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Acetone Sensing Properties and Mechanism of SnO2 Thick-Films In the present work, we investigated the acetone sensing characteristics and mechanism of SnO2 thick-films through experiments and DFT calculations. SnO2 thick film annealed at 600 °C could sensitively detect acetone vapors. At the optimum operating temperature of 180 °C, the responses of the SnO2 sensor were 3.33, 3.94, 5.04, and 7.27 for 1, 3, 5, and 10 ppm acetone, respectively. The DFT calculation results show that the acetone molecule can be adsorbed on the five-fold-coordinated Sn and oxygen vacancy (VO) sites with O-down, with electrons transferring from acetone to the SnO2 (110) surface. The acetone molecule acts as a donor in these modes, which can explain why the resistance of SnO2 or n-type metal oxides decreased after the acetone molecules were introduced into the system. Molecular dynamics calculations show that acetone does not convert to other products during the simulation.
Sensors - Tập 18 Số 10 - Trang 3425
Cảm Biến Vị Giác Tiên Tiến Dựa Trên Lipid Nhân Tạo Với Tính Chọn Lọc Toàn Cầu Đối Với Những Chất Vị Cơ Bản Và Tương Quan Cao Với Điểm Vị Giác Nghiên cứu và phát triển (R&D) hiệu quả cùng với việc kiểm soát chất lượng nghiêm ngặt đối với các loại thực phẩm, đồ uống và sản phẩm dược phẩm đòi hỏi đánh giá vị giác khách quan. Các cảm biến vị giác tiên tiến sử dụng màng lipid nhân tạo đã được phát triển dựa trên các khái niệm về tính chọn lọc toàn cục và sự tương quan cao với điểm vị giác của con người. Những cảm biến này phản ứng tương tự với các vị cơ bản tương tự, mà chúng định lượng với sự tương quan cao với điểm vị giác. Sử dụng những đặc điểm độc đáo này, các cảm biến có thể định lượng các vị cơ bản như mặn, chua, đắng, umami, chát và độ phong phú mà không cần phân tích đa biến hay mạng lưới thần kinh nhân tạo. Bài bình luận này mô tả tất cả các khía cạnh của những cảm biến vị giác dựa trên lipid nhân tạo, từ nguyên tắc phản ứng và phương pháp thiết kế tối ưu đến các ứng dụng trong thị trường thực phẩm, đồ uống, và dược phẩm.
Sensors - Tập 10 Số 4 - Trang 3411-3443
#cảm biến vị giác #lipid nhân tạo #lựa chọn toàn cầu #vị cơ bản #tương quan với điểm vị giác #thực phẩm #đồ uống #dược phẩm
Assist-As-Needed Exoskeleton for Hand Joint Rehabilitation Based on Muscle Effort Detection Robotic-assisted systems have gained significant traction in post-stroke therapies to support rehabilitation, since these systems can provide high-intensity and high-frequency treatment while allowing accurate motion-control over the patient’s progress. In this paper, we tackle how to provide active support through a robotic-assisted exoskeleton by developing a novel closed-loop architecture that continually measures electromyographic signals (EMG), in order to adjust the assistance given by the exoskeleton. We used EMG signals acquired from four patients with post-stroke hand impairments for training machine learning models used to characterize muscle effort by classifying three muscular condition levels based on contraction strength, co-activation, and muscular activation measurements. The proposed closed-loop system takes into account the EMG muscle effort to modulate the exoskeleton velocity during the rehabilitation therapy. Experimental results indicate the maximum variation on velocity was 0.7 mm/s, while the proposed control system effectively modulated the movements of the exoskeleton based on the EMG readings, keeping a reference tracking error <5%.
