Pub Date : 2024-06-14DOI: 10.1109/JSEN.2024.3391189
Fernando Cesar Rufino;Cassio Roberto de Almeida;Geovana Sales;Rodrigo César;Melissa Vidal;Jeany Delafiori;Arthur de Oliveira;Estela Busanello;Rinaldo Siciliano;José Carlos Nicolau;Adriadne Bertolin;Rócio Salsoso;Fabiana Marcondes-Braga;Thebano Santos;Duniskys Larrude;Angelo Gobbi;Carlos Costa;Ricardo Cotrin Teixeira;Rodrigo Catharino;José Alexandre Diniz
In this work, we report a graphene field-effect transistor (GFET) biosensor platform able to sense the SARS-CoV-2 contamination in blood plasma and saliva. The GFET was fabricated on a Si/SiO2 wafer with thin metallic films deposited by sputtering. The gate structure is formed by Ti/Au and the source/drain structure are formed by TiN layer. The dielectric gate is formed by 10 nm TiO2. The transistor channel is formed by ten parallel ribbons of monolayer graphene defined by photolithography and O2 plasma etching. The virus sensing tests were performed with contaminated and non-contaminate SARS-CoV-2 plasma and saliva as analytes on the channel region. The channel shape allows the analyte to contact the ten graphene ribbons and the TiO2 gate dielectric. The sensitivity of the GFET biosensor to SARS-CoV-2 was evidenced by drain-source current versus gate-source voltage ( ${I}_{text {DS}} times {V}_{text {GS}}$ ) and normalized transconductance ( ${G}_{M}$ ) curves, where these measurements with the infected samples showed higher electric currents. The Kelvin probe force microscopy (KPFM) technique was used to extract the graphene ribbons and TiO2 characteristics. These analyses indicate that the TiO2 film promotes the interaction of the two hydroxyl groups at their atomic terminations with the viral proteins in contaminated solutions. Indeed, sensing occurs when the viral particles or induced molecules meet the TiO2 surface, injecting carriers into the graphene channel. Therefore, the main contribution of this work is the presentation of a GFET transistor platform for BioFET to detect the SARS-CoV-2, with no need to functionalize the graphene surface on the channel.
{"title":"Non-Functionalized Graphene Ribbons FET Biosensor Platform: SARS-CoV-2 Detection on TiO2Gate Dielectric Windows","authors":"Fernando Cesar Rufino;Cassio Roberto de Almeida;Geovana Sales;Rodrigo César;Melissa Vidal;Jeany Delafiori;Arthur de Oliveira;Estela Busanello;Rinaldo Siciliano;José Carlos Nicolau;Adriadne Bertolin;Rócio Salsoso;Fabiana Marcondes-Braga;Thebano Santos;Duniskys Larrude;Angelo Gobbi;Carlos Costa;Ricardo Cotrin Teixeira;Rodrigo Catharino;José Alexandre Diniz","doi":"10.1109/JSEN.2024.3391189","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3391189","url":null,"abstract":"In this work, we report a graphene field-effect transistor (GFET) biosensor platform able to sense the SARS-CoV-2 contamination in blood plasma and saliva. The GFET was fabricated on a Si/SiO2 wafer with thin metallic films deposited by sputtering. The gate structure is formed by Ti/Au and the source/drain structure are formed by TiN layer. The dielectric gate is formed by 10 nm TiO2. The transistor channel is formed by ten parallel ribbons of monolayer graphene defined by photolithography and O2 plasma etching. The virus sensing tests were performed with contaminated and non-contaminate SARS-CoV-2 plasma and saliva as analytes on the channel region. The channel shape allows the analyte to contact the ten graphene ribbons and the TiO2 gate dielectric. The sensitivity of the GFET biosensor to SARS-CoV-2 was evidenced by drain-source current versus gate-source voltage (\u0000<inline-formula> <tex-math>${I}_{text {DS}} times {V}_{text {GS}}$ </tex-math></inline-formula>\u0000) and normalized transconductance (\u0000<inline-formula> <tex-math>${G}_{M}$ </tex-math></inline-formula>\u0000) curves, where these measurements with the infected samples showed higher electric currents. The Kelvin probe force microscopy (KPFM) technique was used to extract the graphene ribbons and TiO2 characteristics. These analyses indicate that the TiO2 film promotes the interaction of the two hydroxyl groups at their atomic terminations with the viral proteins in contaminated solutions. Indeed, sensing occurs when the viral particles or induced molecules meet the TiO2 surface, injecting carriers into the graphene channel. Therefore, the main contribution of this work is the presentation of a GFET transistor platform for BioFET to detect the SARS-CoV-2, with no need to functionalize the graphene surface on the channel.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141326270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-07DOI: 10.1109/JSEN.2024.3402660
Linli Li;Qifei Jian
The remaining useful life (RUL) prediction is a crucial aspect of predictive maintenance for equipment. However, main bearings operate in complex, high-frequency vibration-prone nacelle conditions, identifying fault characteristics and accurately predicting the degradation process pose significant challenges. To address this, this article presents the first-ever research on fault diagnosis and prognosis based on historical vibration data from in-service wind turbine units with confirmed damages in a certain offshore wind farm. Proposing a tree seed algorithm optimized long short-term memory (TSA-LSTM) predictive model founded on the sideband energy ratio (SER) principle. Considering the distinctive structural configuration of wind turbines, fault indexes are extracted from the modulation component composed of the main bearing defect frequency occurring on both sides of the gearbox characteristic frequency based on SER. The time sensitivity of LSTM and the excellent global search ability of TSA were combined to complete modeling. This approach effectively captures the degradation process and achieves accurate fault identification. Through comparison, the superior predictive performance and robustness of the proposed optimization algorithm are verified, with mean absolute percentage error (MAPE) lower than 0.228 and root mean square error (RMSE) lower than 0.014. Additionally, the exponential fitting can accurately describe the whole process of the gradual accumulation of faults over time until failure, facilitating RUL prediction. The results demonstrate that SER-based features exhibit higher sensitivity to early-stage faults and better fit the degradation trend, providing a promising solution for wind turbine main bearing fault prognosis.
{"title":"Remaining Useful Life Prediction of Wind Turbine Main-Bearing Based on LSTM Optimized Network","authors":"Linli Li;Qifei Jian","doi":"10.1109/JSEN.2024.3402660","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3402660","url":null,"abstract":"The remaining useful life (RUL) prediction is a crucial aspect of predictive maintenance for equipment. However, main bearings operate in complex, high-frequency vibration-prone nacelle conditions, identifying fault characteristics and accurately predicting the degradation process pose significant challenges. To address this, this article presents the first-ever research on fault diagnosis and prognosis based on historical vibration data from in-service wind turbine units with confirmed damages in a certain offshore wind farm. Proposing a tree seed algorithm optimized long short-term memory (TSA-LSTM) predictive model founded on the sideband energy ratio (SER) principle. Considering the distinctive structural configuration of wind turbines, fault indexes are extracted from the modulation component composed of the main bearing defect frequency occurring on both sides of the gearbox characteristic frequency based on SER. The time sensitivity of LSTM and the excellent global search ability of TSA were combined to complete modeling. This approach effectively captures the degradation process and achieves accurate fault identification. Through comparison, the superior predictive performance and robustness of the proposed optimization algorithm are verified, with mean absolute percentage error (MAPE) lower than 0.228 and root mean square error (RMSE) lower than 0.014. Additionally, the exponential fitting can accurately describe the whole process of the gradual accumulation of faults over time until failure, facilitating RUL prediction. The results demonstrate that SER-based features exhibit higher sensitivity to early-stage faults and better fit the degradation trend, providing a promising solution for wind turbine main bearing fault prognosis.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141474944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-06DOI: 10.1109/JPHOTOV.2024.3402231
Md. Mahmudul Hasan Shihab;Redwan N. Sajjad;Mohammad Ryyan Khan
