Pub Date : 2022-07-26DOI: 10.1149/2754-2726/ac8438
Nguyen H. B. Ho, Dalton L. Glasco, J. G. Bell
Benzalkonium (BA+) chloride is one of the most common preservatives used in prescription-based and over-the-counter eye drops. Knowing the concentration of BA+ in eye drops is important for both quality control (at the pharmaceutical preparation stage) and human health (ocular toxicity has been linked to BA+ use). This paper describes the design and fabrication of a benzalkonium-selective potentiometric sensor for the determination of BA+ in ophthalmic solutions. The sensor is composed of a 3D-printed ion-selective membrane (ISM) that selectively measures BA+ in the presence of potentially interfering ions routinely found in ophthalmic formulations (i.e., Mg2+, Ca2+, Na+ and K+). The 3D printed BA+-ion-selective electrodes (ISEs) produced a Nernstian response of 55 mV/Decade across a range of 1.0 mM to 31.0 μM BA+ along with an LOD of 8 μM, which covers the relevant concentration range found in ophthalmic solutions. The 3D printed BA+-ISEs proved to be highly stable with an average drift of 205 μV/hr. Successful measurement of BA+ in diluted ophthalmic solutions was completed from 100–500 μM. The mass production capability afforded by 3D-printing offers a unique and intriguing fabrication protocol for developing low-cost sensors which could be incorporated quickly and seamlessly by pharmaceutical companies or community-based pharmacies.
{"title":"Potentiometric Analysis of Benzalkonium Chloride with 3D Printed Ion-Selective Membranes","authors":"Nguyen H. B. Ho, Dalton L. Glasco, J. G. Bell","doi":"10.1149/2754-2726/ac8438","DOIUrl":"https://doi.org/10.1149/2754-2726/ac8438","url":null,"abstract":"Benzalkonium (BA+) chloride is one of the most common preservatives used in prescription-based and over-the-counter eye drops. Knowing the concentration of BA+ in eye drops is important for both quality control (at the pharmaceutical preparation stage) and human health (ocular toxicity has been linked to BA+ use). This paper describes the design and fabrication of a benzalkonium-selective potentiometric sensor for the determination of BA+ in ophthalmic solutions. The sensor is composed of a 3D-printed ion-selective membrane (ISM) that selectively measures BA+ in the presence of potentially interfering ions routinely found in ophthalmic formulations (i.e., Mg2+, Ca2+, Na+ and K+). The 3D printed BA+-ion-selective electrodes (ISEs) produced a Nernstian response of 55 mV/Decade across a range of 1.0 mM to 31.0 μM BA+ along with an LOD of 8 μM, which covers the relevant concentration range found in ophthalmic solutions. The 3D printed BA+-ISEs proved to be highly stable with an average drift of 205 μV/hr. Successful measurement of BA+ in diluted ophthalmic solutions was completed from 100–500 μM. The mass production capability afforded by 3D-printing offers a unique and intriguing fabrication protocol for developing low-cost sensors which could be incorporated quickly and seamlessly by pharmaceutical companies or community-based pharmacies.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45995267","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 : 2022-07-26DOI: 10.1149/2754-2726/ac8436
Tran Thanh Tam Toan, D. Nguyen
The features of NMTs such as graphene, molybdenum disulfide, CNTs and quantum dots for unique sensing applicability are mentioned in this review study. Some notable sensors that have been produced are described based on the particular analyte compound to be determined and the functionalization processes that are used. For COVID-19 determination, biocompatible sensors manufactured from these materials capable of determining specific chemical components are also highlighted, which could support efficient and reliable sensing and rapid diagnosis.
