{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Biosensor grating\n",
    "\n",
    "Bragg gratings are structures which 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 sentitive, 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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# basic imports\n",
    "import numpy as np\n",
    "import matplotlib.pylab as plt\n",
    "\n",
    "# Tidy3D imports\n",
    "import tidy3d as td\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Structure Setup\n",
    "\n",
    "Create the grating geometry."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "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)\n"
   ]
  },
  {
   "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": {
    "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",
    ")\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": {
    "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]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Simulation\n",
    "\n",
    "The final simulation object is created and visualized."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "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()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run Simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "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\">[20:20:02] </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'biosensor'</span> with task_id <span style=\"color: #008000; text-decoration-color: #008000\">'fdve-aa145913-f072-451a-b822-e00343966770v1'</span>.       <a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#139\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">139</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[20:20:02]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'biosensor'\u001b[0m with task_id \u001b[32m'fdve-aa145913-f072-451a-b822-e00343966770v1'\u001b[0m.       \u001b]8;id=740689;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=39900;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#139\u001b\\\u001b[2m139\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "aea0533edbc2482da7056d59fa0dbf9b",
       "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\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\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\">[20:20:07] </span>status = queued                                                                            <a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#269\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">269</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[20:20:07]\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                                            \u001b]8;id=709367;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=686368;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#269\u001b\\\u001b[2m269\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[20:20:11] </span>status = preprocess                                                                        <a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#263\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">263</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[20:20:11]\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                                        \u001b]8;id=357802;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=225130;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#263\u001b\\\u001b[2m263\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
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       "<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\">[20:20:15] </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed FlexCredit cost <a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#286\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">286</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>after a simulation run.                                                                    <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
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       "\u001b[2;36m[20:20:15]\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.025\u001b[0m. 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 FlexCredit cost \u001b]8;id=734031;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=751774;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#286\u001b\\\u001b[2m286\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0mafter a simulation run.                                                                    \u001b[2m             \u001b[0m\n"
      ]
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    {
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       "<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>starting up solver                                                                         <a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#290\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">290</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                                         \u001b]8;id=788454;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=515149;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#290\u001b\\\u001b[2m290\u001b[0m\u001b]8;;\u001b\\\n"
      ]
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       "<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                                                                             <a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#300\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">300</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                                             \u001b]8;id=396785;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=769366;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#300\u001b\\\u001b[2m300\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
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       "Output()"
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       "<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\">[20:20:35] </span>early shutoff detected, exiting.                                                           <a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#313\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">313</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[20:20:35]\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected, exiting.                                                           \u001b]8;id=430434;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=414404;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#313\u001b\\\u001b[2m313\u001b[0m\u001b]8;;\u001b\\\n"
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
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       "\n"
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       "<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 = postprocess                                                                       <a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#330\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">330</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                                                       \u001b]8;id=17931;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=33493;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#330\u001b\\\u001b[2m330\u001b[0m\u001b]8;;\u001b\\\n"
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       "Output()"
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     "metadata": {},
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    {
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      "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\">[20:20:38] </span>status = success                                                                           <a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#337\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">337</span></a>\n",
       "</pre>\n"
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       "\u001b[2;36m[20:20:38]\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                                           \u001b]8;id=903546;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=804690;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#337\u001b\\\u001b[2m337\u001b[0m\u001b]8;;\u001b\\\n"
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
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       "\n"
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       "<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\">[20:20:43] </span>loading SimulationData from data/biosensor.hdf5                                            <a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#512\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">512</span></a>\n",
       "</pre>\n"
      ],
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       "\u001b[2;36m[20:20:43]\u001b[0m\u001b[2;36m \u001b[0mloading SimulationData from data/biosensor.hdf5                                            \u001b]8;id=44861;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=72842;file:///home/lucas/Flexcompute/dev/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#512\u001b\\\u001b[2m512\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
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    }
   ],
   "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)\n"
   ]
  },
  {
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   "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": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "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()\n"
   ]
  },
  {
   "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": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "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()\n"
   ]
  }
 ],
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   "display_name": "Flexcompute",
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        {
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