Alongside advancements in photovoltaics (PV) technology, efficient solar farm operation (e.g., strategic panel cleaning) can help lower electricity generation costs in the field. In this work, we study the effects of season-dependent soiling and cleaning on energy yield, revenue, and profit in four locations – Dhaka (Bangladesh), Oregon City (USA), Berlin (Germany), and Rumah (Saudi Arabia). These locations cover a wide range of soiling rates, season-dependent rainfall, cleaning costs, and tariff rates for a broad techno-economic analysis of soiling-affected solar farms. While a two-month cleaning cycle, for example, apparently seems too long for soiling-prone locations (Dhaka and Rumah) – this is too frequent for Oregon City and Berlin due to their high cleaning costs. Therefore, the optimal strategy for maximum profit for the latter two locations is to never clean the panels. Even at optimal cleaning cycle (maximum revenue/profit), there is a profit-loss of 13.28%, 19.97%, 1.39%, and 42.88%, compared with the respective soiling-free rated farm output at these locations. We also show the sensitivity of output and profit to the variations in soiling rate and cleaning cost; farms in Dhaka and Rumah show strong sensitivity due to the high soiling rate and low cleaning costs.
{"title":"Effects of Local Economy and Seasonal Cleaning Cycle on Yield and Profit of Soiled Solar Farms","authors":"Md. Mahmudul Hasan Shihab;Redwan N. Sajjad;Mohammad Ryyan Khan","doi":"10.1109/JPHOTOV.2024.3402231","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2024.3402231","url":null,"abstract":"Alongside advancements in photovoltaics (PV) technology, efficient solar farm operation (e.g., strategic panel cleaning) can help lower electricity generation costs in the field. In this work, we study the effects of season-dependent soiling and cleaning on energy yield, revenue, and profit in four locations – Dhaka (Bangladesh), Oregon City (USA), Berlin (Germany), and Rumah (Saudi Arabia). These locations cover a wide range of soiling rates, season-dependent rainfall, cleaning costs, and tariff rates for a broad techno-economic analysis of soiling-affected solar farms. While a two-month cleaning cycle, for example, apparently seems too long for soiling-prone locations (Dhaka and Rumah) – this is too frequent for Oregon City and Berlin due to their high cleaning costs. Therefore, the optimal strategy for maximum profit for the latter two locations is to never clean the panels. Even at optimal cleaning cycle (maximum revenue/profit), there is a profit-loss of 13.28%, 19.97%, 1.39%, and 42.88%, compared with the respective soiling-free rated farm output at these locations. We also show the sensitivity of output and profit to the variations in soiling rate and cleaning cost; farms in Dhaka and Rumah show strong sensitivity due to the high soiling rate and low cleaning costs.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141435522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-06DOI: 10.1109/JPHOTOV.2024.3405377
James Y. Hartley;Michael A. Shimizu;Jennifer L. Braid;Ryan Flanagan;Phillip L. Reu
Stereo high-speed video of photovoltaic modules undergoing laboratory hail tests was processed using digital image correlation to determine module surface deformation during and immediately following impact. The purpose of this work was to demonstrate a methodology for characterizing module impact response differences as a function of construction and incident hail parameters. Video capture and digital image analysis were able to capture out-of-plane module deformation to a resolution of ±0.1 mm at 11 kHz on an in-plane grid of 10 × 10 mm over the area of a 1 × 2 m commercial photovoltaic module. With lighting and optical adjustments, the technique was adaptable to arbitrary module designs, including size, backsheet color, and cell interconnection. Impacts were observed to produce an initially localized dimple in the glass surface, with peak deflection proportional to the square root of incident energy. Subsequent deformation propagation and dissipation were also captured, along with behavior for instances when the module glass fractured. Natural frequencies of the module were identifiable by analyzing module oscillations postimpact. Limitations of the measurement technique were that the impacting ice ball obscured the data field immediately surrounding the point of contact, and both ice and glass fracture events occurred within 100 μs, which was not resolvable at the chosen frame rate. Increasing the frame rate and visualizing the back surface of the impact could be applied to avoid these issues. Applications for these data include validating computational models for hail impacts, identifying the natural frequencies of a module, and identifying damage initiation mechanisms.
{"title":"Measurement of Photovoltaic Module Deformation Dynamics During Hail Impact Using Digital Image Correlation","authors":"James Y. Hartley;Michael A. Shimizu;Jennifer L. Braid;Ryan Flanagan;Phillip L. Reu","doi":"10.1109/JPHOTOV.2024.3405377","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2024.3405377","url":null,"abstract":"Stereo high-speed video of photovoltaic modules undergoing laboratory hail tests was processed using digital image correlation to determine module surface deformation during and immediately following impact. The purpose of this work was to demonstrate a methodology for characterizing module impact response differences as a function of construction and incident hail parameters. Video capture and digital image analysis were able to capture out-of-plane module deformation to a resolution of ±0.1 mm at 11 kHz on an in-plane grid of 10 × 10 mm over the area of a 1 × 2 m commercial photovoltaic module. With lighting and optical adjustments, the technique was adaptable to arbitrary module designs, including size, backsheet color, and cell interconnection. Impacts were observed to produce an initially localized dimple in the glass surface, with peak deflection proportional to the square root of incident energy. Subsequent deformation propagation and dissipation were also captured, along with behavior for instances when the module glass fractured. Natural frequencies of the module were identifiable by analyzing module oscillations postimpact. Limitations of the measurement technique were that the impacting ice ball obscured the data field immediately surrounding the point of contact, and both ice and glass fracture events occurred within 100 μs, which was not resolvable at the chosen frame rate. Increasing the frame rate and visualizing the back surface of the impact could be applied to avoid these issues. Applications for these data include validating computational models for hail impacts, identifying the natural frequencies of a module, and identifying damage initiation mechanisms.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141435484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An accurate solar irradiance forecast is critical to the reliable operation of electrical grids with increasing integration of photovoltaic systems. This study compares short-term solar irradiance forecasts based on sky images using seven different linear machine learning algorithms. In the first step, several features are extracted from sky images, reconstructed, and next used as exogenous inputs to seven machine learning algorithms, i.e., linear regression, least absolute shrinkage and selection operator (Lasso) regression, ridge regression, Bayesian ridge (BR) regression, stochastic gradient descent (SGD), generalized linear model (GLM) regression, and random sample consensus (RANSAC). A representative dataset of three years of sky images with 1-minute resolution from 2014 to 2016 serves for comparison together with the clear sky indexes as inputs to forecast ground-level solar radiances for up to 30 minutes ahead. The results of the abovementioned algorithms are compared, where for 5 and 10 minutes ahead, Lasso has the highest accuracy with a root-mean-square error (RMSE) of 0.05 and 0.062 kW/m 2 , while for 15 to 30 minutes ahead, stochastic gradient descent provides the most accurate forecast with an RMSE of 0.067, 0.071, 0.074, and 0.076 kW/m 2 for 15, 20, 25, and 30 minutes ahead horizons, respectively. For all the time horizons, Bayesian ridge is among the three most accurate models, and RANSAC has the highest error. The results show that ground-level solar irradiance can be forecasted with a relatively low average instantaneous error ranging from 0.05 to 0.1 kW/m 2 depending on the model and forecasting horizon without imposing a too high execution time overhead, namely, less than 7 s. The accuracy of the forecast can be improved if combined with cloud detection algorithms. Overall, ridge, Bayesian ridge, and stochastic gradient descent provide more accurate forecasts for short-term horizons.
{"title":"Sky Images for Short-Term Solar Irradiance Forecast: A Comparative Study of Linear Machine Learning Models","authors":"Elham Shirazi;Ivan Gordon;Angele Reinders;Francky Catthoor","doi":"10.1109/JPHOTOV.2024.3398365","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2024.3398365","url":null,"abstract":"An accurate solar irradiance forecast is critical to the reliable operation of electrical grids with increasing integration of photovoltaic systems. This study compares short-term solar irradiance forecasts based on sky images using seven different linear machine learning algorithms. In the first step, several features are extracted from sky images, reconstructed, and next used as exogenous inputs to seven machine learning algorithms, i.e., linear regression, least absolute shrinkage and selection operator (Lasso) regression, ridge regression, Bayesian ridge (BR) regression, stochastic gradient descent (SGD), generalized linear model (GLM) regression, and random sample consensus (RANSAC). A representative dataset of three years of sky images with 1-minute resolution from 2014 to 2016 serves for comparison together with the clear sky indexes as inputs to forecast ground-level solar radiances for up to 30 minutes ahead. The results of the abovementioned algorithms are compared, where for 5 and 10 minutes ahead, Lasso has the highest accuracy with a root-mean-square error (RMSE) of 0.05 and 0.062 kW/m\u0000<sup>2</sup>\u0000, while for 15 to 30 minutes ahead, stochastic gradient descent provides the most accurate forecast with an RMSE of 0.067, 0.071, 0.074, and 0.076 kW/m\u0000<sup>2</sup>\u0000 for 15, 20, 25, and 30 minutes ahead horizons, respectively. For all the time horizons, Bayesian ridge is among the three most accurate models, and RANSAC has the highest error. The results show that ground-level solar irradiance can be forecasted with a relatively low average instantaneous error ranging from 0.05 to 0.1 kW/m\u0000<sup>2</sup>\u0000 depending on the model and forecasting horizon without imposing a too high execution time overhead, namely, less than 7 s. The accuracy of the forecast can be improved if combined with cloud detection algorithms. Overall, ridge, Bayesian ridge, and stochastic gradient descent provide more accurate forecasts for short-term horizons.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141435483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The healthcare industry is constantly changing because of technological breakthroughs that spur new methods of diagnosing and treating illnesses. This study investigates the development of Ion Sensitive Field Effect Transistor (ISFET) sensors for DNA-based blood cancer diagnosis. This work presents the design of a two-dimensional ion-sensitive field-effect transistor. Concentration fluctuations and transfer characteristics with different oxides are studied using blood from two electrolyte solutions. It is possible to evaluate how the modeled device can be utilized as a pH sensor or a biosensor in healthcare applications by looking at how the pH changes for different oxides. Additionally, several oxides were examined in the simulated ISFET devices' output characteristics. Blood is the electrolyte to study the device's sensitivity for different oxides. When pH 7.4 is considered, SiO 2 oxide is significantly more sensitive than other oxides. The resulting 2D-ISFET exhibits remarkable blood electrolyte sensitivity and holds potential as a quick detection tool for blood cancer. The results show that the ISFET possesses drain-induced barrier lowering (DIBL), greater ON-current (ION ) and switching ratio ( ION/IOFF ), and decreased subthreshold swing (SS). The pH sensor's sensitivity and the suggested equipment can detect up to 30 fg/mL of blood cancer biomarkers. An important development in technology-driven healthcare is the emergence of DNA-based blood cancer detection utilizing ISFET sensors. This opens up new avenues for improving cancer diagnosis and patient outcomes.
