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Machine learning assisted dual-channel carbon quantum dots-based fluorescence sensor array for detection of tetracyclines

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SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2020年 232卷 118147-118147页

作者： Xu, Zijun Wang, Zhaokun Liu, Mingyang Yan, Binwei Ren, Xueqin Gao, Zideng China Agr Univ Coll Resources & Environm Sci Beijing 100193 Peoples R China China Agr Univ Beijing Key Lab Farmland Soil Pollut Prevent & Re Beijing 100193 Peoples R China

The detection and differentiation of tetracyclines (TCs) has received increasing attention due to the severe threat they pose to human health and the ecological balance. A dual-channel fluorescence sensor array based on two carbon quantum dots (CDs) was fabricated to distinguish between four TCs, including tetracycline (TC), oxytetracydine (OTC), doxycycline (DOX), and metacydine (MTC). A distinct fluorescence variation pattern (I/I-0) was produced when CDs interacted with the four TCs. This pattern was analyzed by LDA and SVM. This was the first time that SVM was used for data processing of fluorescence sensor arrays. IDA and SVM showed that the array has the capacity for parallel and accurate determination of TCs at concentrations between 1.0 mu M and 150 mu M. In addition, the interference experiment using metal ions and antibiotics as possible coexisting interference substances proves that the sensor array has excellent selectivity and anti-interference ability. The array was also used for the accurate detection and identification of TCs in binary mixtures, and furthermore, the four TCs were successfully identified in river water and milk samples. Besides, the sensor array successfully identified the four ICs in 72 unknown samples with a 100% accuracy. The results proved that SW can achieve the same accurate classification and prediction as LDA, and considering its additional advantages, it can be used as an optional supplementary method for data processing, thereby expanding the data processing field. (C) 2020 Published by Elsevier B.V.

关键词： Carbon quantum dots Linear discriminant analysis Support vector machine sensor array Tetracyclines

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Design and optimization of sensor array for magnetic gradient tensor system

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sensor REVIEW 2020年第1期40卷 121-129页

作者： Chen, Shengzhi Zhu, Minghua Zhang, Qing Cai, Xuesong Xiao, Bo East China Normal Univ Shanghai Peoples R China East China Normal Univ Sch Comp Sci & Software Engn Shanghai Peoples R China East China Normal Univ Natl Trusted Embedded Software Engn Technol Res C Shanghai Peoples R China

Purpose The differential magnetic gradient tensor system is usually constructed from the three-axis magnetic sensor array. While the effects of measurement error, sensor performance and baseline distance on localization performance of such systems have been widely reported, the research about the effect of spatial design of sensor array is less presented. This paper aims to provide a spatial design method of sensor array and corresponding optimization strategy to localization based on magnetic tensor gradient to get the optimum design of the sensor array. Based on the results of simulation, magnetic localization systems constructed from the proposed array and the traditional array have been built to carry out a localization experiment. The results of experiment have verified the effectiveness of magnetic localization based on the proposed array. Design/methodology/approach The authors focus on the localization of the magnetic target based on magnetic gradient by using three-axis magnetic sensor array and combine a design method with corresponding optimization strategy to get the optimum design of the sensor array. Findings This paper provides an array design and optimization method for magnetic target localization based on magnetic gradient to improve the localization performance. Originality/value In this paper, the authors focus on the magnetic localization based on magnetic gradient by using three-axis magnetic sensors and study the effect of the spatial design of sensor array on localization performance.

