{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f524391f",
   "metadata": {},
   "source": [
    "# Microwave frequency selective surface (FSS)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73a4ff08",
   "metadata": {},
   "source": [
    "A Frequency Selective Surface (FSS) is a type of electromagnetic structure that allows certain frequencies to pass through while reflecting or blocking other frequencies. It is composed of a periodic array of conductive or dielectric elements that are spaced apart at a distance that is much smaller than the wavelength of the electromagnetic radiation. The FSS can be designed to selectively filter and manipulate the electromagnetic waves that pass through it based on the geometry, spacing, and material properties of its constituent elements. It is often used as a passive component in microwave and millimeter-wave devices, such as antennas, radars, filters, and absorbers.\n",
    "\n",
    "This notebook provides a demonstration of a microwave FSS composed of copper cross structures. Due to its very thin copper layer (0.1 mm) compared to the wavelength (~2.5 cm), we model the copper layer as a 2D surface conductivity to ensure computational efficiency. The FSS has been designed to exhibit a stop band at 12 GHz, where the transmission (S21) reaches as low as -50 dB. By visualizing the field distribution at the resonant frequency, we can observe the dipolar resonance feature of the copper structure. This simulation showcases the effectiveness of FSSs as passive components in microwave devices, and their ability to manipulate electromagnetic waves with high precision.\n",
    "\n",
    "<img src=\"img/frequency_selective_surface.png\" width=\"500\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5cb1ff77",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:00:31.077388Z",
     "iopub.status.busy": "2023-03-28T01:00:31.076753Z",
     "iopub.status.idle": "2023-03-28T01:00:32.348158Z",
     "shell.execute_reply": "2023-03-28T01:00:32.347508Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import tidy3d as td\n",
    "import tidy3d.web as web\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f913f7e",
   "metadata": {},
   "source": [
    "## Simulation Setup"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4911bc70",
   "metadata": {},
   "source": [
    "The default frequency unit in `Tidy3D` is Hz. For convenience, we prefer to work with GHz in this example. A frequency range from 10 GHz to 14 GHz is studied while the FSS is designed to resonate at 12 GHz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7cdf5e48",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:00:32.351051Z",
     "iopub.status.busy": "2023-03-28T01:00:32.350738Z",
     "iopub.status.idle": "2023-03-28T01:00:32.369990Z",
     "shell.execute_reply": "2023-03-28T01:00:32.368526Z"
    }
   },
   "outputs": [],
   "source": [
    "GHz = 1e9  # 1 GHz = 1e9 Hz\n",
    "\n",
    "freq0 = 12 * GHz  # central frequency\n",
    "freqs = np.linspace(10, 14, 500) * GHz  # frequency range of interest\n",
    "\n",
    "fwidth = 0.5 * (np.max(freqs) - np.min(freqs))  # width of the source spectrum\n",
    "\n",
    "lda0 = td.C_0 / freq0  # central wavelength\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4eebf85",
   "metadata": {},
   "source": [
    "The default length unit in Tidy3D is $\\mu m$. For convenience, we prefer to work with mm in this example. Here we define the geometric parameters such as the length and width of the cross structure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "17b42904",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:00:32.375569Z",
     "iopub.status.busy": "2023-03-28T01:00:32.375219Z",
     "iopub.status.idle": "2023-03-28T01:00:32.401550Z",
     "shell.execute_reply": "2023-03-28T01:00:32.400960Z"
    }
   },
   "outputs": [],
   "source": [
    "mm = 1e3  # 1 mm = 1e3 um\n",
    "P = 15 * mm  # periodicity of the unit cell\n",
    "L = 9.4 * mm  # length of the cross\n",
    "W = 2 * mm  # width of the cross\n",
    "t_sub = 2.2 * mm  # thickness of the substrate\n",
