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colorimetric sensor array for sensitive detection and identification of bacteria based on the etching of triangular silver nanoparticles regulated by Cl^- at various concentrations

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MICROCHIMICA ACTA 2025年第1期192卷 1-11页

作者： Liu, Shuang Yan, Peng Naveed, Shahzad Zhu, Yuheng Fu, Tao Wu, Ruijing Wu, Yayan Xi An Jiao Tong Univ Sch Life Sci & Technol Key Lab Biomed Informat Engn Minist Educ Xian 710049 Peoples R China Univ Hlth & Rehabil Sci Qingdao Cent Hosp Sch Hlth & Life Sci Qingdao 266113 Peoples R China

A colorimetric sensor array is proposed for ultrasensitive detection and identification of bacteria by using Cl- at various concentrations as sensing elements and triangular silver nanoparticles (T-AgNPs) as a single sensing nanoprobe. T-AgNPs are easily etched by Cl-. However, in the presence of bacteria, the etching process will be hindered. Different bacteria have differential protective effects on T-AgNPs due to their interactions, resulting in different etching degrees of T-AgNPs by Cl-, and visual color changes. By adjusting the antagonistic action between bacteria protection on T-AgNPs and the etching by using Cl- at various concentrations, different bacteria had their own color response patterns. Combined with linear discriminant analysis (LDA) and orthogonal partial least squares-discriminant analysis (OPLS-DA), the bacteria could be identified. The method was also used for bacteria mixtures identification and showed high sensitivity (OD600 = 1.0 x 10-6) for V. parahaemolyticus detection. Finally, the sensor array was successfully utilized in the identification of bacteria in pure and mineral bottled water. The method is low-cost, simple, sensitive, visual, and has potential application in point-of-care testing of bacteria.

关键词： colorimetric sensor array Bacteria identification Triangular silver nanoparticles Etching

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One-step patterned fabrication of a colorimetric sensor array for heavy metal ions detection

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CHEMICAL ENGINEERING JOURNAL 2025年 512卷

作者： Tang, Shengchang Sun, Cuimin Wei, Xiangfu Huang, Guangyong Dai, Peng Cai, Yongchao You, Hui Guangxi Univ Sch Mech Engn Nanning 530004 Peoples R China Guangxi Univ Sch Comp & Elect Informat Engn Nanning 530004 Peoples R China Guangxi Vocational & Techn Coll Commun Nanning Peoples R China Guangxi Univ Sci & Technol Sch Mech & Automot Engn Liuzhou 545006 Peoples R China

The colorimetric sensor array for heavy metal detection offers unique advantages over traditional colorimetric sensors in terms of detecting the number of heavy metal ions, detection efficiency, analyzing complex analytes, and reliability. However, the fabrication process is typically intricate and may rely on expensive droplet patterning apparatus, with the potential risk of leakage in the hydrophobic barrier. To mitigate these issues, we employed polyvinyl alcohol porous polymer as the substrate and performed hydrophobic treatment via a simple immersion method. Subsequently, a custom-designed array nozzle was used to fabricate patterned hydrophobic barriers and patterned sensing units in a single step. Differential map of the sensors before and after exposure to analytes were subjected to hierarchical clustering analysis and principal component analysis. The results demonstrated that the colorimetric sensor array, fabricated in a single step, was able to successfully identify 28 types of heavy metal ions at ppm levels within approximately two minutes, and it also exhibited semiquantitative capabilities for ion concentration determination. Additionally, we demonstrated the utilization of this sensor for the multiplexed detection and identification of similar multicomponent heavy metal ions and lowconcentration (1 ppm) analytes in actual water samples. The results indicated good recognition performance and reproducibility. Repeated experiments have manifested the feasible potential of the one-step fabricated colorimetric sensor array for applications such as on-site monitoring of heavy metal contamination in wastewater, as well as preliminary screening and tracking.

关键词： One-step fabrication Patterned hydrophobic barrier colorimetric sensor array Heavy metal ions Multivariate analysis

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Machine learning-enabled attapulgite/polyimide nanofiber composite aerogels-based colorimetric sensor array for real-time monitoring of balsa fish freshness

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FOOD CHEMISTRY 2025年第Pt 3期463卷 141382页

作者： Cao, Jiankun Chen, Yumo Su, Xinyang Wang, Zhiqiang Yan, Hongyuan Hebei Univ Coll Publ Hlth Hebei Key Lab Publ Hlth Safety Hebei Key Lab Analyt Sci & Technol Baoding 071002 Peoples R China Hebei Univ Coll Chem & Mat Sci State Key Lab New Pharmaceut Preparat & Excipients Key Lab Med Chem & Mol DiagMinist Educ Baoding 071002 Peoples R China

