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IEEE Sensors Letters

IEEE Sensors Letters is an electronic journal dedicated to publishing short manuscripts, quickly, on the latest and most significant developments in the field of sensors.

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Deadline: October 24, 2025

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0.422
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0.00343
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Latest Articles

Distribution of the Clamped Boundary and Its Impact on Resonator Performance

Haleh Nazemi; Yumna Birjis; Pavithra Munirathinam; Mohd Farhan Arshi; Arezoo Emadi

Capacitive resonator performance, including sensitivity, is determined by its capacitive change and resonant frequency shift in response to an external perturbation, such as added mass. Conventional designs are inherently defined by fully clamped boundaries around the deflectable plate. However, recent advances suggest that bilateral and quadrilateral concentric boundary resonators can offer improved performance through enhanced deflection compared to conventional fully clamped resonators. This letter analyzes how the spatial distribution of clamped boundaries under identical total clamped angles affects key resonator metrics, including sensitivity, which is manifested through a change in capacitance and frequency shift in electrical characterization. Resonators with bilateral and quadrilateral clamped boundary configurations are the focus of this letter to demonstrate the idea. In order to do this, resonators with total clamped angles of 120°, 180°, and 240° are fabricated and characterized using electrical impedance analysis, with results in agreement with the conducted finite element analysis. The quadrilateral configurations outperformed bilateral ones in both frequency shift and capacitance change, indicating that the clamped boundary distribution serves as a critical design parameter. These findings offer new insight into structural optimization strategies for capacitive resonators beyond conventional clamping schemes.

Tunable BTEX Gas Detection At Room Temperature via Composition Engineered MoSe2–WSe2 Nanocomposites

Priyakshi Kalita; Abhik Chanda; Orison Waikhom; Biplob Mondal

The detection of hazardous volatile organic compounds, particularly benzene, toluene, ethylbenzene, and xylene (BTEX), is crucial due to their carcinogenic nature and contribution to environmental pollution. Conventional gas sensors often suffer from high operating temperatures, poor sensitivity and selectivity, and slow response times. To address these limitations, composition-tunable MoSe2–WSe2 heterostructures were synthesized via a facile liquid-phase exfoliation (LPE) technique for room-temperature BTEX sensing applications. A comparative investigation was conducted between two distinct compositional ratios: MoSe2:WSe2 = 3:1 (n-type dominant) and 1:3 (p-type dominant), to elucidate the role of composition on electrical and sensing behavior. The structural, morphological, and optical properties of the synthesized composites were comprehensively characterized using Raman spectroscopy, FESEM, EDX, XRD, and UV–Vis spectroscopy. The 3:1 sample exhibited dominant MoSe2 Raman features with an estimated bandgap of 1.78 eV, whereas the 1:3 sample showed dominant WSe2 features with a bandgap of 1.47 eV. Elemental analysis further validated the targeted Mo:W atomic ratios, closely matching the intended 3:1 and 1:3 compositions. Electrical measurements demonstrated a maximum sensor response of 25.74% toward benzene, with a rapid response time of 30 s at a gas concentration of 50 ppm for MoSe2–WSe2 composite (1:3). This study provides the first detailed report on composition-dependent BTEX sensing performance of MoSe2–WSe2 heterostructures synthesized via LPE. The findings highlight the critical influence of n-/p-type dominance tuning for achieving gas-specific selectivity, offering promising pathways for the development of next-generation, room-temperature, 2D-material-based gas sensors with tailored sensitivity profiles.

Popular Articles

Sustainable Printed Chitosan-Based Humidity Sensor on Flexible Biocompatible Polymer Substrate

Humidity is one of the most relevant physical parameters to sense and control for a wide range of commercial and industrial applications. Consequently, there is continuing demand for the development of innovative and sustainable humidity sensor solutions. Here, the development and characterization of fully additively manufactured, highly sensitive, resistive Chitosan-based humidity sensors on flexible thermoplastic polyurethane (TPU) foil, as well as on a glass carrier substrate are presented. The sensors unite aspects of sustainability and high performance in a broad humidity range (20–90%rH). The humidity response follows an exponential curve progression with relative changes in the resistance per %rH of 6.9% and 5.7% for the glass carrier sensor and the TPU sensor, respectively. In absolute values, this means that the Chitosan-based sensors are particularly sensitive in the low humidity range with a vast dynamic range (ten times larger compared to commonly used capacitive humidity sensors). The flexible sensor on the TPU substrate shows great stability even after repeated bending. In addition, the combination of flexible and biocompatible materials (TPU and Chitosan) with additive manufacturing technologies makes the sensor particularly sustainable while having great potential for a plethora of biomedical applications.

IoT-Enabled Sensors in Automation Systems and Their Security Challenges

Today, Internet of Things (IoT)-based sensor devices are ubiquitous. Being cost effective and easy to deploy, they are also considered for many applications outside their original domain, which was consumer electronics. Factory and process automation, smart buildings and homes, and, in general, Industry 4.0 are application fields in which the use of IoT technology is gaining popularity, often in addition to existing, classical communication architectures on the operational technology level. IoT devices, however, typically have a different philosophy for communication and data exchange, which makes them easy to use but poses security challenges by bypassing established security architectures, such as the classical defense-in-depth concept defined, for instance, in the IEC 62443 standard. This letter highlights today's security needs and concepts in industrial environments. Furthermore, it looks at possible new attack surfaces opened by IoT-based applications and shows ways how to bridge the security gap.

DeepMUSIC: Multiple Signal Classification via Deep Learning

This letter introduces a deep learning (DL) framework for the classification of multiple signals in direction finding (DF) scenario via sensor arrays. Previous works in DL context mostly consider a single or two target scenario, which is a strong limitation in practice. Hence, in this letter, we propose a DL framework called DeepMUSIC for multiple signal classification. We design multiple deep convolutional neural networks (CNNs), each of which is dedicated to a subregion of the angular spectrum. Each CNN learns the MUltiple SIgnal Classification (MUSIC) spectra of the corresponding angular subregion. Hence, it constructs a nonlinear relationship between the received sensor data and the angular spectrum. We have shown, through simulations, that the proposed DeepMUSIC framework has superior estimation accuracy and exhibits less computational complexity in comparison with both DL- and non-DL-based techniques.

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Special Issues

Editorial Board

Andrei Shkel
Editor-in-Chief
University of California, Irvine, USA
Deepak Uttamchandani
Associate Editor-in-Chief
Strathclyde University, Glasgow, UK
Francisco Falcone
Associate Editor-in-Chief
Univ. Publica de Navarra, Spain
Thilo Sauter
Associate Editor-in-Chief
TU Wien and Danube University, Krems, Austria
Giacomo Langfelder
Associate Editor-in-Chief
Politecnico de Milano, Italy
Srinivas Tadigadapa
Founding Editor-in-Chief (2017-2022)
Northeastern University, USA
David Elata
Sensor Phenomena and Modeling Topical Editor
Technion, Haifa, Israel
Michael Kraft
Sensor/Electronic Interfaces Topical Editor
University of Liège, Belgium
Doruk Senka
Associate Editor
Reality Labs, Meta, USA
Chia-Chan Chang
Associate Editor
National Chung-Cheng University, Taiwan
Karthik Shankar
Associate Editor
University of Alberta, Edmonton, Canada
Sheng-Shian Li
Associate Editor
National Tsing Hua University, Taiwan
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