Pub Date : 2024-06-06DOI: 10.1149/2754-2726/ad54d2
Sandeep Arya, Asha Sharma, A. Singh, Aamir Ahmed, Aman Dubey, Bhavya Padha, Saleem Khan, R. Mahadeva, A. Khosla, Vinay Gupta
Wearable sensing technology has quickly transformed from a science-fiction vision to a real-life technology in various fields such as defense, medical sciences, aerospace technology, food tech, etc. Wearable devices are drawing attention in the medical field as they provide relevant information about people's health in real-time. These sensors are flexible, cost-effective, and highly sensitive, which makes them a favorable candidate for future sensing technology. Despite being relatively small, they frequently sense, collect, and upload a variety of physiological data to enhance quality of life. This could lead to a major change in the daily life of people, but for this change to happen, sustainable energy technology that can power flexible wearable devices is needed. Wearable sensors come in a variety of shapes and sizes and require energy for their proper functioning. As a result, it is critical to develop and choose dependable energy supply systems. This review paper discusses different energy sources that are used to power wearable devices along with various challenges that are in the realm of this technology. The future holds great possibilities for wearable sensing technology, which can be explored only if the power sourcing to these devices is more sustainable, eco-friendly, and efficient.
{"title":"Review—Energy and Power Requirements for Wearable Sensors","authors":"Sandeep Arya, Asha Sharma, A. Singh, Aamir Ahmed, Aman Dubey, Bhavya Padha, Saleem Khan, R. Mahadeva, A. Khosla, Vinay Gupta","doi":"10.1149/2754-2726/ad54d2","DOIUrl":"https://doi.org/10.1149/2754-2726/ad54d2","url":null,"abstract":"\u0000 Wearable sensing technology has quickly transformed from a science-fiction vision to a real-life technology in various fields such as defense, medical sciences, aerospace technology, food tech, etc. Wearable devices are drawing attention in the medical field as they provide relevant information about people's health in real-time. These sensors are flexible, cost-effective, and highly sensitive, which makes them a favorable candidate for future sensing technology. Despite being relatively small, they frequently sense, collect, and upload a variety of physiological data to enhance quality of life. This could lead to a major change in the daily life of people, but for this change to happen, sustainable energy technology that can power flexible wearable devices is needed. Wearable sensors come in a variety of shapes and sizes and require energy for their proper functioning. As a result, it is critical to develop and choose dependable energy supply systems. This review paper discusses different energy sources that are used to power wearable devices along with various challenges that are in the realm of this technology. The future holds great possibilities for wearable sensing technology, which can be explored only if the power sourcing to these devices is more sustainable, eco-friendly, and efficient.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141377870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-06DOI: 10.1149/2754-2726/ad54d3
Bhavya Jain, Krishnakant Phand, Vaibhav Jain, Indranil Lahiri, D. Lahiri
Technology is constantly evolving, and chronic health issues are on the rise. It is essential to have affordable and easy access to remote biomedical measurements. This makes flexible sensors a more attractive choice owing to their high sensitivity and flexibility along with low cost and ease of use. As an additional advantage, 3D printing has become increasingly popular in areas such as biomedicine, environment, and industry. This study demonstrates 3D-printed flexible sensors for tactile sensing. A biocompatible silicone elastomer such as polydimethylsiloxane (PDMS) with low elastic modulus and high stretchability makes an excellent wearable sensor material. Incorporating CNTs at varying concentrations (0.5, 1, 2)wt% enhances the sensor’s mechanical strength, conductivity, and responsiveness to mechanical strain. In addition to enhancing the thermal stability of the composite by 44%, multi-walled carbon nanotubes (MWCNTs) also enhanced the breaking strength by 57% with a 2 wt% CNT loading. Moreover, the contact angle values improved by 15%, making it a biomedical-grade hydrophobic surface. The electrical characteristics of these sensors reveal excellent strain sensitivity, making them perfect for monitoring finger movements and biomedical measurements. Overall, 2 wt% CNT-PDMS sensors exhibit optimal performance, paving the way for advanced tactile sensing in biomedical and industrial settings.
