Pub Date : 2024-07-19DOI: 10.1088/1402-4896/ad65bf
Y. EL BASSEM, Mohamed Eladri, A. El Batoul, Mostafa Oulne
The covariant density functional theory is utilized to examine the evolution of shape in even-even 96−130Pd isotopes by using the density-dependent meson-exchange DD-ME2 and the density-dependent point-coupling DD-PC1. This research is carried out by considering the evolution of the ground-state shapes derived from calculations of the axial and triaxial potential energy surfaces. The shape transition in the palladium isotopic chain is very clearly manifested. In addition, various ground-state properties including binding energy, charge radii, two-neutron separation energy, and two-neutron shell gap have been calculated and have been observed to closely match the existing experimental data. Moreover, a robust shell closure is distinctly observed at the magic neutron number N = 82.
通过使用密度依赖介子交换 DD-ME2 和密度依赖点耦合 DD-PC1，利用协变密度泛函理论来研究偶偶 96-130Pd 同位素的形状演变。这项研究是通过考虑轴向和三轴势能面计算得出的基态形状的演变来进行的。钯同位素链的形状转变非常明显。此外，还计算了各种基态性质，包括结合能、电荷半径、双中子分离能和双中子壳间隙，并观察到这些性质与现有的实验数据非常吻合。此外，在神奇的中子数 N = 82 时，可以明显观察到强大的壳封闭。
{"title":"Nuclear shape evolution in even-even Pd isotopic chain","authors":"Y. EL BASSEM, Mohamed Eladri, A. El Batoul, Mostafa Oulne","doi":"10.1088/1402-4896/ad65bf","DOIUrl":"https://doi.org/10.1088/1402-4896/ad65bf","url":null,"abstract":"\u0000 The covariant density functional theory is utilized to examine the evolution of shape in even-even 96−130Pd isotopes by using the density-dependent meson-exchange DD-ME2 and the density-dependent point-coupling DD-PC1. This research is carried out by considering the evolution of the ground-state shapes derived from calculations of the axial and triaxial potential energy surfaces. The shape transition in the palladium isotopic chain is very clearly manifested. In addition, various ground-state properties including binding energy, charge radii, two-neutron separation energy, and two-neutron shell gap have been calculated and have been observed to closely match the existing experimental data. Moreover, a robust shell closure is distinctly observed at the magic neutron number N = 82.","PeriodicalId":503429,"journal":{"name":"Physica Scripta","volume":"118 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141821148","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 : 2024-07-19DOI: 10.1088/1402-4896/ad65be
Hossein Ghazavi, M. Kolahdoozan, Nosratollah Solhjoei, Mohammad Saadat, Sayed Hasan Mirtalaie
This study explores the influence of chromium layer thickness on the thermal stability and agglomeration of Cr/Ag/Cr sandwich layers used in MEMS applications. Achieving uniform and consistent deposition of thin films is crucial for optimal device performance. Magnetron sputtering, a technique offering precise control over film properties, is commonly employed for depositing thin films in MEMS. Silver is a popular choice due to its desirable properties, but it tends to agglomerate at high temperatures. The researchers investigated the effect of chromium layer thickness on thermal stability and agglomeration. They deposited chromium layers of varying thicknesses onto silicon substrates, followed by a silver layer and another chromium layer to create a sandwich structure. Annealing was performed at different temperatures to assess thermal stability and prevent silver agglomeration. Thermal stability was evaluated by measuring electrical resistance using a four-point probe method, and surface topography was analyzed using a non-contact atomic force microscope. The goal was to identify the optimal chromium layer thickness to minimize agglomeration and maximize thermal stability. The results showed that a sandwich structure with a 5 nm top chromium layer (Si/Cr (5 nm)/Ag (100 nm)/Cr (5-10-15-20 nm)) exhibited decreased adhesion force with increasing annealing temperatures. The use of a chromium sandwich layer significantly reduced surface roughness, as indicated by reductions in Ra and RMS values. A 15 nm thick chromium layer above and below the silver layer provided the best thermal stability and prevented silver agglomeration, resulting in the highest degree of adhesion. This thickness also yielded optimal surface parameters for the chromium sandwich layers at the annealing temperatures. In conclusion, the study demonstrates that the thickness of the chromium layer influences thermal stability, agglomeration, and surface parameters in MEMS applications and enables better control over thin film deposition.
