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rcwa simulation tool (MathWorks Inc)

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MathWorks Inc rcwa simulation tool

Principle of the coupled modeling approach (CMA). <t>RCWA</t> is applied to the parts of the structure where nanotextures are present to produce scattering matrices. These matrices are an input for the RT and TMM part of the simulator. By applying iterative coupling, the optical situation in the region of nanostructures, microstructures, thin and thick layers can be simulated in an effective and accurate way.

Rcwa Simulation Tool, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/rcwa simulation tool/product/MathWorks Inc
Average 90 stars, based on 1 article reviews

rcwa simulation tool - by Bioz Stars, 2026-04

90/100 stars

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1) Product Images from "Performance analysis of rigorous coupled-wave analysis and its integration in a coupled modeling approach for optical simulation of complete heterojunction silicon solar cells"

Article Title: Performance analysis of rigorous coupled-wave analysis and its integration in a coupled modeling approach for optical simulation of complete heterojunction silicon solar cells

Journal: Beilstein Journal of Nanotechnology

doi: 10.3762/bjnano.9.216

Principle of the coupled modeling approach (CMA). RCWA is applied to the parts of the structure where nanotextures are present to produce scattering matrices. These matrices are an input for the RT and TMM part of the simulator. By applying iterative coupling, the optical situation in the region of nanostructures, microstructures, thin and thick layers can be simulated in an effective and accurate way.

Figure Legend Snippet: Principle of the coupled modeling approach (CMA). RCWA is applied to the parts of the structure where nanotextures are present to produce scattering matrices. These matrices are an input for the RT and TMM part of the simulator. By applying iterative coupling, the optical situation in the region of nanostructures, microstructures, thin and thick layers can be simulated in an effective and accurate way.

Techniques Used:

The top and cross-sectional views of the simulated partial structures, applied to the front part of the solar cell. (a, b) simulated top views of inverted pyramid and random pyramid textures. (c, d) Corresponding cross-sectional views, including thin layers as present in the front part of the analyzed solar cell (not seen in (d)). The pixilation observable in the thin layers in c) is a result of sublayer discretization in RCWA (100 equivalently thick sublayers for the texture are shown). In a), the area of the pyramid is marked with red square, while area of the unit cell is marked with a green square. The PF factor, defined by the ratio of these two areas, is 0.7.

Figure Legend Snippet: The top and cross-sectional views of the simulated partial structures, applied to the front part of the solar cell. (a, b) simulated top views of inverted pyramid and random pyramid textures. (c, d) Corresponding cross-sectional views, including thin layers as present in the front part of the analyzed solar cell (not seen in (d)). The pixilation observable in the thin layers in c) is a result of sublayer discretization in RCWA (100 equivalently thick sublayers for the texture are shown). In a), the area of the pyramid is marked with red square, while area of the unit cell is marked with a green square. The PF factor, defined by the ratio of these two areas, is 0.7.

Techniques Used:

Analysis of the RCWA convergence for the nanoscale textures. All graphs on the left hand side correspond to the results of the variation in the number of sublayers with a fixed number of modes (ten modes) whereas the right hand side graphs represent the results of the variation in the number of mode with a fixed number of sublayers (300 sublayers). The top two graphs (a, b) correspond to an incident angle of 0° whereas the middle two (c, d) are for the incident angle of 45°. The bottom two graphs (e, f) quantify deviations between RCWA results using the |Δ J SC | measure.

Figure Legend Snippet: Analysis of the RCWA convergence for the nanoscale textures. All graphs on the left hand side correspond to the results of the variation in the number of sublayers with a fixed number of modes (ten modes) whereas the right hand side graphs represent the results of the variation in the number of mode with a fixed number of sublayers (300 sublayers). The top two graphs (a, b) correspond to an incident angle of 0° whereas the middle two (c, d) are for the incident angle of 45°. The bottom two graphs (e, f) quantify deviations between RCWA results using the |Δ J SC | measure.

Techniques Used:

Analysis of RCWA convergence for micrometer-sized textures. Left hand side graphs correspond to the results of variation of the number of sublayers with a fixed number of modes, while the right hand side graphs correspond to the results of variation of the number of modes with a fixed number of sublayers. The top two graphs (a, b) show visual pyramidal texture convergence with number of sublayers and modes. Graphs (c) and (d) quantify the difference between the RCWA results using the |Δ J SC | measure.

Figure Legend Snippet: Analysis of RCWA convergence for micrometer-sized textures. Left hand side graphs correspond to the results of variation of the number of sublayers with a fixed number of modes, while the right hand side graphs correspond to the results of variation of the number of modes with a fixed number of sublayers. The top two graphs (a, b) show visual pyramidal texture convergence with number of sublayers and modes. Graphs (c) and (d) quantify the difference between the RCWA results using the |Δ J SC | measure.