{"title":"3D Printed Carbon Nanotubes Reinforced Polydimethylsiloxane Flexible Sensors for Tactile Sensing","authors":"Bhavya Jain, Krishnakant Phand, Vaibhav Jain, Indranil Lahiri, D. Lahiri","doi":"10.1149/2754-2726/ad54d3","DOIUrl":"https://doi.org/10.1149/2754-2726/ad54d3","url":null,"abstract":"Technology is constantly evolving, and chronic health issues are on the rise. It is essential to have affordable and easy access to remote biomedical measurements. This makes flexible sensors a more attractive choice owing to their high sensitivity and flexibility along with low cost and ease of use. As an additional advantage, 3D printing has become increasingly popular in areas such as biomedicine, environment, and industry. This study demonstrates 3D-printed flexible sensors for tactile sensing. A biocompatible silicone elastomer such as polydimethylsiloxane (PDMS) with low elastic modulus and high stretchability makes an excellent wearable sensor material. Incorporating CNTs at varying concentrations (0.5, 1, 2)wt% enhances the sensor’s mechanical strength, conductivity, and responsiveness to mechanical strain. In addition to enhancing the thermal stability of the composite by 44%, multi-walled carbon nanotubes (MWCNTs) also enhanced the breaking strength by 57% with a 2 wt% CNT loading. Moreover, the contact angle values improved by 15%, making it a biomedical-grade hydrophobic surface. The electrical characteristics of these sensors reveal excellent strain sensitivity, making them perfect for monitoring finger movements and biomedical measurements. Overall, 2 wt% CNT-PDMS sensors exhibit optimal performance, paving the way for advanced tactile sensing in biomedical and industrial settings.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141380857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Electrochemical sensors have become a pivotal tool in ensuring the safety and security of the global food supply chain, which is crucial for public health, economic stability, and environmental sustainability. Modern food systems, with their complex global distribution and varied processing methods, require advanced solutions for detecting contaminants and maintaining food quality. This review delves into recent advancements in electrochemical food sensor technology, highlighting their operating principles, types, cutting-edge materials, and methods enhancing their effectiveness. These sensors are adept at identifying a broad range of foodborne pathogens, chemical contaminants, and adulterants while monitoring food freshness and quality. Innovations include using nanomaterials and conductive polymers and shifting towards miniaturized, portable devices for on-site and real-time analysis. The review also addresses challenges such as sensitivity, selectivity, and matrix effects, pointing out emerging trends and future research avenues to overcome these hurdles. Regulatory and standardization issues relevant to adopting these technologies in food safety protocols are also considered. Highlighting the last three years, this review emphasizes the indispensable role of electrochemical sensors in boosting food safety and security and the need for ongoing innovation and cross-disciplinary cooperation to advance this area.
{"title":"Editors’ Choice—Review—Advances in Electrochemical Sensors: Improving Food Safety, Quality, and Traceability","authors":"Kogularasu Sakthivel, Sriram Balasubramanian, G. Chang-Chien, Sea-Fue Wang, Fnu Ahammad, Wayant Billey, Justin Platero, Thiagarajan Soundappan, Praveen Sekhar","doi":"10.1149/2754-2726/ad5455","DOIUrl":"https://doi.org/10.1149/2754-2726/ad5455","url":null,"abstract":"Electrochemical sensors have become a pivotal tool in ensuring the safety and security of the global food supply chain, which is crucial for public health, economic stability, and environmental sustainability. Modern food systems, with their complex global distribution and varied processing methods, require advanced solutions for detecting contaminants and maintaining food quality. This review delves into recent advancements in electrochemical food sensor technology, highlighting their operating principles, types, cutting-edge materials, and methods enhancing their effectiveness. These sensors are adept at identifying a broad range of foodborne pathogens, chemical contaminants, and adulterants while monitoring food freshness and quality. Innovations include using nanomaterials and conductive polymers and shifting towards miniaturized, portable devices for on-site and real-time analysis. The review also addresses challenges such as sensitivity, selectivity, and matrix effects, pointing out emerging trends and future research avenues to overcome these hurdles. Regulatory and standardization issues relevant to adopting these technologies in food safety protocols are also considered. Highlighting the last three years, this review emphasizes the indispensable role of electrochemical sensors in boosting food safety and security and the need for ongoing innovation and cross-disciplinary cooperation to advance this area.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141384475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-30DOI: 10.1149/2754-2726/ad23df
Sleight Halley, K. Ramaiyan, James Smith, Robert Ian, K. Agi, Fernando Garzon, L. Tsui
Emissions of CH4 from natural gas infrastructure must be addressed to mitigate its effect on global climate. With hundreds of thousands of miles of pipeline in the US used to transport natural gas, current methods of surveying for leaks are inadequate. Mixed potential sensors are a low-cost, field-deployable technology for remote and continuous monitoring of natural gas infrastructure. We demonstrate for the first time a field trial of a mixed potential sensor device coupled with machine learning and Internet-of-Things (IoT) platform at Colorado State University’s Methane Emissions Technology Evaluation Center. Emissions were detected from a simulated buried underground pipeline source. Sensor data was acquired and transmitted from the field test site to a remote cloud server. Quantification of concentration as a function of vertical distance is consistent with previously reported transport modelling efforts and experimental surveys of methane emissions by more sophisticated CH4 analyzers.
