rigorous coupled-wave analysis (rcwa) matlab code Search Results


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Rigorous Coupled Wave Analysis Calculations, 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
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MathWorks Inc library based on rigorous coupled-wave analysis (rcwa)
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Rigorous Coupled Wave Analysis Based (Rcwa) Method, 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
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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
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MathWorks Inc open-access rcwa code reticolo supported on
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.
Open Access Rcwa Code Reticolo Supported On, 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
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MathWorks Inc rcwa algorithm
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 Algorithm, 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
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MathWorks Inc rcwa software
Flowchart of the simulation and calculation processes, including structure profile construction, <t>RCWA,</t> and sensor-quality computation.
Rcwa Software, 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
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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.

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:

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.

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:

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.

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:

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.

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:

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 .

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

Flowchart of the simulation and calculation processes, including structure profile construction, RCWA, and sensor-quality computation.

Journal: Sensors (Basel, Switzerland)

Article Title: Analysis of Effects of Surface Roughness on Sensing Performance of Surface Plasmon Resonance Detection for Refractive Index Sensing Application

doi: 10.3390/s21186164

Figure Lengend Snippet: Flowchart of the simulation and calculation processes, including structure profile construction, RCWA, and sensor-quality computation.

Article Snippet: The RCWA software was developed in-house in the MATLAB environment utilizing the parallel computing and graphic processing toolboxes.

Techniques:

Optical reflectance of the p-polarization for four levels of rough surfaces with the varying number of diffracted orders included in the RCWA calculations. Note that the solid blue curve is for cl of 1 nm and h of 1 nm, the dashed blue curve is for cl of 1 nm and h of 20 nm, the solid black curve is for cl of 50 nm and h of 1 nm, and the dashed blue curve is for cl of 50 nm and h of 20 nm.

Journal: Sensors (Basel, Switzerland)

Article Title: Analysis of Effects of Surface Roughness on Sensing Performance of Surface Plasmon Resonance Detection for Refractive Index Sensing Application

doi: 10.3390/s21186164

Figure Lengend Snippet: Optical reflectance of the p-polarization for four levels of rough surfaces with the varying number of diffracted orders included in the RCWA calculations. Note that the solid blue curve is for cl of 1 nm and h of 1 nm, the dashed blue curve is for cl of 1 nm and h of 20 nm, the solid black curve is for cl of 50 nm and h of 1 nm, and the dashed blue curve is for cl of 50 nm and h of 20 nm.

Article Snippet: The RCWA software was developed in-house in the MATLAB environment utilizing the parallel computing and graphic processing toolboxes.

Techniques:

( a ) The normalized sensitivity based on Equation (8); and ( b ) the difference between Equation (8) and the RCWA simulation.

Journal: Sensors (Basel, Switzerland)

Article Title: Analysis of Effects of Surface Roughness on Sensing Performance of Surface Plasmon Resonance Detection for Refractive Index Sensing Application

doi: 10.3390/s21186164

Figure Lengend Snippet: ( a ) The normalized sensitivity based on Equation (8); and ( b ) the difference between Equation (8) and the RCWA simulation.

Article Snippet: The RCWA software was developed in-house in the MATLAB environment utilizing the parallel computing and graphic processing toolboxes.

Techniques:

( a ) The normalized full width at half maximum using Equation (9); and ( b ) the difference between Equation (9) and the RCWA simulation.

Journal: Sensors (Basel, Switzerland)

Article Title: Analysis of Effects of Surface Roughness on Sensing Performance of Surface Plasmon Resonance Detection for Refractive Index Sensing Application

doi: 10.3390/s21186164

Figure Lengend Snippet: ( a ) The normalized full width at half maximum using Equation (9); and ( b ) the difference between Equation (9) and the RCWA simulation.

Article Snippet: The RCWA software was developed in-house in the MATLAB environment utilizing the parallel computing and graphic processing toolboxes.

Techniques:

( a ) The normalized intensity difference using Equation (10); and ( b ) the difference between Equation (10) and the RCWA simulation.

Journal: Sensors (Basel, Switzerland)

Article Title: Analysis of Effects of Surface Roughness on Sensing Performance of Surface Plasmon Resonance Detection for Refractive Index Sensing Application

doi: 10.3390/s21186164

Figure Lengend Snippet: ( a ) The normalized intensity difference using Equation (10); and ( b ) the difference between Equation (10) and the RCWA simulation.

Article Snippet: The RCWA software was developed in-house in the MATLAB environment utilizing the parallel computing and graphic processing toolboxes.

Techniques:

( a ) The FOM using Monte Carlo simulation; ( b ) the normalized FOM based on Equation (12); and ( c ) the difference between Equation (12) and the RCWA simulation.

Journal: Sensors (Basel, Switzerland)

Article Title: Analysis of Effects of Surface Roughness on Sensing Performance of Surface Plasmon Resonance Detection for Refractive Index Sensing Application

doi: 10.3390/s21186164

Figure Lengend Snippet: ( a ) The FOM using Monte Carlo simulation; ( b ) the normalized FOM based on Equation (12); and ( c ) the difference between Equation (12) and the RCWA simulation.

Article Snippet: The RCWA software was developed in-house in the MATLAB environment utilizing the parallel computing and graphic processing toolboxes.

Techniques: