Pub Date : 2025-04-11DOI: 10.1021/acssensors.4c03250
Parisa Dehghani, Mostafa Salehirozveh, Ataollah Tajabadi, Chi Chung Yeung, Michael Lam, Hing Y. Leung, Vellaisamy A. L. Roy
Prostate cancer (PCa), the second most common cancer in men, demands effective early detection strategies. Elevated spermine levels in the prostate tissue contrast with decreased urinary concentrations in PCa patients. Here, we present a novel sensing platform combining differential pulse voltammetry and an extended gate field-effect transistor (EGFET) with a molecularly imprinted polymer|molecular imprinting (MIP) nanofilm for selective and sensitive spermine detection. Key advancements include successfully constructing and characterizing a pseudoreference electrode and a precisely engineered analyte binding interface. The Ag/AgCl pseudoreference electrode exhibited high reliability and reproducibility, optimized to enhance conductivity and minimize interference noises. Electrochemical analysis confirmed successful MIP modification, creating a precise 3D-imprinted binding interface. The platform accurately quantified spermine in artificial urine across concentrations from 0.1 to 1000 ng/mL, achieving a detection limit of 1.23 ng/mL. High selectivity was demonstrated against competing polyamines such as spermidine and histamine. Analysis of electrical properties indicated that spermine binding induced changes in surface potential, altering the metal-oxide-semiconductor field-effect transistor threshold voltage and validating the system’s sensitivity. The system’s superior performance was confirmed with a high imprinting factor (IF ≈ 4.1) and sensitivity 10 times higher compared to nonimprinted polymers. Hill–Langmuir analysis confirmed a strong binding affinity to spermine. Clinical validation using human urine samples from PCa diagnostic evaluations demonstrated high consistency with liquid chromatography mass spectrometry, exhibiting an excellent linear correlation (R2 = 0.97) without statistically significant differences (p-value <0.0001). This study introduces a robust, miniaturized, and cost-effective EGFET-based sensor for spermine detection, offering substantial potential for clinical diagnostics and PCa biomarker monitoring.
{"title":"Next-Gen Point-of-Care Tool for Ultra-Sensitive Detection of Urinary Spermine for Prostate Cancer Diagnosis","authors":"Parisa Dehghani, Mostafa Salehirozveh, Ataollah Tajabadi, Chi Chung Yeung, Michael Lam, Hing Y. Leung, Vellaisamy A. L. Roy","doi":"10.1021/acssensors.4c03250","DOIUrl":"https://doi.org/10.1021/acssensors.4c03250","url":null,"abstract":"Prostate cancer (PCa), the second most common cancer in men, demands effective early detection strategies. Elevated spermine levels in the prostate tissue contrast with decreased urinary concentrations in PCa patients. Here, we present a novel sensing platform combining differential pulse voltammetry and an extended gate field-effect transistor (EGFET) with a molecularly imprinted polymer|molecular imprinting (MIP) nanofilm for selective and sensitive spermine detection. Key advancements include successfully constructing and characterizing a pseudoreference electrode and a precisely engineered analyte binding interface. The Ag/AgCl pseudoreference electrode exhibited high reliability and reproducibility, optimized to enhance conductivity and minimize interference noises. Electrochemical analysis confirmed successful MIP modification, creating a precise 3D-imprinted binding interface. The platform accurately quantified spermine in artificial urine across concentrations from 0.1 to 1000 ng/mL, achieving a detection limit of 1.23 ng/mL. High selectivity was demonstrated against competing polyamines such as spermidine and histamine. Analysis of electrical properties indicated that spermine binding induced changes in surface potential, altering the metal-oxide-semiconductor field-effect transistor threshold voltage and validating the system’s sensitivity. The system’s superior performance was confirmed with a high imprinting factor (IF ≈ 4.1) and sensitivity 10 times higher compared to nonimprinted polymers. Hill–Langmuir analysis confirmed a strong binding affinity to spermine. Clinical validation using human urine samples from PCa diagnostic evaluations demonstrated high consistency with liquid chromatography mass spectrometry, exhibiting an excellent linear correlation (<i>R</i><sup>2</sup> = 0.97) without statistically significant differences (<i>p</i>-value <0.0001). This study introduces a robust, miniaturized, and cost-effective EGFET-based sensor for spermine detection, offering substantial potential for clinical diagnostics and PCa biomarker monitoring.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"4 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143819853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Noninvasive detection sensors for comfort and moisture absorption are popular for personalized health monitoring, yet integrated sensors that enable the on-demand detection of both physical and chemical indexes remain significantly challenging. Herein, we report a multifunctional fiber-based flexible sensing yarn for improved electrochemical and resistance sensing performance for in situ sweat activating and monitoring of body motion as well as the distinct color variation derived from the pH of sweat. The core–shell structure of the composite yarn (TSY) consists of a core layer of direct wet-spun twisted polyurethane fibers mixed with carbon black and a hydrophilic fiber layer of conductive zinc wires and colored lyocell fiber through the braiding method. The internal confined space between the core–shell layers can induce ion enrichment in sweat, enhancing the electrochemical sensing ability in capturing 0.5 μL of sweat, while the space-separated design can further isolate the interference so that pH and motion can be analyzed. Additionally, the colored hydrophilic lyocell fiber can transmit visual signals by the variance of color derived from the characterization of natural dyes in the process of adsorption of sweat. The designed TSY represents a promising integrated system capable of real-time monitoring of the chemical composition of sweat and the exercise conditions of movement.