{"title":"Field Testing of a Mixed Potential IoT Sensor Platform for Methane Quantification","authors":"Sleight Halley, K. Ramaiyan, James Smith, Robert Ian, K. Agi, Fernando Garzon, L. Tsui","doi":"10.1149/2754-2726/ad23df","DOIUrl":"https://doi.org/10.1149/2754-2726/ad23df","url":null,"abstract":"\u0000 Emissions of CH4 from natural gas infrastructure must be addressed to mitigate its effect on global climate. With hundreds of thousands of miles of pipeline in the US used to transport natural gas, current methods of surveying for leaks are inadequate. Mixed potential sensors are a low-cost, field-deployable technology for remote and continuous monitoring of natural gas infrastructure. We demonstrate for the first time a field trial of a mixed potential sensor device coupled with machine learning and Internet-of-Things (IoT) platform at Colorado State University’s Methane Emissions Technology Evaluation Center. Emissions were detected from a simulated buried underground pipeline source. Sensor data was acquired and transmitted from the field test site to a remote cloud server. Quantification of concentration as a function of vertical distance is consistent with previously reported transport modelling efforts and experimental surveys of methane emissions by more sophisticated CH4 analyzers.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140483913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-24DOI: 10.1149/2754-2726/ad21ea
Srikanth Namuduri, Prateek Mehta, Lise Barbe, Zohreh Faghihmonzavi, Stephanie Lam, steven finkbeiner, S. Bhansali
Comet assays are used to assess the extent of Deoxyribonucleic acid (DNA) damage, in human cells, caused by substances such as novel drugs or nano materials. Deep learning is showing promising results in automating the process of quantifying the percentage of damage using the assay images. But the lack of large datasets and imbalanced data is a challenge. In this study, synthetic comet assay images generated from simple geometric shapes were used to augment the data for training the Convolutional Neural Network. The results from the model trained using the augmented data were compared with the results from a model trained exclusively on real images. It was observed that the use of synthetic data in training not only gave a significantly better coefficient of determination (R2), but also resulted in a more robust model i.e., with less variation in R2 compared to training without synthetic data. This approach can lead to improved training while using a smaller training dataset, saving cost and effort involved in capturing additional experimental images and annotating them. Additional benefits include addressing imbalanced datasets, and data privacy concerns. Similar approaches must be explored in other low data domains to extract the same benefits.