{"title":"Investigating the influence of chromium layer thickness on thermal stability, adhesion and agglomeration of Cr/Ag/Cr sandwich layers in microelectromechanical systems (MEMS)","authors":"Hossein Ghazavi, M. Kolahdoozan, Nosratollah Solhjoei, Mohammad Saadat, Sayed Hasan Mirtalaie","doi":"10.1088/1402-4896/ad65be","DOIUrl":"https://doi.org/10.1088/1402-4896/ad65be","url":null,"abstract":"\u0000 This study explores the influence of chromium layer thickness on the thermal stability and agglomeration of Cr/Ag/Cr sandwich layers used in MEMS applications. Achieving uniform and consistent deposition of thin films is crucial for optimal device performance. Magnetron sputtering, a technique offering precise control over film properties, is commonly employed for depositing thin films in MEMS. Silver is a popular choice due to its desirable properties, but it tends to agglomerate at high temperatures. The researchers investigated the effect of chromium layer thickness on thermal stability and agglomeration. They deposited chromium layers of varying thicknesses onto silicon substrates, followed by a silver layer and another chromium layer to create a sandwich structure. Annealing was performed at different temperatures to assess thermal stability and prevent silver agglomeration. Thermal stability was evaluated by measuring electrical resistance using a four-point probe method, and surface topography was analyzed using a non-contact atomic force microscope. The goal was to identify the optimal chromium layer thickness to minimize agglomeration and maximize thermal stability. The results showed that a sandwich structure with a 5 nm top chromium layer (Si/Cr (5 nm)/Ag (100 nm)/Cr (5-10-15-20 nm)) exhibited decreased adhesion force with increasing annealing temperatures. The use of a chromium sandwich layer significantly reduced surface roughness, as indicated by reductions in Ra and RMS values. A 15 nm thick chromium layer above and below the silver layer provided the best thermal stability and prevented silver agglomeration, resulting in the highest degree of adhesion. This thickness also yielded optimal surface parameters for the chromium sandwich layers at the annealing temperatures. In conclusion, the study demonstrates that the thickness of the chromium layer influences thermal stability, agglomeration, and surface parameters in MEMS applications and enables better control over thin film deposition.","PeriodicalId":503429,"journal":{"name":"Physica Scripta","volume":" April","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141824223","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 : 2024-07-19DOI: 10.1088/1402-4896/ad65c3
Bin Cai, Lingling Yang, Lingxiao Wu, Yongzhi Cheng, Xiangcheng Li
In this paper, a novel design of a dual-narrowband metamaterial absorber (MMA) was proposed for use as a high-performance refractive index (RI) sensor in the terahertz (THz) region. The proposed MMA is based on a vertical-ring-shaped (VRS) structure gold film array. Through numerical simulation, it was found that the MMA can achieve high absorption levels of 99.8% and 94.6% at 1.723 THz and 2.457 THz, respectively, which are consistent with the values obtained using coupling mode theory (CMT). The MMA also exhibits high Q-factor values of about 27.35 and 102.38, respectively, which are close to the CMT values of 29.94 and 98.34. The dual-band strong absorption of the MMA is attributed to the guided modes of the critical coupling resonance, and the absorption properties can be adjusted by changing the geometrical parameters of the unit-cell structure of the MMA. The proposed MMA has a narrowband and a higher Q-factor, making it suitable for RI sensing, with a sensitivity of about 1.66 and 1.88 THz/RIU, and a figure-of-merit (FOM) of about 259.4 and 659.7 RIU−1, respectively. These findings open up new opportunities for the development of highly efficient MMAs, which have potential applications in biochemical sensing and detection in the THz region.
{"title":"Dual-narrowband terahertz metamaterial absorber based on all-metal vertical ring array for enhanced sensing application","authors":"Bin Cai, Lingling Yang, Lingxiao Wu, Yongzhi Cheng, Xiangcheng Li","doi":"10.1088/1402-4896/ad65c3","DOIUrl":"https://doi.org/10.1088/1402-4896/ad65c3","url":null,"abstract":"\u0000 In this paper, a novel design of a dual-narrowband metamaterial absorber (MMA) was proposed for use as a high-performance refractive index (RI) sensor in the terahertz (THz) region. The proposed MMA is based on a vertical-ring-shaped (VRS) structure gold film array. Through numerical simulation, it was found that the MMA can achieve high absorption levels of 99.8% and 94.6% at 1.723 THz and 2.457 THz, respectively, which are consistent with the values obtained using coupling mode theory (CMT). The MMA also exhibits high Q-factor values of about 27.35 and 102.38, respectively, which are close to the CMT values of 29.94 and 98.34. The dual-band strong absorption of the MMA is attributed to the guided modes of the critical coupling resonance, and the absorption properties can be adjusted by changing the geometrical parameters of the unit-cell structure of the MMA. The proposed MMA has a narrowband and a higher Q-factor, making it suitable for RI sensing, with a sensitivity of about 1.66 and 1.88 THz/RIU, and a figure-of-merit (FOM) of about 259.4 and 659.7 RIU−1, respectively. These findings open up new opportunities for the development of highly efficient MMAs, which have potential applications in biochemical sensing and detection in the THz region.","PeriodicalId":503429,"journal":{"name":"Physica Scripta","volume":"118 41","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822093","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}
Potassium doped lanthanum manganese perovskite oxides, La1-xKxMnO3, with nanofibrous structure, are prepared and used for Photo-Fenton degradation of antibiotics, including ciprofloxacin (CIP), tetracycline (TC), and sulfathiazole (ST). Effects of K doping on the textural structure, optical property, band gap and surface chemistry of LaMnO3 are investigated, showing that La0.95K0.05MnO3 (LKMO-5) has the optimal properties. The photoelectric measurements, including photoluminescence (PL), photocurrent response (PCR) and electrochemical impedance spectroscopy (EIS), also suggest that the LKMO-5 has the best electron-hole separation efficiency, the most amounts of irradiated electrons and the lowest impedance. Photocatalytic tests indicate that LKMO-5 not only shows the best activity for CIP degradation, but also exhibits good stability in the reaction, with negligible activity loss within four cycles. Mechanism investigations, explored by the radical trapping experiments and with the reference of band positions, indicate that superoxide radical ions (•O2-) and holes (h+) are the major reactive species of the reaction.