{"title":"Review—A Nanomaterial-Based Sensor for Detecting the COVID-19 Virus through Various Techniques","authors":"Tran Thanh Tam Toan, D. Nguyen","doi":"10.1149/2754-2726/ac8436","DOIUrl":"https://doi.org/10.1149/2754-2726/ac8436","url":null,"abstract":"The features of NMTs such as graphene, molybdenum disulfide, CNTs and quantum dots for unique sensing applicability are mentioned in this review study. Some notable sensors that have been produced are described based on the particular analyte compound to be determined and the functionalization processes that are used. For COVID-19 determination, biocompatible sensors manufactured from these materials capable of determining specific chemical components are also highlighted, which could support efficient and reliable sensing and rapid diagnosis.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46548660","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 : 2022-07-26DOI: 10.1149/2754-2726/ac8437
Ajeet Singh, A. Verma, B. Yadav
In this work, MnO2-SnO2 nanocomposite based below lower exposure limit (0.5–2.0 vol%) sensing device for liquefied petroleum gas (LPG) is reported. The synthesized material is highly crystalline with an average crystallite size of 16.786 nm, confirmed by the X-ray diffraction pattern. Williamson-Hall plot shows that the induced strain of 2.627 × 10−4, present in the nanocomposite, lies between the induced strains of both of its constituents. The XRD pattern of nanocomposite contains the cubic phase of MnO2 and the tetragonal phase of SnO2. Tauc plot shows the optical energy band gap of MnO2, SnO2, and MnO2-SnO2 of 3.407 eV, 3.037 eV, and 3.202 eV respectively. The surface morphological investigation shows the brush-like structure which enhances sensor performance by providing activation sites. The energy dispersive X-ray (EDS) spectrum found that materials are highly pure because other peaks are not observed. The functional group analysis by using FTIR found to be Sn–O and Mn–O both vibration bands existed. The highest sensor response was found to be 2.42 for 2.0 vol% whereas for a lower concentration of 0.5 vol% the sensor response was observed to be 1.44. The fast response and recovery of this sensing device were found to17.30 and 23.25 s respectively for 0.5 vol% of LPG.
{"title":"MnO2-SnO2 Based Liquefied Petroleum Gas Sensing Device for Lowest Explosion Limit Gas Concentration","authors":"Ajeet Singh, A. Verma, B. Yadav","doi":"10.1149/2754-2726/ac8437","DOIUrl":"https://doi.org/10.1149/2754-2726/ac8437","url":null,"abstract":"In this work, MnO2-SnO2 nanocomposite based below lower exposure limit (0.5–2.0 vol%) sensing device for liquefied petroleum gas (LPG) is reported. The synthesized material is highly crystalline with an average crystallite size of 16.786 nm, confirmed by the X-ray diffraction pattern. Williamson-Hall plot shows that the induced strain of 2.627 × 10−4, present in the nanocomposite, lies between the induced strains of both of its constituents. The XRD pattern of nanocomposite contains the cubic phase of MnO2 and the tetragonal phase of SnO2. Tauc plot shows the optical energy band gap of MnO2, SnO2, and MnO2-SnO2 of 3.407 eV, 3.037 eV, and 3.202 eV respectively. The surface morphological investigation shows the brush-like structure which enhances sensor performance by providing activation sites. The energy dispersive X-ray (EDS) spectrum found that materials are highly pure because other peaks are not observed. The functional group analysis by using FTIR found to be Sn–O and Mn–O both vibration bands existed. The highest sensor response was found to be 2.42 for 2.0 vol% whereas for a lower concentration of 0.5 vol% the sensor response was observed to be 1.44. The fast response and recovery of this sensing device were found to17.30 and 23.25 s respectively for 0.5 vol% of LPG.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47325752","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 : 2022-07-20DOI: 10.1149/2754-2726/ac82bc
Sayali Upasham, Paul Rice, Sarah Shahub, V. N. Dhamu, Shalini Prasad
Interleukin-31 has been reported to be involved with chronic skin conditions like atopic dermatitis (AD). This work focuses on the development of a portable IL-31 detection system that works with passive sweat over the physiologically relevant range-150–620 pg ml−1. Four simulated flaring profiles were used to benchmark the IL-31 rise and fall detection capabilities of the sensor. These temporal profiles were generated according to the SCORAD range for severity of AD and were spanned across different dosing regimens. The sensing platform displays good sensitivity with a limit of detection of 50 pg ml−1 and dynamic range of 50–750 pg ml−1 for the flaring profiles in synthetic and human sweat, and with coupled portable electronics. Furthermore, in order to create a robust and predictive system, a machine learning algorithm was incorporated to create a flare prediction system. This algorithm shows high accuracy for the test data sets and provides the proof-of-concept for the use of ml coupled electrochemical systems for chronic diseases like AD.
