Pub Date : 2020-09-23DOI: 10.23919/SISPAD49475.2020.9241590
Junhyeok Kim, Jaehyun Yoo, Jaehyun Jung, Kwangtea Kim, Jae-Soon Bae, Yoon-suk Kim, Ohkyum kwon, U. Kwon, D. Kim
The novel optimization method for BCD(Bipolar-CMOS-DMOS) process development based on Machine Learning(ML) and statistical process modeling considering the entire wafer variation is proposed to improve the device and process competitiveness. The self-align PBODY process is used for high-performance N-type Lateral Diffused Metal Oxide Semiconductor(NLDMOS) in BCD process and it also is related to stability in PMIC operation. The process modeling embracing the performance and the stability of LDMOS is performed with TCAD using inline data. For the development of BCD process, the PBODY process parameters are optimized through the ML algorithms and the condition is verified with TCAD and silicon test. Finally, we can secure new low voltage NLDMOS with the improved performance and stability respectively for without any degradation in the new 0.13μm BCD process.
{"title":"Novel Optimization Method using Machine-learning for Device and Process Competitiveness of BCD Process","authors":"Junhyeok Kim, Jaehyun Yoo, Jaehyun Jung, Kwangtea Kim, Jae-Soon Bae, Yoon-suk Kim, Ohkyum kwon, U. Kwon, D. Kim","doi":"10.23919/SISPAD49475.2020.9241590","DOIUrl":"https://doi.org/10.23919/SISPAD49475.2020.9241590","url":null,"abstract":"The novel optimization method for BCD(Bipolar-CMOS-DMOS) process development based on Machine Learning(ML) and statistical process modeling considering the entire wafer variation is proposed to improve the device and process competitiveness. The self-align PBODY process is used for high-performance N-type Lateral Diffused Metal Oxide Semiconductor(NLDMOS) in BCD process and it also is related to stability in PMIC operation. The process modeling embracing the performance and the stability of LDMOS is performed with TCAD using inline data. For the development of BCD process, the PBODY process parameters are optimized through the ML algorithms and the condition is verified with TCAD and silicon test. Finally, we can secure new low voltage NLDMOS with the improved performance and stability respectively for without any degradation in the new 0.13μm BCD process.","PeriodicalId":206964,"journal":{"name":"2020 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132737034","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 : 2020-09-23DOI: 10.23919/SISPAD49475.2020.9241592
Peter D. Reyntjens, Sabyasachi Tiwari, M. V. D. Put, B. Sorée, W. Vandenberghe
We theoretically investigate the effect of intercalation of third row transition metals (Co, Cr, Fe, Mn, Ti and V) in the layers of WSe2. Using density functional theory (DFT), we investigate the structural stability. We also compute the DFT energies of various magnetic spin configurations. Using these energies, we construct a Heisenberg Hamiltonian and perform a Monte Carlo study on each WSe2 + intercalant system to estimate the Curie or Néel temperature. We find ferromagnetic ground states for Ti and Cr intercalation, with Curie temperatures of 31K and 225K, respectively. In Fe-intercalated WSe2, we predict that antiferromagnetic ordering is present up to 564K. For V intercalation, we find that the system exhibits a double phase transition.
{"title":"Ab-initio Study of Magnetically Intercalated Tungsten Diselenide","authors":"Peter D. Reyntjens, Sabyasachi Tiwari, M. V. D. Put, B. Sorée, W. Vandenberghe","doi":"10.23919/SISPAD49475.2020.9241592","DOIUrl":"https://doi.org/10.23919/SISPAD49475.2020.9241592","url":null,"abstract":"We theoretically investigate the effect of intercalation of third row transition metals (Co, Cr, Fe, Mn, Ti and V) in the layers of WSe2. Using density functional theory (DFT), we investigate the structural stability. We also compute the DFT energies of various magnetic spin configurations. Using these energies, we construct a Heisenberg Hamiltonian and perform a Monte Carlo study on each WSe2 + intercalant system to estimate the Curie or Néel temperature. We find ferromagnetic ground states for Ti and Cr intercalation, with Curie temperatures of 31K and 225K, respectively. In Fe-intercalated WSe2, we predict that antiferromagnetic ordering is present up to 564K. For V intercalation, we find that the system exhibits a double phase transition.","PeriodicalId":206964,"journal":{"name":"2020 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132776000","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 : 2020-09-23DOI: 10.23919/SISPAD49475.2020.9241631
T. Kunikiyo, Hidenori Sato, T. Kamino, Koji Iizuka, K. Sonoda, T. Yamashita
A novel phase-detection auto focus (PDAF) technique for incident 850 nm plane wave is demonstrated using Ge-on-Si layer and deep trench isolation (DTI), which are locally arranged on light receiving surface (LRS) of crystalline silicon (c-Si). No metal light shielding film (LSF) for pupil division is formed. The key concept of the present work for PDAF is to perform the pupil division by the locally arranged Geon-Si layer in a pixel according to incident angle. The present pixel is based on a back-side illuminated CMOS image sensor pixel; the pixel pitch is 1.85 μm and the thickness of c-Si is around 3 μm. The simulation, based on three-dimensional finite difference time domain (3D-FDTD) method, shows that the external quantum efficiency (EQE) of the present pixel exhibits above 44.3 % with the maximum of 76.0 % for incident angles of - 30° to + 30°, owing to the selectively arranged Ge-on-Si layer; it exhibits 3.6 times improvement in the EQE at normal incidence compared to that of current state-of-the-art pixel with half metal-shielded aperture; the EQE is 49.2 % and 13.8 %, respectively. The present technique can enhance the accuracy of AF under low-illuminated condition.
