Simulation of light trapping in thin-film solar cells
Main.NewsFeb-2017 History
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(:cellnr align='center':) Symmetrized model. Whitle lines indicate the limits of each submodel.
(:cell align='center':) Full model with regular periodic boundaries.
(:cell align='center':) Full model with regular periodic boundaries.
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(:cellnr align='center':) Figure 3. Symmetrized model. Whitle lines indicate the limits of each submodel.
(:cell align='center':) Figure 4. Full model with regular periodic boundaries.
(:cell align='center':) Figure 4. Full model with regular periodic boundaries.
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(:cellnr align='center':) Symmetrized model. Whitle lines indicate the limits of each submodel
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(:cellnr align='center':) Symmetrized model. Whitle lines indicate the limits of each submodel
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(:cellnr align='center':) %width=350px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_model_sym1.png
(:cell align='center':) %width=350px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_model_sym2.png
(:cellnr align='center':) Symmetrized model. Whitle lines indicate the limits of each submodel.
(:cell align='center':) %width=350px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_model_sym2.png
(:cellnr align='center':) Symmetrized model. Whitle lines indicate the limits of each submodel.
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(:cell align='center':) width=300px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_model_sym2.png
(:cellnr align='center':) Symmetrized model. Whitle lines indicate the limits of each submodel
(:cell align='center':) Full model with regular periodic boundaries.
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(:cellnr align='center':) width=300px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_model_sym1.png
(:cell align='center':) width=300px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_model_sym2.png
(:cellnr align='center':) Symmetrized model. Whitle lines indicate the limits of each submodel
(:cell align='center':) Full model with regular periodic boundaries.
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%lfloat text-align=center width=400px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_model_sym1.png | Figure 3. Symmetrized model. Whitle lines indicate the limits of each submodel.\\\
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%lfloat text-align=center width=300px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_model_sym1.png | Figure 3. Symmetrized model. Whitle lines indicate the limits of each submodel.\\\
%lfloat text-align=center width=300px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_model_sym2.png | Figure 4. Full model with regular periodic boundaries.
%lfloat text-align=center width=300px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_model_sym2.png | Figure 4. Full model with regular periodic boundaries.
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We choose to use Periodic Boundary Conditions (PBC) which allow to simulate artificially infinite mono-directional or bi-directional arrays while considering only one elementary pattern. To do so, cells from a periodic boundary face are matched with their neighbors on the opposite boundary of the domain. We have two possibilities to obtained such boundaries. The first one consist of symmetrizing the mesh. The main drawback of this method is the multiplication of the domain size by 4. This is not a major issue for a small model like in Figure 3, but for the full device this is not a feasible approach.
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We choose to use Periodic Boundary Conditions (PBC) which allow to simulate artificially infinite mono-directional or bi-directional arrays while considering only one elementary pattern. To do so, cells from a periodic boundary face are matched with their neighbors on the opposite boundary of the domain. We have two possibilities to obtained such boundaries. The first one consist of symmetrizing the mesh. The main drawback of this method is the multiplication of the domain size by 4. This is not a major issue for a small model like in Figure 3, but for the full device this is not a feasible approach. The second option is to manually force the periodicity of the faces using a regular mesh. Before that, we need to modify the topography of each layer to have the same 1D border for each layer. The disadvantage here is the loss of information on the edges of the structure as can be seen in Figure 4.
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The second option is to manually force the periodicity of the faces using a regular mesh. Before that, we need to modify the topography of each layer to have the same 1D border for each layer. The disadvantage here is the loss of information on the edges of the structure as can be seen in Figure 4.
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%lfloat text-align=center width=500px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_model_sym1.png | Figure 3. Symmetrized model. Whitle lines indicate the limits of each submodel.\\\
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%lfloat text-align=center width=400px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_model_sym1.png | Figure 3. Symmetrized model. Whitle lines indicate the limits of each submodel.\\\
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%lfloat text-align=center width=500px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/olar_cell_model_sym1.png | Figure 3. Symmetrized model. Whitle lines indicate the limits of each submodel.\\\
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%lfloat text-align=center width=500px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_model_sym1.png | Figure 3. Symmetrized model. Whitle lines indicate the limits of each submodel.\\\
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We choose to use Periodic Boundary Conditions (PBC) which allow to simulate artificially infinite mono-directional or bi-directional arrays while considering only one elementary pattern. To do so, cells from a periodic boundary face are matched with their neighbors on the opposite boundary of the domain. We have two possibilities to obtained such boundaries. The first one consist of symmetrizing the mesh. The main drawback of this method is the multiplication of the domain size by 4. This is not a major issue for a small model like in Figure 3, but for the full device this is not a feasible approach. The second option is to manually force the periodicity of the faces using a regular mesh. Before that, we need to modify the topography of each layer to have the same 1D border for each layer. The disadvantage here is the loss of information on the edges of the structure as can be seen in Figure 4.