{"title":"Passive Sweat-Based Pruritic Cytokine Detection and Monitoring System","authors":"Sayali Upasham, Paul Rice, Sarah Shahub, V. N. Dhamu, Shalini Prasad","doi":"10.1149/2754-2726/ac82bc","DOIUrl":"https://doi.org/10.1149/2754-2726/ac82bc","url":null,"abstract":"Interleukin-31 has been reported to be involved with chronic skin conditions like atopic dermatitis (AD). This work focuses on the development of a portable IL-31 detection system that works with passive sweat over the physiologically relevant range-150–620 pg ml−1. Four simulated flaring profiles were used to benchmark the IL-31 rise and fall detection capabilities of the sensor. These temporal profiles were generated according to the SCORAD range for severity of AD and were spanned across different dosing regimens. The sensing platform displays good sensitivity with a limit of detection of 50 pg ml−1 and dynamic range of 50–750 pg ml−1 for the flaring profiles in synthetic and human sweat, and with coupled portable electronics. Furthermore, in order to create a robust and predictive system, a machine learning algorithm was incorporated to create a flare prediction system. This algorithm shows high accuracy for the test data sets and provides the proof-of-concept for the use of ml coupled electrochemical systems for chronic diseases like AD.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44354724","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 : 2022-07-07DOI: 10.1149/2754-2726/aca034
Art Matthew Mamaril, Dalton L. Glasco, F. L. Leal Yepes, J. G. Bell
This paper describes the design, fabrication, and validation of a paper-based diagnostic device for the rapid diagnosis of hypocalcemia in dairy cattle at the point-of-care (POC). The device incorporates a 3D printed calcium ion-selective membrane (ISM) as the sensing element for free—unbound—calcium in real bovine whole blood samples. With a linear response range of 100 mM to 97.7 μM, the sensor covers the clinically relevant concentrations of Ca2+ associated with both healthy cattle as well as those suffering from hypocalcemia. The components of the Ca2+ ion-selective electrodes were successfully translated to a paper-based device to provide a sensing platform that is simple to use, disposable, and low-cost, and is therefore well-situated for applications at the POC. The paper-based calcium sensor showed a Nernstian response between 10 mM and 100 μM and required only 12 μl of sample to perform a measurement, which can be accomplished in less than two minutes without the need for time-consuming separation steps. The performance of the paper-based Ca2+ sensor was validated using the commercially available epoc® Blood Analysis System, which provided results within 5% of the data obtained with 3D printed Ca2+-ISM integrated paper-based device.
{"title":"Identifying Hypocalcemia in Dairy Cattle by Combining 3D Printing and Paper Diagnostics","authors":"Art Matthew Mamaril, Dalton L. Glasco, F. L. Leal Yepes, J. G. Bell","doi":"10.1149/2754-2726/aca034","DOIUrl":"https://doi.org/10.1149/2754-2726/aca034","url":null,"abstract":"This paper describes the design, fabrication, and validation of a paper-based diagnostic device for the rapid diagnosis of hypocalcemia in dairy cattle at the point-of-care (POC). The device incorporates a 3D printed calcium ion-selective membrane (ISM) as the sensing element for free—unbound—calcium in real bovine whole blood samples. With a linear response range of 100 mM to 97.7 μM, the sensor covers the clinically relevant concentrations of Ca2+ associated with both healthy cattle as well as those suffering from hypocalcemia. The components of the Ca2+ ion-selective electrodes were successfully translated to a paper-based device to provide a sensing platform that is simple to use, disposable, and low-cost, and is therefore well-situated for applications at the POC. The paper-based calcium sensor showed a Nernstian response between 10 mM and 100 μM and required only 12 μl of sample to perform a measurement, which can be accomplished in less than two minutes without the need for time-consuming separation steps. The performance of the paper-based Ca2+ sensor was validated using the commercially available epoc® Blood Analysis System, which provided results within 5% of the data obtained with 3D printed Ca2+-ISM integrated paper-based device.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41892338","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 : 2022-06-28DOI: 10.1149/2754-2726/ac7c78