{"title":"Nanofibrous La0.95K0.05MnO3 perovskite with improved photoelectrical properties for photocatalytic degradation of antibiotics","authors":"Tianzong Yang, Yating Mei, Lulu Chen, Xuelian Xu, Jiaqi Wei, Junjiang Zhu","doi":"10.1088/1402-4896/ad65c8","DOIUrl":"https://doi.org/10.1088/1402-4896/ad65c8","url":null,"abstract":"\u0000 Potassium doped lanthanum manganese perovskite oxides, La1-xKxMnO3, with nanofibrous structure, are prepared and used for Photo-Fenton degradation of antibiotics, including ciprofloxacin (CIP), tetracycline (TC), and sulfathiazole (ST). Effects of K doping on the textural structure, optical property, band gap and surface chemistry of LaMnO3 are investigated, showing that La0.95K0.05MnO3 (LKMO-5) has the optimal properties. The photoelectric measurements, including photoluminescence (PL), photocurrent response (PCR) and electrochemical impedance spectroscopy (EIS), also suggest that the LKMO-5 has the best electron-hole separation efficiency, the most amounts of irradiated electrons and the lowest impedance. Photocatalytic tests indicate that LKMO-5 not only shows the best activity for CIP degradation, but also exhibits good stability in the reaction, with negligible activity loss within four cycles. Mechanism investigations, explored by the radical trapping experiments and with the reference of band positions, indicate that superoxide radical ions (•O2-) and holes (h+) are the major reactive species of the reaction.","PeriodicalId":503429,"journal":{"name":"Physica Scripta","volume":"115 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141821927","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 : 2024-07-19DOI: 10.1088/1402-4896/ad65c1
Pallavi Priyadarshini, Jose V. Mathew, Deepak N N Mathad, Rajesh Kumar
The Low Energy High Intensity Proton Accelerator (LEHIPA) has been commissioned to the design energy of 20 MeV at BARC, India. The low energy beam transport (LEBT) channel of LEHIPA consists of two solenoids and drift spaces for matching the 50 keV proton beam from the ECR ion source (ECR-IS) to the RFQ. The ion beam extracted from the ECR-IS also contains molecular species like H2+ and H3+. Proton fraction in the beam is found to degrade slowly with time due to surface contamination of the plasma chamber and this reduction in proton beam current has implications for longitudinal and transverse beam dynamics. Hence, it becomes important to characterise the beam at different proton fraction levels to understand the end-to-end beam dynamics of LEHIPA. Computed Tomography (CT) technique has been used for the beam phase-space reconstruction in LEHIPA, using a Python program, incorporating the feature of filtering secondary species from the beam profiles measured using slit scanners in the LEBT. Simultaneous Algebraic Reconstruction Technique (SART) is used in the reconstruction since it is identified to be a better technique for a limited number of projections. The reconstruction program is benchmarked with the TraceWin beam dynamics code and implemented on the measured beam profiles to recreate the phase space distribution at the beginning of LEBT. Further, the tomographic reconstruction method is compared with the solenoid scan method and the rms emittance values are found to be in good agreement. The measured tomographic phase space distribution has then been used as TraceWin input for LEHIPA end-end beam dynamics simulations and the LEHIPA beam line parameters are re-optimized for minimum beam emittance growth. This paper presents the simulations of CT technique, benchmarking simulations with TraceWin, phase space reconstruction with measured beam profiles and beam dynamics studies of LEHIPA using the reconstructed beam distributions.
{"title":"Phase space reconstruction technique for beam optimization in the Low Energy High Intensity Proton Accelerator (LEHIPA)","authors":"Pallavi Priyadarshini, Jose V. Mathew, Deepak N N Mathad, Rajesh Kumar","doi":"10.1088/1402-4896/ad65c1","DOIUrl":"https://doi.org/10.1088/1402-4896/ad65c1","url":null,"abstract":"\u0000 The Low Energy High Intensity Proton Accelerator (LEHIPA) has been commissioned to the design energy of 20 MeV at BARC, India. The low energy beam transport (LEBT) channel of LEHIPA consists of two solenoids and drift spaces for matching the 50 keV proton beam from the ECR ion source (ECR-IS) to the RFQ. The ion beam extracted from the ECR-IS also contains molecular species like H2+ and H3+. Proton fraction in the beam is found to degrade slowly with time due to surface contamination of the plasma chamber and this reduction in proton beam current has implications for longitudinal and transverse beam dynamics. Hence, it becomes important to characterise the beam at different proton fraction levels to understand the end-to-end beam dynamics of LEHIPA. Computed Tomography (CT) technique has been used for the beam phase-space reconstruction in LEHIPA, using a Python program, incorporating the feature of filtering secondary species from the beam profiles measured using slit scanners in