coupling depends on the relative position and orientation between the line and resonant element/s, it follows that the canonical application of coupling‐modulation sensors is the measurement of displacements and velocities (both linear and angular). The output variable in such sensors is usually the magnitude of the transmission, or reflection, coefficient at the operating frequency (such sensors are typically single‐frequency devices). Sensors based on electromagnetic symmetry properties, particularly symmetry truncation, and sensors based on line‐to‐resonator proximity are presented in the chapter. Special attention is focused on the so‐called electromagnetic encoders (linear and rotary), since such sensors may have application in industrial scenarios where motion control is required and where their optical counterparts (optical encoders) may experience difficulties related to the presence of pollution, grease, contaminants, etc. Nevertheless, the chapter reports also an example of a coupling‐modulation sensor devoted to material characterization.

In Chapter 5, frequency splitting, generated in a transmission line (or transmission line‐based structure) symmetrically loaded with a pair of identical resonators when such resonators are asymmetrically loaded, or perturbed, is the considered working principle. These sensors are not true differential sensors, but they exhibit similar characteristics, in particular, they are robust against potential cross‐sensitivities caused by ambient factors (e.g. temperature and humidity). The chapter highlights that inter‐resonator coupling tends to degrade the sensitivity, especially in the limit of small perturbations. Thus, several methods reported to circumvent this limitative aspect are presented, discussed, and experimentally validated in Chapter 5.

Although differential sensing is not exactly a working principle, but rather a strategy to eliminate the undesired effects of potential common‐mode stimuli, a dedicated chapter (Chapter 6) is focused on differential‐mode sensors. Nevertheless, some examples of differential sensors are included in previous chapters (e.g. in Chapter 3, where differential phase‐variation sensors are reported, since the physical sensing mechanism in such sensors is phase variation). True differential sensors should consist at least of two independent and noninteracting (uncoupled) sensor units (sensor pair). Each unit can operate independently as a single‐ended sensor, but in differential sensors, the input and output variables are the incremental variables of their single‐ended constitutive counterparts. In most sensors in Chapter 6, the output variable is the cross‐mode transmission, or reflection, coefficient, which is, intrinsically, a differential variable, whereas the input variable is usually the differential permittivity between the sample under test and a reference sample. The chapter shows that such sensors can be used as highly sensitive comparators, as well. The reported examples include differential‐mode sensors for solid and liquid characterization. It is remarkable that the high sensitivity and resolution of some of the sensors included in the chapter and able to discriminate, e.g. concentrations of electrolytes in aqueous solutions as small as 0.25 g/L. The chapter demonstrates also the possibility to determine the total electrolyte concentration in animal (horse) urine, of potential interest as a real‐time monitoring and prescreening method, useful to detect certain pathologies related to an excess, or defect, of electrolytes.

Chapter 7 is devoted to the topic of RFID sensors, justified by the increasing demand of distributed sensors wirelessly connected to the central unit (the reader in the framework of RFID) within the context of the IoT and the Smart World. The key elements in RFID sensing systems are the sensor tags, equipped with sensing functionality and, usually, with identification capability. The chapter reports a classification scheme of RFID sensors where the main distinction is between chipped‐ and chipless‐RFID sensors. The former are not true planar sensors, as far as they include an integrated circuit where the identification code is stored. Nevertheless, in the so‐called electromagnetic chipped‐RFID sensors, sensing is performed by means of the planar antenna of the tag, eventually altered to increase the sensitivity, rather than by means of a dedicated electronic sensor module (as the so‐called electronic chipped‐RFID sensors use). By contrast, chipless‐RFID sensor tags are fully planar, and, consequently, such sensors have been the subject of a further consideration in Chapter 7, despite the fact that their performance cannot compete against the one of chip‐based tags. The chapter succinctly reviews several functional (or smart) materials typically used in chipless‐RFID sensors (as coating films) in order to sensitively measure several physical or chemical variables (e.g. temperature, or humidity, to cite some variables sensed in several of the reported prototypes). The chapter includes a list of potential applications of RFID sensors in fields as diverse as Smart Agriculture, Smart Packaging, Smart Healthcare, Structural Health Monitoring, Smart Cities, Smart Cars, Space, etc. It ends by presenting some commercial RFID sensors, by pointing out the main limitative aspects of RFID sensors (primarily concerning chipless‐RFID tags) and by pointing out some challenging issues for future investigation. The main efforts should be focused on the topic of chipless‐RFID sensing tags, since their limited performance is one of the bottlenecks toward the full deployment of the IoT.

