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Smart Sensors and Integration Technology for MEMS Devices
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Smart Sensors and Integration Technology for MEMS Devices

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

Deadline for manuscript submissions: closed (28 February 2025) | Viewed by 9455

Special Issue Editors

Dr. Chong Lei

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Guest Editor
Key Laboratory of Thin Film and Microfabrication Technology (Ministry of Education), Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Interests: MEMS devices and integration technology; intelligent target sensing; biochip systems
Dr. Zhen Yang

E-Mail
Guest Editor
1. School of Electronic and Information Engineering/School of Integrated Circuits, Guangxi Normal University, Guilin 541004, China
2. Department of Biomedical Engineering, National University of Singapore, Singapore 119276, Singapore
Interests: MEMS technique; magnetism and magnetic nanomaterials; micro magnetic sensor and microsystem; smart sensors; biochips; bioMEMS and microfluidics

Special Issue Information

Dear Colleagues,

The MEMS industry has gained vital recognition as the electronics industry is shifting its focus from traditional sensors to MEMS technology. The explosive development of Internet of Things (IoTs) is driving the demand for MEMS devices in areas including smart grids, asset-tracking systems, and building automation. From the perspective of technology and product trends, MEMS devices are evolving to the four modernizations: intelligence, integration, low power consumption, and miniaturization. Smart sensors are evolving through intricate interactions with artificial intelligence, Bluetooth, medical, cloud computing, and other technologies. Smart sensors and MEMS include a variety of devices and systems that have a high level of functionality. They do this either by integrating multiple sensing and actuating modes into one device, or else by integrating sensing and actuating with information processing, analog-to-digital conversion, and memory functions.

Potential topics include, but are not limited to, the following:

  • Microfabrication technologies used for creating smart devices;
  • Microactuators;
  • Dynamic behavior of smart MEMS;
  • MEMS integrating motion and displacement sensors;
  • MEMS print heads for industrial printing;
  • Photovoltaic and fuel cells in power MEMS for smart energy management;
  • Radio frequency (RF) MEMS for smart communication microsystems;
  • Intelligent devices and microsystems.

This Special Issue aims to collate original research and review articles on recent advances, technologies, solutions, applications, and new challenges in the field of intelligent and integrated MEMS devices.

Dr. Chong Lei
Dr. Zhen Yang
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

  • MEMS processing techniques
  • integrating microelectronics and MEMS
  • design, modeling, and simulation of microdevices
  • smart devices
  • MEMS and smart structures

