Materials Horizons
·
2020
·Vol. 7
·期 10
·2673-2682
·
IF 12.319
Qiao Wang,Hongyao Ding,Xiaosai Hu,Xiaoxu Liang,Miaomiao Wang,Qing Liu,Zongjin Li,Guoxing Sun
The intelligent flexible sensors with high responsivity and detectivity are highly desired for wearable devices and human–machine interfaces (HMI). However, the existing sensors are usually limited to onefold detection performance in either contact or noncontact mode. Here, a sandwiched hydrogel capacitive system is designed to fabricate a multi-operational-mode ionic sensor (MOMS) that simultaneously recognizes mechanical stimuli and remote gestures. The novel MOMS performs satisfying sensitivity (1.7 gauge factor and 3.3 Pa−1 pressure sensitivity), rapid response for contactless gesture recognition, a quite wide working range (up to 100 kPa and 300% elongation) and a good touch-free operating distance (40 mm). Moreover, the spatial resolution of the structured sensor array meets the accurate positioning requirements under both contact and touch-free conditions. This is the first time that a capacitive hydrogel system exhibited outstanding performance in detecting contact stimuli and noncontact hand motions at the same time. Hence, the MOMS will allow significant advances in intelligent detection techniques and facilitate innovative thinking for the applications of synchronous monitoring devices.
研究领域:
材料科学
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生物医学工程
·
智能传感技术
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DOI
高影响因子
ACS Applied Materials & Interfaces
·
2024
·
IF 8.3
Lu Ju,Buyun Yu,Hao Chen,Zhida Xiao,Wei Xiang,Junlin Zhan,Chao Zhang,Zhenguo Liu,Li Tao,Weibing Lu
As a noncontact target recognition technique, radio-frequency identification (RFID) technology demonstrates attractive potential in constructing human–machine interaction (HMI) systems. However, the current development of RFID technologies in HMI systems is hampered by critical challenges in manufacturing high-performance RFID readers with superior flexibility and wearing comfort. Hence, we propose a multilevel printing strategy to overcome the difficulties in manufacturing high-performance large-scale microwave systems. Compared to traditional processes, the RFID system fabricated by the hybrid additive manufacturing technique exhibits equivalent electromagnetic performance and has obvious advantages in terms of manufacturing cost and environmental friendliness. A printed reconfigurable antenna with intelligent radiation mode is seamlessly integrated with the reader circuit via a “one-step” printing technology. Additionally, through chemical doping and artificial intelligence (AI) prediction, we have developed a modified polydimethylsiloxane (PDMS) encapsulation to miniaturize the system volume and enhance reliability. Electromagnetic and mechanical measurements demonstrated that our flexible RFID platform offers superior reliability and stability during long-term daily use. The RFID platform possesses exceptional capabilities in target positioning and accurate identification, demonstrating unique potential in noncontact sensing and recognition, which are highly demanded by flexible and wearable HMI systems.
研究领域:
电子工程
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材料科学
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人工智能
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产品关联
DOI
PubMed
高影响因子
ChemistrySelect
·
2022
·Vol. 7
·期 28
·e202201584
·
IF 2.307
Cheng-hui Wang,Hong-qian Zou,Hang Cong,Ying Huang,Zhu Tao,Carl Redshaw,Xin Xiao
Graphical A fluorescent probe based on supramolecular assembly between acridine orange (AO) and cucurbit[10]uril (Q[10]). Subsequent addition of dodine (DD) displaces AO from the Q[10] cavity, and results in a fluorescent output. Results revealed that the system is capable of the selective recognition of DD. The interaction between acridine orange (AO) and cucurbit[10]uril, Q[10] affords the ternary complex 2AO@Q[10]. Subsequent addition of dodine (DD) displaces AO from the Q[10] cavity, and results in a fluorescent output. The effect of 20 different pesticides, as well as a number of common interferents, on the fluorescent output is presented. Results revealed that the system is capable of the selective recognition of DD, with a limit of detection (LOD) for DD of 1.12×10 −7 M.