Finally, Chapter 8 summarizes the different sensing approaches considered in the previous chapters in the form of a comparative analysis and points out the main concluding remarks.

It is the authors' hope that the present book constitutes a reference manuscript in the topic of planar microwave sensors. The authors have done their best to generate a useful product of practical interest for the academy and the industry, specially for engineers, students, and researchers involved in sensing technologies, in RF/microwave engineering, in IoT systems, and, in general, in any transversal field where planar microwave sensors are expected to play a fundamental role in next future.

Ferran Martín

Paris Vélez

Jonathan Muñoz‐Enano

Lijuan Su

Bellaterra (Cerdanyola del Vallès), Barcelona

February 2022

Acknowledgments

This book is mainly the result of the research activity by the authors in the field of planar microwave sensors carried out in recent years. However, it also includes many ideas, sensing devices, and their practical applications (extracted from the available literature) that belong to others. Thus, the book has been written under the perspective, viewpoint, and experience of the authors, but the objective has been to provide a wide overview on the topic and an up‐to‐date state‐of‐the‐art. It is impossible to enumerate all the people whose ideas have contributed to make this book a reality, but all the authors of the cited literature in the different chapters should be felt part of the list to which the authors are in debt. Nevertheless, special thanks are given to some researchers with whom the authors have had a close and fruitful collaboration in the field of planar microwave sensors in recent years, including Dr. Katia Grenier (CNRS‐LAAS, Toulouse, France), Prof. David Dubuc (University of Toulouse and CNRS‐LAAS, Toulouse, France), Dr. Amir Ebrahimi (RMIT University, Melbourne, Australia), Dr. Ali Karami‐Horestani (Gdansk University of Technology, Poland), Dr. Marta Gil‐Barba (Universidad Politécnica de Madrid, Spain), Dr. Ignacio Gil (Universitat Politècnica de Catalunya, Spain), and Dr. Rosa Villa (IMB‐CNM‐CSIC, Spain). Dr. Paris Vélez and Jonathan Muñoz‐Enano explicitly express their gratitude to Dr. Katia Grenier and Prof. David Dubuc for accepting them to be part of their Group at CNRS‐LAAS during their respective research stays (both in the field of microfluidic sensors). Dr. Paris Vélez acknowledges also Dr. Rosa Villa and Dr. Ignacio Gil for accepting him in their respective Groups during two consecutive research stays, one devoted to microfluidic sensors and the other one to textile‐based sensors. Prof. Ferran Martín would also like to mention the numerous and productive discussions on electromagnetism topics related to planar microwave sensors (in part included in the book) with Prof. Francisco Medina and his Team at the Universidad de Sevilla, Spain.

The authors are also very grateful to the members of their Group and Research Transfer Centre (CIMITEC), ascribed to the Departament d’Enginyeria Electrònica at the Universitat Autònoma de Barcelona, Spain. Among them, special thanks are given to Dr. Ferran Paredes and Dr. Cristian Herrojo, since some of the results related to electromagnetic encoders included in the book have been mostly generated by them (and also by Dr. Jordi Naqui and Dr. Javier Mata‐Contreras, past members of CIMITEC). Jan Coromina and Pau Casacuberta are also included in the acknowledgment list, since part of their PhD research is devoted to planar microwave sensors, and hence related to the topics of the book. The authors are also in debt to Dr. Gerard Sisó and Javier Hellín, who have fabricated many of the reported prototypes, to Anna Cedenilla, for handling the permissions of reproduced figures, and to Marta Mora, head of the Administrative Staff of the Department.