This paper presents the development and application of attapulgite/polyimide nanofiber composite aerogels (ATP/PI NFAs) integrated with a range of acid-base indicators, fabricated using electrospinning and freezedrying technologies. A detailed characterization of the ATP/PI NFAs revealed a 3D multi-level pore structure that enhanced the mass transfer of target gas molecules and their interaction with probe molecules. Utilizing machine learning approaches, we designed an ATP/PI NFAs-based colorimetric sensor array capable of real-time evaluation of balsa fish freshness. Color features sensitive to changes in freshness were selected using principal component analysis and random forest. Partial least squares regression and random forest regression models were established, achieving the prediction of total volatile basic nitrogen content in balsa fish. The system was validated using a national standard method to demonstrate its accuracy and practicality. The combination of advanced ATP/PI NFAs-based colorimetric sensor array with robust machine learning models paves the way for food safety monitoring.

关键词： Nanofiber aerogels colorimetric sensor array Machine learning Freshness

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Inhibition effect-involved colorimetric sensor array based on PtBi aerogel nanozymes for discrimination of antioxidants

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FOOD CHEMISTRY 2025年 478卷 143729页

作者： Yan, Dongbo Wang, Congxiao Jia, Xiangkun Chen, Chengjie Hu, Lijun Zhai, Yanling Strizhak, Peter E. Tang, Jianguo Jiao, Lei Zhu, Zhijun Qingdao Univ Inst Hybrid Mat Coll Mat Sci & Engn Qingdao 266071 Peoples R China Qingdao Univ Inst Mol Metrol Coll Chem & Chem Engn Qingdao 266071 Peoples R China Qingdao Univ Affiliated Hosp Dept Intervent Med Ctr Qingdao 266000 Peoples R China

Nanozymes, as superior alternatives to natural enzymes, frequently employ the inhibition effect in turn-off sensors for analyte detection. However, limited attention has been paid to the inhibition mechanisms between analytes and nanozymes, limiting advancements in nanozyme-based sensing. Benefiting from the synergistic effects between three-dimensional network structure of aerogel and ligand effect triggered electronic regulation, Pt100Bi2 aerogel nanozymes (Pt100Bi2 ANs) exhibit superior peroxidase-like activity (293.48 U/mg). We found that antioxidants are able to inhibit the peroxidase-like activity of Pt100Bi2 ANs. The inhibition type (gallic acid as model) is reversible mixed-inhibition with the inhibition constants (Ki and Ki') of 0.213 mM and 0.108 mM. The inhibition effect-involved colorimetric sensor arrays were developed to overcome the "lock-key" limitation of traditional sensors, enabling distinguish five antioxidants via principal component analysis, with detection limit below 2 mu M. This work provides new perspective on the inhibition mechanisms of nanozymes and optimization strategies for high-performance nanozyme-based sensors.

关键词： Aerogel nanozymes Peroxidase-like activity Antioxidants Reversible mixed-inhibition colorimetric sensor array

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Antioxidants Recognition colorimetric sensor array Based on Multicolor System

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APPLIED ORGANOMETALLIC CHEMISTRY 2025年第3期39卷

作者： Huang, Wei Wen, Hongkuan Li, Yao Wang, Wenhua Long, Dengying Sichuan Univ Sci & Engn Coll Chem Engn Natl Circular Econ Engn Lab Zigong Peoples R China Sichuan Univ Sci & Engn Innovat Ctr Chenguang High Performance Fluorine Ma Zigong Peoples R China Sichuan Univ Sci & Engn Key Labs Fine Chem & Surfactants Sichuan Prov Univ Zigong Peoples R China

A colorimetric sensor array with three identification signals has been developed to visually recognize five antioxidants based on CuFe Prussian blue analogs nanocubes (CuFe PBA NCs) and 3,3 ',5,5 '-tetramethylbenzidine (TMB). The CuFe PBA NCs can oxidize TMB to produce three ultraviolet-visible (UV-Vis) absorption peaks at different wavelengths (370, 450, and 650 nm). Depending on the different reduction capacity of dopamine, cysteine, ascorbic acid, glutathione, and melatonin, the redox process can be inhibited to varying degrees, resulting in different changes in the signal generation of three identification elements. And in the presence of different antioxidants, the color of the solution also changes in different degrees. Five antioxidants (20 mu M) can be identified by this colorimetric sensor array, and the identification accuracy was 100% for 40 unknown antioxidants. In addition, these antioxidants can also be quantified based on the regression equation between the concentration of the antioxidants and the absorbance change. The correlation coefficient is greater than 0.990, and the detection limit is less than 3.5 mu M.