{"title":"Flexible and Stretchable Electrochemical Sensor Merging the Multifunction of Monitoring Movement and Rapid Visual Signal Transmission","authors":"Sijie Zhou, Wanjin Hu, Xiaofeng Wang, Mengyao Cai, Xinjie Wei, Jieyao Qin, Xuelin Wang, Zhuan Fu, Junyao Gong, Chunhua Zhang, Weilin Xu, Liangjun Xia","doi":"10.1021/acssensors.4c03709","DOIUrl":"https://doi.org/10.1021/acssensors.4c03709","url":null,"abstract":"Noninvasive detection sensors for comfort and moisture absorption are popular for personalized health monitoring, yet integrated sensors that enable the on-demand detection of both physical and chemical indexes remain significantly challenging. Herein, we report a multifunctional fiber-based flexible sensing yarn for improved electrochemical and resistance sensing performance for in situ sweat activating and monitoring of body motion as well as the distinct color variation derived from the pH of sweat. The core–shell structure of the composite yarn (TSY) consists of a core layer of direct wet-spun twisted polyurethane fibers mixed with carbon black and a hydrophilic fiber layer of conductive zinc wires and colored lyocell fiber through the braiding method. The internal confined space between the core–shell layers can induce ion enrichment in sweat, enhancing the electrochemical sensing ability in capturing 0.5 μL of sweat, while the space-separated design can further isolate the interference so that pH and motion can be analyzed. Additionally, the colored hydrophilic lyocell fiber can transmit visual signals by the variance of color derived from the characterization of natural dyes in the process of adsorption of sweat. The designed TSY represents a promising integrated system capable of real-time monitoring of the chemical composition of sweat and the exercise conditions of movement.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"60 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143822805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-11DOI: 10.1021/acssensors.5c00198
Fei Yang, Xiuzhu Huo, Xiaoyu Fu, Xiaoyu Wang, Ye Liu, Zisheng Guo, Jiao Chen, Mengyao She, Jianli Li
Hard-healing wounds are a serious issue faced by diabetic patients, and the cellular autophagy level is closely related to the wound healing progress. However, it is difficult to monitor the real-time autophagy levels in living organisms. In this work, we provided a new autophagy fluorescent sensor IN-NH2 based on the modification of 2-substituted quinoline, giving an excellent ability to quantify the pH fluctuation in lysosomes during autophagy. This sensor was successfully applied in the real-time monitoring of autophagy levels in a wound healing model of diabetic rats, showing potential for exploring the internal mechanism between autophagy and disease progression.