the LEBT. Simultaneous Algebraic Reconstruction Technique (SART) is used in the reconstruction since it is identified to be a better technique for a limited number of projections. The reconstruction program is benchmarked with the TraceWin beam dynamics code and implemented on the measured beam profiles to recreate the phase space distribution at the beginning of LEBT. Further, the tomographic reconstruction method is compared with the solenoid scan method and the rms emittance values are found to be in good agreement. The measured tomographic phase space distribution has then been used as TraceWin input for LEHIPA end-end beam dynamics simulations and the LEHIPA beam line parameters are re-optimized for minimum beam emittance growth. This paper presents the simulations of CT technique, benchmarking simulations with TraceWin, phase space reconstruction with measured beam profiles and beam dynamics studies of LEHIPA using the reconstructed beam distributions.","PeriodicalId":503429,"journal":{"name":"Physica Scripta","volume":"116 34","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822212","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 : 2024-07-19DOI: 10.1088/1402-4896/ad65c6
Yiqing Zhang, Feng Xu, Zhenbo Li
The outstanding physical properties of hexagonal boron nitride (h-BN) make it highly valuable for use in nanoelectromechanical systems. We investigate the nonlinear stochastic vibration of h-BN nanowire affected by piezoelectric. The nonlinear beam model considering the impact of piezoelectric effect excited by random force is established. Molecular dynamic simulations were utilized to determine the potential energy of h-BN nanowires under varying amplitudes affected by an external electric field. The findings suggest that an increase in the intensity of the electric field can result in buckling behavior, leading to the appearance of two stable points. The cases of pre-buckling and post-buckling of nonlinear dynamic behavior of h-BN nanowire induced by piezoelectric effect is discussed in this paper. Furthermore, the impact of the intensity of random force on the nonlinear stochastic vibration characteristics of h-BN nanowire is also examined.
{"title":"The influence of Piezoelectric on the Nonlinear Stochastic Vibration of BN Nanoresonator","authors":"Yiqing Zhang, Feng Xu, Zhenbo Li","doi":"10.1088/1402-4896/ad65c6","DOIUrl":"https://doi.org/10.1088/1402-4896/ad65c6","url":null,"abstract":"\u0000 The outstanding physical properties of hexagonal boron nitride (h-BN) make it highly valuable for use in nanoelectromechanical systems. We investigate the nonlinear stochastic vibration of h-BN nanowire affected by piezoelectric. The nonlinear beam model considering the impact of piezoelectric effect excited by random force is established. Molecular dynamic simulations were utilized to determine the potential energy of h-BN nanowires under varying amplitudes affected by an external electric field. The findings suggest that an increase in the intensity of the electric field can result in buckling behavior, leading to the appearance of two stable points. The cases of pre-buckling and post-buckling of nonlinear dynamic behavior of h-BN nanowire induced by piezoelectric effect is discussed in this paper. Furthermore, the impact of the intensity of random force on the nonlinear stochastic vibration characteristics of h-BN nanowire is also examined.","PeriodicalId":503429,"journal":{"name":"Physica Scripta","volume":"111 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141821326","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 : 2024-07-19DOI: 10.1088/1402-4896/ad65c0
S. Dash
In this work, we have designed a chemical gas sensor using a Z-shaped gate tunnel FET with a SiGe source. Here, the gate material is a conducting organic polymer, which allows for the effective detection of a variety of chemical analytes. Over the course of the sensitivity investigation, several chemical analytes were exposed, including hexane, methanol, iso-propanol, and chloroform. Detecting chemical gases is feasible due to the work-function modification of the conducting polymer with exposure to the chemical gas vapors. This leads to modifications in the electrical properties of the suggested gas sensor, which serves as a sensing metric. The impact of surrounding temperature on various sensitivity parameters of the TFET-based gas sensor is also investigated. The proposed heterostructure Z-TFET (ZHS-TFET) offers a peak drain current sensitivity of 5.65×105 in the case of chloroform, which is four times higher than the sensitivity provided by the ZTFET sensor. Further, the suggested chemical sensor offers a higher subthreshold swing sensitivity (SSS) of 0.29 and a current ratio sensitivity (Sratio) of 3.18. As a result of its higher-sensitivity nature and improved electrostatic performance, the proposed sensor with conducting polymer as the gate metal may be able to meet the needs of the chemical and pharmaceutical industries, as well as environmental monitoring and biological diagnostics.