    "t_copper = 0.1 * mm  # thickness of the copper layer\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2eb43d28",
   "metadata": {},
   "source": [
    "Since the copper layer is very thin, we model it as a [Medium2D](../_autosummary/tidy3d.Medium2D.html) instead of a regular [Medium](../_autosummary/tidy3d.Medium.html). This way, we do not need to use a very fine grid to resolve the actual thickness of the copper layer. The conductivity of copper is about $5\\times 10^7$ S/m, which is 50 S/$\\mu m$. We use the `from_medium` method to construct a [Medium2D](../_autosummary/tidy3d.Medium2D.html) from a regular [Medium](../_autosummary/tidy3d.Medium.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "fbce46a3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:00:32.404097Z",
     "iopub.status.busy": "2023-03-28T01:00:32.403953Z",
     "iopub.status.idle": "2023-03-28T01:00:32.421598Z",
     "shell.execute_reply": "2023-03-28T01:00:32.421041Z"
    }
   },
   "outputs": [],
   "source": [
    "sigma_copper = 50  # copper conductivity in S/um\n",
    "copper = td.Medium2D.from_medium(\n",
    "    td.Medium(conductivity=sigma_copper), thickness=t_copper\n",
    ")  # define copper as a Medium2D\n",
    "\n",
    "eps_sub = 2.5  # permittivity of the substrate\n",
    "sub_medium = td.Medium(permittivity=eps_sub)  # define substrate medium\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f28b280",
   "metadata": {},
   "source": [
    "Next, we define the [Structures](../_autosummary/tidy3d.Structure.html). [Medium2D](../_autosummary/tidy3d.Medium2D.html) can only be applied to geometry with zero thickness in one of the dimensions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c49e7a95",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:00:32.423985Z",
     "iopub.status.busy": "2023-03-28T01:00:32.423849Z",
     "iopub.status.idle": "2023-03-28T01:00:32.442326Z",
     "shell.execute_reply": "2023-03-28T01:00:32.441782Z"
    }
   },
   "outputs": [],
   "source": [
    "cross = []\n",
    "cross.append(\n",
    "    td.Structure(\n",
    "        geometry=td.Box.from_bounds(\n",
    "            rmin=(-L / 2, -W / 2, t_sub), rmax=(L / 2, W / 2, t_sub)\n",
    "        ),\n",
    "        medium=copper,\n",
    "    )\n",
    ")\n",
    "cross.append(\n",
    "    td.Structure(\n",
    "        geometry=td.Box.from_bounds(\n",
    "            rmin=(-W / 2, -L / 2, t_sub), rmax=(W / 2, L / 2, t_sub)\n",
    "        ),\n",
    "        medium=copper,\n",
    "    )\n",
    ")\n",
    "\n",
    "substrate = td.Structure(\n",
    "    geometry=td.Box(center=(0, 0, t_sub / 2), size=(td.inf, td.inf, t_sub)),\n",
    "    medium=sub_medium,\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acf9173e",
   "metadata": {},
   "source": [
    "A [PlaneWave](../_autosummary/tidy3d.PlaneWave.html) source polarized in the x direction is added as the incident wave from the top of the FSS. To measure reflection (S11) and transmission (S21), two [FluxMonitors](../_autosummary/tidy3d.FluxMonitor.html) are added on the top and bottom of the simulation domain. Lastly, to visualize the resonant mode field, a [FieldMonitor](../_autosummary/tidy3d.FieldMonitor.html) is added to the copper layer plane."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d0fb135b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:00:32.444643Z",
     "iopub.status.busy": "2023-03-28T01:00:32.444507Z",
     "iopub.status.idle": "2023-03-28T01:00:32.465022Z",
     "shell.execute_reply": "2023-03-28T01:00:32.463557Z"
    }
   },
   "outputs": [],
   "source": [
    "offset = lda0 / 2  # extra spacing added in the positive and negative z directions\n",
    "\n",
    "# define a plane wave source\n",
    "plane_wave = td.PlaneWave(\n",
    "    center=(0, 0, t_sub + 0.1 * offset),\n",
    "    size=(td.inf, td.inf, 0),\n",
    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
    "    direction=\"-\",\n",
    ")\n",
    "\n",
    "# define a flux monitor to measure reflection\n",
    "S11_monitor = td.FluxMonitor(\n",
