{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Biosensor grating simulation\n",
    "\n",
    "Bragg gratings are structures that involve a periodic variation in the refractive index or geometry of waveguide, so that certain frequencies of light are reflected off the grating while others are transmitted.\n",
    "\n",
    "Since gratings can be designed to be extremely sensitive, one possible application they have is to detect the presence of foreign molecules. If particles such as biomolecules are deposited on the device, it will no longer have the same reflective properties in the band of frequencies for which it was designed. Therefore, carefully designed Bragg gratings can be used as biosensors.\n",
    "\n",
    "In this example, an optical biosensor grating is modeled to detect the presence of biomolecules. The grating is designed to be reflective over a narrow band around its resonant frequency, which is modified by the presence of a biomolecule.\n",
    "\n",
    "Reference:  `Brian Cunningham, Bo Lin, Jean Qiu, Peter Li, Jane Pepper, Brenda Hugh, \"A plastic colorimetric resonant optical biosensor for multiparallel detection of label-free biochemical interactions,\" Sensors and Actuators B 85 (2002)`, DOI: [10.1016/S0925-4005(02)00111-9](<https://doi.org/10.1016/S0925-4005(02)00111-9>).\n",
    "\n",
    "If you are new to the finite-difference time-domain (FDTD) method, we highly recommend going through our [FDTD101](https://www.flexcompute.com/fdtd101/) tutorials. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:17:40.627279Z",
     "iopub.status.busy": "2023-08-18T17:17:40.627114Z",
     "iopub.status.idle": "2023-08-18T17:17:41.885984Z",
     "shell.execute_reply": "2023-08-18T17:17:41.885364Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# basic imports\n",
    "import matplotlib.pylab as plt\n",
    "import numpy as np\n",
    "\n",
    "# Tidy3D imports\n",
    "import tidy3d as td"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Structure Setup\n",
    "\n",
    "Create the grating geometry."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:17:41.888479Z",
     "iopub.status.busy": "2023-08-18T17:17:41.888152Z",
     "iopub.status.idle": "2023-08-18T17:17:41.910515Z",
     "shell.execute_reply": "2023-08-18T17:17:41.910023Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# materials\n",
    "Si3N4 = td.Medium(permittivity=2.05**2)\n",
    "epoxy = td.Medium(permittivity=1.5**2)\n",
    "background = td.Medium(permittivity=1.333**2)\n",
    "\n",
    "# set basic geometric parameters (units in microns)\n",
    "nm = 1e-3\n",
    "period = 550 * nm\n",
    "grating_fill_factor = 0.5\n",
    "grating_height = 200 * nm\n",
    "film_height = 120 * nm\n",
    "epoxy_height = 380 * nm\n",
    "monitor_distance = 1.0\n",
    "monitor_gap = 0.1\n",
    "\n",
    "# the epoxy layer top surface is at z=0\n",
    "sim_center = (0, 0, 0.5 * (grating_height + film_height - epoxy_height))\n",
    "sim_size = (\n",
    "    period,\n",
    "    0,\n",
    "    epoxy_height + grating_height + film_height + 2 * (monitor_distance + monitor_gap),\n",
    ")\n",
    "\n",
    "# wavelength / frequency setup\n",
    "wavelength_min = 770 * nm\n",
    "wavelength_max = 900 * nm\n",
    "freq_min = td.C_0 / wavelength_max\n",
    "freq_max = td.C_0 / wavelength_min\n",
    "freq0 = (freq_min + freq_max) / 2.0\n",
    "fwidth = freq_max - freq_min\n",
    "run_time = 10e-12\n",
    "\n",
    "# epoxy layer\n",
    "epoxy_layer = td.Structure(\n",
    "    geometry=td.Box(\n",
    "        center=[0.0, 0.0, -0.5 * epoxy_height],\n",
    "        size=[td.inf, td.inf, epoxy_height],\n",
    "    ),\n",
    "    medium=epoxy,\n",
    "    name=\"epoxy_layer\",\n",
    ")\n",
    "\n",
    "# bottom Si3N4 film layer\n",
    "bottom_film = td.Structure(\n",
    "    geometry=td.Box(\n",
    "        center=[0.0, 0.0, 0.5 * film_height],\n",
    "        size=[td.inf, td.inf, film_height],\n",
    "    ),\n",
    "    medium=Si3N4,\n",
    "    name=\"bottom_film\",\n",
    ")\n",
    "\n",
    "# epoxy grating teeth (partially covers the film layer)\n",
    "grating_teeth = td.Structure(\n",
    "    geometry=td.Box(\n",
    "        center=[0.0, 0.0, 0.5 * grating_height],\n",
    "        size=[period * grating_fill_factor, td.inf, grating_height],\n",
    "    ),\n",
    "    medium=epoxy,\n",
    "    name=\"grating_teeth\",\n",
    ")\n",
    "\n",
    "# top Si3N4 film layer\n",
    "top_film = td.Structure(\n",
    "    geometry=td.Box(\n",
    "        center=[0.0, 0.0, grating_height + 0.5 * film_height],\n",
    "        size=[period * grating_fill_factor, td.inf, film_height],\n",
    "    ),\n",
    "    medium=Si3N4,\n",
    "    name=\"top_film\",\n",
    ")\n",
    "\n",
    "# the order her matters, because the teeth must override the bottom film layer\n",