Sensors - Tập 21 Số 13 - Trang 4372
A Highly Selective and Sensitive Fluorescent Chemosensor for Detecting Al3+ Ion in Aqueous Solution and Plant Systems The solubilized form of aluminum, Al3+, is present under acid soil conditions and toxic to both animals and plants. Detecting and quantifying Al3+ is vital for both chemistry and biology. A new Schiff-based fluorescent turn-on sensor (probe L) for the selective detection of the Al3+ ion was synthesized by coupling 2-hydroxy-1-naphthaldehyde and 2-aminoisoindoline-1,3-dione, and the structure was characterized by nuclear magnetic resonance spectra. The probe L exhibited an excellent selective and sensitive response to the Al3+ ion over other metal ions in DMSO-H2O (1:9 v/v). Fluorescence quantification revealed that probe L was promising for the detection and accumulation of Al3+. Treating rice seedlings with Al3+ at 25–200 μM inhibited their growth. Al3+ treatment produced reactive oxygen species in rice roots. Practical applications of the fluorescent probe for the quantification of Al3+ in water samples and rice seedlings are demonstrated. Detecting the Al3+ ion with the probe L is easy and a potential alternative to existing analytical methods. The method can be used for detecting the Al3+ content of aqueous solution and plant systems. The novel fluorescent probe L has good potential for monitoring Al3+ content in the environment and biological systems.
Sensors - Tập 19 Số 3 - Trang 623
Human-Like Lane Change Decision Model for Autonomous Vehicles that Considers the Risk Perception of Drivers in Mixed Traffic Determining an appropriate time to execute a lane change is a critical issue for the development of Autonomous Vehicles (AVs).However, few studies have considered the rear and the front vehicle-driver’s risk perception while developing a human-like lane-change decision model. This paper aims to develop a lane-change decision model for AVs and to identify a two level threshold that conforms to a driver’s perception of the ability to safely change lanes with a rear vehicle approaching fast. Based on the signal detection theory and extreme moment trials on a real highway, two thresholds of safe lane change were determined with consideration of risk perception of the rear and the subject vehicle drivers, respectively. The rear vehicle’s Minimum Safe Deceleration (MSD) during the lane change maneuver of the subject vehicle was selected as the lane change safety indicator, and was calculated using the proposed human-like lane-change decision model. The results showed that, compared with the driver in the front extreme moment trial, the driver in the rear extreme moment trial is more conservative during the lane change process. To meet the safety expectations of the subject and rear vehicle drivers, the primary and secondary safe thresholds were determined to be 0.85 m/s2 and 1.76 m/s2, respectively. The decision model can help make AVs safer and more polite during lane changes, as it not only improves acceptance of the intelligent driving system, but also further ensures the rear vehicle’s driver’s safety.
Sensors - Tập 20 Số 8 - Trang 2259
Calibration of a Sensor Array (an Electronic Tongue) for Identification and Quantification of Odorants from Livestock Buildings This contribution serves a dual purpose. The first purpose was to investigate the possibility of using a sensor array (an electronic tongue) for on-line identification and quantification of key odorants representing a variety of chemical groups at two different acidities, pH 6 and 8. The second purpose was to simplify the electronic tongue by decreasing the number of electrodes from 14, which was the number of electrodes in the prototype. Different electrodes were used for identification and quantification of different key odorants. A total of eight electrodes were sufficient for identification and quantification in micromolar concentrations of the key odorants n-butyrate, ammonium and phenolate in test mixtures also containing iso-valerate, skatole and p-cresolate. The limited number of electrodes decreased the standard deviation and the relative standard deviation of triplicate measurements in comparison with the array comprising 14 electrodes. The electronic tongue was calibrated using 4 different test mixtures, each comprising 50 different combinations of key odorants in triplicates, a total of 600 measurements. Back propagation artificial neural network, partial least square and principal component analysis were used in the data analysis. The results indicate that the electronic tongue has a promising potential as an on- line sensor for odorants absorbed in the bioscrubber used in livestock buildings.