{"title":"Design and Performance Analysis of ISFET Using Various Oxide Materials for Biosensing Applications","authors":"Sankararao Majji;Asisa Kumar Panigrahy;Depuru Shobha Rani;Muralidhar Nayak Bhukya;Chandra Sekhar Dash","doi":"10.1109/OJNANO.2024.3408845","DOIUrl":"https://doi.org/10.1109/OJNANO.2024.3408845","url":null,"abstract":"The healthcare industry is constantly changing because of technological breakthroughs that spur new methods of diagnosing and treating illnesses. This study investigates the development of Ion Sensitive Field Effect Transistor (ISFET) sensors for DNA-based blood cancer diagnosis. This work presents the design of a two-dimensional ion-sensitive field-effect transistor. Concentration fluctuations and transfer characteristics with different oxides are studied using blood from two electrolyte solutions. It is possible to evaluate how the modeled device can be utilized as a pH sensor or a biosensor in healthcare applications by looking at how the pH changes for different oxides. Additionally, several oxides were examined in the simulated ISFET devices' output characteristics. Blood is the electrolyte to study the device's sensitivity for different oxides. When pH 7.4 is considered, SiO\u0000<sub>2</sub>\u0000 oxide is significantly more sensitive than other oxides. The resulting 2D-ISFET exhibits remarkable blood electrolyte sensitivity and holds potential as a quick detection tool for blood cancer. The results show that the ISFET possesses drain-induced barrier lowering (DIBL), greater ON-current \u0000<italic>(I<sub>ON</sub></i>\u0000) and switching ratio (\u0000<italic>I<sub>ON</sub>/I<sub>OFF</sub></i>\u0000), and decreased subthreshold swing (SS). The pH sensor's sensitivity and the suggested equipment can detect up to 30 fg/mL of blood cancer biomarkers. An important development in technology-driven healthcare is the emergence of DNA-based blood cancer detection utilizing ISFET sensors. This opens up new avenues for improving cancer diagnosis and patient outcomes.","PeriodicalId":446,"journal":{"name":"IEEE Open Journal of Nanotechnology","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10547399","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141334029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-04DOI: 10.1109/TNANO.2024.3409055
Sanu Gayen;Suchismita Tewari;Avik Chattopadhyay
In this paper, for the first time, a unique Ge (1-x) Sn x alloy-based TFET sensor with a deliberate corner-point in the channel has been proposed for successful detection of S-protein, a significant biomarker. After the validation of our simulation scheme through a process of calibration of an experimentally realized mother GeSn TFET device, the same is turned into the proposed sensor device by suitably creating nanogap cavity in it. The performance of the proposed sensor device has been thoroughly investigated as a function of channel epilayer thickness (CH epi ) in terms of a set of performance metrics – P-responsivity and P-sensitivity. Then, by varying the mole-fraction of Ge (1-x) Sn x in the proposed sensor, the sensing performance has been studied in terms of the aforementioned performance metrics, along with an additional unique metric known as dynamic sensitivity. Interestingly, it has been observed that the most suitable device in pure electronic domain (digital or analog) is the least suited in sensing domain and vice-versa. This forbids the tendency of blind-picking of device with enhanced performance in pure electronic domain for sensing purpose as well without proper investigation. After a thorough analysis, it is observed that the proposed sensor with CH epi = 10 nm has evolved as the most optimized sensor device while the choice of mole-fraction remains application specific. Also, the ultimately optimized sensor shows a fairly good performance in dealing with the real-time position variability aspect (even if it is due to the repulsive steric effects of S-protein molecules) which results in a partial hybridization issue.
