ACS Sensors最新文献_第4页

Food Freshness Prediction Platform Utilizing Deep Learning-Based Multimodal Sensor Fusion of Volatile Organic Compounds and Moisture Distribution

IF 8.9 1区化学

ACS Sensors Pub Date : 2025-03-23 DOI: 10.1021/acssensors.5c00254

Zepeng Gu, Qinyan Xu, Xiaoyao Wang, Xianfeng Lin, Nuo Duan, Zhouping Wang, Shijia Wu

{"title":"Food Freshness Prediction Platform Utilizing Deep Learning-Based Multimodal Sensor Fusion of Volatile Organic Compounds and Moisture Distribution","authors":"Zepeng Gu, Qinyan Xu, Xiaoyao Wang, Xianfeng Lin, Nuo Duan, Zhouping Wang, Shijia Wu","doi":"10.1021/acssensors.5c00254","DOIUrl":"https://doi.org/10.1021/acssensors.5c00254","url":null,"abstract":"Various sensing methods have been developed for food spoilage research, but in practical applications, the accuracy of these methods is frequently constrained by the limitation of single-source data and challenges in cross-validating multimodal data. To address these issues, a new method combining multidimensional sensing technology with deep learning-based dynamic fusion has been developed, which can precisely monitor the spoilage process of beef. This study designs a gas sensor based on surface-enhanced Raman scattering (SERS) to directly analyze volatile organic compounds (VOCs) adsorbed on MIL-101(Cr) with amine-specific adsorption for data collection while also evaluating the moisture distribution of beef through low-field nuclear magnetic resonance (LF-NMR), providing multidimensional recognition and readings. By introducing the self-attention mechanism and SENet scaling features into the multimodal deep learning model, the system is able to adaptively fuse and focus on the important features of the sensors. After training, the system can predict the storage time of beef under controlled storage conditions, with an R2 value greater than 0.98. Furthermore, it can provide accurate freshness assessments for beef samples under unknown storage conditions. Relative to single-modality methods, accuracy improves from 90 to over 97%. Overall, the newly developed dynamic fusion deep learning multimodal model effectively integrates multimodal information, enabling the fast and reliable monitoring of beef freshness.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"71 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143677926","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}

引用次数: 0

Highly Selective and Instant Ratio Fluorescence-Scattering Sensor for Phosphate Detection in a Water Environment by a Stable Eu3+/Y3+-Modified Nitrogen-Doped Carbon Quantum Dot

IF 8.9 1区化学

ACS Sensors Pub Date : 2025-03-21 DOI: 10.1021/acssensors.4c03627

Zheping Zhou, Tianhao Liu, Xilian Ouyang, Jing Tang, Xinya Fan, Yibo Liao, Xu Zhu, Ziling Zhang, Lin Tang

{"title":"Highly Selective and Instant Ratio Fluorescence-Scattering Sensor for Phosphate Detection in a Water Environment by a Stable Eu3+/Y3+-Modified Nitrogen-Doped Carbon Quantum Dot","authors":"Zheping Zhou, Tianhao Liu, Xilian Ouyang, Jing Tang, Xinya Fan, Yibo Liao, Xu Zhu, Ziling Zhang, Lin Tang","doi":"10.1021/acssensors.4c03627","DOIUrl":"https://doi.org/10.1021/acssensors.4c03627","url":null,"abstract":"Developing an accurate sensor for the detection of phosphate ions (Pi, a crucial indicator of water quality) in water environments is of great significance. Fluorescence-scattering ratiometric probes with great promise to achieve sensitive and selective detection are still hindered by the poor solubility and stability and complex construction of fluorescence composites. In this paper, a simple ratio fluorescence-scattering sensor based on Eu3+- and Y3+-modified nitrogen-doped carbon quantum dots (NCQDs) was developed for Pi rapid detection. It is found that Eu3+ can specifically recognize Pi and form ternary ion chelates with Pi and NCQDs, resulting in decreased fluorescence signals of NCQDs at 420 nm and increased second-order scattering (SOS) signals at 640 nm. Y3+ as the sensitizer of Eu3+ promotes the aggregation of NCQDs, thereby enhancing the sensitivity of the sensor. The ratio fluorescence-scattering probe based on NCQDs-Eu3+-Y3+ shows a high sensitivity, a low detection limit of 0.08 μM, a rapid response time of within 2 s, and a wide detection range from 1 to 150 μM. Moreover, the proposed probe showed excellent selectivity and stability, and the relative standard deviation (RSD) of seven cycles of Pi detection is only 0.559%. Furthermore, the accurate detection of Pi (RSD < 5%) in real environmental water samples confirmed the practicality of the proposed sensor. This ratio fluorescence-scattering sensor provides a novel method for the detection of Pi with a simple preparation process and excellent detection performance, having great application potential for the fast on-site detection of Pi.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"95 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672633","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}