{"title":"Automated Quantification of DNA Damage Using Deep Learning and Use of Synthetic Data Generated from Basic Geometric Shapes","authors":"Srikanth Namuduri, Prateek Mehta, Lise Barbe, Zohreh Faghihmonzavi, Stephanie Lam, steven finkbeiner, S. Bhansali","doi":"10.1149/2754-2726/ad21ea","DOIUrl":"https://doi.org/10.1149/2754-2726/ad21ea","url":null,"abstract":"\u0000 Comet assays are used to assess the extent of Deoxyribonucleic acid (DNA) damage, in human cells, caused by substances such as novel drugs or nano materials. Deep learning is showing promising results in automating the process of quantifying the percentage of damage using the assay images. But the lack of large datasets and imbalanced data is a challenge. In this study, synthetic comet assay images generated from simple geometric shapes were used to augment the data for training the Convolutional Neural Network. The results from the model trained using the augmented data were compared with the results from a model trained exclusively on real images. It was observed that the use of synthetic data in training not only gave a significantly better coefficient of determination (R2), but also resulted in a more robust model i.e., with less variation in R2 compared to training without synthetic data. This approach can lead to improved training while using a smaller training dataset, saving cost and effort involved in capturing additional experimental images and annotating them. Additional benefits include addressing imbalanced datasets, and data privacy concerns. Similar approaches must be explored in other low data domains to extract the same benefits.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139600416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-22DOI: 10.1149/2754-2726/ad2152
A. Pathania, Neetu Dhanda, Ritesh Verma, A. C. Sun, P. Thakur, A. Thakur
Economic growth depends upon Micro, Small and Medium Enterprises (MSMEs) as they play a vital role in GDP and employment. Transportation is considered the lifeline of any country. In the last 10 years, ferrite-based sensors have been used primarily to detect harmful gases, pollutants from vehicle exhaust, and for environmental pollution monitoring. These soft ferrites have excellent electrical and magnetic properties that can be tuned to increase sensitivity and selectivity. The tuning of ferrite sensors depends upon synthesis technique, optimizing preparation conditions, sintering temperatures, operating temperatures, dopant concentration, etc. This paper is based on a deep study of the gas sensing mechanisms, parameters, and application of chemo-resistive metal oxide gas sensors. The key parameters for the ferrite gas sensors are phase formation, crystallite size, grain size, surface area, selectivity, dopants, sensitivity, gas concentration, operating temperature, response/recovery time. This review paper also includes the study of different researchers to find the impact of high concentration of gases like hydrogen, carbon monoxide, carbon dioxide , oxygen (O2), ethylene glycol 〖〖(CH〗_2 OH)〗_(2 ), methane (CH4), ammonia (NH3) liquid petroleum gas (LPG), acetylene (C2H2), and nitrogen oxides (NOx) in the environment and the metal oxide materials selected sensor applications.
{"title":"Review—Metal Oxide Chemoresistive Gas Sensing Mechanism, Parameters, and Applications","authors":"A. Pathania, Neetu Dhanda, Ritesh Verma, A. C. Sun, P. Thakur, A. Thakur","doi":"10.1149/2754-2726/ad2152","DOIUrl":"https://doi.org/10.1149/2754-2726/ad2152","url":null,"abstract":"\u0000 Economic growth depends upon Micro, Small and Medium Enterprises (MSMEs) as they play a vital role in GDP and employment. Transportation is considered the lifeline of any country. In the last 10 years, ferrite-based sensors have been used primarily to detect harmful gases, pollutants from vehicle exhaust, and for environmental pollution monitoring. These soft ferrites have excellent electrical and magnetic properties that can be tuned to increase sensitivity and selectivity. The tuning of ferrite sensors depends upon synthesis technique, optimizing preparation conditions, sintering temperatures, operating temperatures, dopant concentration, etc. This paper is based on a deep study of the gas sensing mechanisms, parameters, and application of chemo-resistive metal oxide gas sensors. The key parameters for the ferrite gas sensors are phase formation, crystallite size, grain size, surface area, selectivity, dopants, sensitivity, gas concentration, operating temperature, response/recovery time. This review paper also includes the study of different researchers to find the impact of high concentration of gases like hydrogen, carbon monoxide, carbon dioxide , oxygen (O2), ethylene glycol 〖〖(CH〗_2 OH)〗_(2 ), methane (CH4), ammonia (NH3) liquid petroleum gas (LPG), acetylene (C2H2), and nitrogen oxides (NOx) in the environment and the metal oxide materials selected sensor applications.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139607175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-14DOI: 10.1149/2754-2726/ad15a2
Blaise J Ostertag, Ashley E Ross
Carbon-based sensors have remained critical materials for electrochemical detection of neurochemicals rooted in their inherent biocompatibility and broad potential window. Real-time monitoring, using fast-scan cyclic voltammetry, has resulted in the rise of minimally invasive carbon -fiber microelectrodes as the material of choice for making measurements in tissue, but challenges with carbon fiber’s innate properties have limited its applicability to understudied neurochemicals. Here, we provide a critical review of the state of carbon-based real-time neurochemical detection and offer insight into ways we envision addressing these limitations in the future. We focus on three main hinderances of traditional carbon-fiber based materials: diminished temporal resolution due to geometric properties and adsorption/desorption properties of the material, poor selectivity/specificity to most neurochemicals, and the inability to tune amorphous carbon surfaces for specific interfacial interactions. Routes to addressing these challenges could lie in methods like computational modeling of single-molecule interfacial interactions, expansion to tunable carbon-based materials, and novel approaches to synthesizing these materials. We hope this critical piece does justice to describing the novel carbon-based materials that have preceded this work, and we hope this review provides useful solutions to innovate carbon-based material development in the future for individualized neurochemical structures.