研究领域:
分析化学
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环境科学
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生物化学
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DOI
高影响因子
ANALYTICAL CHEMISTRY
·
2015
·
IF 5.636
Xiaodong Bi,Daojin Li,Zhen Liu
Lectin array is an important tool in the fields of carbohydrate chemistry, glycobiology, and glycomics. Because natural lectins are associated with some apparent disadvantages such as tedious purification and easy loss of activity, artificial materials are applied to overcome such shortages by mimicking and replacing lectins in an artificial lectin array, among which boronate affinity-based materials are very outstanding and widely used. However, complicated synthetic works are often involved to design and create boronate affinity-based lectin-mimics. In this work, a facile and novel method was proposed to establish a virtual lectin array based on boronate affinity-based pH-featured encoding for discrimination of monosaccharides by pattern recognition. The dependence of boronate affinity on environmental pH was selected to encode each monosaccharide for feature generation, and the pH-featured encoding was used to construct the virtual lectin array. On the basis of the virtual array, pattern recognition algorithms were applied for data analysis. Monosaccharides were discriminated by principal component analysis, and the relations in the virtual lectin array were unraveled by cluster analysis. In this proof-of-concept work, without complicated synthesis or preparation, the proposed method was successful in mimicking lectin array and discriminating nine elementary monosaccharides found in nature, and it was also a new way of encoding in expanding the applications of boronate affinity-based materials and methods in the field of biomimetics.
研究领域:
糖化学
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生物信息学
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仿生学
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产品关联
DOI
PubMed
高影响因子
Nature Communications
·
2022
·Vol. 13
·期 1
·1-14
·
IF 17.694
Arabi Maryam,Ostovan Abbas,Wang Yunqing,Mei Rongchao,Fu Longwen,Li Jinhua,Wang Xiaoyan,Chen Lingxin
Chiral discrimination is critical in environmental and life sciences. However, an ideal chiral discrimination strategy has not yet been developed because of the inevitable nonspecific binding entity of wrong enantiomers or insufficient intrinsic optical activities of chiral molecules. Here, we propose an “inspector” recognition mechanism (IRM), which is implemented on a chiral imprinted polydopamine (PDA) layer coated on surface-enhanced Raman scattering (SERS) tag layer. The IRM works based on the permeability change of the imprinted PDA after the chiral recognition and scrutiny of the permeability by an inspector molecule. Good enantiomer can specifically recognize and fully fill the chiral imprinted cavities, whereas the wrong cannot. Then a linear shape aminothiol molecule, as an inspector of the recognition status is introduced, which can only percolate through the vacant and nonspecifically occupied cavities, inducing the SERS signal to decrease. Accordingly, chirality information exclusively stems from good enantiomer specific binding, while nonspecific recognition of wrong enantiomer is curbed. The IRM benefits from sensitivity and versatility, enabling absolute discrimination of a wide variety of chiral molecules regardless of size, functional groups, polarities, optical activities, Raman scattering, and the number of chiral centers.
研究领域:
环境科学
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生命科学
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分析化学
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材料科学
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产品关联
DOI
PubMed
高影响因子
ANALYTICA CHIMICA ACTA
·
2018
·
IF 5.123
Xiaoping Tan,Genfu Zhao,Xu Zhou,Taohong Li,Hong Lei,Guanben Du,Long Yang
The rational design of electrochemical methods for isomer recognition is a focus of research in the molecular recognition and separation fields. In this work, a novel, rapid, and convenient electrochemical approach for recognition of nitrophenol isomers was constructed based on the alternating layer-by-layer (LbL) assembly of water-soluble cationic and anionic pillar [5]arene on a carboxylic graphene (C-Gra) modified glass carbon electrode. The electrochemical recognition of nitrophenol isomers was investigated by differential pulse voltammetry (DPV). The electrochemical results reveal that both the peak currents of m -nitrophenol ( m -NP) and p -nitrophenol ( p -NP) increased with the increasing of the layer number of the assembled pillar [5]arene, whereas the peak current of o -nitrophenol ( o -NP) decreased with the increased layers, which demonstrated an efficient route for discriminating the nitrophenol isomers. The molecular recognition mechanism was studied by 1 H NMR spectra, which indicated that the m -NP and p -NP can be included in the cavity of the pillar [5]arene host. However, the o -NP could not enter into the host of pillar [5]arene, which was ascribed to the formation of intramolecular hydrogen bond of o -NP. The LbL assembly modified GCE was used for detecting p -NP and m -NP. A low detection limit of 0.33 μM (S/N = 3) and a linear response range of 1–90 μM for p -NP were obtained by using this method. And the detection limit of 0.16 μM (S/N = 3) and a linear response range of 0.5–70 μM for m -NP were obtained. This method of LbL assembly modified GCE has potential application in molecular recognition and separation.