引用次数: 0

A Patient-Centered Approach in Sensor Science: Embracing Patient Engagement for Translational Clinical Technologies

IF 8.9 1区化学

ACS Sensors Pub Date : 2025-03-19 DOI: 10.1021/acssensors.4c03292

Alana F. Ogata, Julia Kramer

{"title":"A Patient-Centered Approach in Sensor Science: Embracing Patient Engagement for Translational Clinical Technologies","authors":"Alana F. Ogata, Julia Kramer","doi":"10.1021/acssensors.4c03292","DOIUrl":"https://doi.org/10.1021/acssensors.4c03292","url":null,"abstract":"With the goal of impacting patient quality of life and outcomes, sensor science offers significant potential to revolutionize healthcare by providing advances in the detection of molecular biomarkers for personalized clinical technologies. The sensor community has achieved significant technical advancements that can impact diagnostics, health monitoring, and disease treatment; however, many sensor innovations remain confined to the laboratory, failing to bridge the translational gap between research and real-world clinical applications. This perspective presents a new direction for the sensor community, where sensor development centers on the needs and experiences of the primary beneficiaries: the patients. We provide guidelines and resources for researchers to engage with patients early and continuously throughout the research process to inform sensor specifications and better align sensor technologies with real-world clinical needs, improving their adoption and impact. We also present examples for implementing a patient-centered approach in sensor development and planning for patient engagement in sensor research. In the design of impactful sensors for patients, researchers must expand focus beyond technical specifications to embrace a patient-centered approach, which will likely lead to new opportunities for collaboration and evolution in the sensor science community.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"21 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143653979","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}

引用次数: 0

Fully Inorganic Metal Halide Perovskite CsGeBr3 Photoferroelectrics for Room-Temperature Photovoltaic Self-Powered Ammonia Detection

IF 8.2 1区化学

ACS Sensors Pub Date : 2025-03-19 DOI: 10.1021/acssensors.4c0335510.1021/acssensors.4c03355

Xirui Yan, and , Haiming Zhang*,

{"title":"Fully Inorganic Metal Halide Perovskite CsGeBr3 Photoferroelectrics for Room-Temperature Photovoltaic Self-Powered Ammonia Detection","authors":"Xirui Yan,  and , Haiming Zhang*, ","doi":"10.1021/acssensors.4c0335510.1021/acssensors.4c03355","DOIUrl":"https://doi.org/10.1021/acssensors.4c03355https://doi.org/10.1021/acssensors.4c03355","url":null,"abstract":"Chemiresistive sensing technology plays a significant role in the field of gas monitoring. However, conventional metal oxide gas monitoring devices typically require high operating temperatures and external power supplies to power them. In this paper, we have exploited the property that the photoferroelectric material CsGeBr3 can provide a stable output source through a self-polarization field under light illumination to achieve a good self-powered gas sensing response to NH3 at room temperature, including extremely fast response/recovery time (30 s/40 s), and low concentration sensing (response value of 2.02 at 50 ppm of NH3). This demonstrates significant advantages and a wider range of application scenarios than those of conventional metal oxide gas sensors that require an external power supply. Fourier transform infrared (FTIR) spectroscopic measurements confirmed the high selectivity of CsGeBr3 for NH3, which to our knowledge is the first time that Ge-based all-inorganic photoferroelectric materials of perovskite have been applied to the field of self-powered gas sensing, and the present work provides a new material and direction in the study of self-powered gas sensors.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"10 3","pages":"2090–2099 2090–2099"},"PeriodicalIF":8.2,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143714143","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}

引用次数: 0

A Patient-Centered Approach in Sensor Science: Embracing Patient Engagement for Translational Clinical Technologies

IF 8.2 1区化学

ACS Sensors Pub Date : 2025-03-19 DOI: 10.1021/acssensors.4c0329210.1021/acssensors.4c03292