    "geometry = [epoxy_layer, bottom_film, grating_teeth, top_film]\n",
    "\n",
    "# boundary conditions: the simulation is periodic in the x-y plane, and simulates\n",
    "# an infinite domain along z\n",
    "boundary_spec = td.BoundarySpec(\n",
    "    x=td.Boundary.periodic(),\n",
    "    y=td.Boundary.periodic(),\n",
    "    z=td.Boundary.pml(),\n",
    ")\n",
    "\n",
    "# grid specification\n",
    "grid_spec = td.GridSpec.auto(min_steps_per_wvl=30)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Source Setup\n",
    "\n",
    "Create the plane wave source which excites the structure from underneath."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:17:41.912760Z",
     "iopub.status.busy": "2023-08-18T17:17:41.912615Z",
     "iopub.status.idle": "2023-08-18T17:17:41.929876Z",
     "shell.execute_reply": "2023-08-18T17:17:41.929324Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "source_time = td.GaussianPulse(freq0=freq0, fwidth=fwidth)\n",
    "source = td.PlaneWave(\n",
    "    center=[0, 0, -(epoxy_height + monitor_distance - monitor_gap)],\n",
    "    size=[td.inf, td.inf, 0.0],\n",
    "    source_time=source_time,\n",
    "    pol_angle=0,\n",
    "    direction=\"+\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Monitor Setup\n",
    "\n",
    "Create field and flux monitors to measure reflecting and transmitted flux."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:17:41.931832Z",
     "iopub.status.busy": "2023-08-18T17:17:41.931694Z",
     "iopub.status.idle": "2023-08-18T17:17:42.081953Z",
     "shell.execute_reply": "2023-08-18T17:17:42.081591Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# create field monitor\n",
    "monitor_xz = td.FieldMonitor(\n",
    "    center=sim_center,\n",
    "    size=[td.inf, 0, td.inf],\n",
    "    freqs=[freq0],\n",
    "    name=\"fields_xz\",\n",
    ")\n",
    "\n",
    "# create flux monitors\n",
    "freqs = np.linspace(freq_min, freq_max, 1000)\n",
    "monitor_flux_refl = td.FluxMonitor(\n",
    "    center=[0, 0, -(epoxy_height + monitor_distance)],\n",
    "    size=[td.inf, td.inf, 0.0],\n",
    "    freqs=freqs,\n",
    "    name=\"flux_refl\",\n",
    ")\n",
    "monitor_flux_tran = td.FluxMonitor(\n",
    "    center=[0, 0, grating_height + film_height + monitor_distance],\n",
    "    size=[td.inf, td.inf, 0.0],\n",
    "    freqs=freqs,\n",
    "    name=\"flux_tran\",\n",
    ")\n",
    "\n",
    "monitors = [monitor_xz, monitor_flux_refl, monitor_flux_tran]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Simulation\n",
    "\n",
    "The final simulation object is created and visualized."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:17:42.083953Z",
     "iopub.status.busy": "2023-08-18T17:17:42.083812Z",
     "iopub.status.idle": "2023-08-18T17:17:42.324853Z",
     "shell.execute_reply": "2023-08-18T17:17:42.324373Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create the simulation\n",
    "sim = td.Simulation(\n",
    "    center=sim_center,\n",
    "    size=sim_size,\n",
    "    grid_spec=grid_spec,\n",
    "    structures=geometry,\n",
    "    sources=[source],\n",
    "    monitors=monitors,\n",
    "    run_time=run_time,\n",
    "    boundary_spec=boundary_spec,\n",
    "    medium=background,\n",
    "    shutoff=1e-6,\n",
    ")\n",
    "\n",
    "# plot the simulation domain\n",
    "sim.plot(y=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run Simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:17:42.326976Z",
     "iopub.status.busy": "2023-08-18T17:17:42.326797Z",
     "iopub.status.idle": "2023-08-18T17:18:25.747798Z",
     "shell.execute_reply": "2023-08-18T17:18:25.747177Z"
    },
    "tags": []
   },
   "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\">19:24:03 CEST </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'biosensor'</span> with task_id                             \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>. \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:24:03 CEST\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'biosensor'\u001b[0m with task_id                             \n",
       "\u001b[2;36m              \u001b[0m\u001b[32m'fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m. \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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\">              </span>View task using web UI at                                         \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e8</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">02-4d0e-b920-4fd13a70d138'</span></a>.                                       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                         \n",