本文首次提出了一种独特的基于 Ge(1-x)Snx 合金的 TFET 传感器，该传感器在通道中特意设置了一个角点，用于成功检测 S 蛋白这种重要的生物标志物。通过对实验中实现的母 GeSn TFET 器件进行校准，验证了我们的模拟方案。根据一组性能指标--P 反应性和 P 灵敏度--沟道外延层厚度 (CHepi) 的函数，对所提出的传感器件的性能进行了深入研究。然后，通过改变拟议传感器中 Ge(1-x)Snx 的摩尔分数，根据上述性能指标以及称为动态灵敏度的额外独特指标对传感性能进行了研究。有趣的是，我们发现在纯电子领域（数字或模拟）最合适的设备在传感领域却最不合适，反之亦然。这就避免了在未进行适当调查的情况下，盲目选择在纯电子领域性能更强的器件用于传感目的。经过深入分析，我们发现 CHepi = 10 nm 的拟议传感器已发展成为最优化的传感器设备，而分子分数的选择仍与具体应用有关。此外，最终优化的传感器在处理实时位置变化方面（即使是由于 S 蛋白分子的排斥立体效应）表现出相当好的性能，这导致了部分杂交问题。
{"title":"A Judicious Exploitation of Electrical Characteristics of a Unique GeSn TFET With Corner-Point for Sensing S-Protein Biomarker","authors":"Sanu Gayen;Suchismita Tewari;Avik Chattopadhyay","doi":"10.1109/TNANO.2024.3409055","DOIUrl":"https://doi.org/10.1109/TNANO.2024.3409055","url":null,"abstract":"In this paper, for the first time, a unique Ge\u0000<sub>(1-x)</sub>\u0000Sn\u0000<sub>x</sub>\u0000 alloy-based TFET sensor with a deliberate corner-point in the channel has been proposed for successful detection of S-protein, a significant biomarker. After the validation of our simulation scheme through a process of calibration of an experimentally realized mother GeSn TFET device, the same is turned into the proposed sensor device by suitably creating nanogap cavity in it. The performance of the proposed sensor device has been thoroughly investigated as a function of channel epilayer thickness (CH\u0000<sub>epi</sub>\u0000) in terms of a set of performance metrics – P-responsivity and P-sensitivity. Then, by varying the mole-fraction of Ge\u0000<sub>(1-x)</sub>\u0000Sn\u0000<sub>x</sub>\u0000 in the proposed sensor, the sensing performance has been studied in terms of the aforementioned performance metrics, along with an additional unique metric known as dynamic sensitivity. Interestingly, it has been observed that the most suitable device in pure electronic domain (digital or analog) is the least suited in sensing domain and vice-versa. This forbids the tendency of blind-picking of device with enhanced performance in pure electronic domain for sensing purpose as well without proper investigation. After a thorough analysis, it is observed that the proposed sensor with CH\u0000<sub>epi</sub>\u0000 = 10 nm has evolved as the most optimized sensor device while the choice of mole-fraction remains application specific. Also, the ultimately optimized sensor shows a fairly good performance in dealing with the real-time position variability aspect (even if it is due to the repulsive steric effects of S-protein molecules) which results in a partial hybridization issue.","PeriodicalId":449,"journal":{"name":"IEEE Transactions on Nanotechnology","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141435358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-03DOI: 10.1109/TNANO.2024.3408253
Tauseef Ahmed;Mukul Kumar Das
This paper introduces a highly effective method to enhance the power conversion efficiency of thin-film solar cells with a microcrystalline absorber layer. The study involves the creation of a device simulation model that takes into account optical phenomena like light scattering and diffusive reflection, as well as electrical aspects related to the physics of heterointerfaces. The proposed design includes a textured front surface, silicon nanowires on the rear side of the absorber layer, and a back contact-cum-reflector composed of multiple alternative layers. To achieve optimal outcomes, it is essential to determine the ideal values for parameters such as the average width-to-height ratio of the textured front surface, the height of the backside nanowires, and the thickness and doping levels of different layers like ITO, emitter, buffer, and BSF. The findings indicate that when these parameters are set to their optimal values, the proposed structure can achieve a peak efficiency of 13.62%. This marks a substantial improvement of 34.70% when compared to the optimized flat thin-film solar cell structure.