Sensors - Tập 7 Số 1 - Trang 103-128
Fuzzy Evaluation Output of Taste Information for Liquor Using Electronic Tongue Based on Cloud Model As a taste bionic system, electronic tongues can be used to derive taste information for different types of food. On this basis, we have carried forward the work by making it, in addition to the ability of accurately distinguish samples, be more expressive by speaking evaluative language like human beings. Thus, this paper demonstrates the correlation between the qualitative digital output of the taste bionic system and the fuzzy evaluation language that conform to the human perception mode. First, through principal component analysis (PCA), backward cloud generator and forward cloud generator, two-dimensional cloud droplet groups of different flavor information were established by using liquor taste data collected by electronic tongue. Second, the frequency and order of the evaluation words for different flavor of liquor were obtained by counting and analyzing the data appeared in the artificial sensory evaluation experiment. According to the frequency and order of words, the cloud droplet range corresponding to each word was calculated in the cloud drop group. Finally, the fuzzy evaluations that originated from the eight groups of liquor data with different flavor were compared with the artificial sense, and the results indicated that the model developed in this work is capable of outputting fuzzy evaluation that is consistent with human perception rather than digital output. To sum up, this method enabled the electronic tongue system to generate an output, which conforms to human’s descriptive language, making food detection technology a step closer to human perception.
Sensors - Tập 20 Số 3 - Trang 686
Biosensing with Luminescent Semiconductor Quantum Dots Luminescent semiconductor nanocrystals or quantum dots (QDs) are a recentlydeveloped class of nanomaterial whose unique photophysical properties are helping tocreate a new generation of robust fluorescent biosensors. QD properties of interest forbiosensing include high quantum yields, broad absorption spectra coupled to narrow sizetunablephotoluminescent emissions and exceptional resistance to both photobleaching andchemical degradation. In this review, we examine the progress in adapting QDs for severalpredominantly in vitro biosensing applications including use in immunoassays, asgeneralized probes, in nucleic acid detection and fluorescence resonance energy transfer(FRET) - based sensing. We also describe several important considerations when workingwith QDs mainly centered on the choice of material(s) and appropriate strategies forattaching biomolecules to the QDs.
Sensors - Tập 6 Số 8 - Trang 925-953
Chemical Sensors Based on Cyclodextrin Derivatives This review focuses on chemical sensors based on cyclodextrin (CD) derivatives. This has been a field of classical interest, and is now of current interest for numerous scientists. First, typical chemical sensors using chromophore appended CDs are mentioned. Various “turn-off” and “turn-on” fluorescent chemical sensors, in which fluorescence intensity was decreased or increased by complexation with guest molecules, respectively, were synthesized. Dye modified CDs and photoactive metal ion-ligand complex appended CDs, metallocyclodextrins, were also applied for chemical sensors. Furthermore, recent novel approaches to chemical sensing systems using supramolecular structures such as CD dimers, trimers and cooperative binding systems of CDs with the other macrocycle [2]rotaxane and supramolecular polymers consisting of CD units are mentioned. New chemical sensors using hybrids of CDs with p-conjugated polymers, peptides, DNA, nanocarbons and nanoparticles are also described in this review.
Sensors - Tập 8 Số 8 - Trang 4961-4982
A Time-Distributed Spatiotemporal Feature Learning Method for Machine Health Monitoring with Multi-Sensor Time Series Data-driven methods with multi-sensor time series data are the most promising approaches for monitoring machine health. Extracting fault-sensitive features from multi-sensor time series is a daunting task for both traditional data-driven methods and current deep learning models. A novel hybrid end-to-end deep learning framework named Time-distributed ConvLSTM model (TDConvLSTM) is proposed in the paper for machine health monitoring, which works directly on raw multi-sensor time series. In TDConvLSTM, the normalized multi-sensor data is first segmented into a collection of subsequences by a sliding window along the temporal dimension. Time-distributed local feature extractors are simultaneously applied to each subsequence to extract local spatiotemporal features. Then a holistic ConvLSTM layer is designed to extract holistic spatiotemporal features between subsequences. At last, a fully-connected layer and a supervised learning layer are stacked on the top of the model to obtain the target. TDConvLSTM can extract spatiotemporal features on different time scales without any handcrafted feature engineering. The proposed model can achieve better performance in both time series classification tasks and regression prediction tasks than some state-of-the-art models, which has been verified in the gearbox fault diagnosis experiment and the tool wear prediction experiment.
Sensors - Tập 18 Số 9 - Trang 2932
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