Reflective polarizer film is an optical layer used in modern TVs to improve brightness and energy efficiency. It works by reflecting unused light polarization back into the backlight unit, where it can be recycled and redirected through the display in the correct polarization state. This process increases overall light utilization, allowing the display to appear brighter without increasing power consumption.
Overview
Understand the simulation workflow and key results
In this example, we will simulate a multilayer birefringent polymeric reflective polarizer film, and the results will be exported in a json file that can be used in Lumerical Sub-Wavelength Model (LSWM) plugin in Ansys Speos for optical simulation.
The simulated reflective polarizer film is illustrated below. It consists of alternating layers of isotropic and birefringent materials.
The refractive indices are dispersive according to the following equation:
$$n_{1,2}=A_{1,2}+\frac{B_{1,2}}{λ^2}+\frac{C_{1,2}}{λ^4}$$
where 𝐴 1,2 , 𝐵 1,2 and 𝐶 1,2 are the fitting parameters.
The thicknesses 𝑑 1 and 𝑑 2 of material 1 and 2 can be derived from the following equation:
$$n_1d_1+n_2d_2=\frac{λ_B}{2}$$
In this example we consider:
$$\frac{n_1d_1}{n_2d_2}=1$$
and
$$dn=n_2-n_1=0.25$$
Step 1. Run and export results for reflective polarizer with uniform layers
In this step, the reflection characteristics of the reflective polarizer are evaluated by sweeping the incident angles (theta and phi). The results are exported to a json file for use in Speos.
Step 2. Run and export results for reflective polarizer with varying thickness distribution
To get broadband reflection, layers with varying thicknesses can be used. In this step we start with the layer thicknesses of the previous step, and we vary them linearly according to:
$$4nd_i=λ_{Bi}=0.38+0.48\frac{i}{N}$$
The results for different incident angles (theta and phi) are exported to a json file for use in Speos.
Step 3. Validate and visualize results in Speos
In this step, the exported JSON file is imported into Speos and linked to a surface defined using the Lumerical Sub-Wavelength Plugin. A series of simulations is then performed using different wavelength sources at the specified incident angles to quantify the reflection and transmission energy introduced by the reflective polarizer.
An additional simulation is conducted with a back reflector included, demonstrating the energy recycling behavior within a display panel.
Run and results
Instructions for running the model and discussion of key results
Step 1 Run and export results for reflective polarizer with uniform layers
- Open and run the reflective_polarizer.lsf script file. The script will run STACK solver for all combinations of incident theta and phi angles and for all specified frequency points.
| Note : The script might require several minutes to run depending on the number of wavelengths and incident angles. |
The reflection result for normal incidence for both p and s polarization is presented below.
Step 2 Run and export results for reflective polarizer with varying thickness distribution
- Open and run the reflective_polarizer_varying_thickness.lsf script file. The script will run STACK solver for all combinations of incident theta and phi angles and for all specified frequency points. The equation above will be used to vary the layers’ thickness.
| Note : The script might require several minutes to run depending on the number of wavelengths and incident angles. |
The reflectance of p-polarization and s-polarization using gradient thickness distribution for normal incidence is presented below:
Using varying layer thickness, the reflection for p-polarization covers approximately a wavelength range of 430nm – 860nm for normal incidence.
Step 3 Validate and visualize results in Speos
- Open the project reflective_polarizer.scdocx and check the setting for material definition for “reflective_polarizer”. The method of using LSWM plugin in Speos can also be found in the article . In the project provided, three collimated surface sources are defined with incident angles of 0°, 30°, and 60°.
- Load the script Speos validation.py .
- Modify line 7 to select the appropriate source based on the incident angle calculated in STACK (e.g., use 0° for normal incidence when working with the JSON files provided in the article). If necessary, adjust line 9 to select the sampling data calculated in STACK.
- Execute the script.
The script outputs the reflectance and transmittance of the reflective polarizer as functions of wavelength for the specified incident angle.
When using reflective_polarizer.json for the reflective polarizer surface, the reflectance results should show behavior consistent with the Lumerical STACK solver: near 100% reflection in the 520–580 nm wavelength range when uniform layers are used.
If the JSON file is changed to reflective_polarizer_gradient.json , the total reflection range extends from 400–700 nm, which also agrees with the results obtained from the Lumerical STACK solver.
Remove the vertical polarizer surface and add a back reflector to the simulation, or alternatively use the preconfigured simulation named “System.” The updated configuration consists of a reflective polarizer, a surface backlight source, and a reflector defined as an ideal perfect mirror.
In this configuration, one polarization state is transmitted through the reflective polarizer, while the orthogonal polarization state is reflected. The reflected component then interacts with the back reflector and is further redirected toward the reflective polarizer, enabling energy recycling within the system. Verify the simulation settings to ensure that the maximum number of surface interactions is set to 10,000, as light undergoes multiple reflections between the reflective polarizer and the reflector.
Finally, check the total transmitted energy of the system. It should be approximately 99.9%, confirming that the energy recycling mechanism is functioning as expected.
Important model settings
Description of important objects and settings used in this model
Lumerical model setting
Permittivity rotation
The STACK solver assumes that the plane of incidence is always the xz plane (i.e., φ =0). To obtain the response of anisotropic layers for incident light with a given azimuthal angle φ , the optic axis-equivalently, the permittivity tensor-of the corresponding materials must be rotated by -φ .
Speos model setting
Sensor colorimetric and spectral sampling
It is important to choose the match sampling that are simulated in STACK.
Updating the model
Instructions for updating the model based on your device parameters
Customized materials
In the model, dispersive materials are implemented using predefined fitting parameters. Users can define additional dispersive or non-dispersive materials. Materials may also be added to the material database, which supports only diagonal permittivity tensors. More information can be found in Creating anisotropic optical materials in FDTD and MODE – Ansys Optics.
Customized layer thicknesses
Users can specify the thickness of each layer in the reflective polarizer model. The thickness profile can be uniform or vary following a linear or exponential profile.
Additional Resources
Additional documentation, examples and training material
Related Publications
- Y. Li, T. X. Wu and S. -T. Wu, "Design Optimization of Reflective Polarizers for LCD Backlight Recycling," in Journal of Display Technology, vol. 5, no. 8, pp. 335-340, Aug. 2009, doi: 10.1109/JDT.2009.2027033
See Also
- Antireflective circular polarizers in OLED display
- STACK Optical Solver Overview
- stackrt - Script command
- Lumerical Sub-Wavelength Model plugin: Introduction and Data Generation
- High-Resolution OLED Modeling with 2D Spatially Varying RGB Intensity
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