{"title":"Ratiometric Fluorescent Sensors for Real-Time Monitoring Cellular Autophagy Levels during Diabetic Wound Healing","authors":"Fei Yang, Xiuzhu Huo, Xiaoyu Fu, Xiaoyu Wang, Ye Liu, Zisheng Guo, Jiao Chen, Mengyao She, Jianli Li","doi":"10.1021/acssensors.5c00198","DOIUrl":"https://doi.org/10.1021/acssensors.5c00198","url":null,"abstract":"Hard-healing wounds are a serious issue faced by diabetic patients, and the cellular autophagy level is closely related to the wound healing progress. However, it is difficult to monitor the real-time autophagy levels in living organisms. In this work, we provided a new autophagy fluorescent sensor <b>IN-NH</b><sub><b>2</b></sub> based on the modification of 2-substituted quinoline, giving an excellent ability to quantify the pH fluctuation in lysosomes during autophagy. This sensor was successfully applied in the real-time monitoring of autophagy levels in a wound healing model of diabetic rats, showing potential for exploring the internal mechanism between autophagy and disease progression.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"78 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143822806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Flexible flexion sensors are attracting attention due to their wide range of applications. It is urgent to develop a flexible sensor matrix to detect strain distribution on curved surfaces for object surface posture reconstruction, fault detection, and predictive maintenance. Herein, a convenient and universal method for preparing a flexible flexion sensor matrix is proposed using a versatile screen-printing technique. Compared to traditional thin film configurations, this process improved the sensitivity by introducing multiple interfaces and can be used for the fabrication of large-area flexion sensor matrix with high stability and consistency. The prepared flexible flexion sensors performed with a low detection limit (0.07%), a remarkable gauge factor (>50), and high stability (no apparent decay after 2000 bending–releasing cycles). We also demonstrated their applications in monitoring human body movement and gesture recognition. The sensors were integrated into a data glove for real-time robotic arm control, and achieved an accuracy rate of over 96% in recognizing various gestures with a neural network model. A large area flexible flexion sensor matrix (8 × 8) was fabricated by full-printing technique and enables simultaneous monitoring of multiposition bending states, which has significant potential in real-time tracking the strain distribution in bendable and curved surfaces.
{"title":"Large Area and Flexible Flexion Sensing Matrix for Detection of Strain Distribution in Bendable and Curved Surface","authors":"Huihui Ma, Weiwei Li, Qixuan Zhu, Yunqiang Cao, Manzhang Xu, Yuxuan Xu, Siying Dang, Zihao Xu, Gaojie Chen, Lu Zheng, Xuewen Wang, Wei Huang","doi":"10.1021/acssensors.5c00153","DOIUrl":"https://doi.org/10.1021/acssensors.5c00153","url":null,"abstract":"Flexible flexion sensors are attracting attention due to their wide range of applications. It is urgent to develop a flexible sensor matrix to detect strain distribution on curved surfaces for object surface posture reconstruction, fault detection, and predictive maintenance. Herein, a convenient and universal method for preparing a flexible flexion sensor matrix is proposed using a versatile screen-printing technique. Compared to traditional thin film configurations, this process improved the sensitivity by introducing multiple interfaces and can be used for the fabrication of large-area flexion sensor matrix with high stability and consistency. The prepared flexible flexion sensors performed with a low detection limit (0.07%), a remarkable gauge factor (>50), and high stability (no apparent decay after 2000 bending–releasing cycles). We also demonstrated their applications in monitoring human body movement and gesture recognition. The sensors were integrated into a data glove for real-time robotic arm control, and achieved an accuracy rate of over 96% in recognizing various gestures with a neural network model. A large area flexible flexion sensor matrix (8 × 8) was fabricated by full-printing technique and enables simultaneous monitoring of multiposition bending states, which has significant potential in real-time tracking the strain distribution in bendable and curved surfaces.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"34 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143819851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-09DOI: 10.1021/acssensors.4c03517
Meleskow Cox, Jaymi January, Kefilwe Vanessa Mokwebo, Sodiq T. Yussuf, Nelia Abraham Sanga, Zandile Dennis Leve, Samantha Fiona Douman, Emmanuel Iheanyichukwu Iwuoha
Tuberculosis (TB) is a highly contagious bacterial infection that remains a leading cause of death and persistent threat to global health. The spread of TB is exacerbated by the major limitations of conventional diagnostic approaches, such as complex technicalities, high cost, and low sensitivity. To address these challenges, recent research has focused on using electrochemiluminescence (ECL) as an alternative detection strategy coupled to biosensors. ECL biosensors leverage electrochemically generated chemiluminescence, converting electrical energy to light, as a novel transduction mechanism for TB biosensors. This unique approach offers several advantages, namely, wide linear dynamic ranges, improved device sensitivities, and prompt response times for sensitive early detection. This Review offers a comprehensive overview of advancements in ECL biosensor configurations, including detection and amplification strategies, substrates, and the development of luminophores and coreactants tailored for TB biomarker detection. The focus is on ECL biosensor designs, including biorecognition elements like immunosensors, DNA sensors, and aptasensors, along with various immobilization strategies tailored to target specific TB biomarkers. A comprehensive discussion spans biomarker detection trends over the past decade, clinical relevance, sensitivity thresholds, and detection limits. Furthermore, widely recognized TB biomarkers commonly detected in commercial diagnostic tests are discussed alongside novel markers that, while not exclusive to TB, have demonstrated clinical importance. This Review aims to highlight the potential of ECL-based biosensors as an effective means to advance an early, reliable, and accessible TB detection approach.