在这项工作中，我们设计了一种化学气体传感器，采用了带有硅锗源的 Z 型栅极隧道场效应晶体管。这里的栅极材料是一种导电有机聚合物，可以有效检测多种化学分析物。在灵敏度调查过程中，暴露了多种化学分析物，包括正己烷、甲醇、异丙醇和氯仿。由于导电聚合物在接触化学气体蒸汽后会发生功函数改变，因此可以检测化学气体。这导致所建议的气体传感器的电特性发生改变，从而成为一种传感指标。此外，还研究了周围温度对基于 TFET 的气体传感器各种灵敏度参数的影响。所提出的异质结构 Z-TFET（ZHS-TFET）对氯仿的漏极电流峰值灵敏度为 5.65×105，是 ZTFET 传感器灵敏度的四倍。此外，所建议的化学传感器还具有更高的阈下摆动灵敏度（SSS）（0.29）和电流比灵敏度（Sratio）（3.18）。由于具有更高的灵敏度和更好的静电性能，使用导电聚合物作为栅极金属的拟议传感器可以满足化学和制药行业以及环境监测和生物诊断的需要。
{"title":"Design and Sensitivity Study of a Novel Z-shaped Gate TFET Sensor with SiGe Source for Chemical Analyte Detection","authors":"S. Dash","doi":"10.1088/1402-4896/ad65c0","DOIUrl":"https://doi.org/10.1088/1402-4896/ad65c0","url":null,"abstract":"\u0000 In this work, we have designed a chemical gas sensor using a Z-shaped gate tunnel FET with a SiGe source. Here, the gate material is a conducting organic polymer, which allows for the effective detection of a variety of chemical analytes. Over the course of the sensitivity investigation, several chemical analytes were exposed, including hexane, methanol, iso-propanol, and chloroform. Detecting chemical gases is feasible due to the work-function modification of the conducting polymer with exposure to the chemical gas vapors. This leads to modifications in the electrical properties of the suggested gas sensor, which serves as a sensing metric. The impact of surrounding temperature on various sensitivity parameters of the TFET-based gas sensor is also investigated. The proposed heterostructure Z-TFET (ZHS-TFET) offers a peak drain current sensitivity of 5.65×105 in the case of chloroform, which is four times higher than the sensitivity provided by the ZTFET sensor. Further, the suggested chemical sensor offers a higher subthreshold swing sensitivity (SSS) of 0.29 and a current ratio sensitivity (Sratio) of 3.18. As a result of its higher-sensitivity nature and improved electrostatic performance, the proposed sensor with conducting polymer as the gate metal may be able to meet the needs of the chemical and pharmaceutical industries, as well as environmental monitoring and biological diagnostics.","PeriodicalId":503429,"journal":{"name":"Physica Scripta","volume":"107 40","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141821649","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 : 2024-07-19DOI: 10.1088/1402-4896/ad65c5
C. Ibebuchi, Seth Rainey, O. Obarein, Silva Alindomar, Cameron C. Lee
Accurate forecasting of the El Niño Southern Oscillation (ENSO) plays a critical role in mitigating the impacts of extreme weather conditions linked to ENSO variability on ecosystems. This study evaluates the performance of six machine learning models in forecasting two ENSO types: the Central Pacific El Niño (Niño 4 index) and the East Central Pacific El Niño (Niño 3.4 index). The models analyzed include the Feed Forward Neural Network (FFNN), Long Short-term Memory (LSTM) neural network, eXtreme Gradient Boosting Regressor, K-Nearest Neighbors Regressor, Gradient Boosting Regressor, and Support Vector Regressor, using the ENSO index lagged by six months as the predictor. The models were trained on the monthly ENSO indices from 1870 to 1992 and tested from 1993 to 2023. We also assess the relative predictability of the two ENSO types. Events were defined as when the ENSO index exceeded ±0.4. Our evaluation during the testing period reveals that for the analyzed models, the deep neural network models (LSTM and FFNN) demonstrated superior performance in forecasting ENSO at a 6-month lead time. Furthermore, all models achieved impressive all-season correlations ranging from 0.93 to 0.97 and threat score for the ENSO phases between 0.71 to 0.88 for Niño 3.4 events, and 0.72 to 0.93 for Niño 4 events. The predictability of the two ENSO types depended on the model and strength of the ENSO event. Considering both ENSO phases, La Niña events were forecasted with a higher accuracy relative to El Niño events, and all models, besides the deep learning models, notably fell short in capturing the extreme 2015/2016 Central Pacific El Niño event. These results highlight the potential of machine learning models, particularly the deep learning approaches, for skillful ENSO forecasting, by leveraging its historical data.