关键词： array optimization Magnetic gradient tensor system Magnetic localization sensor array

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The characteristics of a "stop-flow" mode of sensor array operation using data with the best classification performance

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sensorS AND ACTUATORS B-CHEMICAL 2009年第2期141卷 417-423页

作者： Maciejewska, M. Szczurek, A. Ochromowicz, L. Wroclaw Univ Technol Fac Microsyst Elect & Photon PL-50370 Wroclaw Poland

The paper presents an approach to characterizing a "stop-flow" mode of sensor array operation. The considered operation mode involves three successive phases of sensors exposure: flow (in a stream of measured gas), stop (in zero flow conditions) and recovery (in a stream of pure air). The mode was characterized by describing the distribution of information, which is relevant for classification of measured gases in the response of sensor array. The input data for classifier were the sets of sensors output values, acquired in discrete time moments of the measurement. Discriminant Function Analysis was used for data analysis. Organic vapours of ethanol, acetic acid and ethyl acetate in air were measured and classified. Our attention was focused on data sets which allowed for 100% efficient recognition of analytes. The number, size and composition of those data sets were examined versus time of sensor array response. This methodology allowed to observe the distribution of classification-relevant information in the response of sensor array obtained in "stop-flow" mode. Hence, it provided for the characterization of this mode. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Stop-flow mode sensor array Dynamic response VOCs

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Surface chemistry modified upconversion nanoparticles as fluorescent sensor array for discrimination of foodborne pathogenic bacteria

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JOURNAL OF NANOBIOTECHNOLOGY 2020年第1期18卷 41-41页

作者： Yin, Mingyuan Jing, Chuang Li, Haijie Deng, Qiliang Wang, Shuo Tianjin Univ Sci & Technol Coll Chem Engn & Mat Sci Sch Food Engn & Biotechnol State Key Lab Food Nutr & Safety Tianjin 300457 Peoples R China Nankai Univ Sch Med Tianjin Key Lab Food Sci & Hlth Tianjin 300071 Peoples R China

Background The identification of foodborne pathogenic bacteria types plays a crucial role in food safety and public health. In consideration of long culturing times, tedious operations and the desired specific recognition elements in conventional methods, the alternative fluorescent sensor arrays can offer a high-effective approach in bacterial identification by using multiple cross-reactive receptors. Herein, we achieve this goal by constructing an upconversion fluorescent sensor array based on anti-stokes luminogens featuring a series of functional lanthanide-doped upconversion nanoparticles (UCNPs) with phenylboronic acid, phosphate groups, or imidazole ionic liquid. The prevalent spotlight effect of microorganism and the electrostatic interaction between UCNPs and bacteria endow such sensor array an excellent discrimination property. Results Seven common foodborne pathogenic bacteria including two Gram-positive bacteria (Staphylococcus aureus and Listeria monocytogenes) and five Gram-negative bacteria (Escherichia coli, Salmonella, Cronobacter sakazakii, Shigella flexneri and Vibrio parahaemolyticus) are precisely identified with 100% accuracy via linear discriminant analysis (LDA). Furthermore, blends of bacteria have been identified accurately. Bacteria in real samples (tap water, milk and beef) have been effectively discriminated with 92.1% accuracy. Conclusions Current fluorescence sensor array is a powerful tool for high-throughput bacteria identification, which overcomes the time-consuming bacteria culture and heavy dependence of specific recognition elements. The high efficiency of whole bacterial cell detection and the discrimination capability of life and death bacteria can brighten the application of fluorescence sensor array.

关键词： Upconversion nanoparticles Foodborne bacteria sensor array Identification

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Qualitative Identification of Single/Mixture Gases Based on Fe-ZnO sensor array and PSO-BP Neural Network

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IEEE sensorS JOURNAL 2023年第17期23卷 20037-20043页

作者： Li, Meihua Ge, Shikun Gu, Yunlong Zhang, Yunfan Li, Xiao Zhu, Huichao Wei, Guangfen Shandong Technol & Business Univ Sch Informat & Elect Engn Yantai 264005 Peoples R China Dalian Univ Technol Sch Artificial Intelligence Dalian 116024 Peoples R China