Alana F. Ogata*, and , Julia Kramer,

{"title":"A Patient-Centered Approach in Sensor Science: Embracing Patient Engagement for Translational Clinical Technologies","authors":"Alana F. Ogata*,  and , Julia Kramer, ","doi":"10.1021/acssensors.4c0329210.1021/acssensors.4c03292","DOIUrl":"https://doi.org/10.1021/acssensors.4c03292https://doi.org/10.1021/acssensors.4c03292","url":null,"abstract":"With the goal of impacting patient quality of life and outcomes, sensor science offers significant potential to revolutionize healthcare by providing advances in the detection of molecular biomarkers for personalized clinical technologies. The sensor community has achieved significant technical advancements that can impact diagnostics, health monitoring, and disease treatment; however, many sensor innovations remain confined to the laboratory, failing to bridge the translational gap between research and real-world clinical applications. This perspective presents a new direction for the sensor community, where sensor development centers on the needs and experiences of the primary beneficiaries: the patients. We provide guidelines and resources for researchers to engage with patients early and continuously throughout the research process to inform sensor specifications and better align sensor technologies with real-world clinical needs, improving their adoption and impact. We also present examples for implementing a patient-centered approach in sensor development and planning for patient engagement in sensor research. In the design of impactful sensors for patients, researchers must expand focus beyond technical specifications to embrace a patient-centered approach, which will likely lead to new opportunities for collaboration and evolution in the sensor science community.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"10 3","pages":"1521–1537 1521–1537"},"PeriodicalIF":8.2,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143713939","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}

引用次数: 0

Accurate Diagnosis of Alzheimer’s Disease Using Specific Breath Volatile Organic Compounds

IF 8.9 1区化学

ACS Sensors Pub Date : 2025-03-19 DOI: 10.1021/acssensors.4c03329

Sizhe Zhang, Haokun Liu, Ziyu Ouyang, Tianyan Xu, Qijie Yang, Yuan Zhu, Meidan Wan, Xuewen Xiao, Xuan Yang, Shuliang Chen, Li Yuan, Yuzhang Bei, Junling Wang, Jifeng Guo, Haibin Chen, Beisha Tang, Shilin Luo, Bin Jiao, Lu Shen

{"title":"Accurate Diagnosis of Alzheimer’s Disease Using Specific Breath Volatile Organic Compounds","authors":"Sizhe Zhang, Haokun Liu, Ziyu Ouyang, Tianyan Xu, Qijie Yang, Yuan Zhu, Meidan Wan, Xuewen Xiao, Xuan Yang, Shuliang Chen, Li Yuan, Yuzhang Bei, Junling Wang, Jifeng Guo, Haibin Chen, Beisha Tang, Shilin Luo, Bin Jiao, Lu Shen","doi":"10.1021/acssensors.4c03329","DOIUrl":"https://doi.org/10.1021/acssensors.4c03329","url":null,"abstract":"Whether volatile organic compounds (VOCs) from exhaled breath can be used as a novel biomarker for Alzheimer’s disease (AD) diagnosis is unclear. To determine the significantly distinctive VOCs for AD, a total of 970 participants were enrolled, including 60 individuals in data set 1 (AD, 30; controls, 30), 164 individuals in data set 2 (AD, 82; controls, 82), 637 individuals in data set 3 (AD, 31; controls, 606), and 109 individuals in data set 4 (frontotemporal dementia, 19; vascular dementia, 21; Parkinson’s disease, 69). The participants in data sets 1, 2, and 4 were from Xiangya Hospital, Central South University. Participants in data set 3 were from a two-year follow-up cohort. VOCs in breath and plasma, neuropsychological scores, plasma p-tau181 levels, metabolites in plasma, and brain functional connectivity were detected. We found that six VOCs were significantly different between the two groups in data set 1 and were verified in data set 2 and data set 3. Ethanol (m/z = 46) and pyrrole (m/z = 67) presented AUC values of 0.907 and 0.895 in data sets 1 and 2 (clinical data sets) and 0.849 and 0.974 in data set 3 (community data set), respectively. The six VOCs were associated with cognitive decline as reflected by neuropsychological tests; five of them were correlated with plasma p-tau181, and these five plasma VOCs were consistently altered as breath VOCs. Correlation between metabolites and five VOCs in plasma was noted, and the five VOCs may originate from blood metabolites. Moreover, four breath VOCs were associated with altered brain connectivity. In conclusion, specific breath VOCs may be used as biomarkers for AD detection.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"9 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143660823","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}

