Surface Relief Grating Design for AR and HUDs
Introduction
In our previous discussion, we explored the ANSYS optics and photonics workload. In this segment, we will focus on numerical simulations for nanoscale applications, particularly in designing 1D or 2D gratings for AR glasses and AR waveguides.
Workflow Overview
We will examine a workflow involving a 1D grating. Key parameters include:
- Height
- Period
- Width
- Filling Factor
- Angle
The goal is to optimize the grating geometry to direct light into the minus one grating order for normally incident light. This involves optimizing the grating across a range of angles for full characterization, using a JSON file for integration with other software.
Numerical FDTD and RCWA
We will focus on the RCWA (Rigorous Coupled-Wave Analysis) method. In the RCWA setup, the grating structure is defined, and the simulation considers the periodic nature of the grating, allowing one cell to suffice for the simulation.
Key steps include:
- Adding RCWA to the simulation.
- Setting the direction as backward to the Y normal.
- Defining interference reference positions and solver parameters.
- Simulating a single incident angle or a range of angles.
Optimization Process
We aim to report the index, grating order, and fill amplitude. The optimization process involves:
- Running the simulation and visualizing results.
- Focusing on the TS grating, with the horizontal axis representing the grating number and order.
- Optimizing the grating order of minus one, initially around 0.56%.
Advanced Optimization Techniques
Using numerical FDTD, we can perform optimization and sweep using particle swarm algorithms. The setup includes:
- 12 generations with a generation size of 24.
- Parameters to optimize: fill factor, height, and slant angle.
- Defining a figure of merit (FOM) for the S-polarized grating order of minus one.
Results and Visualization
After running the simulation, the best FOM achieved is 0.94, compared to the initial 0.56%. The optimized parameters are:
- Filling Factor: 0.6
- Height: 0.32 micrometers
- Angle: 32.8 degrees
These values enable achieving approximately 94% efficiency for the first grating order.
Conclusion
This example demonstrates the application of RCWA in optimizing surface relief gratings for augmented reality systems, with detailed steps and parameters available in the ANSYS knowledge base article.
For further information, please refer to the ANSYS knowledge base article on surface relief grating for augmented reality systems.
Okay, so in our previous part we discussed ANSYS optics and photonics workload. In this part, we want to focus on numerical simulation for nanoscale design, specifically for AR glasses and waveguides.
Here's a workflow: 1D or 2D grating design for AR waveguides involves optimizing grating geometry to direct light into minus one order for normally incident light. Grating parameters include height, period, width, filling factor, and angle.
In the next part, we will optimize grating performance over a range of angles and both directions using a JSON file compatible with other software. Production time and grating quality may vary depending on your machine and the C Cloud. Using the numerical FDTD method, we want to focus on RCWA.
In RCWA, you can add the grating structure as shown. Our grating structure consists of a base and multiple gratings. Since it's a periodic structure, one cell is enough for simulation. In RCWA, the direction is backward to the Y normal.
The interference reference positions and solver parameters are also shown. You can simulate one incident angle or a range of angles. After simulation, we report the index, grating order, and fill amplitude. Here's the result.
In the optimization and sweep step, we use the particle swarm algorithm to optimize the pre-auth width, height, and other parameters. Our goal is to find the grating order for the s-polarized grating as a TS, and then find the number of gratings with order minus one.
The figure of merit (FOM) is defined as the s-polarized grating order for minus one. If the simulation runs and returns the grating order, the optimization will find the best filling factor, height, and angle. By using these values, we can achieve around 0.94 for the first grating order.
This is one example of RCWA.
