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Nanomaterials
Special Issues
The Application of Nanosensors in Energy and Environment
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The Application of Nanosensors in Energy and Environment

A special issue of Nanomaterials (ISSN 2079-4991). This special issue belongs to the section "Nanoelectronics, Nanosensors and Devices".

Deadline for manuscript submissions: 10 October 2024 | Viewed by 2031

Special Issue Editor

Prof. Dr. Di Wei

E-Mail Website
Guest Editor
Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, China
Interests: nanosenosr

Special Issue Information

Dear Colleagues,

Information flow in the central nervous system consumes little energy; the human brain, as a typical highly integrated iontronic center processing unit enabled by nanoconfined quantum superfluid, consumes only about 12 W. From the ubiquitous Internet of Things (IoTs) to highly integrated human brains, energy efficiency plays a critical role in the flow of information. Nanomaterials, nanostructures and nanointerfaces play essential roles in highly efficient energy and information flow, offering possibilities for novel sensors.

The present Special Issue of Nanomaterials presents the current state of the art in the use of nanomaterials, nanostructures, or nanointerfaces to generate new sensors, including approach perception sensors, gesture sensors, touch sensors, electronic tongues, self-powered sensors, etc. We also welcome work on new nanomaterials and nanostructures, for example nanofluidic materials and iontronic materials, for novel sensing technology and systems.

We invite contributions from leading groups in the field with the aim of giving a balanced view of the current state of the art in this discipline.

Prof. Dr. Di Wei
Guest Editor

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. Nanomaterials 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 2900 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

  • nanomaterials
  • nanotechnology
  • energy
  • environment
  • sensors

Published Papers (2 papers)

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Research

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12 pages, 6986 KiB  
Article
WO3 Nanoplates Decorated with Au and SnO2 Nanoparticles for Real-Time Detection of Foodborne Pathogens
by Xueyan Li, Zeyi Wu, Xiangyu Song, Denghua Li, Jiajia Liu and Jiatao Zhang
Nanomaterials 2024, 14(8), 719; https://doi.org/10.3390/nano14080719 - 19 Apr 2024
Viewed by 327
Abstract
Nowadays, metal oxide semiconductor gas sensors have diverse applications ranging from human health to smart agriculture with the development of Internet of Things (IoT) technologies. However, high operating temperatures and an unsatisfactory detection capability (high sensitivity, fast response/recovery speed, etc.) hinder their integration [...] Read more.
Nowadays, metal oxide semiconductor gas sensors have diverse applications ranging from human health to smart agriculture with the development of Internet of Things (IoT) technologies. However, high operating temperatures and an unsatisfactory detection capability (high sensitivity, fast response/recovery speed, etc.) hinder their integration into the IoT. Herein, a ternary heterostructure was prepared by decorating WO3 nanoplates with Au and SnO2 nanoparticles through a facial photochemical deposition method. This was employed as a sensing material for 3-hydroxy-2-butanone (3H-2B), a biomarker of Listeria monocytogenes. These Au/SnO2–WO3 nanoplate-based sensors exhibited an excellent response (Ra/Rg = 662) to 25 ppm 3H-2B, which was 24 times higher than that of pure WO3 nanoplates at 140 °C. Moreover, the 3H-2B sensor showed an ultrafast response and recovery speed to 25 ppm 3H-2B as well as high selectivity. These excellent sensing performances could be attributed to the rich Au/SnO2–WO3 active interfaces and the excellent transport of carriers in nanoplates. Furthermore, a wireless portable gas sensor equipped with the Au/SnO2–WO3 nanoplates was assembled, which was tested using 3H-2B with known concentrations to study the possibilities of real-time gas monitoring in food quality and safety. Full article
(This article belongs to the Special Issue The Application of Nanosensors in Energy and Environment)
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Review

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30 pages, 18195 KiB  
Review
Synergizing Machine Learning Algorithm with Triboelectric Nanogenerators for Advanced Self-Powered Sensing Systems
by Roujuan Li, Di Wei and Zhonglin Wang
Nanomaterials 2024, 14(2), 165; https://doi.org/10.3390/nano14020165 - 12 Jan 2024
Viewed by 1409
Abstract
The advancement of the Internet of Things (IoT) has increased the demand for large-scale intelligent sensing systems. The periodic replacement of power sources for ubiquitous sensing systems leads to significant resource waste and environmental pollution. Human staffing costs associated with replacement also increase [...] Read more.
The advancement of the Internet of Things (IoT) has increased the demand for large-scale intelligent sensing systems. The periodic replacement of power sources for ubiquitous sensing systems leads to significant resource waste and environmental pollution. Human staffing costs associated with replacement also increase the economic burden. The triboelectric nanogenerators (TENGs) provide both an energy harvesting scheme and the possibility of self-powered sensing. Based on contact electrification from different materials, TENGs provide a rich material selection to collect complex and diverse data. As the data collected by TENGs become increasingly numerous and complex, different approaches to machine learning (ML) and deep learning (DL) algorithms have been proposed to efficiently process output signals. In this paper, the latest advances in ML algorithms assisting solid–solid TENG and liquid–solid TENG sensors are reviewed based on the sample size and complexity of the data. The pros and cons of various algorithms are analyzed and application scenarios of various TENG sensing systems are presented. The prospects of synergizing hardware (TENG sensors) with software (ML algorithms) in a complex environment and their main challenges for future developments are discussed. Full article
(This article belongs to the Special Issue The Application of Nanosensors in Energy and Environment)
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