引用次数: 0

Fully Inorganic Metal Halide Perovskite CsGeBr3 Photoferroelectrics for Room-Temperature Photovoltaic Self-Powered Ammonia Detection

IF 8.9 1区化学

ACS Sensors Pub Date : 2025-03-19 DOI: 10.1021/acssensors.4c03355

Xirui Yan, Haiming Zhang

{"title":"Fully Inorganic Metal Halide Perovskite CsGeBr3 Photoferroelectrics for Room-Temperature Photovoltaic Self-Powered Ammonia Detection","authors":"Xirui Yan, Haiming Zhang","doi":"10.1021/acssensors.4c03355","DOIUrl":"https://doi.org/10.1021/acssensors.4c03355","url":null,"abstract":"Chemiresistive sensing technology plays a significant role in the field of gas monitoring. However, conventional metal oxide gas monitoring devices typically require high operating temperatures and external power supplies to power them. In this paper, we have exploited the property that the photoferroelectric material CsGeBr3 can provide a stable output source through a self-polarization field under light illumination to achieve a good self-powered gas sensing response to NH3 at room temperature, including extremely fast response/recovery time (30 s/40 s), and low concentration sensing (response value of 2.02 at 50 ppm of NH3). This demonstrates significant advantages and a wider range of application scenarios than those of conventional metal oxide gas sensors that require an external power supply. Fourier transform infrared (FTIR) spectroscopic measurements confirmed the high selectivity of CsGeBr3 for NH3, which to our knowledge is the first time that Ge-based all-inorganic photoferroelectric materials of perovskite have been applied to the field of self-powered gas sensing, and the present work provides a new material and direction in the study of self-powered gas sensors.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"91 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143653977","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}

引用次数: 0

A Biohydrogel-Enabled Microneedle Sensor for In Situ Monitoring of Reactive Oxygen Species in Plants

IF 8.9 1区化学

ACS Sensors Pub Date : 2025-03-19 DOI: 10.1021/acssensors.4c02645

Nawab Singh, Qinming Zhang, Weihui Xu, Steven A. Whitham, Liang Dong

{"title":"A Biohydrogel-Enabled Microneedle Sensor for In Situ Monitoring of Reactive Oxygen Species in Plants","authors":"Nawab Singh, Qinming Zhang, Weihui Xu, Steven A. Whitham, Liang Dong","doi":"10.1021/acssensors.4c02645","DOIUrl":"https://doi.org/10.1021/acssensors.4c02645","url":null,"abstract":"This study introduces a plant sensor utilizing an array of microneedles to monitor hydrogen peroxide (H2O2) in tobacco and soybean plants under biotic stress response. The microneedle array features a biohydrogel layer composed of the natural biopolymer chitosan (Cs) and reduced graphene oxide (rGO), functionalized with horseradish peroxidase (HRP) (HRP/Cs-rGO). This HRP/Cs-rGO biohydrogel combines biocompatibility, hydrophilicity, porosity, and electron transfer ability, making it a suitable bioelectrode material for an electrochemical sensor. The sensor detects H2O2 through the catalytic reaction of the enzyme, either by direct attachment to the plant leaf with the inserted microneedle or by exposure to the solution extracted from plant parts such as leaves. Utilizing chronoamperometry, the sensor demonstrates high sensitivity of 14.7 μA/μM across a concentration range of 0.1–4500 μM with a low detection limit of 0.06 μM. The sensor enables rapid detection of H2O2 levels by exposing the sensor to extracted leaf solutions. For in situ measurements within the leaf, results are obtained in approximately 1 min, eliminating the need for sample preparation. H2O2 levels in leaves following bacterial pathogen inoculation are evaluated alongside results from qualitative histological staining and quantitative fluorescence-based Amplex Red Assay, validating the ability of the sensor to detect changes in H2O2 concentrations during plant defense responses. This sensor technology has the potential to function as a portable device for on-site measurement of reactive oxygen species in plants, providing a rapid and cost-effective solution for H2O2 quantification.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"56 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143653976","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}

引用次数: 0

A Biohydrogel-Enabled Microneedle Sensor for In Situ Monitoring of Reactive Oxygen Species in Plants