{"title":"Comparison of machine learning models in forecasting different ENSO types","authors":"C. Ibebuchi, Seth Rainey, O. Obarein, Silva Alindomar, Cameron C. Lee","doi":"10.1088/1402-4896/ad65c5","DOIUrl":"https://doi.org/10.1088/1402-4896/ad65c5","url":null,"abstract":"\u0000 Accurate forecasting of the El Niño Southern Oscillation (ENSO) plays a critical role in mitigating the impacts of extreme weather conditions linked to ENSO variability on ecosystems. This study evaluates the performance of six machine learning models in forecasting two ENSO types: the Central Pacific El Niño (Niño 4 index) and the East Central Pacific El Niño (Niño 3.4 index). The models analyzed include the Feed Forward Neural Network (FFNN), Long Short-term Memory (LSTM) neural network, eXtreme Gradient Boosting Regressor, K-Nearest Neighbors Regressor, Gradient Boosting Regressor, and Support Vector Regressor, using the ENSO index lagged by six months as the predictor. The models were trained on the monthly ENSO indices from 1870 to 1992 and tested from 1993 to 2023. We also assess the relative predictability of the two ENSO types. Events were defined as when the ENSO index exceeded ±0.4. Our evaluation during the testing period reveals that for the analyzed models, the deep neural network models (LSTM and FFNN) demonstrated superior performance in forecasting ENSO at a 6-month lead time. Furthermore, all models achieved impressive all-season correlations ranging from 0.93 to 0.97 and threat score for the ENSO phases between 0.71 to 0.88 for Niño 3.4 events, and 0.72 to 0.93 for Niño 4 events. The predictability of the two ENSO types depended on the model and strength of the ENSO event. Considering both ENSO phases, La Niña events were forecasted with a higher accuracy relative to El Niño events, and all models, besides the deep learning models, notably fell short in capturing the extreme 2015/2016 Central Pacific El Niño event. These results highlight the potential of machine learning models, particularly the deep learning approaches, for skillful ENSO forecasting, by leveraging its historical data.","PeriodicalId":503429,"journal":{"name":"Physica Scripta","volume":"121 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141820920","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 : 2024-07-19DOI: 10.1088/1402-4896/ad65c9
Genji Fujii
Tunneling magnetoresistance effects result in a high-performance magnetic head, enabling a high magnetic domain density in a platter. This conventional method of using magnetic flux to read or write is close to the magnetic domain density limit. Herein, we propose a conceptional method for developing a magnetic head by controlling phase-induced tunneling magnetoresistance effects. The developed magnetic head can be read out in units of 1 qubit. However, because recording data per BEC qubit is difficult due to thermal fluctuations, we evaluated the robustness of the method and concluded that it is robust to bit flips. Our method does not use a magnetic field for reading or writing, further suggesting that one may use a microwave instead. This is a distinguishing feature, allowing further integration of the magnetic domain density in a platter.