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

16 pages, 6326 KiB  
Article
Enhancing E-Nose Performance via Metal-Oxide Based MEMS Sensor Arrays Optimization and Feature Alignment for Drug Classification
by Ruiwen Kong, Wenfeng Shen, Yang Gao, Dawu Lv, Ling Ai, Weijie Song and Ruiqin Tan
Sensors 2025, 25(5), 1480; https://doi.org/10.3390/s25051480 - 28 Feb 2025
Cited by 1 | Viewed by 1838
Abstract
This article introduces a novel approach to improve electronic nose classification accuracy by optimizing sensor arrays and aligning features. This involves selecting the best sensor combinations and reducing redundant information for better odor recognition. We employ a feature alignment algorithm to address the [...] Read more.
This article introduces a novel approach to improve electronic nose classification accuracy by optimizing sensor arrays and aligning features. This involves selecting the best sensor combinations and reducing redundant information for better odor recognition. We employ a feature alignment algorithm to address the discrepancies that impede model sharing between electronic nose devices. Our research focuses on overcoming challenges associated with material selection and the constraints of transferring classification models across different electronic nose devices for drug classification. We fabricated six SnO2-based MEMS gas sensors using physical vapor deposition. The ReliefF algorithm was employed to rank and score each sensor’s contribution to drug classification, identifying the optimal sensor array. We then applied feature alignment from transfer learning to enhance model sharing among three inconsistent devices. This study resolves the issue of electronic noses being hard to use on the same database due to hardware inconsistencies in batch production, laying the groundwork for future mass production. Full article
(This article belongs to the Special Issue Smart Sensors and Integration Technology for MEMS Devices)
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15 pages, 4946 KiB  
Article
Noise Analysis and Suppression Methods for the Front-End Readout Circuit of a Microelectromechanical Systems Gyroscope
by Chunhua He, Yingyu Xu, Xiaoman Wang, Heng Wu, Lianglun Cheng, Guizhen Yan and Qinwen Huang
Sensors 2024, 24(19), 6283; https://doi.org/10.3390/s24196283 - 28 Sep 2024
Cited by 2 | Viewed by 3937
Abstract
Circuit noise is a critical factor that affects the performances of an MEMS gyroscope. Therefore, it is essential to analyze and suppress the noises in the key analog circuits, which are the main noise sources. This study presents an optimized front-end readout circuit [...] Read more.
Circuit noise is a critical factor that affects the performances of an MEMS gyroscope. Therefore, it is essential to analyze and suppress the noises in the key analog circuits, which are the main noise sources. This study presents an optimized front-end readout circuit and noise suppression methods. First, the noise analysis of the front-end readout circuit is carried out with theoretical derivation to clarify the main noise contributors. To suppress the output noise, an improved readout circuit based on the T-resistor networks is proposed, and the corresponding noise equation is derived in detail. In addition, the noise analysis of the critical circuits of the detection and control system, such as the inverting amplifiers, the first-order low-pass filters, and the first-order high-pass filters, is carried out, and the noise suppression strategy with the optimization of the resistances and is proposed. Taking the inverting amplifier as an example, the theoretical derivation is verified by measuring and comparing the output noises of different resistance schemes. In addition, the output noises of the gyroscope before and after circuit optimization are measured. Experimental results demonstrate that the output noise with the circuit optimization is reduced from 60 μV/Hz1/2 to 30 μV/Hz1/2 and the bias instability is reduced from 3.8 deg/h to 1.38 deg/h. In addition, the ARW is significantly improved from 0.035 deg/h1/2 to 0.018 deg/h1/2, which indicates that the proposed noise analysis and suppression methods are effective and feasible. Full article
(This article belongs to the Special Issue Smart Sensors and Integration Technology for MEMS Devices)
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13 pages, 4504 KiB  
Article
Enhanced Magnetoimpedance Effect in Co-Based Micron Composite CoFeNiSiB Ribbon Strips Coated by Carbon and FeCoGa Nanofilms for Sensing Applications
by Zhen Yang, Mengyu Liu, Jingyuan Chen, Xuecheng Sun, Chong Lei, Yuanwei Shen, Zhenbao Wang, Mengjiao Zhu and Ziqin Meng
Sensors 2024, 24(10), 2961; https://doi.org/10.3390/s24102961 - 7 May 2024
Viewed by 2971
Abstract
Quenched Co-based ribbon strips are widely used in the fields of magnetic amplifier, magnetic head material, magnetic shield, electric reactor, inductance core, sensor core, anti-theft system label, and so on. In this study, Co-based composite CoFeNiSiB ribbon strips with a micron width were [...] Read more.
Quenched Co-based ribbon strips are widely used in the fields of magnetic amplifier, magnetic head material, magnetic shield, electric reactor, inductance core, sensor core, anti-theft system label, and so on. In this study, Co-based composite CoFeNiSiB ribbon strips with a micron width were fabricated by micro-electro-mechanical systems (MEMS) technology. The carbon and FeCoGa nanofilms were deposited for surface modification. The effect of carbon and FeCoGa nanofilm coatings on the crystal structure, surface morphology, magnetic properties, and magnetoimpedance (MI) effect of composite ribbon strips were systematically investigated. The results show that the surface roughness and coercivity of the composite ribbon strips are minimum at a thickness of the carbon coating of 60 nm. The maximum value of MI effect is 41% at 2 MHz, which is approximately 2.4 times greater than plain ribbon and 1.6 times greater than FeCoGa-coated composite ribbon strip. The addition of a carbon layer provides a conductive path for high frequency currents, which effectively reduces the characteristic frequency of the composite ribbon strip. The FeCoGa coating is able to close the flux path and reduce the coercivity, which, in turn, increases the transverse permeability and improves the MI effect. The findings indicate that a successful combination of carbon layer and magnetostrictive FeCoGa nanofilm layer can improve the MI effect and magnetic field sensitivity of the ribbon strips, demonstrating the potential of the composite strips for local and micro area field sensing applications. Full article
(This article belongs to the Special Issue Smart Sensors and Integration Technology for MEMS Devices)
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