Fe-zinc oxide (ZnO) materials with self-assembled rod-flower structure were synthesized. X-ray diffraction (XRD), energy-dispersive spectroscopy (EDS), scanning electron microscope (SEM), and X-ray photoelectron spectroscopy (XPS) were used to characterize the morphology, elemental composition, and valence analysis of Fe-ZnO. It was verified that Fe-ZnO sensors have good performances for single/mixed test gases. Combining the sensor array with a back propagation neural network algorithm optimized by particle swarm (PSO-BPNN), qualitative identification of ten different gas concentration levels under three categories was achieved with a detection accuracy of 95%. High classification detection was achieved using the PSO-BPNN model even under the influence of different humidity levels (RH = 35%, 50%, and 80%). So, the combined Fe-ZnO sensor array with PSO-BPNN model can effectively detect toxic gases at different concentration levels and therefore has some potential practical values.

关键词： Zinc oxide II-VI semiconductor materials sensors Temperature sensors Gas detectors Iron Zinc Concentration level analysis particle swarm algorithm qualitative identification self-assembled rod-flower structure sensor array

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A novel electronic nose based on porous In₂O₃ microtubes sensor array for the discrimination of VOCs

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BIOsensorS & BIOELECTRONICS 2015年 64卷 547-553页

作者： Yang, Wei Wan, Peng Jia, Mingyan Hu, Jiming Guan, Yafeng Feng, Liang Chinese Acad Sci Dalian Inst Chem Phys Key Lab Separat Sci Analyt Chem Dalian 116023 Liaoning Peoples R China Wuhan Univ Coll Chem & Mol Sci Wuhan 430072 Hubei Peoples R China Dalian Univ Technol Fac Chem Environm & Biol Sci & Technol Dalian 116024 Liaoning Peoples R China

We have innovatively developed an electronic nose consisting of only one type of semiconductor metal oxide (SMO) material. The representative SMO material, porous In2O3 microtubes in this work, offered great surface area and large gas penetration channels. By using a solvent casting process, different amounts of porous In2O3 microtubes were coated on Al2O3 substrate, forming a resistometric SMO sensor array-based electronic nose. Each sensing unit in the electronic nose exhibited independent response toward ethanol. We have successfully applied this electronic nose to distinguish four alcohols at the same concentrations (100 ppm), and also utilized the electronic nose for the discrimination of 14 volatile organic compounds (VOCs). Clear differentiation among all the 14 VOCs both at their immediately dangerous to life or health (IDLH) and the permissible exposure limit (PEL) concentrations has been achieved with no errors or misclassifications. We expect that this method will expand the application of SMO sensor array-based electronic nose which has been largely limited by the selection of commercially available SMOs and dopants. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Electronic nose sensor array In2O3 Microtubes Volatile organic compound

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Quantification of Binary and Ternary Mixtures of Homologous Nonylphenol Polyethoxylates Using the Potentiometric sensor array

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ELECTROANALYSIS 2009年第3-5期21卷 521-529页

作者： Makarova, Natalia Mikhailovna Kulapina, Elena Grigorevna Saratov NG Chernyshevskii State Univ Dept Chem Saratov 410012 Russia

The electronic tongue system based on the potentiometric sensor array for the determination of nomonic surfactants was developed. Multivariate statistical analysis techniques as partial least squares (PLS) method and backpropagation artificial neural networks (ANN) were used for data processing. The proposed system was applied for the quantitative analysis of homologous polyoxyethylated nonylphenols in complex multicomponent model mixtures and natural water samples. The least relative errors of detection were obtained for artificial neural network. Proposed approach could be applied to further analyze of sewage waters and commercial technical samples.