       "\u001b[2;36m              \u001b[0m\u001b]8;id=698201;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=182263;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=698201;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=31642;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=698201;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138\u001b\\\u001b[32m-8c36c09e-e8\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m              \u001b[0m\u001b]8;id=698201;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138\u001b\\\u001b[32m02-4d0e-b920-4fd13a70d138'\u001b[0m\u001b]8;;\u001b\\.                                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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\">              </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/folder-7a0ee478-ee62-43e0-9a9e-26a06b299b0a\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                           \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=410545;https://tidy3d.simulation.cloud/folders/folder-7a0ee478-ee62-43e0-9a9e-26a06b299b0a\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                           \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b377cbf2d1074ee2b768f168d05b66e3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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\">19:24:04 CEST </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Minimum cost depends on task      \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>FlexCredit cost after a simulation run.                           \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:24:04 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.025\u001b[0m. Minimum cost depends on task      \n",
       "\u001b[2;36m              \u001b[0mexecution details. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed \n",
       "\u001b[2;36m              \u001b[0mFlexCredit cost after a simulation run.                           \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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\">19:24:05 CEST </span>status = queued                                                   \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:24:05 CEST\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                   \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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\">              </span>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or             \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.     \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>Terminating the Python script will not stop the job running on the\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>cloud.                                                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use \u001b[32m'web.abort\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or             \n",
       "\u001b[2;36m              \u001b[0m\u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or abort/delete the task in the web UI.     \n",
       "\u001b[2;36m              \u001b[0mTerminating the Python script will not stop the job running on the\n",
       "\u001b[2;36m              \u001b[0mcloud.                                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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       "model_id": "7efe15a9415f4cbf9b52aef7267e48a5",
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       "version_minor": 0
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      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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\">19:27:15 CEST </span>status = preprocess                                               \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:27:15 CEST\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                               \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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\">19:27:20 CEST </span>starting up solver                                                \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:27:20 CEST\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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\">              </span>running solver                                                    \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                    \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d35b655007be47fbb914c40713ff98de",