{"title":"Advances on Electrochemiluminescent Biosensors for TB Biomarkers","authors":"Meleskow Cox, Jaymi January, Kefilwe Vanessa Mokwebo, Sodiq T. Yussuf, Nelia Abraham Sanga, Zandile Dennis Leve, Samantha Fiona Douman, Emmanuel Iheanyichukwu Iwuoha","doi":"10.1021/acssensors.4c03517","DOIUrl":"https://doi.org/10.1021/acssensors.4c03517","url":null,"abstract":"Tuberculosis (TB) is a highly contagious bacterial infection that remains a leading cause of death and persistent threat to global health. The spread of TB is exacerbated by the major limitations of conventional diagnostic approaches, such as complex technicalities, high cost, and low sensitivity. To address these challenges, recent research has focused on using electrochemiluminescence (ECL) as an alternative detection strategy coupled to biosensors. ECL biosensors leverage electrochemically generated chemiluminescence, converting electrical energy to light, as a novel transduction mechanism for TB biosensors. This unique approach offers several advantages, namely, wide linear dynamic ranges, improved device sensitivities, and prompt response times for sensitive early detection. This Review offers a comprehensive overview of advancements in ECL biosensor configurations, including detection and amplification strategies, substrates, and the development of luminophores and coreactants tailored for TB biomarker detection. The focus is on ECL biosensor designs, including biorecognition elements like immunosensors, DNA sensors, and aptasensors, along with various immobilization strategies tailored to target specific TB biomarkers. A comprehensive discussion spans biomarker detection trends over the past decade, clinical relevance, sensitivity thresholds, and detection limits. Furthermore, widely recognized TB biomarkers commonly detected in commercial diagnostic tests are discussed alongside novel markers that, while not exclusive to TB, have demonstrated clinical importance. This Review aims to highlight the potential of ECL-based biosensors as an effective means to advance an early, reliable, and accessible TB detection approach.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"2 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143806140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Capturing the electrooculography (EOG) signals is very attractive for assistive devices and user interfaces for virtual reality (VR) systems. However, the current EOG acquisition systems face challenges in ensuring user comfort, particularly in terms of electrode electrical and mechanical performance, long-term usability, thermal effects, and overall system portability. This study presents polymeric dry flexible electrodes, composed of a composite of poly(3,4-ethylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS), poly(vinyl alcohol) (PVA), Gallic acid (GA), and D-sorbitol, forming a dynamic cross-linked network that ensures strong adhesion, stretchability, and electrical stability. These electrodes maintain their performance for up to 72 h, and can be restored through heat reactivation if performance degrades after prolonged storage. This electrode exhibits excellent biocompatibility, causing no skin irritation or thermal effects with continuous use. We have also developed a flexible circuit for real-time signal processing and wireless transmission, which operates in coordination with the EOG electrodes. The system employs a convolutional neural network (CNN) to achieve a 97.1% accuracy in classifying various eye movement patterns. The system enables contactless control of digital interfaces through simple eye movements, offering a solution for long-term, comfortable, and high-fidelity EOG-based human-machine interfaces, particularly for VR integration and assistive technologies for individuals with disabilities.
