We report the performances of a chalcopyrite Cu(In, Ga)Se<sub>2 </sub>CIGS-based thin-film solar cell with a newly employed high conductive n-Si layer. The data analysis was performed with the help of the ...We report the performances of a chalcopyrite Cu(In, Ga)Se<sub>2 </sub>CIGS-based thin-film solar cell with a newly employed high conductive n-Si layer. The data analysis was performed with the help of the 1D-Solar Cell Capacitance Simulator (1D-SCAPS) software program. The new device structure is based on the CIGS layer as the absorber layer, n-Si as the high conductive layer, i-In<sub>2</sub>S<sub>3</sub>, and i-ZnO as the buffer and window layers, respectively. The optimum CIGS bandgap was determined first and used to simulate and analyze the cell performance throughout the experiment. This analysis revealed that the absorber layer’s optimum bandgap value has to be 1.4 eV to achieve maximum efficiency of 22.57%. Subsequently, output solar cell parameters were analyzed as a function of CIGS layer thickness, defect density, and the operating temperature with an optimized n-Si layer. The newly modeled device has a p-CIGS/n-Si/In<sub>2</sub>S<sub>3</sub>/Al-ZnO structure. The main objective was to improve the overall cell performance while optimizing the thickness of absorber layers, defect density, bandgap, and operating temperature with the newly employed optimized n-Si layer. The increase of absorber layer thickness from 0.2 - 2 µm showed an upward trend in the cell’s performance, while the increase of defect density and operating temperature showed a downward trend in solar cell performance. This study illustrates that the proposed cell structure shows higher cell performances and can be fabricated on the lab-scale and industrial levels.展开更多
As an important indicator parameter of fluid identification,fluid factor has always been a concern for scholars.However,when predicting Russell fluid factor or effective pore-fluid bulk modulus,it is necessary to intr...As an important indicator parameter of fluid identification,fluid factor has always been a concern for scholars.However,when predicting Russell fluid factor or effective pore-fluid bulk modulus,it is necessary to introduce a new rock skeleton parameter which is the dry-rock VP/VS ratio squared(DVRS).In the process of fluid factor calculation or inversion,the existing methods take this parameter as a static constant,which has been estimated in advance,and then apply it to the fluid factor calculation and inversion.The fluid identification analysis based on a portion of the Marmousi 2 model and numerical forward modeling test show that,taking the DVRS as a static constant will limit the identification ability of fluid factor and reduce the inversion accuracy.To solve the above problems,we proposed a new method to regard the DVRS as a dynamic variable varying with depth and lithology for the first time,then apply it to fluid factor calculation and inversion.Firstly,the exact Zoeppritz equations are rewritten into a new form containing the fluid factor and DVRS of upper and lower layers.Next,the new equations are applied to the four parameters simultaneous inversion based on the generalized nonlinear inversion(GNI)method.The testing results on a portion of the Marmousi 2 model and field data show that dynamic DVRS can significantly improve the fluid factor identification ability,effectively suppress illusion.Both synthetic and filed data tests also demonstrate that the GNI method based on Bayesian deterministic inversion(BDI)theory can successfully solve the above four parameter simultaneous inversion problem,and taking the dynamic DVRS as a target inversion parameter can effectively improve the inversion accuracy of fluid factor.All these results completely verified the feasibility and effectiveness of the proposed method.展开更多
文摘We report the performances of a chalcopyrite Cu(In, Ga)Se<sub>2 </sub>CIGS-based thin-film solar cell with a newly employed high conductive n-Si layer. The data analysis was performed with the help of the 1D-Solar Cell Capacitance Simulator (1D-SCAPS) software program. The new device structure is based on the CIGS layer as the absorber layer, n-Si as the high conductive layer, i-In<sub>2</sub>S<sub>3</sub>, and i-ZnO as the buffer and window layers, respectively. The optimum CIGS bandgap was determined first and used to simulate and analyze the cell performance throughout the experiment. This analysis revealed that the absorber layer’s optimum bandgap value has to be 1.4 eV to achieve maximum efficiency of 22.57%. Subsequently, output solar cell parameters were analyzed as a function of CIGS layer thickness, defect density, and the operating temperature with an optimized n-Si layer. The newly modeled device has a p-CIGS/n-Si/In<sub>2</sub>S<sub>3</sub>/Al-ZnO structure. The main objective was to improve the overall cell performance while optimizing the thickness of absorber layers, defect density, bandgap, and operating temperature with the newly employed optimized n-Si layer. The increase of absorber layer thickness from 0.2 - 2 µm showed an upward trend in the cell’s performance, while the increase of defect density and operating temperature showed a downward trend in solar cell performance. This study illustrates that the proposed cell structure shows higher cell performances and can be fabricated on the lab-scale and industrial levels.
基金the National Natural Science Foundation of China(41904116,41874156,42074167 and 42204135)the Natural Science Foundation of Hunan Province(2020JJ5168)the China Postdoctoral Science Foundation(2021M703629)for their funding of this research.
文摘As an important indicator parameter of fluid identification,fluid factor has always been a concern for scholars.However,when predicting Russell fluid factor or effective pore-fluid bulk modulus,it is necessary to introduce a new rock skeleton parameter which is the dry-rock VP/VS ratio squared(DVRS).In the process of fluid factor calculation or inversion,the existing methods take this parameter as a static constant,which has been estimated in advance,and then apply it to the fluid factor calculation and inversion.The fluid identification analysis based on a portion of the Marmousi 2 model and numerical forward modeling test show that,taking the DVRS as a static constant will limit the identification ability of fluid factor and reduce the inversion accuracy.To solve the above problems,we proposed a new method to regard the DVRS as a dynamic variable varying with depth and lithology for the first time,then apply it to fluid factor calculation and inversion.Firstly,the exact Zoeppritz equations are rewritten into a new form containing the fluid factor and DVRS of upper and lower layers.Next,the new equations are applied to the four parameters simultaneous inversion based on the generalized nonlinear inversion(GNI)method.The testing results on a portion of the Marmousi 2 model and field data show that dynamic DVRS can significantly improve the fluid factor identification ability,effectively suppress illusion.Both synthetic and filed data tests also demonstrate that the GNI method based on Bayesian deterministic inversion(BDI)theory can successfully solve the above four parameter simultaneous inversion problem,and taking the dynamic DVRS as a target inversion parameter can effectively improve the inversion accuracy of fluid factor.All these results completely verified the feasibility and effectiveness of the proposed method.