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       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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\">19:27:31 CEST </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">32</span>%, exiting.                           \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:27:31 CEST\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m32\u001b[0m%, exiting.                           \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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\">              </span>status = success                                                  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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\">              </span>View simulation result at                                         \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e8</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">02-4d0e-b920-4fd13a70d138'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                         \n",
       "\u001b[2;36m              \u001b[0m\u001b]8;id=188328;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=300033;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=188328;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=245535;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=188328;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138\u001b\\\u001b[4;34m-8c36c09e-e8\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m              \u001b[0m\u001b]8;id=188328;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8c36c09e-e802-4d0e-b920-4fd13a70d138\u001b\\\u001b[4;34m02-4d0e-b920-4fd13a70d138'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                       \n"
      ]
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       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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\">19:27:33 CEST </span>loading simulation from data/biosensor.hdf5                       \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m19:27:33 CEST\u001b[0m\u001b[2;36m \u001b[0mloading simulation from data/biosensor.hdf5                       \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# run simulation\n",
    "import tidy3d.web as web\n",
    "\n",
    "sim_data = web.run(sim, task_name=\"biosensor\", path=\"data/biosensor.hdf5\", verbose=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot Fields\n",
    "\n",
    "The frequency-domain fields recorded are plotted at the center frequency in an `xz` plane. The resonance can be clearly seen in the power flow pattern shown by the Poynting vector plots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:18:26.454089Z",
     "iopub.status.busy": "2023-08-18T17:18:26.453908Z",
     "iopub.status.idle": "2023-08-18T17:18:27.648898Z",
     "shell.execute_reply": "2023-08-18T17:18:27.648351Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 3, figsize=(8, 6), tight_layout=True)\n",
    "\n",
    "sim_data.plot_field(\"fields_xz\", field_name=\"Ex\", val=\"abs\", f=freq0, ax=ax[0])\n",
    "sim_data.plot_field(\"fields_xz\", field_name=\"Sz\", val=\"real\", f=freq0, ax=ax[1])\n",
    "sim_data.plot_field(\"fields_xz\", field_name=\"Sx\", val=\"real\", f=freq0, ax=ax[2])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot Transmission and Reflection\n",
    "\n",
    "To see the effectiveness of the grating, we can compute and plot the reflection and transmission via the flux measured by the flux monitor. As the plot shows, the structure is highly reflective in a narrow frequency range around the design frequency, allowing one to detect small variations in the frequency response due to the presence of biological materials. The vertical dashed line shows the wavelength used in the previous plots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T17:18:27.651135Z",
     "iopub.status.busy": "2023-08-18T17:18:27.650887Z",
     "iopub.status.idle": "2023-08-18T17:18:27.796125Z",
     "shell.execute_reply": "2023-08-18T17:18:27.795542Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "transmission = sim_data[\"flux_tran\"].flux\n",
    "reflection = -sim_data[\"flux_refl\"].flux\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(9, 4))\n",
    "\n",
    "ax.plot(td.C_0 / freqs * 1e3, reflection, label=\"Reflection\")\n",
    "ax.plot(td.C_0 / freqs * 1e3, transmission, label=\"Transmission\")\n",
    "\n",
    "# wavelength for the field plots\n",
    "ax.axvline(td.C_0 / freq0 * 1e3, ls=\"--\", color=\"k\", lw=1)\n",
    "\n",
    "ax.set(\n",
    "    xlabel=\"Wavelength (nm)\",\n",
    "    ylabel=\"Flux\",\n",
    "    xlim=(wavelength_min * 1e3, wavelength_max * 1e3),\n",
    ")\n",
    "ax.legend()\n",
    "ax.grid()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "applications": [
   "Metamaterials, gratings, and other periodic structures",
   "Sensors"
  ],
  "description": "This notebook demonstrates how to model a biosensor grating in Tidy3D FDTD.",
  "feature_image": "./img/biosensor_grating.png",
  "features": [],
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "keywords": "grating, biosensor, Tidy3D, FDTD",
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.5"
  },
  "title": "Biosensor grating Modeling in Tidy3D | Flexcompute",
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