{"title":"A technique for phase-detection auto focus under near-infrared-ray incidence in a back-side illuminated CMOS image sensor pixel with selectively grown germanium on silicon","authors":"T. Kunikiyo, Hidenori Sato, T. Kamino, Koji Iizuka, K. Sonoda, T. Yamashita","doi":"10.23919/SISPAD49475.2020.9241631","DOIUrl":"https://doi.org/10.23919/SISPAD49475.2020.9241631","url":null,"abstract":"A novel phase-detection auto focus (PDAF) technique for incident 850 nm plane wave is demonstrated using Ge-on-Si layer and deep trench isolation (DTI), which are locally arranged on light receiving surface (LRS) of crystalline silicon (c-Si). No metal light shielding film (LSF) for pupil division is formed. The key concept of the present work for PDAF is to perform the pupil division by the locally arranged Geon-Si layer in a pixel according to incident angle. The present pixel is based on a back-side illuminated CMOS image sensor pixel; the pixel pitch is 1.85 μm and the thickness of c-Si is around 3 μm. The simulation, based on three-dimensional finite difference time domain (3D-FDTD) method, shows that the external quantum efficiency (EQE) of the present pixel exhibits above 44.3 % with the maximum of 76.0 % for incident angles of - 30° to + 30°, owing to the selectively arranged Ge-on-Si layer; it exhibits 3.6 times improvement in the EQE at normal incidence compared to that of current state-of-the-art pixel with half metal-shielded aperture; the EQE is 49.2 % and 13.8 %, respectively. The present technique can enhance the accuracy of AF under low-illuminated condition.","PeriodicalId":206964,"journal":{"name":"2020 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132984392","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 : 2020-09-23DOI: 10.23919/SISPAD49475.2020.9241604
Junsung Park, Minjae Kim, Jae‐Hyung Jang, Sung-Min Hong
The HfO2-based resistive random-access-memory (RRAM) is studied. In the first part, two parameters of oxygen vacancies are extracted. The migration barrier of the oxygen vacancy (or the extended Frenkel pair) is calculated. The resistivity of a filament is also calculated. In the second part, an existing compact model for the RRAM is implemented and its results are compared with the experimental data
{"title":"Properties of Conductive Oxygen Vacancies and Compact Modeling of IV Characteristics in HfO2 Resistive Random-Access-Memories","authors":"Junsung Park, Minjae Kim, Jae‐Hyung Jang, Sung-Min Hong","doi":"10.23919/SISPAD49475.2020.9241604","DOIUrl":"https://doi.org/10.23919/SISPAD49475.2020.9241604","url":null,"abstract":"The HfO2-based resistive random-access-memory (RRAM) is studied. In the first part, two parameters of oxygen vacancies are extracted. The migration barrier of the oxygen vacancy (or the extended Frenkel pair) is calculated. The resistivity of a filament is also calculated. In the second part, an existing compact model for the RRAM is implemented and its results are compared with the experimental data","PeriodicalId":206964,"journal":{"name":"2020 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)","volume":"437 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134149863","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 : 2020-09-23DOI: 10.23919/SISPAD49475.2020.9241607
Hiromu Yamasaki, K. Miyazaki, Yang Lo, A. M. Mahfuzul Islam, Katsuhiro Hata, T. Sakurai, M. Takamiya
The emitter resistance (RE), the junction temperature (TJ), the collector current (IC), and the threshold voltage (VTH) of power devices are key parameters that determine the reliability of power devices. Adding dedicated sensors to measure the key parameters, however, will increase the cost of the power converters. To solve the problem, power device degradation estimation methods by the machine learning of gate waveforms are proposed. Two methods are shown in this paper. First, in order to detect the bond wire lift-off of power devices, the estimation of the number of the connected bond wires using the linear regression of two feature points extracted from the gate waveforms of a SiC MOSFET is shown using SPICE simulations. Then, in order to detect the power device degradation, the estimation of R E, TJ, IC, and VTH using the convolutional neural network (CNN) with the gate waveforms of an IGBT for input is shown using both simulations and measurements.
功率器件的发射极电阻(RE)、结温(TJ)、集电极电流(IC)和阈值电压(VTH)是决定功率器件可靠性的关键参数。然而，增加专用传感器来测量关键参数将增加功率转换器的成本。为了解决这一问题，提出了基于门波形机器学习的功率器件退化估计方法。本文给出了两种方法。首先，为了检测功率器件的键合线上升，使用SPICE模拟显示了使用从SiC MOSFET的栅极波形中提取的两个特征点的线性回归来估计连接的键合线的数量。然后，为了检测功率器件退化，使用卷积神经网络(CNN)估计R E, TJ, IC和VTH，并通过仿真和测量显示输入IGBT的门波形。
{"title":"Power Device Degradation Estimation by Machine Learning of Gate Waveforms","authors":"Hiromu Yamasaki, K. Miyazaki, Yang Lo, A. M. Mahfuzul Islam, Katsuhiro Hata, T. Sakurai, M. Takamiya","doi":"10.23919/SISPAD49475.2020.9241607","DOIUrl":"https://doi.org/10.23919/SISPAD49475.2020.9241607","url":null,"abstract":"The emitter resistance (RE), the junction temperature (TJ), the collector current (IC), and the threshold voltage (VTH) of power devices are key parameters that determine the reliability of power devices. Adding dedicated sensors to measure the key parameters, however, will increase the cost of the power converters. To solve the problem, power device degradation estimation methods by the machine learning of gate waveforms are proposed. Two methods are shown in this paper. First, in order to detect the bond wire lift-off of power devices, the estimation of the number of the connected bond wires using the linear regression of two feature points extracted from the gate waveforms of a SiC MOSFET is shown using SPICE simulations. Then, in order to detect the power device degradation, the estimation of R E, TJ, IC, and VTH using the convolutional neural network (CNN) with the gate waveforms of an IGBT for input is shown using both simulations and measurements.","PeriodicalId":206964,"journal":{"name":"2020 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114075676","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 : 2020-09-23DOI: 10.23919/sispad49475.2020.9241620
{"title":"SISPAD 2020 Committees","authors":"","doi":"10.23919/sispad49475.2020.9241620","DOIUrl":"https://doi.org/10.23919/sispad49475.2020.9241620","url":null,"abstract":"","PeriodicalId":206964,"journal":{"name":"2020 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125104478","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 : 2020-09-23DOI: 10.23919/SISPAD49475.2020.9241661
Seung-Cheol Han, Jonghyun Choi, Sung-Min Hong
As efficiency is one of the bottlenecks of device simulation, we propose to employ deep neural networks to generate two-dimensional electrostatic potential profiles for efficiency. Supervising with previously obtained simulation results for various BJT devices, we train deep neural networks to generate an electrostatic potential profile as an initial guess for a non-equilibrium condition with estimating carrier densities by the frozen field simulation. With the generated potential profiles, we significantly reduce the number of Newton iterations without loss of accuracy.
{"title":"Electrostatic Potential Profile Generator for Two-Dimensional Semiconductor Devices","authors":"Seung-Cheol Han, Jonghyun Choi, Sung-Min Hong","doi":"10.23919/SISPAD49475.2020.9241661","DOIUrl":"https://doi.org/10.23919/SISPAD49475.2020.9241661","url":null,"abstract":"As efficiency is one of the bottlenecks of device simulation, we propose to employ deep neural networks to generate two-dimensional electrostatic potential profiles for efficiency. Supervising with previously obtained simulation results for various BJT devices, we train deep neural networks to generate an electrostatic potential profile as an initial guess for a non-equilibrium condition with estimating carrier densities by the frozen field simulation. With the generated potential profiles, we significantly reduce the number of Newton iterations without loss of accuracy.","PeriodicalId":206964,"journal":{"name":"2020 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115522386","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 : 2020-09-23DOI: 10.23919/SISPAD49475.2020.9241690
S. Amoroso, Jaehyun Lee, A. Brown, P. Asenov, Xi-Wei Lin, V. Moroz, Thomas Yang
This paper presents a TCAD-to-SPICE high-sigma analysis of DRAM write and retention performance. Both statistical and process-induced variability are taken into- account. We highlight that the interplay between discrete traps and discrete dopants is ruling the leakage statistical tails and therefore can play a fundamental role in determining yield and reliability of ultra-scaled DRAMs.