关键词： Surfactants Potentiometric sensors Electronic tongue sensor array Partial least squares Artificial neural networks

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A multi-module artificial neural network approach to pattern recognition with optimized nanostructured sensor array

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sensorS AND ACTUATORS B-CHEMICAL 2006年第1期117卷 65-73页

作者： Shi, Xiajing Wang, Lingyan Kariuki, Nancy Luo, Jin Zhong, Chuan-Jian Lu, Susan SUNY Binghamton Dept Chem Binghamton NY 13902 USA

The selection of appropriate sensing array nanomaterials and the pattern recognition of sensing signals are two challenges for the development of sensitive, selective, and cost-effective sensor array systems. To tackle both challenges, the work described in this paper focuses on the development of a new hybrid method which couples multi-module method with artificial neural networks (ANNs) for the optimization-optimized multi-module ANN classifier (OMAC) to enhance the correct detection rate for multiple volatile organic compounds (VOCs). In this OMAC method, each module is dedicated to a group of VOCs with specific inputs. Each sensor element's selectivity is quantitatively evaluated to assist the selection of sensing array materials, which also facilitates the selection of inputs to each dedicated neural network module. This OMAC method is shown to be useful for achieving a high overall recognition rate for a selected set of vapor analytes. The results are discussed, along with the implications to the better design of ANN pattern classifiers in chemical sensor applications. (c) 2005 Elsevier B.V. All rights reserved.

关键词： sensor array pattern recognition neural networks volatile organic compounds selectivity nanostructures

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CNT-based sensor array for selective and steady detection of SO2 and NO

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MATERIALS RESEARCH BULLETIN 2020年第0期124卷 110772-000页

作者： Song, Hui Li, Quanfu Zhang, Yong Qufu Normal Univ Sch Software Engn Qufu 273165 Shandong Peoples R China Guangxi Normal Univ Coll Elect Engn Guilin 541004 Guangxi Peoples R China Xi An Jiao Tong Univ Sch Elect Engn Xian 710049 Shaanxi Peoples R China

The accurate detection of NO and SO2 emitted from fossil fuel power plants is critical for realizing the real-time control of clean combustion systems and environmental protection. An array of two CNT-based ionization sensors with different electrode separations is used to detect NO and SO2 in flue gas. The responses of each sensor show a monotone decreasing response, and are obviously separated but almost parallel. The decreasing response is attributed to strong consumption of N-2(A(3)Sigma u(+)) and N-2(a'(1)Sigma u(+)) in collision with SO2 or NO. And the separated and parallel responses in gas mixture indicates a good selectivity and the ability to simultaneously detect SO2 and NO concentrations with no other means. In addition, the array also have excellent long-term stability due to its non-self-sustaining discharge, which reducing the damage of CNTs caused by electrical breakdown. And the sensor has a fast response and recovery times of 8 s and 7 s, respectively.

关键词： sensor array CNT Non-self-sustaining discharge Mechanism Stability

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Nondestructive evaluation of a crack on austenitic stainless steel using a sheet type induced current and a Hall sensor array

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JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2008年第9期22卷 1684-1691页

作者： Jun, Jongwoo Lee, Jinyi Chosun Univ Dept Control & Instrumentat Robot Engn Kwangju 501759 South Korea Chosun Univ Grad Sch Dept Informat & Commun Engn Kwangju 501759 South Korea

Austenitic stainless steels (hereafter A-STS) Such as STS304 and STS316 are paramagnetic metals. However, a small amount of partial magnetization is generated in A-STS because of the imperfect final heat treatment and mechanical processing. Surface cracks on paramagnetic metal with a partially magnetized region (hereafter PMR) are difficult to inspect. In this paper, we propose a method for high speed inspection and evaluation of a crack on A-STS. Cracks can be inspected with high speed by using 64 arrayed Hall sensors (HSA) with 3.5 mm spatial resolution and a sheet type induced current (STIC). Then, a crack can be evaluated quantitatively by using the detailed distribution of the magnetic field obtained by using single Hall sensor scanning (SSS) around the inspected crack area. Several cracks on A-STS with partially magnetized areas were examined and the experimental formulas were derived.

关键词： nondestructive evaluation sheet type induced current austenitic stainless steel sensor array sensor scanning

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