{"title":"Enhanced Efficiency in Thin Film Solar Cells: Optimized Design With Front Nanotextured and Rear Nanowire-Based Light Trapping Structure","authors":"Tauseef Ahmed;Mukul Kumar Das","doi":"10.1109/TNANO.2024.3408253","DOIUrl":"https://doi.org/10.1109/TNANO.2024.3408253","url":null,"abstract":"This paper introduces a highly effective method to enhance the power conversion efficiency of thin-film solar cells with a microcrystalline absorber layer. The study involves the creation of a device simulation model that takes into account optical phenomena like light scattering and diffusive reflection, as well as electrical aspects related to the physics of heterointerfaces. The proposed design includes a textured front surface, silicon nanowires on the rear side of the absorber layer, and a back contact-cum-reflector composed of multiple alternative layers. To achieve optimal outcomes, it is essential to determine the ideal values for parameters such as the average width-to-height ratio of the textured front surface, the height of the backside nanowires, and the thickness and doping levels of different layers like ITO, emitter, buffer, and BSF. The findings indicate that when these parameters are set to their optimal values, the proposed structure can achieve a peak efficiency of 13.62%. This marks a substantial improvement of 34.70% when compared to the optimized flat thin-film solar cell structure.","PeriodicalId":449,"journal":{"name":"IEEE Transactions on Nanotechnology","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141435331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The adoption of a feasible bump shape exerts a significant impact on the functionality of a 3D IC. The cylindrical bump structure, considered among the most prevalent shape, endures significant delay, power loss and crosstalk challenges. The tapered based TSV-bump structure recently acquired prominence due to their ultra-low fraction of volume and coupling, resulting in significant alleviation of delay and crosstalk issues. The electrical RLGC modeling has been accomplished for cylindrical, barrel, hourglass and the tapered bump structures along with the impact of coupling, passivation and fringing on the redistribution layer (RDL). In order to validate the proposed TSV bump structure, the quantitative values of a via is compared against the EM and experimental results, and a subsequent investigation have been accomplished for the propagation delay, power dissipation, peak noise, insertion and reflection losses. The proposed via bump structure is remarkable consistence with the experimental results with an average deviation of only 3.51%. In addition, the Finite difference time-domain (FDTD) electromagnetic computation is employed to further examine the performance characteristics. Furthermore, it is worth emphasizing that the tapered bump structure can effectively reduce the propagation delay, power dissipation, peak noise, insertion and reflection losses with an average deviation of 34.83%, 28.62%, 29.98%, 13.57%, and 41.06%, respectively, when compared to the barrel, cylindrical and hourglass bumps.
{"title":"Electrical Modeling and Performance Analysis of Cu and CNT Based TSV-Bump-RDL","authors":"Shivangi Chandrakar;Kamal Solanki;Deepika Gupta;Manoj Kumar Majumder","doi":"10.1109/TNANO.2024.3408310","DOIUrl":"https://doi.org/10.1109/TNANO.2024.3408310","url":null,"abstract":"The adoption of a feasible bump shape exerts a significant impact on the functionality of a 3D IC. The cylindrical bump structure, considered among the most prevalent shape, endures significant delay, power loss and crosstalk challenges. The tapered based TSV-bump structure recently acquired prominence due to their ultra-low fraction of volume and coupling, resulting in significant alleviation of delay and crosstalk issues. The electrical \u0000<italic>RLGC</i>\u0000 modeling has been accomplished for cylindrical, barrel, hourglass and the tapered bump structures along with the impact of coupling, passivation and fringing on the redistribution layer (RDL). In order to validate the proposed TSV bump structure, the quantitative values of a via is compared against the EM and experimental results, and a subsequent investigation have been accomplished for the propagation delay, power dissipation, peak noise, insertion and reflection losses. The proposed via bump structure is remarkable consistence with the experimental results with an average deviation of only 3.51%. In addition, the Finite difference time-domain (FDTD) electromagnetic computation is employed to further examine the performance characteristics. Furthermore, it is worth emphasizing that the tapered bump structure can effectively reduce the propagation delay, power dissipation, peak noise, insertion and reflection losses with an average deviation of 34.83%, 28.62%, 29.98%, 13.57%, and 41.06%, respectively, when compared to the barrel, cylindrical and hourglass bumps.","PeriodicalId":449,"journal":{"name":"IEEE Transactions on Nanotechnology","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141435359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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