to:
We choose to use Periodic Boundary Conditions (PBC) which allow to simulate artificially infinite mono-directional or bi-directional arrays while considering only one elementary pattern. To do so, cells from a periodic boundary face are matched with their neighbors on the opposite boundary of the domain. We have two possibilities to obtained such boundaries. The first one consist of symmetrizing the mesh. The main drawback of this method is the multiplication of the domain size by 4. This is not a major issue for a small model like in Figure 3, but for the full device this is not a feasible approach.
%lfloat text-align=center width=500px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/olar_cell_model_sym1.png | Figure 3. Symmetrized model. Whitle lines indicate the limits of each submodel.\\\
The second option is to manually force the periodicity of the faces using a regular mesh. Before that, we need to modify the topography of each layer to have the same 1D border for each layer. The disadvantage here is the loss of information on the edges of the structure as can be seen in Figure 4.
%lfloat text-align=center width=500px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/olar_cell_model_sym1.png | Figure 3. Symmetrized model. Whitle lines indicate the limits of each submodel.\\\
The second option is to manually force the periodicity of the faces using a regular mesh. Before that, we need to modify the topography of each layer to have the same 1D border for each layer. The disadvantage here is the loss of information on the edges of the structure as can be seen in Figure 4.
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We choose to use Periodic Boundary Conditions (PBC) which allow to simulate artificially infinite mono-directional or bi-directional arrays while considering only one elementary pattern. To do so, cells from a periodic boundary face are matched with their neighbors on the opposite boundary of the domain. We have two possibilities to obtained such boundaries. The first one consist of symmetrizing the mesh. The main drawback of this method is the multiplication of the domain size by 4. This i s not a major issue for a small model like in Figure 3, but for the full device this is not a feasible approach. The second option is to manually force the periodicity of the faces using a regular mesh. Before that, we need to modify the topography of each layer to have the same 1D border for each layer. The disadvantage here is the loss of information on the edges of the structure as can be seen in Figure 4.
to:
We choose to use Periodic Boundary Conditions (PBC) which allow to simulate artificially infinite mono-directional or bi-directional arrays while considering only one elementary pattern. To do so, cells from a periodic boundary face are matched with their neighbors on the opposite boundary of the domain. We have two possibilities to obtained such boundaries. The first one consist of symmetrizing the mesh. The main drawback of this method is the multiplication of the domain size by 4. This is not a major issue for a small model like in Figure 3, but for the full device this is not a feasible approach. The second option is to manually force the periodicity of the faces using a regular mesh. Before that, we need to modify the topography of each layer to have the same 1D border for each layer. The disadvantage here is the loss of information on the edges of the structure as can be seen in Figure 4.
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%center% Figure 2. Real and imaginary parts of the relative permittivity of amorphous silicon a-Si:H fitted to a generalized dispersion model () compared to experimental data.
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%center% Figure 2. Real and imaginary parts of the relative permittivity of amorphous silicon a-Si:H fitted to a generalized dispersion model compared to experimental data.
We choose to use Periodic Boundary Conditions (PBC) which allow to simulate artificially infinite mono-directional or bi-directional arrays while considering only one elementary pattern. To do so, cells from a periodic boundary face are matched with their neighbors on the opposite boundary of the domain. We have two possibilities to obtained such boundaries. The first one consist of symmetrizing the mesh. The main drawback of this method is the multiplication of the domain size by 4. This i s not a major issue for a small model like in Figure 3, but for the full device this is not a feasible approach. The second option is to manually force the periodicity of the faces using a regular mesh. Before that, we need to modify the topography of each layer to have the same 1D border for each layer. The disadvantage here is the loss of information on the edges of the structure as can be seen in Figure 4.
We choose to use Periodic Boundary Conditions (PBC) which allow to simulate artificially infinite mono-directional or bi-directional arrays while considering only one elementary pattern. To do so, cells from a periodic boundary face are matched with their neighbors on the opposite boundary of the domain. We have two possibilities to obtained such boundaries. The first one consist of symmetrizing the mesh. The main drawback of this method is the multiplication of the domain size by 4. This i s not a major issue for a small model like in Figure 3, but for the full device this is not a feasible approach. The second option is to manually force the periodicity of the faces using a regular mesh. Before that, we need to modify the topography of each layer to have the same 1D border for each layer. The disadvantage here is the loss of information on the edges of the structure as can be seen in Figure 4.