    "    center=(0, 0, t_sub + offset),\n",
    "    size=(td.inf, td.inf, 0),\n",
    "    freqs=freqs,\n",
    "    name=\"S11\",\n",
    ")\n",
    "\n",
    "# define a flux monitor to measure reflection\n",
    "S21_monitor = td.FluxMonitor(\n",
    "    center=(0, 0, -t_sub - offset),\n",
    "    size=(td.inf, td.inf, 0),\n",
    "    freqs=freqs,\n",
    "    name=\"S21\",\n",
    "    normal_dir=\"-\",\n",
    ")\n",
    "\n",
    "# define a field monitor to visualize field distribution\n",
    "field_monitor = td.FieldMonitor(\n",
    "    center=(0, 0, t_sub), size=(td.inf, td.inf, 0), freqs=[freq0], name=\"field\"\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c69509c7",
   "metadata": {},
   "source": [
    "With the previously defined structures, source, and monitors, we are ready to define a `Tidy3D` [Simulation](../_autosummary/tidy3d.Simulation.html). Periodic boundary condition is applied in the $x$ and $y$ directions while [PML](../_autosummary/tidy3d.PML.html) is applied in the $z$ direction. \n",
    "\n",
    "We also set up automatic nonuniform grids. In addition, we use a mesh override structure around the FFS unit cell to further refine the grids."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1a42e3b2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:00:32.470524Z",
     "iopub.status.busy": "2023-03-28T01:00:32.470174Z",
     "iopub.status.idle": "2023-03-28T01:00:32.503002Z",
     "shell.execute_reply": "2023-03-28T01:00:32.502431Z"
    }
   },
   "outputs": [],
   "source": [
    "# simulation domain size in z\n",
    "Lz = t_sub + 2.2 * offset\n",
    "\n",
    "# define a BoundarySpec\n",
    "boundary_spec = td.BoundarySpec(\n",
    "    x=td.Boundary.periodic(),\n",
    "    y=td.Boundary.periodic(),\n",
    "    z=td.Boundary(minus=td.PML(), plus=td.PML()),\n",
    ")\n",
    "\n",
    "# define a mesh override structure\n",
    "refine_box = td.Structure(\n",
    "    geometry=td.Box(center=(0, 0, t_sub / 2), size=(td.inf, td.inf, 2 * t_sub)),\n",
    "    medium=td.Medium(permittivity=5**2),\n",
    ")\n",
    "\n",
    "# define a GridSpec\n",
    "grid_spec = td.GridSpec.auto(\n",
    "    min_steps_per_wvl=100, wavelength=lda0, override_structures=[refine_box]\n",
    ")\n",
    "\n",
    "run_time = 1e-8  # simulation run time\n",
    "\n",
    "# define simulation\n",
    "sim = td.Simulation(\n",
    "    size=(P, P, Lz),\n",
    "    grid_spec=grid_spec,\n",
    "    structures=[substrate] + cross,\n",
    "    sources=[plane_wave],\n",
    "    monitors=[S11_monitor, S21_monitor, field_monitor],\n",
    "    run_time=run_time,\n",
    "    boundary_spec=boundary_spec,\n",
    "    symmetry=(-1, 1, 0),  # symmetry is used to reduce the computational load\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93cc2c38",
   "metadata": {},
   "source": [
    "Before submitting the simulation job to the server, we can validate the simulation setup by plotting it. Here we overlay the grids on top to make sure the grid is sufficiently fine compared to the structure sizes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "21d5ee79",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:00:32.505317Z",
     "iopub.status.busy": "2023-03-28T01:00:32.505179Z",
     "iopub.status.idle": "2023-03-28T01:00:32.999576Z",
     "shell.execute_reply": "2023-03-28T01:00:32.999079Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(1, 2, tight_layout=True, figsize=(10, 5))\n",
    "sim.plot(z=t_sub, ax=ax[0])\n",
    "sim.plot_grid(z=0, ax=ax[0])\n",
    "ax[0].set_xlim(0, 5000)\n",
    "ax[0].set_ylim(0, 5000)\n",
    "\n",
    "sim.plot(x=0, ax=ax[1])\n",
    "sim.plot_grid(x=0, ax=ax[1])\n",
    "ax[1].set_xlim(0, 5000)\n",
    "ax[1].set_ylim(-2000, 5000)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7acb394",
   "metadata": {},
   "source": [
    "Submit the simulation job to the server."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ced2b1d8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:00:33.001561Z",
     "iopub.status.busy": "2023-03-28T01:00:33.001392Z",