研究领域:
分析化学
·
分子识别与分离
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DOI
高影响因子
Frontiers in Psychology
·
2023
·
IF 3.8
Hao Zhang,Mingyao Wang,Meiyu Qian,Hongquan Wei
Aims This study aimed to design the Chinese Modified Olfactory Identification (CMOI) test based on the Sniffin' Sticks Olfactory Identification (SSOI) test by changing unfamiliar distractors and odors for more familiar ones for the Chinese population. Materials and methods We recruited 200 healthy volunteers (103 males and 97 females, aged 18–65 years, mean age 35.04 years, SD 10.96); in a survey, 100 volunteers rated their familiarity with 121 odors, including all the SSOI test odor descriptors and common odors in Chinese daily life. The SSOI test was modified according to the survey results. The other 100 volunteers were tested three times using the SSOI test, the Modified Distractors Olfactory Identification (MDOI) test established by modifying distractors in the SSOI test, and the CMOI test developed by using familiar unpleasant odors to displace the odors with low correct recognition rates in the MDOI test. We compared the test scores of the volunteers during the modification process. Results Volunteers were unfamiliar with 31 odor descriptors in the SSOI test; 23 distractors with low familiarity were displaced with more familiar distractors. The three odors with the lowest correct recognition rate in the MDOI test (apple, leather, and pineapple) were displaced with familiar unpleasant odors. The test scores were significantly higher in the CMOI test than in others ( p < 0.0001); the correct recognition rate in the CMOI test was significantly higher than in the SSOI test ( p < 0.01). Conclusion The test scores in the CMOI test were significantly improved; it prevented choosing wrongly due to unfamiliarity with an odor and its distractors.
研究领域:
医学
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神经科学
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产品关联
DOI
PubMed
高影响因子
ELECTROCHEMISTRY COMMUNICATIONS
·
2016
·
IF 4.569
Liping Bao,Yongxin Tao,Xiaogang Gu,Baozhu Yang,Linhong Deng,Yong Kong
A simple but highly enantioselective system based on potato starch (PS) modified electrode was developed for electrochemical recognition of tryptophan (Trp) isomers. Due to favorability of host–guest interactions between PS and D-Trp, PS preferably combined with D-Trp compared with L-Trp, resulting in larger amount of L-Trp penetrating through the left-handed double helices of PS to the electrode surface than D-Trp. And therefore, successful recognition of Trp isomers was achieved at the PS-based electrode. The PS-based chiral recognition was temperature dependent, which was attributed to the significant influence of temperature on the H-bonds between PS and the guest molecules. The recognition efficiency was remarkably decreased after hydroxypropyl groups were introduced to PS, and the decreased recognition efficiency at the hydroxypropyl PS (H-PS) might be due to the extra steric hindrance .
研究领域:
生物化学
·
分析化学
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产品关联
DOI
高影响因子
SENSORS AND ACTUATORS B-CHEMICAL
·
2017
·
IF 5.401
Zhenbo Wei,Yana Yang,Xize Xiao,Weilin Zhang,Jun Wang
In previous studies, conductive polymers (CPs)/noble metal nanoparticles (NMNPs) composite materials modified electrodes were always applied to distinguish the trace amounts of specific analytes in complex liquid mixtures. In this paper, polymer sulfanilic acid (PABSA)/AuNPs/glassy carbon electrode (GCE), polymer acid chrome blue K (PACBK)/AuNPs/GCE and polymer aspartic acid (PASP)/PtNPs/GCE were fabricated for the identification of the wine age of rice wines with pattern recognitions. The sensitivity of those modified electrodes was exhibited by cyclic voltammetry, and the parameters of electrochemical behaviors was optimized and confirmed gradually. The original responses were recorded by chronoamperometry with multi-frequency rectangle pulse voltammetry and multi-frequency staircase pulse voltammetry, and the feature data correlated with the wine age were extracted from original responses by ‘area method’. Based on the feature data, principal component analysis (PCA, unsupervised method), locality preserving projections (LPP, semi-supervised method) and differential financial analysis (DFA, supervised method) were applied for the classification of rice wine samples with different marked age, and DFA exhibited the most clear result; least squares support vector machines (LSSVM) and library for support vector machines (LIBSVM) were applied for the prediction of the wine ages, and LIBSVM worked better than LSSVM, the correlations based on the training and testing dataset were R 2 = 0.9999 and R 2 = 0.9998, respectively. In conclusion, the CPs/NMNPs/GCEs with pattern recognitions were powerful tools to identify the marked ages of rice wines.