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Figure 2. Real and imaginary parts of the relative permittivity of amorphous silicon a-Si:H fitted to a generalized dispersion model () compared to experimental data.
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%center% Figure 2. Real and imaginary parts of the relative permittivity of amorphous silicon a-Si:H fitted to a generalized dispersion model () compared to experimental data.
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Figure 2. Real and imaginary parts of the relative permittivity of amorphous silicon a-Si:H fitted to a generalized dispersion model () compared to experimental data.
Figure 2. Real and imaginary parts of the relative permittivity of amorphous silicon a-Si:H fitted to a generalized dispersion model () compared to experimental data.
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Optical data of the constitutive materials have been fitted to a generalized dispersion model, which was originally intended for metals. The obtained permittivity functions for the amorphous silicon a-Si:H are plotted in Figure 2. As can be seen, this material is relatively well approximated.
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Optical data of the constitutive materials have been fitted to a generalized dispersion model, which was originally intended for metals. The obtained permittivity functions for the amorphous silicon a-Si:H are plotted in Figure 2. As can be seen, this material is relatively well approximated.
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%lfloat text-align=center width=500px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_stack.png | Figure 1. Geometrical model of the solar cell structure and composition of the different layers. Layer thicknesses are in the order of the wavelength of relevant sunlight.\\\
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%lfloat text-align=center width=500px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_stack.png | Figure 1. Geometrical model of the solar cell structure and composition of the different layers. Layer thicknesses are in the order of the wavelength of relevant sunlight.\\\
Optical data of the constitutive materials have been fitted to a generalized dispersion model, which was originally intended for metals. The obtained permittivity functions for the amorphous silicon a-Si:H are plotted in Figure 2. As can be seen, this material is relatively well approximated.
Optical data of the constitutive materials have been fitted to a generalized dispersion model, which was originally intended for metals. The obtained permittivity functions for the amorphous silicon a-Si:H are plotted in Figure 2. As can be seen, this material is relatively well approximated.
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%lfloat text-align=center width=400px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_stack.png | Figure 1. Geometrical model of the solar cell structure and composition of the different layers. Layer thicknesses are in the order of the wavelength of relevant sunlight.\\\
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%lfloat text-align=center width=500px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_stack.png | Figure 1. Geometrical model of the solar cell structure and composition of the different layers. Layer thicknesses are in the order of the wavelength of relevant sunlight.\\\
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We study light trapping in a silicon-based thin-film solar cell setup that consists of several randomly textured layers. The focus is on amorphous and microcrystalline silicon (a-Si:H and µc-Si:H) which belong to the family of disordered semiconductors. The main characteristics of those materials is the structural disorder, which affect in an essential way the optical and electronic properties.
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We study light trapping in a silicon-based thin-film solar cell setup that consists of several randomly textured layers. The focus is on amorphous and microcrystalline silicon (a-Si:H and µc-Si:H) which belong to the family of disordered semiconductors. The main characteristics of those materials is the structural disorder, which affect in an essential way the optical and electronic properties.
%lfloat text-align=center width=400px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_stack.png | Figure 1. Geometrical model of the solar cell structure and composition of the different layers. Layer thicknesses are in the order of the wavelength of relevant sunlight.\\\
%lfloat text-align=center width=400px% http://www-sop.inria.fr/nachos/pics/news/2017/feb/solar_cell_stack.png | Figure 1. Geometrical model of the solar cell structure and composition of the different layers. Layer thicknesses are in the order of the wavelength of relevant sunlight.\\\
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We study light trapping in a silicon-based thin-film solar cell setup that consists of several randomly textured layers. The focus is on amorphous and microcrystalline silicon (a-Si:H and µc-Si:H) which belong to the family of disordered semiconductors. The main characteristics of those materials is the structural disorder, which affect in an essential way the optical and electronic properties.
We study light trapping in a silicon-based thin-film solar cell setup that consists of several randomly textured layers. The focus is on amorphous and microcrystalline silicon (a-Si:H and µc-Si:H) which belong to the family of disordered semiconductors. The main characteristics of those materials is the structural disorder, which affect in an essential way the optical and electronic properties.
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(:title Simulation of light trapping in thin-film solar cells with textured layers:)
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(:title Simulation of light trapping in thin-film solar cells:)
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(:title Simulation of light trapping in thin-film solar cells with textured layers:)