{"title":"Conceptional proposal of a microwave-only quantum magnetic head by phase-induced tunneling magnetoresistance effects and of a 3-dimensional multilayer platter","authors":"Genji Fujii","doi":"10.1088/1402-4896/ad65c9","DOIUrl":"https://doi.org/10.1088/1402-4896/ad65c9","url":null,"abstract":"\u0000 Tunneling magnetoresistance effects result in a high-performance magnetic head, enabling a high magnetic domain density in a platter. This conventional method of using magnetic flux to read or write is close to the magnetic domain density limit. Herein, we propose a conceptional method for developing a magnetic head by controlling phase-induced tunneling magnetoresistance effects. The developed magnetic head can be read out in units of 1 qubit. However, because recording data per BEC qubit is difficult due to thermal fluctuations, we evaluated the robustness of the method and concluded that it is robust to bit flips. Our method does not use a magnetic field for reading or writing, further suggesting that one may use a microwave instead. This is a distinguishing feature, allowing further integration of the magnetic domain density in a platter.","PeriodicalId":503429,"journal":{"name":"Physica Scripta","volume":"121 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822224","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 : 2024-07-19DOI: 10.1088/1402-4896/ad65bd
Feng Han, Hua Han, Rui Zhang, Yong Zou, Long Xue, Caimei Wang
In the process of industrial production, product defects often arise due to improper operations among other reasons, rendering the detection of such flaws an indispensable procedure. However, the vast array of defect types, coupled with their complex characteristics, poses ongoing challenges for contemporary defect detection algorithms within industrial settings. To solve this problem, the present study introduces an enhanced steel surface defect detection model based on the modified YOLOv8 algorithm—termed the MAA-YOLOv8 model—to augment the accuracy and practicality of the algorithm. Initially, a multi-head attention mechanism was incorporated into the C2f to bolster the feature extraction capabilities within the backbone network and diversify the attention maps. Secondly, in the neck structure, we design a multi-channel feature fusion module (McPAN) to solve the problem of balance between computational efficiency and the ability to capture useful features. A series of experiments conducted on the NEU-DET dataset reveal that the MAA-YOLOv8 model achieves a mean Average Precision (mAP) of 94.4%, representing an enhancement of 11.1% over the original YOLOv8s model. The MAA-YOLOv8 model proposed in this study substantially elevates the performance of steel surface defect detection while ensuring the speed of detection.
{"title":"MAA-YOLOv8: enhanced steel surface defect detection through multi-head attention mechanism and lightweight feature fusion","authors":"Feng Han, Hua Han, Rui Zhang, Yong Zou, Long Xue, Caimei Wang","doi":"10.1088/1402-4896/ad65bd","DOIUrl":"https://doi.org/10.1088/1402-4896/ad65bd","url":null,"abstract":"\u0000 In the process of industrial production, product defects often arise due to improper operations among other reasons, rendering the detection of such flaws an indispensable procedure. However, the vast array of defect types, coupled with their complex characteristics, poses ongoing challenges for contemporary defect detection algorithms within industrial settings. To solve this problem, the present study introduces an enhanced steel surface defect detection model based on the modified YOLOv8 algorithm—termed the MAA-YOLOv8 model—to augment the accuracy and practicality of the algorithm. Initially, a multi-head attention mechanism was incorporated into the C2f to bolster the feature extraction capabilities within the backbone network and diversify the attention maps. Secondly, in the neck structure, we design a multi-channel feature fusion module (McPAN) to solve the problem of balance between computational efficiency and the ability to capture useful features. A series of experiments conducted on the NEU-DET dataset reveal that the MAA-YOLOv8 model achieves a mean Average Precision (mAP) of 94.4%, representing an enhancement of 11.1% over the original YOLOv8s model. The MAA-YOLOv8 model proposed in this study substantially elevates the performance of steel surface defect detection while ensuring the speed of detection.","PeriodicalId":503429,"journal":{"name":"Physica Scripta","volume":" 980","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141823192","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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