研究领域:
分析化学
·
电化学
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DOI
高影响因子
RSC Advances
·
2018
·Vol. 8
·期 24
·13333-13343
·
IF 2.936
Zhenbo Wei,Yanan Yang,Luyi Zhu,Weilin Zhang,Jun Wang
In this paper, poly(acid chrome blue K) (PACBK)/AuNP/glassy carbon electrode (GCE), polysulfanilic acid (PABSA)/AuNP/GCE and polyglutamic acid (PGA)/CuNP/GCE were self-fabricated for the identification of rice wines of different brands. The physical and chemical characterization of the modified electrodes were obtained using scanning electron microscopy and cyclic voltammetry, respectively. The rice wine samples were detected by the modified electrodes based on multi-frequency large amplitude pulse voltammetry. Chronoamperometry was applied to record the response values, and the feature data correlating with wine brands were extracted from the original responses using the ‘area method’. Principal component analysis, locality preserving projections and linear discriminant analysis were applied for the classification of different wines, and all three methods presented similarly good results. Extreme learning machine (ELM), the library for support vector machines (LIB-SVM) and the backpropagation neural network (BPNN) were applied for predicting wine brands, and BPNN worked best for prediction based on the testing dataset (R2 = 0.9737 and MSE = 0.2673). The fabricated modified electrodes can therefore be applied to identify rice wines of different brands with pattern recognition methods, and the application also showed potential for the detection aspects of food quality analysis.
研究领域:
食品科学
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电化学
·
人工智能
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产品关联
DOI
PubMed
高影响因子
Journal of Materials Chemistry A
·
2023
·Vol. 11
·期 34
·18441-18453
·
IF 11.9
Junjun Huang,Wenqing Zhang,Xin Chen,Sanlong Wang,Zhenming Chen,Peng Li,Honglin Li,Chengmei Gui
Textile-based triboelectric nanogenerators (T-TENGs) have great potential in new-generation tactile sensors because their output signal is determined by the specific charge interaction between the target and triboelectric material. However, gesture recognition by existing T-TENG tactile sensors is very challenging because the electron affinity and polarity of the volunteer skin are similar. This study proposes a new structural sensor that integrates a Ni particle-encapsulated carbon tube (Ni@C tube) with polydimethylsiloxane (PDMS) by means of multiple strain mechanisms for improving recognition accuracy using a signal superposition technique. Interestingly, dynamic strain from multiple sources, i.e., PDMS layer strain (1.24–2.47 kPa), Ni@C tube crack (2.47–5.56 kPa), PDMS layer further strain (5.56–52.97 kPa), and Ni@C tube slip laterally (52.97–139.05 kPa), was established in the PDMS-coated Ni@C tube. In addition, the output signal of the as-fabricated T-TENG device was a combination of output signals from the PDMS/Ni@C tube and PDMS/contact object devices, which could fully reflect the stress field caused by the contact material pressing the surface and the surface characteristics, promoting the deep learning algorithm to be able to extract more hidden features of the identified materials. By integrating convolutional neural network (CNN) analysis based on the voltage signals of the T-TENG device, we explored a strategy that could enable the as-fabricated device to recognize 6 gestures with 99.3% recognition accuracy and 8 different materials with 99.8% recognition accuracy in the natural environment.
研究领域:
纳米技术
·
传感器技术
·
人工智能
·
材料科学
✓ 已验证
DOI
高影响因子
Nano Energy
·
2024
·
IF 16.8
Wenke Yang,Shun Liu,Ziqi Wang,Hu Liu,Caofeng Pan,Chuntai Liu,Changyu Shen
Machine-learning-assisted human activity and gesture recognition are valuable for human-computer interaction, and data acquisition often necessitates high-performance sensors. Here, inspired by spider web and bat wing airflow sensing system, polyimide fiber (PIF)/carbon black (CB) composite fiber aerogel (CFA) pressure sensor with biomimetic hair-Merkel cell sensitive unit was developed, exhibiting ultralow detection limit (2 Pa), high pressure sensitivity (S=23.1 kPa -1 ), wide linear detection capacity up to 67.61 kPa, and fast response/recovery time (140/100 ms). Thanks to the excellent mechanical property and environmental tolerance of CFA, it also possesses excellent low fatigue over >4000 cycles and good durability even at extreme high-temperature (200 °C) and underwater conditions. The superior signal data of the sensor, combined with the Convolutional Neural Network machine learning algorithm , achieves ultra-high prediction accuracies of 96.73% and 98.26% for human activity and gesture recognition, respectively. Additionally, CFA also has amazing thermal management properties, making it to be an ideal candidate for wearable electronics with excellent wearing comfort and safety.
研究领域:
材料科学
·
人工智能
·
生物医学工程
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产品关联
DOI
高影响因子
危险品化学品经营许可证（带存储）