关键词： antioxidants colorimetric sensor array CuFe PBA NCs visualization

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Real-Time Monitoring and Rapid Determination of Pork Freshness Using a colorimetric sensor array Based on Porphyrin and pH Indicator Ligand Combination

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JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2025年第18期73卷 11327-11339页

作者： Huang, Baochen Zhang, Kexin Kwadzokpui, Bridget Ama Han, En Guan, Binbin Lin, Hao Jiangsu Univ Sch Food & Biol Engn Zhenjiang 212013 Peoples R China Nantong Food & Drug Supervis & Inspect Ctr Nantong 226400 Peoples R China

This study presents the development of a colorimetric sensor array (CSA) that combines pH indicators with porphyrin solutions to create a sensitive and stable sensor for monitoring pork freshness. Four pH indicators-bromophenol blue, bromocresol green, bromocresol violet, and chlorophenol red-were chosen for their ability to detect volatile gases produced during pork spoilage. Color changes were quantified by extracting grayscale values, and various porphyrins, including TPPNi, TPPMnCl, and TPPCu, were screened for their interactions with the pH indicators. Principal component analysis was used to determine the optimal concentration of the porphyrin solution. The CSA was then constructed by combining the four pH indicators with the selected porphyrins, resulting in an average stability improvement of 21.94%, 23.59%, 28.84%, and 23.31%, respectively. The occurrence of coordination is verified by Fourier transform infrared (FTIR), and theoretical calculations are applied to explain the possible reasons for the increased stability. The CSA was tested on pork samples stored for different periods, and a partial least squares regression model was built using grayscale data to predict freshness. Furthermore, storage experiments were conducted to evaluate the CSA's stability over 3, 7, and 15 days, and the retention of color in CSA was 99.02%, 99.01%, and 98.84%, respectively. The models achieved 98.89% average accuracy (n = 30 samples) in predicting the freshness grades of pork samples from different batches and in assessing the stability of the CSA, demonstrating its potential as a reliable tool for rapid and accurate pork freshness discrimination.

关键词： pork colorimetric sensor array stability rapid determination of freshness grade

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Development of a colorimetric sensor array with weighted RGB strategy for quality differentiation of Anji white tea

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JOURNAL OF FOOD ENGINEERING 2025年 391卷

作者： Xu, Qilin Yin, Xianggang Huo, Xinyi Zhao, Xiaohan Wu, Linlin Zhou, Yifeng Huang, Jun Zhejiang Univ Sci & Technol Sch Biol & Chem Engn Hangzhou 310023 Peoples R China

This study presents the development of an innovative colorimetric sensor array system designed to differentiate the quality of Anji white tea by detecting and analyzing its aromatic components. The colorimetric sensor array utilizes chemically reactive dyes that selectively respond to specific aromatic compounds, effectively capturing aroma variations across different grades of tea. Under optimized experimental conditions, response data from the colorimetric sensor array for various tea samples were collected and processed using a weighted RGB strategy, which assigns values of 30%, 59%, and 11% to the red, green, and blue channels, respectively, to better replicate human visual perception. Tea grade classification was performed using principal component analysis and orthogonal partial least squares discriminant analysis. Comparative analysis of the performance of the four supervised learning models demonstrated that the weighted RGB method was more accurate, with the Extreme Learning Machine achieving an impressive classification accuracy of 96.30%. This novel method provides a rapid, efficient, and user-friendly tool for tea quality assessment, with significant implications for the food engineering industry.

关键词： Anji white tea Aroma colorimetric sensor array Weighted RGB Multivariate data analysis

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Carboxymethyl cellulose-based colorimetric sensor array incorporating ionic liquid-tuned anthocyanin and nano-silica coating for pork freshness monitoring

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FOOD HYDROCOLLOIDS 2025年 158卷

作者： Zhao, Yali El-Sherif, Dina M. Cheng, Jun Zhang, Huan Hu, Zhenyang Wu, Qin Shen, Hui Yu, Zhilong Xie, Yunfei Jiangnan Univ State Key Lab Food Sci & Technol 1800 Lihu Ave Wuxi 214122 Jiangsu Peoples R China Jiangnan Univ Sch Food Sci & Technol 1800 Lihu Ave Wuxi 214122 Jiangsu Peoples R China Jiangnan Univ Sch Artificial Intelligence & Comp Sci 1800 Lihu Ave Wuxi 214122 Jiangsu Peoples R China Natl Inst Oceanog & Fisheries NIOF Cairo 11516 Egypt