P. Murugan, Ramila D. Nagarajan, A. Sundramoorthy, Dhanraj M. Ganapathy, R. Atchudan, D. Nallaswamy, A. Khosla
Hydrogen peroxide (H2O2) is extensively used for sterilization purposes in the food industries and pharmaceuticals as an antimicrobial agent. According to the Food and Agriculture Organization (FAO), the permissible level of H2O2 in milk is in the range of 0.04 to 0.05% w/v, so it has been prohibited to use as a preservative agent. Herein, we reported the electrochemical sensing of H2O2 in milk samples using an activated glassy carbon electrode (AGCE). For this purpose, activation of GCE was carried out in 0.1 M H2SO4 by continuous potential sweeping between −0.7 to 1.8 V for 25 cycles. The AGCE showed a redox peak at -0.18 V in the neutral medium corresponding to the quinone functional groups present on the electrode surface. AGCE was studied in (pH 7.4) 0.1 M PBS for the electro-catalysis of H2O2. The surface of the activated electrode was analysed by Raman spectroscopy and contact angle measurements. In addition, for the activated surface, the contact angle was found to be 85° which indicated the hydrophilic nature of the surface. The different optimization parameters such as (1) effect of electrolyte ions, (2) electrooxidation cycles, and (3) oxidation potential windows were studied to improve the activation process. Finally, AGCE was used to detect H2O2 from 0.1 to 10 mM and the limit of detection (LOD) was found to be 0.053 mM with a linear correlation coefficient (R2) of 0.9633. The selectivity of the sensor towards H2O2 was carried out in the presence of other interferents. The sensitivity of the AGCE sensor was calculated as 17.16 μA mol cm−2. Finally, the commercial application of the sensor was verified by testing it in milk samples with H2O2 in the recovery range of 95%–98%.
过氧化氢（H2O2）作为一种抗菌剂广泛用于食品工业和制药中的杀菌目的。根据粮食及农业组织（FAO）的数据，牛奶中H2O2的允许含量在0.04至0.05%w/v之间，因此禁止将其用作防腐剂。在此，我们报道了使用活性玻璃碳电极（AGCE）对牛奶样品中H2O2的电化学传感。为此，GCE的活化是在0.1 M H2SO4中，通过在−0.7至1.8 V之间连续电位扫描进行25次循环。AGCE在中性介质中显示出-0.18V的氧化还原峰，对应于电极表面上存在的醌官能团。研究了AGCE在（pH 7.4）0.1M PBS中对H2O2的电催化作用。通过拉曼光谱和接触角测量对活化电极的表面进行分析。此外，对于活化表面，发现接触角为85°，这表明表面的亲水性。研究了不同的优化参数，如（1）电解质离子的影响，（2）电氧化循环和（3）氧化电位窗口，以改善活化过程。最后，使用AGCE检测0.1至10mM的H2O2，发现检测限（LOD）为0.053mM，线性相关系数（R2）为0.9633。传感器对H2O2的选择性是在存在其他干扰物的情况下进行的。AGCE传感器的灵敏度计算为17.16μA mol cm−2。最后，通过在含有H2O2的牛奶样品中进行测试，验证了该传感器的商业应用，回收率范围为95%-98%。
{"title":"Electrochemical Detection of H2O2 Using an Activated Glassy Carbon Electrode","authors":"P. Murugan, Ramila D. Nagarajan, A. Sundramoorthy, Dhanraj M. Ganapathy, R. Atchudan, D. Nallaswamy, A. Khosla","doi":"10.1149/2754-2726/ac7c78","DOIUrl":"https://doi.org/10.1149/2754-2726/ac7c78","url":null,"abstract":"Hydrogen peroxide (H2O2) is extensively used for sterilization purposes in the food industries and pharmaceuticals as an antimicrobial agent. According to the Food and Agriculture Organization (FAO), the permissible level of H2O2 in milk is in the range of 0.04 to 0.05% w/v, so it has been prohibited to use as a preservative agent. Herein, we reported the electrochemical sensing of H2O2 in milk samples using an activated glassy carbon electrode (AGCE). For this purpose, activation of GCE was carried out in 0.1 M H2SO4 by continuous potential sweeping between −0.7 to 1.8 V for 25 cycles. The AGCE showed a redox peak at -0.18 V in the neutral medium corresponding to the quinone functional groups present on the electrode surface. AGCE was studied in (pH 7.4) 0.1 M PBS for the electro-catalysis of H2O2. The surface of the activated electrode was analysed by Raman spectroscopy and contact angle measurements. In addition, for the activated surface, the contact angle was found to be 85° which indicated the hydrophilic nature of the surface. The different optimization parameters such as (1) effect of electrolyte ions, (2) electrooxidation cycles, and (3) oxidation potential windows were studied to improve the activation process. Finally, AGCE was used to detect H2O2 from 0.1 to 10 mM and the limit of detection (LOD) was found to be 0.053 mM with a linear correlation coefficient (R2) of 0.9633. The selectivity of the sensor towards H2O2 was carried out in the presence of other interferents. The sensitivity of the AGCE sensor was calculated as 17.16 μA mol cm−2. Finally, the commercial application of the sensor was verified by testing it in milk samples with H2O2 in the recovery range of 95%–98%.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47618643","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 : 2022-06-21DOI: 10.1149/2754-2726/ac7abb