{"title":"Editors' Choice—Review—The Future of Carbon-Based Neurochemical Sensing: A Critical Perspective","authors":"Blaise J Ostertag, Ashley E Ross","doi":"10.1149/2754-2726/ad15a2","DOIUrl":"https://doi.org/10.1149/2754-2726/ad15a2","url":null,"abstract":"\u0000 Carbon-based sensors have remained critical materials for electrochemical detection of neurochemicals rooted in their inherent biocompatibility and broad potential window. Real-time monitoring, using fast-scan cyclic voltammetry, has resulted in the rise of minimally invasive carbon -fiber microelectrodes as the material of choice for making measurements in tissue, but challenges with carbon fiber’s innate properties have limited its applicability to understudied neurochemicals. Here, we provide a critical review of the state of carbon-based real-time neurochemical detection and offer insight into ways we envision addressing these limitations in the future. We focus on three main hinderances of traditional carbon-fiber based materials: diminished temporal resolution due to geometric properties and adsorption/desorption properties of the material, poor selectivity/specificity to most neurochemicals, and the inability to tune amorphous carbon surfaces for specific interfacial interactions. Routes to addressing these challenges could lie in methods like computational modeling of single-molecule interfacial interactions, expansion to tunable carbon-based materials, and novel approaches to synthesizing these materials. We hope this critical piece does justice to describing the novel carbon-based materials that have preceded this work, and we hope this review provides useful solutions to innovate carbon-based material development in the future for individualized neurochemical structures.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139002124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-14DOI: 10.1149/2754-2726/ad15a0
Alex Lonergan, U. Gulzar, Yan Zhang, C. O’Dwyer
Innovative new materials are consistently emerging as electrode candidates from lithium-ion battery research, promising high energy densities and high-rate capabilities. Understanding potential structural changes, morphology evolution, degradation mechanisms, and side reactions during lithiation is important for designing, optimizing, and assessing aspiring electrode materials. In-situ and operando analysis techniques provide a means to investigate these material properties under realistic operating conditions. Here, we demonstrate operando spectroscopic sensing using photonic crystal-structured electrodes that uses the optical transmission spectrum to monitor changes to the state of charge or discharge during lithiation, and the change to electrode structure, in real-time. Photonic crystals possess a signature optical response, with a photonic bandgap (or stopband) presenting as a structural color reflection from the material. We leverage the presence of this photonic stopband, alongside its intricate relationship to the electrode structure and material phase, to correlate electrode lithiation with changes to the optical spectrum during operation. We explore the optical and electrochemical behavior of a TiO2 anode in a lithium-ion battery, structured as a photonic crystal. The operando optical sensing demonstrated here is versatile and applicable to a wide range of electrochemical electrode material candidates when structured with ordered porosity akin to a photonic crystal structure.
{"title":"Operando Color-Coding of Reversible Lithiation and Cycle Life in Batteries Using Photonic Crystal Materials","authors":"Alex Lonergan, U. Gulzar, Yan Zhang, C. O’Dwyer","doi":"10.1149/2754-2726/ad15a0","DOIUrl":"https://doi.org/10.1149/2754-2726/ad15a0","url":null,"abstract":"\u0000 Innovative new materials are consistently emerging as electrode candidates from lithium-ion battery research, promising high energy densities and high-rate capabilities. Understanding potential structural changes, morphology evolution, degradation mechanisms, and side reactions during lithiation is important for designing, optimizing, and assessing aspiring electrode materials. In-situ and operando analysis techniques provide a means to investigate these material properties under realistic operating conditions. Here, we demonstrate operando spectroscopic sensing using photonic crystal-structured electrodes that uses the optical transmission spectrum to monitor changes to the state of charge or discharge during lithiation, and the change to electrode structure, in real-time. Photonic crystals possess a signature optical response, with a photonic bandgap (or stopband) presenting as a structural color reflection from the material. We leverage the presence of this photonic stopband, alongside its intricate relationship to the electrode structure and material phase, to correlate electrode lithiation with changes to the optical spectrum during operation. We explore the optical and electrochemical behavior of a TiO2 anode in a lithium-ion battery, structured as a photonic crystal. The operando optical sensing demonstrated here is versatile and applicable to a wide range of electrochemical electrode material candidates when structured with ordered porosity akin to a photonic crystal structure.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138971919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-14DOI: 10.1149/2754-2726/ad15a1
Celeste R. Rousseau, Hope Kumakli, Ryan J. White
Electrochemical, aptamer-based (E-AB) sensors provide a generalizable strategy to quantitatively detect a variety of targets including small molecules and proteins. The key signaling attributes of E-AB sensors (sensitivity, selectivity, specificity, and reagentless and dynamic sensing ability) make them well suited to monitor dynamic processes in complex environments. A key bioanalytical challenge that could benefit from the detection capabilities of E-AB sensors is that of cell signaling, which involves the release of molecular messengers into the extracellular space. Here, we provide a perspective on why E-AB sensors are suited for this measurement, sensor requirements, and pioneering examples of cellular signaling measurements.