Several funding institutions, research agencies, and companies have supported the research activity carried out by the authors and reported in the book. Among them, special thanks are given to the Ministry of Science and Innovation and National Research Agency (MCIN/AEI 10.13039/501100011033), Spain, and ERDF European Union, for the financial support through the projects TEC‐2016‐75650‐R, RTC‐2017‐6303‐7, PID2019‐103904RB‐I00, and PDC2021‐121085‐I00 (European Union Next Generation EU/PRTR), to the AGAUR Research Agency, Catalonia Government, for their support through the projects 2014SGR‐157, 2017SGR‐1159, and 2014LLAV00046, and to the European Space Agency (ESA) for the contract 4000111799/14/NL/SC. The authors have had several collaborations, or are in close contact, with companies in the field of sensors and related topics, including EMXYS, Hohner Automáticos, García Carrión, and ZIP BCN Solutions, among others. Let us also mention the support received by the authors for their professional development and progress. This support includes ICREA (Institució Catalana de Recerca i Estudis Avançats), a Catalan Institution that has awarded Prof. Ferran Martín (calls 2008, 2013, and 2018), the TECNIOSPRING Program (ACCIÓ, Catalonia Government, and Horizon 2020 Marie Sklodowska‐Curie Funds), that has awarded Dr. Paris Vélez through the project TECSPR15‐1‐0050, and the Juan de la Cierva Program (Ministry of Science and Innovation, Spain), for the grants IJCI‐2017‐31339 and IJC‐2019‐040786‐I given to Dr. Paris Vélez and Dr. Lijuan Su, respectively. Let us also include in the list the FI‐Grant (Secretaria d’Universitats i Recerca, Government of Catalonia, and European Social Fund) awarded to Jonathan Muñoz‐Enano for the realization of the PhD.

Finally, the authors would like to express their most sincere gratitude to their respective families for creating the necessary atmosphere to write a complex manuscript like this, for being so patient during many times the authors have had an almost exclusive dedication to the preparation of the book, and for their continuous and unconditional support. This book also belongs to them. Thank you very much!

Ferran Martín

Paris Vélez

Jonathan Muñoz‐Enano

Lijuan Su

About the Authors

Ferran Martín received BS degree in Physics from the Universitat Autònoma de Barcelona (UAB), Spain, in 1988 and PhD degree in 1992. He is a full professor of Electronics in the Electronics Engineering Department, UAB, since 2007. He is the head of the Microwave Engineering, Metamaterials and Antennas (GEMMA) Group, director of CIMITEC (a Research and Technology Transfer Centre, ascribed to UAB), and past head of the Electronics Engineering Department (period 2015–2021). His research interests include microwave circuits and sensors, metamaterials, and radiofrequency identification (RFID). Ferran Martín has organized several international events related to metamaterials and related topics, including Workshops at the IEEE International Microwave Symposium (years 2005 and 2007) and European Microwave Conference (2009, 2015, 2017, and 2018), and the Fifth International Congress on Advanced Electromagnetic Materials in Microwaves and Optics (Metamaterials 2011), where he acted as Chair of the Local Organizing Committee. He has acted as a guest editor for several special issues on metamaterials and sensors in different international journals, and he is the associated editor of IET Microwaves Antennas and Propagation and Sensors.

Ferran Martín has authored and co‐authored over 650 technical conferences, letters, journal papers, and book chapters. Professor Martín is the co‐author of the book on metamaterials entitled Metamaterials with Negative Parameters: Theory, Design and Microwave Applications (John Wiley & Sons Inc.), author of the book Artificial Transmission Lines for RF and Microwave Applications (John Wiley & Sons Inc.), co‐editor of the book Balanced Microwave Filters (Wiley/IEEE Press), co‐author of the book Time‐Domain Signature Barcodes for Chipless‐RFID and Sensing Applications (Springer), and co‐author of the book Planar Microwave Sensors (Wiley/IEEE Press). Ferran Martín has generated 22 PhDs; he has filed several patents on metamaterials and other topics related to microwave engineering; and he has headed dozens of research projects and development contracts with companies. Among his distinctions, Ferran Martín has received the 2006 Duran Farell Prize for Technological Research; he holds the Parc de Recerca UAB – Santander Technology Transfer Chair; and he has been the recipient of three ICREA ACADEMIA Awards (calls 2008, 2013, and 2018). He is Fellow of the IEEE (since 2012) and Fellow of the IET (since 2016).

Paris Vélez