Saroj Kumar Das, Kavya K. Nayak, P. Krishnaswamy, Vinay Kumar, N. Bhat
Diabetes leads to chronic microvascular complications for the heart, kidney, and eyes due to uncontrolled glycemic fluctuations. Self-monitoring blood glucose meters can only provide a snapshot of glucose level and are incapable of capturing the granular glucose fluctuations over the 24 h in day. The clinical research has indicated that random blood glucose fluctuations can lead to organ damage. In pursuit of better glucose management, Continuous Glucose Monitoring (CGM) is emerging as a popular alternative owing to its ability to detect instantaneous changes in glucose levels and to alert the users of impending hypo- or hyper-glycemic events. In the last decade, several CGM devices have been launched in the market based on different glucose sensing chemistries and techniques. More research is still needed to come up with novel bio sensing concepts to make CGM low cost and highly accurate. Here, we elaborate the CGM techniques such as electrochemical, optical, reverse iontophoresis, microdialysis, and impedance spectroscopy. We emphasize on the widely used electrochemical CGMs with a focus on sensor design and bio-compatibility. We also provide an outlook for the future technologies, highlighting the need for innovative materials, possibility of integrating with the Internet of Things (IoT) for real-time e-health monitoring.
{"title":"Review—Electrochemistry and Other Emerging Technologies for Continuous Glucose Monitoring Devices","authors":"Saroj Kumar Das, Kavya K. Nayak, P. Krishnaswamy, Vinay Kumar, N. Bhat","doi":"10.1149/2754-2726/ac7abb","DOIUrl":"https://doi.org/10.1149/2754-2726/ac7abb","url":null,"abstract":"Diabetes leads to chronic microvascular complications for the heart, kidney, and eyes due to uncontrolled glycemic fluctuations. Self-monitoring blood glucose meters can only provide a snapshot of glucose level and are incapable of capturing the granular glucose fluctuations over the 24 h in day. The clinical research has indicated that random blood glucose fluctuations can lead to organ damage. In pursuit of better glucose management, Continuous Glucose Monitoring (CGM) is emerging as a popular alternative owing to its ability to detect instantaneous changes in glucose levels and to alert the users of impending hypo- or hyper-glycemic events. In the last decade, several CGM devices have been launched in the market based on different glucose sensing chemistries and techniques. More research is still needed to come up with novel bio sensing concepts to make CGM low cost and highly accurate. Here, we elaborate the CGM techniques such as electrochemical, optical, reverse iontophoresis, microdialysis, and impedance spectroscopy. We emphasize on the widely used electrochemical CGMs with a focus on sensor design and bio-compatibility. We also provide an outlook for the future technologies, highlighting the need for innovative materials, possibility of integrating with the Internet of Things (IoT) for real-time e-health monitoring.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42159204","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 : 2022-06-21DOI: 10.1149/2754-2726/ac7abd
H. Atchison, Zachary Bailey, D. Wetz, Matthew Davis, J. Heinzel
Lithium-ion batteries are widely deployed in commercial and industrial applications. Continuous monitoring is necessary to prevent destructive results that can occur due to thermal runaway. Thermocouples and thermistors are traditional sensors used for thermally monitoring cells, modules, and batteries, but they only sense changes at the physical point where they are deployed. A high density of these sensors within a module or battery is desirable but also impractical. The study documented here shows that a commercial grade fiber optic sensor can be used as a practical replacement for multiple discrete thermocouples or strain gauges for a battery or module, to monitor a battery module at millimeter resolution along the fiber length. It is shown here that multiple fiber optic sensors can be series connected to allow for monitoring of a battery consisting of more than one module. In addition, it is shown that the same type of fiber can also be used to identify the onset of fault conditions by correlating the response in a fiber optic sensor suspended close to the module with an audible signature detected by a microphone at the time of failure. Early detection and identification of abnormal cell operation is demonstrated within batteries employing many cells.