IF 8.2 1区化学

ACS Sensors Pub Date : 2025-03-19 DOI: 10.1021/acssensors.4c0264510.1021/acssensors.4c02645

Nawab Singh, Qinming Zhang, Weihui Xu, Steven A. Whitham and Liang Dong*,

{"title":"A Biohydrogel-Enabled Microneedle Sensor for In Situ Monitoring of Reactive Oxygen Species in Plants","authors":"Nawab Singh, Qinming Zhang, Weihui Xu, Steven A. Whitham and Liang Dong*, ","doi":"10.1021/acssensors.4c0264510.1021/acssensors.4c02645","DOIUrl":"https://doi.org/10.1021/acssensors.4c02645https://doi.org/10.1021/acssensors.4c02645","url":null,"abstract":"This study introduces a plant sensor utilizing an array of microneedles to monitor hydrogen peroxide (H2O2) in tobacco and soybean plants under biotic stress response. The microneedle array features a biohydrogel layer composed of the natural biopolymer chitosan (Cs) and reduced graphene oxide (rGO), functionalized with horseradish peroxidase (HRP) (HRP/Cs-rGO). This HRP/Cs-rGO biohydrogel combines biocompatibility, hydrophilicity, porosity, and electron transfer ability, making it a suitable bioelectrode material for an electrochemical sensor. The sensor detects H2O2 through the catalytic reaction of the enzyme, either by direct attachment to the plant leaf with the inserted microneedle or by exposure to the solution extracted from plant parts such as leaves. Utilizing chronoamperometry, the sensor demonstrates high sensitivity of 14.7 μA/μM across a concentration range of 0.1–4500 μM with a low detection limit of 0.06 μM. The sensor enables rapid detection of H2O2 levels by exposing the sensor to extracted leaf solutions. For in situ measurements within the leaf, results are obtained in approximately 1 min, eliminating the need for sample preparation. H2O2 levels in leaves following bacterial pathogen inoculation are evaluated alongside results from qualitative histological staining and quantitative fluorescence-based Amplex Red Assay, validating the ability of the sensor to detect changes in H2O2 concentrations during plant defense responses. This sensor technology has the potential to function as a portable device for on-site measurement of reactive oxygen species in plants, providing a rapid and cost-effective solution for H2O2 quantification.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"10 3","pages":"1797–1810 1797–1810"},"PeriodicalIF":8.2,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acssensors.4c02645","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143714177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

High-Sensitivity Flexible Self-Powered Pressure Sensor Based on Solid–Liquid Triboelectrification

IF 8.9 1区化学

ACS Sensors Pub Date : 2025-03-18 DOI: 10.1021/acssensors.5c00165

Yu Wu, Rui Lei, Jie Cao, Si Chen, Yan Zhong, Jie Song, Zhelin Jin, Guanggui Cheng, Jianning Ding

{"title":"High-Sensitivity Flexible Self-Powered Pressure Sensor Based on Solid–Liquid Triboelectrification","authors":"Yu Wu, Rui Lei, Jie Cao, Si Chen, Yan Zhong, Jie Song, Zhelin Jin, Guanggui Cheng, Jianning Ding","doi":"10.1021/acssensors.5c00165","DOIUrl":"https://doi.org/10.1021/acssensors.5c00165","url":null,"abstract":"Self-powered sensors based on triboelectric nanogenerators (TENG) possess advantages such as lightweight, small size, and low cost. However, the trade-off among response time, sensitivity, and wear resistance of the triboelectric layer in such sensors remains unresolved. In this paper, a hydrophobic triboelectric layer was prepared using polydimethylsiloxane (PDMS) doped with polytetrafluoroethylene (PTFE), generating triboelectric signals through the contact and separation of the triboelectric layer with water. Compared to the traditional solid–solid triboelectric charging method in self-powered sensors, this sensor primarily relies on solid–liquid triboelectric charging, effectively avoiding the wear issues caused by traditional solid–solid triboelectric charging. Simultaneously, thanks to the solid–liquid contact mode, the response time of the self-powered sensor is significantly improved, and it maintains high sensitivity under extremely small trigger forces. Finally, this paper demonstrates the application of this self-powered sensor in scenarios such as detecting human joint movements, mechanical finger states, and robotic hand grasping states, showing its promising application prospects in the field of intelligent monitoring.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"33 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143653978","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}

引用次数: 0