{"title":"High-sigma analysis of DRAM write and retention performance: a TCAD-to-SPICE approach","authors":"S. Amoroso, Jaehyun Lee, A. Brown, P. Asenov, Xi-Wei Lin, V. Moroz, Thomas Yang","doi":"10.23919/SISPAD49475.2020.9241690","DOIUrl":"https://doi.org/10.23919/SISPAD49475.2020.9241690","url":null,"abstract":"This paper presents a TCAD-to-SPICE high-sigma analysis of DRAM write and retention performance. Both statistical and process-induced variability are taken into- account. We highlight that the interplay between discrete traps and discrete dopants is ruling the leakage statistical tails and therefore can play a fundamental role in determining yield and reliability of ultra-scaled DRAMs.","PeriodicalId":206964,"journal":{"name":"2020 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116173888","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 : 2020-09-23DOI: 10.23919/SISPAD49475.2020.9241650
H. Kosina, Heribert Seiler, V. Sverdlov
Surface Green’s functions describe the coupling of the device region with the attached leads. A lead represents a semi-infinite region with uniform properties such as cross section and electrostatic potential. The scattering states in the leads can be determined in different ways. In this work we exploit the uniformity of the system and formulate the problem in reciprocal space where the Green’s function takes on a simple form. A Fourier transformation yields the elements of the Green’s function in real space. We present the principal steps of this calculation and discuss results for nanoribbons. The 2D materials considered are graphene and $mathrm{M}mathrm{o}mathrm{S}_{2}$ in the 1T’ phase, their electronic structure is represented by k$cdot$ p Hamiltonians.
{"title":"Analytical Formulae for the Surface Green’s Functions of Graphene and 1T’ MoS2 Nanoribbons","authors":"H. Kosina, Heribert Seiler, V. Sverdlov","doi":"10.23919/SISPAD49475.2020.9241650","DOIUrl":"https://doi.org/10.23919/SISPAD49475.2020.9241650","url":null,"abstract":"Surface Green’s functions describe the coupling of the device region with the attached leads. A lead represents a semi-infinite region with uniform properties such as cross section and electrostatic potential. The scattering states in the leads can be determined in different ways. In this work we exploit the uniformity of the system and formulate the problem in reciprocal space where the Green’s function takes on a simple form. A Fourier transformation yields the elements of the Green’s function in real space. We present the principal steps of this calculation and discuss results for nanoribbons. The 2D materials considered are graphene and $mathrm{M}mathrm{o}mathrm{S}_{2}$ in the 1T’ phase, their electronic structure is represented by k$cdot$ p Hamiltonians.","PeriodicalId":206964,"journal":{"name":"2020 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114648605","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 : 2020-09-23DOI: 10.23919/SISPAD49475.2020.9241691
Koki Arihori, M. Ogawa, S. Souma, J. Sato-Iwanaga, Masayuki Suzuki
We present a numerical study on the electrical conduction characteristics of the graphene channel FET with electrolyte medium for gate control. By using the tight-binding formalism to calculate the electronic band structure and the Nernst-Planck-Poisson (NPP) equation to calculate the formation of the electric double layer at the interface of the ionic liquid, we found that the drain current after the EDL is formed is almost independent of the IL thickness, while the transient behavior is greatly influenced by the thickness of ionic liquid. In addition, we present our simulation results for the case of solid electrolyte gate, where the effect of finite ion concentration in the solid electrolyte has been successfully taken into account appropriately by using the extended NPP equation.
{"title":"Transient simulation of graphene FET gated by electrolyte medium","authors":"Koki Arihori, M. Ogawa, S. Souma, J. Sato-Iwanaga, Masayuki Suzuki","doi":"10.23919/SISPAD49475.2020.9241691","DOIUrl":"https://doi.org/10.23919/SISPAD49475.2020.9241691","url":null,"abstract":"We present a numerical study on the electrical conduction characteristics of the graphene channel FET with electrolyte medium for gate control. By using the tight-binding formalism to calculate the electronic band structure and the Nernst-Planck-Poisson (NPP) equation to calculate the formation of the electric double layer at the interface of the ionic liquid, we found that the drain current after the EDL is formed is almost independent of the IL thickness, while the transient behavior is greatly influenced by the thickness of ionic liquid. In addition, we present our simulation results for the case of solid electrolyte gate, where the effect of finite ion concentration in the solid electrolyte has been successfully taken into account appropriately by using the extended NPP equation.","PeriodicalId":206964,"journal":{"name":"2020 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130984196","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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