{"title":"Thermal Monitoring of Series and Parallel Connected Lithium-ion Battery Modules Using Fiber Optic Sensors","authors":"H. Atchison, Zachary Bailey, D. Wetz, Matthew Davis, J. Heinzel","doi":"10.1149/2754-2726/ac7abd","DOIUrl":"https://doi.org/10.1149/2754-2726/ac7abd","url":null,"abstract":"Lithium-ion batteries are widely deployed in commercial and industrial applications. Continuous monitoring is necessary to prevent destructive results that can occur due to thermal runaway. Thermocouples and thermistors are traditional sensors used for thermally monitoring cells, modules, and batteries, but they only sense changes at the physical point where they are deployed. A high density of these sensors within a module or battery is desirable but also impractical. The study documented here shows that a commercial grade fiber optic sensor can be used as a practical replacement for multiple discrete thermocouples or strain gauges for a battery or module, to monitor a battery module at millimeter resolution along the fiber length. It is shown here that multiple fiber optic sensors can be series connected to allow for monitoring of a battery consisting of more than one module. In addition, it is shown that the same type of fiber can also be used to identify the onset of fault conditions by correlating the response in a fiber optic sensor suspended close to the module with an audible signature detected by a microphone at the time of failure. Early detection and identification of abnormal cell operation is demonstrated within batteries employing many cells.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45158119","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 : 2022-06-21DOI: 10.1149/2754-2726/ac7abc
Sandeep Maurya, Santosh Kumar, Umang Garg, M. Kumar
The Internet of Things (IoT) has become an integral requirement to equip common life. According to IDC, the number of IoT devices may increase exponentially up to a trillion in near future. Thus, their cyberspace having inherent vulnerabilities leads to various possible serious cyber-attacks. So, the security of IoT systems becomes the prime concern for its consumers and businesses. Therefore, to enhance the reliability of IoT security systems, a better and real-time approach is required. For this purpose, the creation of a real-time dataset is essential for IoT traffic analysis. In this paper, the experimental testbed has been devised for the generation of a real-time dataset using the IoT botnet traffic in which each of the bots consists of several possible attacks. Besides, an extensive comparative study of the proposed dataset and existing datasets are done using popular Machine Learning (ML) techniques to show its relevance in the real-time scenario.
{"title":"An Efficient Framework for Detection and Classification of IoT Botnet Traffic","authors":"Sandeep Maurya, Santosh Kumar, Umang Garg, M. Kumar","doi":"10.1149/2754-2726/ac7abc","DOIUrl":"https://doi.org/10.1149/2754-2726/ac7abc","url":null,"abstract":"The Internet of Things (IoT) has become an integral requirement to equip common life. According to IDC, the number of IoT devices may increase exponentially up to a trillion in near future. Thus, their cyberspace having inherent vulnerabilities leads to various possible serious cyber-attacks. So, the security of IoT systems becomes the prime concern for its consumers and businesses. Therefore, to enhance the reliability of IoT security systems, a better and real-time approach is required. For this purpose, the creation of a real-time dataset is essential for IoT traffic analysis. In this paper, the experimental testbed has been devised for the generation of a real-time dataset using the IoT botnet traffic in which each of the bots consists of several possible attacks. Besides, an extensive comparative study of the proposed dataset and existing datasets are done using popular Machine Learning (ML) techniques to show its relevance in the real-time scenario.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44508601","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 : 2022-06-06DOI: 10.1149/2754-2726/ac75f5
Xuefeng Liang, Xingyu Liu, Longshan Yao
Deep Learning has achieved remarkable successes in many industry applications and scientific research fields. One essential reason is that deep models can learn rich information from large-scale training datasets through supervised learning. It has been well accepted that the robust deep models heavily rely on the quality of data labels. However, current large-scale datasets mostly involve noisy labels, which are caused by sensor errors, human mistakes, or inaccuracy of search engines, and may severely degrade the performance of deep models. In this survey, we summaries existing works on noisy label learning into two main categories, Loss Correction and Sample Selection, and present their methodologies, commonly used experimental setups, datasets, and the state-of-the-art results. Finally, we discuss a promising research direction that might be valuable for the future study.
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