{"title":"Highly Stable Polymeric Electrooculography Electrodes for Contactless Human-Machine Interactions","authors":"Xingge Yu, Zebang Luo, Xilin Ouyang, Wenqiang Wang, Yuxuan Rao, Yulong Yuan, Zhenpeng Cai, Youfan Hu, Li Xiang","doi":"10.1021/acssensors.5c00031","DOIUrl":"https://doi.org/10.1021/acssensors.5c00031","url":null,"abstract":"Capturing the electrooculography (EOG) signals is very attractive for assistive devices and user interfaces for virtual reality (VR) systems. However, the current EOG acquisition systems face challenges in ensuring user comfort, particularly in terms of electrode electrical and mechanical performance, long-term usability, thermal effects, and overall system portability. This study presents polymeric dry flexible electrodes, composed of a composite of poly(3,4-ethylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS), poly(vinyl alcohol) (PVA), Gallic acid (GA), and D-sorbitol, forming a dynamic cross-linked network that ensures strong adhesion, stretchability, and electrical stability. These electrodes maintain their performance for up to 72 h, and can be restored through heat reactivation if performance degrades after prolonged storage. This electrode exhibits excellent biocompatibility, causing no skin irritation or thermal effects with continuous use. We have also developed a flexible circuit for real-time signal processing and wireless transmission, which operates in coordination with the EOG electrodes. The system employs a convolutional neural network (CNN) to achieve a 97.1% accuracy in classifying various eye movement patterns. The system enables contactless control of digital interfaces through simple eye movements, offering a solution for long-term, comfortable, and high-fidelity EOG-based human-machine interfaces, particularly for VR integration and assistive technologies for individuals with disabilities.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"39 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143814042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nanomaterials-integrated CRISPR/Cas systems have rapidly emerged as powerful next-generation platforms for optical biosensing. These integrated platforms harness the precision of CRISPR/Cas-mediated nucleic acid detection while leveraging the unique properties of nanomaterials to achieve enhanced sensitivity and expanded analytical capabilities, thereby broadening their diagnostic potential. By incorporating a diverse range of nanomaterials, these systems effectively expand the analytical toolbox for optical detection, offering adaptable solutions tailored to various diagnostic challenges. This review provides a comprehensive overview of the nanomaterials successfully integrated into CRISPR/Cas-based optical sensing systems. It examines multiple optical detection modalities, including fluorescence, electrochemiluminescence, colorimetry, and surface-enhanced Raman spectroscopy, highlighting how nanomaterials facilitate signal amplification, enable multiplexing, and support the development of point-of-care applications. Additionally, practical applications of these integrated systems in critical fields such as healthcare diagnostics and environmental monitoring are showcased. While these platforms offer considerable advantages, several real-world challenges such as the complexity of assay workflows, environmental impact of nanomaterials, cost, and regulatory hurdles must be addressed before widespread implementation can be achieved. By identifying these critical obstacles and proposing strategic solutions, we aim to pave the way for the continued advancement and adoption of nanomaterial-integrated CRISPR/Cas optical biosensing technologies.
{"title":"Nanomaterials-Integrated CRISPR/Cas Systems: Expanding the Toolbox for Optical Detection","authors":"Tianying Sun, Wenfen He, Xiangmei Chen, Xiaoying Shu, Wei Liu, Gangfeng Ouyang","doi":"10.1021/acssensors.5c00020","DOIUrl":"https://doi.org/10.1021/acssensors.5c00020","url":null,"abstract":"Nanomaterials-integrated CRISPR/Cas systems have rapidly emerged as powerful next-generation platforms for optical biosensing. These integrated platforms harness the precision of CRISPR/Cas-mediated nucleic acid detection while leveraging the unique properties of nanomaterials to achieve enhanced sensitivity and expanded analytical capabilities, thereby broadening their diagnostic potential. By incorporating a diverse range of nanomaterials, these systems effectively expand the analytical toolbox for optical detection, offering adaptable solutions tailored to various diagnostic challenges. This review provides a comprehensive overview of the nanomaterials successfully integrated into CRISPR/Cas-based optical sensing systems. It examines multiple optical detection modalities, including fluorescence, electrochemiluminescence, colorimetry, and surface-enhanced Raman spectroscopy, highlighting how nanomaterials facilitate signal amplification, enable multiplexing, and support the development of point-of-care applications. Additionally, practical applications of these integrated systems in critical fields such as healthcare diagnostics and environmental monitoring are showcased. While these platforms offer considerable advantages, several real-world challenges such as the complexity of assay workflows, environmental impact of nanomaterials, cost, and regulatory hurdles must be addressed before widespread implementation can be achieved. By identifying these critical obstacles and proposing strategic solutions, we aim to pave the way for the continued advancement and adoption of nanomaterial-integrated CRISPR/Cas optical biosensing technologies.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"74 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143806141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-08DOI: 10.1021/acssensors.4c03349
