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Feature Papers in Physical Sensors 2024
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Feature Papers in Physical Sensors 2024

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 1074

Special Issue Editors

Dr. Guillermo Villanueva

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Guest Editor
Mechanical Engineering Institute, École Polytechnique Fédérale de Lausanne (EPFL), Route Cantonale, 1015 Lausanne, Switzerland
Interests: MEMS; NEMS; piezoelectric transduction; resonators; nonlinearity; 2D materials
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Sabina Merlo

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Guest Editor
Dipartimento di Ingegneria Industriale e dell'Informazione, Università degli Studi di Pavia, 27100 Pavia, Italy
Interests: MEMS; MOEMS; optical sensors; interferometry; microphotonics; biophotonics; biosensors; lab on a chip
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Nunzio Cennamo

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Guest Editor
Department of Engineering, University of Campania Luigi Vanvitelli, Via Roma 29, 81031 Aversa, Italy
Interests: optical sensors; biosensors and chemical sensors; optical fiber sensors and optoelectronic devices
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Prof. Dr. Aldo Minardo

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Department of Engineering, University of Campania Luigi Vanvitelli, Via Roma, 29, 81031 Aversa, Italy
Interests: distributed optical fiber sensors; structural health monitoring; polymer optical fiber sensors
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Dr. Cosimo Trono

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“Nello Carrara” Institute of Applied Physics, IFAC-CNR, Via Madonna del Piano 10, 50019 Firenze, Italy
Interests: optics; optical sensors; fibre optic sensors; point of care testing (POCT)
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Dr. Faisal Mohd-Yasin

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School of Engineering and Built Environment, Griffith University, Nathan, QLD 4111, Australia
Interests: integrated circuit; VLSI; MEMS; piezoelectric films
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Prof. Dr. Andreas Savakis

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Guest Editor
Rochester Institute of Technology, Rochester, NY 14623, USA
Interests: image processing; pattern recognition; computer vision; machine learning; digital image processing; feature extraction; classification object recognition; pattern classification; feature selection
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce that the Physical Sensors section is currently compiling a collection of papers submitted exclusively by Editorial Board Members (EBMs) of our section, who are outstanding scholars in this research field.

The purpose of this Special Issue is to publish a set of papers that typify the most insightful, influential, and original articles or reviews, in which our section’s EBMs discuss key topics in the field. We expect these papers to be widely read and highly influential within the field. All papers in this Special Issue will be collected in a printed book after the deadline and will be widely promoted.

We would also like to take this opportunity to invite the most accomplished scholars to join the Physical Sensors section so that we can achieve further milestones together.

Dr. Guillermo Villanueva
Prof. Dr. Sabina Merlo
Prof. Dr. Nunzio Cennamo
Prof. Dr. Aldo Minardo
Dr. Cosimo Trono
Dr. Faisal Mohd-Yasin
Prof. Dr. Andreas Savakis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • electrical and thermal-based sensors
  • mass-sensitive and fiber-optic sensors
  • gas sensors
  • physical sensor applications for food industry and environmental monitoring
  • physical sensor arrays
  • modeling, design and software for physical sensors
  • sensor technology and new physical sensor principles

Related Special Issue

Published Papers (2 papers)

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Research

14 pages, 4569 KiB  
Article
Magnetoelectric Sensor Operating in d15 Thickness-Shear Mode for High-Frequency Current Detection
by Fuchao Li, Jingen Wu, Sujie Liu, Jieqiang Gao, Bomin Lin, Jintao Mo, Jiacheng Qiao, Yiwei Xu, Yongjun Du, Xin He, Yifei Zhou, Lan Zeng, Zhongqiang Hu and Ming Liu
Sensors 2024, 24(8), 2396; https://0-doi-org.brum.beds.ac.uk/10.3390/s24082396 - 09 Apr 2024
Viewed by 385
Abstract
For the application of high-frequency current detection in power systems, such as very fast transient current, lightning current, partial discharge pulse current, etc., current sensors with a quick response are indispensable. Here, we propose a high-frequency magnetoelectric current sensor, which consists of a [...] Read more.
For the application of high-frequency current detection in power systems, such as very fast transient current, lightning current, partial discharge pulse current, etc., current sensors with a quick response are indispensable. Here, we propose a high-frequency magnetoelectric current sensor, which consists of a PZT piezoelectric ceramic and Metglas amorphous alloy. The proposed sensor is designed to work under d15 thickness-shear mode, with the resonant frequency around 1.029 MHz. Furthermore, the proposed sensor is fabricated as a high-frequency magnetoelectric current sensor. A comparative experiment is carried out between the tunnel magnetoresistance sensor and the magnetoelectric sensor, in the aspect of high-frequency current detection up to 3 MHz. Our experimental results demonstrate that the d15 thickness-shear mode magnetoelectric sensor has great potential for high-frequency current detection in smart grids. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors 2024)
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18 pages, 1457 KiB  
Article
Development of a Robust Sensor Calibration for a Commercially Available Rising Platemeter to Estimate Herbage Mass on Temperate Seminatural Pastures
by Jessica Werner, Khaterine Salazar-Cubillas, Sari Perdana-Decker, Kilian Obermeyer, Elizabeth Velasco, Leonie Hart and Uta Dickhoefer
Sensors 2024, 24(7), 2326; https://0-doi-org.brum.beds.ac.uk/10.3390/s24072326 - 05 Apr 2024
Viewed by 511
Abstract
Rising platemeters are commonly used in Ireland and New Zealand for managing intensive pastures. To assess the applicability of a commercial rising platemeter operating with a microsonic sensor to estimate herbage mass with its own equation, the objectives were (i) to validate the [...] Read more.
Rising platemeters are commonly used in Ireland and New Zealand for managing intensive pastures. To assess the applicability of a commercial rising platemeter operating with a microsonic sensor to estimate herbage mass with its own equation, the objectives were (i) to validate the original equation; (ii) to identify possible factors hampering its accuracy and precision; and (iii) to develop a new equation for heterogeneous swards. A comprehensive dataset (n = 1511) was compiled on the pastures of dairy farms. Compressed sward heights were measured by the rising platemeter. Herbage mass was harvested to determine reference herbage availability. The adequacy of estimating herbage mass was assessed using root mean squared error (RMSE) and mean bias. As the adequacy of the original equation was low, a new equation was developed using multiple regression models. The mean bias and the RMSE for the new equation were overall low with 201 kg dry matter/ha and 34.6%, but it tended to overestimate herbage availability at herbage mass < 500 kg dry matter/ha and underestimate it at >2500 kg dry matter/ha. Still, the newly developed equation for the microsonic sensor-based rising platemeter allows for accurate and precise estimation of available herbage mass on pastures. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors 2024)
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