Techniques Used:

Simulated absorptances in the c-Si layer of the HJ Si solar cell using RCWA, RT/TMM (CROWM simulator) and CMA. Comparison between RCWA and RT/TMM is shown in (a). (b) RT/TMM and CMA simulations of the solar cell with a nanotexture with PF 1. Corresponding J SC values calculated from the absorptance curves are listed in .

Figure Legend Snippet: Simulated absorptances in the c-Si layer of the HJ Si solar cell using RCWA, RT/TMM (CROWM simulator) and CMA. Comparison between RCWA and RT/TMM is shown in (a). (b) RT/TMM and CMA simulations of the solar cell with a nanotexture with PF 1. Corresponding J SC values calculated from the absorptance curves are listed in .

Techniques Used: Comparison

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Journal: Beilstein Journal of Nanotechnology

Article Title: Performance analysis of rigorous coupled-wave analysis and its integration in a coupled modeling approach for optical simulation of complete heterojunction silicon solar cells

doi: 10.3762/bjnano.9.216

Figure Lengend Snippet: Principle of the coupled modeling approach (CMA). RCWA is applied to the parts of the structure where nanotextures are present to produce scattering matrices. These matrices are an input for the RT and TMM part of the simulator. By applying iterative coupling, the optical situation in the region of nanostructures, microstructures, thin and thick layers can be simulated in an effective and accurate way.

Article Snippet: For the purpose of further integration and adaptation, we developed and verified our own RCWA simulation tool in MATLAB, following the physics described above.

Techniques:

Journal: Beilstein Journal of Nanotechnology

Article Title: Performance analysis of rigorous coupled-wave analysis and its integration in a coupled modeling approach for optical simulation of complete heterojunction silicon solar cells

doi: 10.3762/bjnano.9.216

Figure Lengend Snippet: The top and cross-sectional views of the simulated partial structures, applied to the front part of the solar cell. (a, b) simulated top views of inverted pyramid and random pyramid textures. (c, d) Corresponding cross-sectional views, including thin layers as present in the front part of the analyzed solar cell (not seen in (d)). The pixilation observable in the thin layers in c) is a result of sublayer discretization in RCWA (100 equivalently thick sublayers for the texture are shown). In a), the area of the pyramid is marked with red square, while area of the unit cell is marked with a green square. The PF factor, defined by the ratio of these two areas, is 0.7.

Article Snippet: For the purpose of further integration and adaptation, we developed and verified our own RCWA simulation tool in MATLAB, following the physics described above.

Techniques:

Journal: Beilstein Journal of Nanotechnology

Article Title: Performance analysis of rigorous coupled-wave analysis and its integration in a coupled modeling approach for optical simulation of complete heterojunction silicon solar cells

doi: 10.3762/bjnano.9.216

Figure Lengend Snippet: Analysis of the RCWA convergence for the nanoscale textures. All graphs on the left hand side correspond to the results of the variation in the number of sublayers with a fixed number of modes (ten modes) whereas the right hand side graphs represent the results of the variation in the number of mode with a fixed number of sublayers (300 sublayers). The top two graphs (a, b) correspond to an incident angle of 0° whereas the middle two (c, d) are for the incident angle of 45°. The bottom two graphs (e, f) quantify deviations between RCWA results using the |Δ J SC | measure.

Article Snippet: For the purpose of further integration and adaptation, we developed and verified our own RCWA simulation tool in MATLAB, following the physics described above.

Techniques:

Journal: Beilstein Journal of Nanotechnology

Article Title: Performance analysis of rigorous coupled-wave analysis and its integration in a coupled modeling approach for optical simulation of complete heterojunction silicon solar cells

doi: 10.3762/bjnano.9.216

Figure Lengend Snippet: Analysis of RCWA convergence for micrometer-sized textures. Left hand side graphs correspond to the results of variation of the number of sublayers with a fixed number of modes, while the right hand side graphs correspond to the results of variation of the number of modes with a fixed number of sublayers. The top two graphs (a, b) show visual pyramidal texture convergence with number of sublayers and modes. Graphs (c) and (d) quantify the difference between the RCWA results using the |Δ J SC | measure.

Article Snippet: For the purpose of further integration and adaptation, we developed and verified our own RCWA simulation tool in MATLAB, following the physics described above.

Techniques:

Journal: Beilstein Journal of Nanotechnology

Article Title: Performance analysis of rigorous coupled-wave analysis and its integration in a coupled modeling approach for optical simulation of complete heterojunction silicon solar cells

doi: 10.3762/bjnano.9.216

Figure Lengend Snippet: Simulated absorptances in the c-Si layer of the HJ Si solar cell using RCWA, RT/TMM (CROWM simulator) and CMA. Comparison between RCWA and RT/TMM is shown in (a). (b) RT/TMM and CMA simulations of the solar cell with a nanotexture with PF 1. Corresponding J SC values calculated from the absorptance curves are listed in .

Article Snippet: For the purpose of further integration and adaptation, we developed and verified our own RCWA simulation tool in MATLAB, following the physics described above.

Techniques: Comparison

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