The development of a real-time monitoring system for meat freshness is crucial for ensuring food safety and enhancing the efficiency of the food supply chain. Herein, this study constructed a carboxymethyl cellulose-based colorimetric nanosensor array incorporating ionic liquid-tuned anthocyanins, a porous metal-organic framework particle (UiO-66), and nano-silica coating for real-time monitoring of pork freshness. Density functional theory calculations and multiple spectral analysis confirmed the mechanism by which ionic liquids tuned the anthocyanin color gamut. The sensor array's mechanical properties, thermal stability and sensitivity were significantly improved through the incorporation of UiO-66. The hydrophobic coating of the sensor array greatly enhanced the water contact angle rising from 76.5 degrees to 134.8 degrees, rendering excellent stability in high humidity conditions. The sensor array demonstrated good responsiveness and the durability up to 11 cycles to 5 common amine gases produced by meat spoilage. Additionally, the sensor array was integrated with 4 deep convolutional neural network models to predict pork freshness, all achieving accuracy rates above 97%. Notably, the VGG16 model achieved an accuracy rate of 99.16%. The designed monitoring system demonstrates significant potential for practical applications in intelligent meat packaging.

关键词： Anthocyanin Ionic liquid Hydrophobic nanocoating colorimetric sensor array Deep convolutional neural network Meat freshness

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Single-well colorimetric sensor array for discrimination and smartphone-assisted detection of catecholamines based on Fe-carbon dots nanozymes

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ANALYTICA CHIMICA ACTA 2025年 1355卷

作者： Bao, Guang-Ming Chen, Dan-Dan Xia, Yi-Fan Cai, Zhi-Qiang Cui, Shun-Qiang Wei, Xia Dou, Zhen-Chong Yuan, Yuan Sandra, Akimana Yuan, Hou-Qun Hubei Univ Technol Natl Ctr Cellular Regulat & Mol Pharmaceut 111 Sch Life & Hlth Sci Key Lab Fermentat EngnMinist EngnHubei Key Lab I Wuhan 430068 Peoples R China

Background: Catecholamines (CAs), such as noradrenaline (NE), adrenaline (AD), and dopamine (DA), are essential signaling mediators that regulate various physiological functions. Monitoring their levels is crucial for studying and diagnosing diseases, as abnormal concentrations are associated with numerous health conditions. However, distinguishing between these CAs is challenging due to their highly similar molecular structures. Results: In this study, Fe-doped carbon dot-based nanozymes (Fe-CDs) with strong peroxidase-like activity were synthesized using a simple one-pot method. Fe-CDs-based sensing systems exhibit excellent stability, reproducibility, sensitivity (with detection limits of 26.6 nM for NE, 46.0 nM for AD, and 33.3 nM for DA), and antiinterference properties. A triple-channel single-well colorimetric sensor array was developed by collecting the absorbance at 20, 40, and 60 min as sensing units, enabling the effective differentiation and identification of various CAs. Significance: The Fe-CDs-based system has proven capable of detecting CAs in real human urine and fetal bovine serum. Additionally, the Fe-CDs-based smartphone-assisted platform provides efficient, highly sensitive, and onsite CAs detection, making it highly promising for biomedical and diagnostic applications.

关键词： Catecholamines Smartphone-assisted detection colorimetric sensor array

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Integrated colorimetric sensor array with outlier detection and feature selection to detect adulterated camellia oil

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MICROCHEMICAL JOURNAL 2025年 209卷

作者： Li, Dapeng Jiang, Ke Yang, Gan Gong, Zhongliang Wen, Tao Cent South Univ Forestry & Technol Coll Mech & Intelligent Mfg Changsha 410004 Hunan Peoples R China

colorimetric sensor arrays (CSA) offer a promising method for distinguishing complex chemical compositions using color-sensitive dyes with cross-reactivity. However, the extensive data provided by the CSA poses challenges for data analysis, requiring advanced methods to enhance data quality. This study explores the potential of machine learning (ML) combined with outlier detection and feature selection algorithms to address these challenges, resulting in improving the detection of adulterated camellia oil. We employed two outlier detection algorithms, Empirical Cumulative Distribution -based Outlier Detection (ECOD) and Z score analysis, and two feature selection algorithms, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), to identify the most effective combination for enhancing data quality. Using CSA data from oil samples that included genuine camellia oil and the adulterated counterparts, we evaluated the classification performance of a multilayer perceptron (MLP) model integrated with the outlier detection and feature selection algorithms. The results showed that the combination of ECOD-PSO-MLP achieved superior results with an Accuracy of 90.613 % f 0.214 %, Average Precision of 91.141 % f 0.205 %, Average Recall of 90.613 % f 0.214 %, and Average F1 score of 90.741 % f 0.213 %, outperforming other combinations in distinguishing adulterated camellia oil. The study further conducted a comparative analysis of the features associated with the outlier detection and feature selection processes, respectively. This examination provided insights into the potential contributions of these features towards enhancing data quality. Consequently, the innovative strategies proposed in this study yield a substantial enhancement in data quality, thereby facilitating the effective identification of adulterated camellia oil using ML techniques.

关键词： Camellia oil colorimetric sensor array Outlier detection Feature selection Machine learning

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