{"title":"Assessing Electrochemical, Aptamer-Based Sensors for Dynamic Monitoring of Cellular Signaling","authors":"Celeste R. Rousseau, Hope Kumakli, Ryan J. White","doi":"10.1149/2754-2726/ad15a1","DOIUrl":"https://doi.org/10.1149/2754-2726/ad15a1","url":null,"abstract":"\u0000 Electrochemical, aptamer-based (E-AB) sensors provide a generalizable strategy to quantitatively detect a variety of targets including small molecules and proteins. The key signaling attributes of E-AB sensors (sensitivity, selectivity, specificity, and reagentless and dynamic sensing ability) make them well suited to monitor dynamic processes in complex environments. A key bioanalytical challenge that could benefit from the detection capabilities of E-AB sensors is that of cell signaling, which involves the release of molecular messengers into the extracellular space. Here, we provide a perspective on why E-AB sensors are suited for this measurement, sensor requirements, and pioneering examples of cellular signaling measurements.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139002335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-16DOI: 10.1149/2754-2726/ad0cd6
Srinivasulu Kanaparthi, S. Singh
Developing a multi-analyte gas sensing system that simultaneously detects trace levels of CO and NO2 at low temperatures is necessary for the Internet of Things (IoT) based air quality monitoring applications. Nevertheless, gas sensors operating at low temperatures are nonspecific and rarely detect target gases at lower ppb levels in the air. Herein, an array of two SnS2 sensors with different bias voltages has been developed and characterized upon exposure to individual and binary mixtures of CO and NO2 gases at different concentrations. The developed gas sensors array achieved the lower detection limit of 45 ppb for NO2 and 150 ppb for CO. Further, co-adsorption-induced interaction analysis was carried out to predict the target gas concentration in the binary mixture using the mixed gas response. The mean absolute percentage error of 7.86% is observed in predicting the target gas concentrations in the binary mixture, which indicates the high prediction accuracy of proposed method. As a minimal resource intensive approach, the proposed method can be used in air quality monitoring applications that require low-power and low-cost sensors.
{"title":"Simultaneous Detection of CO and NO2 Gases using Interaction Analysis of SnS2 Sensor Array Response","authors":"Srinivasulu Kanaparthi, S. Singh","doi":"10.1149/2754-2726/ad0cd6","DOIUrl":"https://doi.org/10.1149/2754-2726/ad0cd6","url":null,"abstract":"Developing a multi-analyte gas sensing system that simultaneously detects trace levels of CO and NO2 at low temperatures is necessary for the Internet of Things (IoT) based air quality monitoring applications. Nevertheless, gas sensors operating at low temperatures are nonspecific and rarely detect target gases at lower ppb levels in the air. Herein, an array of two SnS2 sensors with different bias voltages has been developed and characterized upon exposure to individual and binary mixtures of CO and NO2 gases at different concentrations. The developed gas sensors array achieved the lower detection limit of 45 ppb for NO2 and 150 ppb for CO. Further, co-adsorption-induced interaction analysis was carried out to predict the target gas concentration in the binary mixture using the mixed gas response. The mean absolute percentage error of 7.86% is observed in predicting the target gas concentrations in the binary mixture, which indicates the high prediction accuracy of proposed method. As a minimal resource intensive approach, the proposed method can be used in air quality monitoring applications that require low-power and low-cost sensors.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139267108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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