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Micro-Nano Systems Technology and Micro-Nano Intelligent Manufacture
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Micro-Nano Systems Technology and Micro-Nano Intelligent Manufacture

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

Deadline for manuscript submissions: closed (31 December 2018) | Viewed by 15095

Special Issue Editors

Prof. Dr. Tao Dong

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Guest Editor
Institute for Microsystems - IMS, Faculty of Technology, Natural Sciences and Maritime Sciences, University College of Southeast Norway, Postboks 235, 3603 Kongsberg, Norway
Interests: micro sensors and micro actuators; micro devices for biological and chemical detection; heat & mass transfer in micro and nano systems; microfluidic and nanofluidics; point-of-care systems; Energy conversion in thermal systems
Prof. Zhaochu Yang

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Guest Editor
Institute of Applied Micro-Nano Science and Technology, Chongqing Key Laboratory of Micro-Nano Systems Technology and Smart Transducing, Chongqing Technology and Business University, Nan’an District, Chongqing 400067, China
Interests: Microsystems technologies; Heat mass transportation in micro and nano scale; Microfluidic and nanofluidics; Energy harvesting from the environment

Special Issue Information

Dear Colleagues,

As a multi- and interdisciplinary research field, micro- and nano systems make full use of electronics, optics, mechanics, chemistry, materials science, among others, to achieve high-performance devices and systems for biomedical, energy, environment and communications applications. For instance, in the field of health care, intelligent micro- and nano systems have boosted developments in off/on-line health continuous monitoring and disease detection with affordable micro-nano devices. Combined with the emerging artificial intelligence and cloud technologies, smart transducers based on micro- and nano systems technology become realistic; however, manufacturing these devices with enhanced efficiency and realizing associated systems have much room for innovation, adaptation, and cost reduction in various fields.

The goal of this Special Issue is to highlight the recent progresses on advanced micro- and nano systems as well as their intelligent manufacture with emphasis on applications in health care, environment, food industry and energy, electronics communications, among others. Of special interest is research work addressing real-time and continuous signal processing and detection, modelling and simulation in micro and nano systems, microfabrication principles and techniques, MEMS sensors and actuators fabrication and applications, on-chip networks and network-on-chip (NoC), microfluidic- and nanofluidic devices.

It is solicited submissions of both original research papers and review articles for this special issue.

Keywords

  • Design principles and fabrication techniques of micro- and nano systems
  • MEMS sensors and actuators
  • Lab on chip devices
  • Microfluidics and nanofluidics
  • Signal processing and detection based on integrated micro- and nano systems
  • Modelling and simulation in micro and nano systems
  • Heat & mass transfer in micro and nano systems

Published Papers (3 papers)