Li Zhou, Rui Ou, Pu Zhang, Lin Shen, Kai Xu, Weijie Wang, Sanjida Afrin, Yange Luan, Jiaru Zhang, Guanghui Ren, Yinfen Cheng, Zhong Li, Guanyu Chen, Bao Yue Zhang, Jian Zhen Ou
Accurate, low-cost, and energy-efficient detection of hydrogen sulfide (H2S) is vital for industries such as petroleum, natural gas, and wastewater treatment. While chemiresistive sensors are well suited for this purpose, traditional metal oxides typically require high operating temperatures (>100 °C) or external stimuli (e.g., UV light) for activation. In this work, we introduce two-dimensional (2D) copper oxysulfide nanoflakes (∼10 nm thick) as a novel material for room-temperature, reversible, and selective H2S sensing. These 2D copper oxysulfides, synthesized via the calcination of copper sulfide under both oxygen-deficient and oxygen-rich conditions, show significant changes in crystal structure and electronic band properties compared to copper sulfide while retaining p-type semiconducting behavior. This alteration enables efficient interfacial charge transfer with adsorbed H2S molecules. The oxygen-rich copper oxysulfide exhibits a response magnitude of 143% for 2 ppm of H2S in air at room temperature, with a linear response across concentrations ranging from 0.25 to 2 ppm. Furthermore, the sensor demonstrates complete reversibility, excellent selectivity, and high stability. This work presents a promising strategy for high-performance room-temperature H2S sensing utilizing metal oxysulfides as an emerging class of materials derived from metal oxides and sulfides.
{"title":"Tailorable Ultrathin Copper Oxysulfide for Room-Temperature, Reversible, and Selective Hydrogen Sulfide Sensing","authors":"Li Zhou, Rui Ou, Pu Zhang, Lin Shen, Kai Xu, Weijie Wang, Sanjida Afrin, Yange Luan, Jiaru Zhang, Guanghui Ren, Yinfen Cheng, Zhong Li, Guanyu Chen, Bao Yue Zhang, Jian Zhen Ou","doi":"10.1021/acssensors.4c03349","DOIUrl":"https://doi.org/10.1021/acssensors.4c03349","url":null,"abstract":"Accurate, low-cost, and energy-efficient detection of hydrogen sulfide (H<sub>2</sub>S) is vital for industries such as petroleum, natural gas, and wastewater treatment. While chemiresistive sensors are well suited for this purpose, traditional metal oxides typically require high operating temperatures (>100 °C) or external stimuli (e.g., UV light) for activation. In this work, we introduce two-dimensional (2D) copper oxysulfide nanoflakes (∼10 nm thick) as a novel material for room-temperature, reversible, and selective H<sub>2</sub>S sensing. These 2D copper oxysulfides, synthesized via the calcination of copper sulfide under both oxygen-deficient and oxygen-rich conditions, show significant changes in crystal structure and electronic band properties compared to copper sulfide while retaining p-type semiconducting behavior. This alteration enables efficient interfacial charge transfer with adsorbed H<sub>2</sub>S molecules. The oxygen-rich copper oxysulfide exhibits a response magnitude of 143% for 2 ppm of H<sub>2</sub>S in air at room temperature, with a linear response across concentrations ranging from 0.25 to 2 ppm. Furthermore, the sensor demonstrates complete reversibility, excellent selectivity, and high stability. This work presents a promising strategy for high-performance room-temperature H<sub>2</sub>S sensing utilizing metal oxysulfides as an emerging class of materials derived from metal oxides and sulfides.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"75 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143798326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-08DOI: 10.1021/acssensors.4c03594
Hyeran Cho, Geonhee Lee, Doyoon Kim, DongHyeon Kim, BeomJun Kim, YunJae Choi, Jeong-O. Lee, Gyu-Tae Kim
Many studies have focused on smart electronic noses combining machine learning and gas sensor arrays, but feature extraction for training has generally relied on dimensionality reduction techniques based on raw time-series data. These methods do not reflect the principles of sensor responses, limiting their applicability in diverse gas environments. In this study, we propose a new phase space, expressed through the first and second derivatives of dynamic response signals, to effectively characterize the nonlinear responses between gas sensors and gases. Sensing data transformed into a phase space showed unique patterns depending on the type and concentration of gases, and these were investigated for alkanes with various chain lengths (CH4, C3H8, C4H10). By applying these patterns as a preprocessing method, CNN-based gas identification machine learning achieved a high classification accuracy of 99.1% and a low concentration prediction error of 2.23 ppm using only a single sensor. Additionally, the algorithm was trained and validated across various regions of the phase space, identifying the minimum time and region required for simultaneous gas classification and concentration prediction. This study presents a novel strategy for the fast and accurate identification of gases within seconds and is expected to have significant scalability in diverse gas environments.