     "iopub.status.idle": "2023-03-28T01:01:17.518786Z",
     "shell.execute_reply": "2023-03-28T01:01:17.518239Z"
    }
   },
   "outputs": [],
   "source": [
    "job = web.Job(simulation=sim, task_name=\"frequency_selective_surface\")\n",
    "sim_data = job.run(path=\"data/simulation_data.hdf5\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "398bb3f5",
   "metadata": {},
   "source": [
    "## Result Visualization "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c77716d",
   "metadata": {},
   "source": [
    "After the simulation is complete, we first visualize the S-parameters. A prominent resonance feature is observed at 12 GHz where S21 reaches -50 dB. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "765dc01b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:01:18.221038Z",
     "iopub.status.busy": "2023-03-28T01:01:18.220855Z",
     "iopub.status.idle": "2023-03-28T01:01:18.388905Z",
     "shell.execute_reply": "2023-03-28T01:01:18.388398Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "S11 = sim_data[\"S11\"].flux\n",
    "S21 = sim_data[\"S21\"].flux\n",
    "\n",
    "plt.plot(freqs / GHz, 10 * np.log10(S11), label=\"S11\")\n",
    "plt.plot(freqs / GHz, 10 * np.log10(S21), label=\"S21\")\n",
    "plt.xlim(10, 14)\n",
    "plt.ylim(-60, 0)\n",
    "plt.xlabel(\"Frequency (GHz)\")\n",
    "plt.ylabel(\"S-parameters (dB)\")\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "75414fcf",
   "metadata": {},
   "source": [
    "Lastly, we plot the field intensity distribution at the resonant frequency. A strong dipolar field pattern is observed in the horizontal copper pattern. This dipolar resonance is responsible for the total reflection of the electromagnetic wave at this frequency."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9c9bb0ad",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:01:18.390913Z",
     "iopub.status.busy": "2023-03-28T01:01:18.390763Z",
     "iopub.status.idle": "2023-03-28T01:01:19.289839Z",
     "shell.execute_reply": "2023-03-28T01:01:19.289310Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[11:54:32] </span>WARNING: Evaluating permittivity of a <span style=\"color: #008000; text-decoration-color: #008000\">'Medium2D'</span> is unphysical.                                <a href=\"file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[11:54:32]\u001b[0m\u001b[2;36m \u001b[0mWARNING: Evaluating permittivity of a \u001b[32m'Medium2D'\u001b[0m is unphysical.                                \u001b]8;id=303589;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=47986;file://C:\\Users\\xinzhong\\Desktop\\tidy3d\\tidy3d\\log.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_data.plot_field(field_monitor_name=\"field\", field_name=\"E\", val=\"abs^2\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2d88f2e7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
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   "language": "python",
   "name": "python3"
  },
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       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000\">\ud83d\udeb6 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Finishing 'frequency_selective_surface'...</span>\n</pre>\n",
          "text/plain": "\u001b[32m\ud83d\udeb6 \u001b[0m \u001b[1;32mFinishing 'frequency_selective_surface'...\u001b[0m\n"
         },
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       "outputs": [
        {
         "data": {
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         },
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       "layout": "IPY_MODEL_6b0389bfb9814a73ae2e978901701b43",
       "msg_id": "",
       "outputs": [
        {
         "data": {
          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000\">\ud83c\udfc3 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Starting 'frequency_selective_surface'...</span>\n</pre>\n",
          "text/plain": "\u001b[32m\ud83c\udfc3 \u001b[0m \u001b[1;32mStarting 'frequency_selective_surface'...\u001b[0m\n"
         },
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