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Research

16 pages, 12266 KiB  
Article
Monitoring Aquaculture Water Quality: Design of an Early Warning Sensor with Aliivibrio fischeri and Predictive Models
by Luís F. B. A. Da Silva, Zhaochu Yang, Nuno M. M. Pires, Tao Dong, Hans-Christian Teien, Trond Storebakken and Brit Salbu
Sensors 2018, 18(9), 2848; https://doi.org/10.3390/s18092848 - 29 Aug 2018
Cited by 13 | Viewed by 5020
Abstract
A novel toxicity-warning sensor for water quality monitoring in recirculating aquaculture systems (RAS) is presented. The design of the sensor system mainly comprises a whole-cell biosensor. Aliivibrio fischeri, a luminescent bacterium widely used in toxicity analysis, was tested for a mixture of [...] Read more.
A novel toxicity-warning sensor for water quality monitoring in recirculating aquaculture systems (RAS) is presented. The design of the sensor system mainly comprises a whole-cell biosensor. Aliivibrio fischeri, a luminescent bacterium widely used in toxicity analysis, was tested for a mixture of known fish-health stressors, namely nitrite, un-ionized ammonia, copper, aluminum and zinc. Two toxicity predictive models were constructed. Correlation, root mean squared error, relative error and toxic behavior were analyzed. The linear concentration addition (LCA) model was found suitable to ally with a machine learning algorithm for prediction of toxic events, thanks to additive behavior near the limit concentrations for these stressors, with a root-mean-squared error (RMSE) of 0.0623, and a mean absolute error of 4%. The model was proved to have a smaller relative deviation than other methods described in the literature. Moreover, the design of a novel microfluidic chip for toxicity testing is also proposed, which is to be integrated in a fluidic system that functions as a bypass of the RAS tank to enable near-real time monitoring. This chip was tested with simulated samples of RAS water spiked with zinc, with an EC50 of 6,46E-7 M. Future work will be extended to the analysis of other stressors with the novel chip. Full article
(This article belongs to the Special Issue Micro-Nano Systems Technology and Micro-Nano Intelligent Manufacture)
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14 pages, 3647 KiB  
Article
Continuous and Real-Time Detection of Drinking-Water Pathogens with a Low-Cost Fluorescent Optofluidic Sensor
by João Simões and Tao Dong
Sensors 2018, 18(7), 2210; https://doi.org/10.3390/s18072210 - 10 Jul 2018
Cited by 30 | Viewed by 5115
Abstract
Growing access to tap water and consequent expansion of water distribution systems has created numerous challenges to maintaining water quality between the treatment node and final consumer. Despite all efforts to develop sustainable monitoring systems, there is still a lack of low cost, [...] Read more.
Growing access to tap water and consequent expansion of water distribution systems has created numerous challenges to maintaining water quality between the treatment node and final consumer. Despite all efforts to develop sustainable monitoring systems, there is still a lack of low cost, continuous and real time devices that demonstrate potential for large-scale implementation in wide water distribution networks. The following work presents a study of a low-cost, optofluidic sensor, based on Trypthopan Intrinsic Fluorescence. The fluorospectrometry analysis performed (before sensor development) supports the existence of a measurable fluorescence output signal originating from the tryptophan contained within pathogenic bacteria. The sensor was mounted using a rapid prototyping technique (3D printing), and the integrated optical system was achieved with low-cost optical components. The sensor performance was evaluated with spiked laboratory samples containing E. coli and Legionella, in both continuous and non-continuous flow situations. Results have shown a linear relationship between the signal measured and pathogen concentration, with limits of detection at 1.4 × 103 CFU/mL. The time delay between contamination and detection of the bacteria was practically null. Therefore, this study supports the potential application of tryptophan for monitoring drinking water against water pathogens. Full article
(This article belongs to the Special Issue Micro-Nano Systems Technology and Micro-Nano Intelligent Manufacture)
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18 pages, 11304 KiB  
Article
Lower-Order Compensation Chain Threshold-Reduction Technique for Multi-Stage Voltage Multipliers
by Francesco Dell’ Anna, Tao Dong, Ping Li, Yumei Wen, Mehdi Azadmehr, Mario Casu and Yngvar Berg
Sensors 2018, 18(4), 1245; https://doi.org/10.3390/s18041245 - 17 Apr 2018
Cited by 1 | Viewed by 3752
Abstract
This paper presents a novel threshold-compensation technique for multi-stage voltage multipliers employed in low power applications such as passive and autonomous wireless sensing nodes (WSNs) powered by energy harvesters. The proposed threshold-reduction technique enables a topological design methodology which, through an optimum control [...] Read more.
This paper presents a novel threshold-compensation technique for multi-stage voltage multipliers employed in low power applications such as passive and autonomous wireless sensing nodes (WSNs) powered by energy harvesters. The proposed threshold-reduction technique enables a topological design methodology which, through an optimum control of the trade-off among transistor conductivity and leakage losses, is aimed at maximizing the voltage conversion efficiency (VCE) for a given ac input signal and physical chip area occupation. The conducted simulations positively assert the validity of the proposed design methodology, emphasizing the exploitable design space yielded by the transistor connection scheme in the voltage multiplier chain. An experimental validation and comparison of threshold-compensation techniques was performed, adopting 2N5247 N-channel junction field effect transistors (JFETs) for the realization of the voltage multiplier prototypes. The attained measurements clearly support the effectiveness of the proposed threshold-reduction approach, which can significantly reduce the chip area occupation for a given target output performance and ac input signal. Full article
(This article belongs to the Special Issue Micro-Nano Systems Technology and Micro-Nano Intelligent Manufacture)
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