{"title":"New Dynamic Fingerprint in Derivative-Based Phase Space: Rapid Gas Sensing in Seconds","authors":"Hyeran Cho, Geonhee Lee, Doyoon Kim, DongHyeon Kim, BeomJun Kim, YunJae Choi, Jeong-O. Lee, Gyu-Tae Kim","doi":"10.1021/acssensors.4c03594","DOIUrl":"https://doi.org/10.1021/acssensors.4c03594","url":null,"abstract":"Many studies have focused on smart electronic noses combining machine learning and gas sensor arrays, but feature extraction for training has generally relied on dimensionality reduction techniques based on raw time-series data. These methods do not reflect the principles of sensor responses, limiting their applicability in diverse gas environments. In this study, we propose a new phase space, expressed through the first and second derivatives of dynamic response signals, to effectively characterize the nonlinear responses between gas sensors and gases. Sensing data transformed into a phase space showed unique patterns depending on the type and concentration of gases, and these were investigated for alkanes with various chain lengths (CH<sub>4</sub>, C<sub>3</sub>H<sub>8</sub>, C<sub>4</sub>H<sub>10</sub>). By applying these patterns as a preprocessing method, CNN-based gas identification machine learning achieved a high classification accuracy of 99.1% and a low concentration prediction error of 2.23 ppm using only a single sensor. Additionally, the algorithm was trained and validated across various regions of the phase space, identifying the minimum time and region required for simultaneous gas classification and concentration prediction. This study presents a novel strategy for the fast and accurate identification of gases within seconds and is expected to have significant scalability in diverse gas environments.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"60 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143798327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-08DOI: 10.1021/acssensors.4c03655
Kai Jiang, Min Zeng, Tao Wang, Yu Wu, Wangze Ni, Lechen Chen, Jianhua Yang, Nantao Hu, Bowei Zhang, Fuzhen Xuan, Siying Li, Anwei Shi, Zhi Yang
The drift compensation of gas sensors is a significant and challenging issue in the field of electronic noses (E-nose). Compensating sensor drift has a great benefit in improving the performance of E-nose systems. However, conventional methods often perform poorly due to complex data relationships before and after drifting, or require label information for both nondrift (source data) and drift data (target data) to enhance performance, which is hard to achieve and even unrealistic. In this study, we propose a semisupervised domain adaptive convolutional neural network (CNN) based on ensemble classifiers of multilevel features, pretraining, and center loss to tackle the drift problem. The main idea is to make full use of multilevel features extracted from the network and apply Hilbert space's maximum mean discrepancy (MMD) to evaluate the domain similarity of the features at different levels. Then the corresponding MMD is used as a weight to achieve the weighted fusion of predictions in the classifier ensemble module, so as to obtain a more reliable result. Furthermore, to optimize training, MMD is used as a loss for pretraining to help feature extractors learn more robust and common features in two domains. Center loss is also applied to achieve more focused learning for features of the same class. The results on two data sets demonstrate the effectiveness of our method. The average classification accuracies under different settings reach 76.06% (long-drift) and 82.07% (short-drift), respectively, and the average R2 score reaches 0.804 in the regression task, which has significant improvements compared with several conventional methods. Our work provides an effective and reliable method at the algorithm level to solve the drift compensation problem of gas sensors.
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