BiosensorGrating.ipynb

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   "source": [
    "# Biosensor grating simulation\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>).\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. "
   ]
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   "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."
   ]
  },
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   "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"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Source Setup\n",
    "\n",
    "Create the plane wave source which excites the structure from underneath."
   ]
  },
  {
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   "execution_count": 3,
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   "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."
   ]
  },
  {
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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\">[10:17:42] </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Default value for the field monitor          </span> <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/monitor.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">monitor.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/monitor.py#261\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">261</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'colocate'</span><span style=\"color: #800000; text-decoration-color: #800000\"> setting has changed to </span><span style=\"color: #008000; text-decoration-color: #008000\">'True'</span><span style=\"color: #800000; text-decoration-color: #800000\"> in Tidy3D    </span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2.4</span><span style=\"color: #800000; text-decoration-color: #800000\">.</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span><span style=\"color: #800000; text-decoration-color: #800000\">. All field components will be colocated to the  </span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #800000; text-decoration-color: #800000\">grid boundaries. Set to </span><span style=\"color: #008000; text-decoration-color: #008000\">'False'</span><span style=\"color: #800000; text-decoration-color: #800000\"> to get the raw fields </span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #800000; text-decoration-color: #800000\">on the Yee grid instead.                              </span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:17:42]\u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Default value for the field monitor          \u001b[0m \u001b]8;id=949399;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/monitor.py\u001b\\\u001b[2mmonitor.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=853929;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/monitor.py#261\u001b\\\u001b[2m261\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m\u001b[32m'colocate'\u001b[0m\u001b[31m setting has changed to \u001b[0m\u001b[32m'True'\u001b[0m\u001b[31m in Tidy3D    \u001b[0m \u001b[2m              \u001b[0m\n",
       "\u001b[2;36m           \u001b[0m\u001b[1;36m2.4\u001b[0m\u001b[31m.\u001b[0m\u001b[1;36m0\u001b[0m\u001b[31m. All field components will be colocated to the  \u001b[0m \u001b[2m              \u001b[0m\n",
       "\u001b[2;36m           \u001b[0m\u001b[31mgrid boundaries. Set to \u001b[0m\u001b[32m'False'\u001b[0m\u001b[31m to get the raw fields \u001b[0m \u001b[2m              \u001b[0m\n",
       "\u001b[2;36m           \u001b[0m\u001b[31mon the Yee grid instead.                              \u001b[0m \u001b[2m              \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "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."
   ]
  },
  {
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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()\n"
   ]
  },
  {
   "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\">           </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'biosensor'</span> with task_id                   <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/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/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#188\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">188</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-c04d48f9-487b-40e5-9542-c812c2952b2av1'</span>.          <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'biosensor'\u001b[0m with task_id                   \u001b]8;id=412864;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=802531;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#188\u001b\\\u001b[2m188\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m\u001b[32m'fdve-c04d48f9-487b-40e5-9542-c812c2952b2av1'\u001b[0m.          \u001b[2m             \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                               <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/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/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#190\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">190</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c04d48f9-487b-40e5-9542-c812c2952b2av1\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-</span></a> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c04d48f9-487b-40e5-9542-c812c2952b2av1\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">c04d48f9-487b-40e5-9542-c812c2952b2av1'</span></a>.                <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                               \u001b]8;id=549397;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=518758;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#190\u001b\\\u001b[2m190\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m\u001b]8;id=900649;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c04d48f9-487b-40e5-9542-c812c2952b2av1\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=795660;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c04d48f9-487b-40e5-9542-c812c2952b2av1\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=900649;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c04d48f9-487b-40e5-9542-c812c2952b2av1\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=405776;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c04d48f9-487b-40e5-9542-c812c2952b2av1\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=900649;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c04d48f9-487b-40e5-9542-c812c2952b2av1\u001b\\\u001b[32m-\u001b[0m\u001b]8;;\u001b\\ \u001b[2m             \u001b[0m\n",
       "\u001b[2;36m           \u001b[0m\u001b]8;id=900649;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c04d48f9-487b-40e5-9542-c812c2952b2av1\u001b\\\u001b[32mc04d48f9-487b-40e5-9542-c812c2952b2av1'\u001b[0m\u001b]8;;\u001b\\.                \u001b[2m             \u001b[0m\n"
      ]
     },
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       "Output()"
      ]
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     "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\">[10:17:49] </span>status = queued                                         <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/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/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#361\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">361</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:17:49]\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                         \u001b]8;id=911669;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=293846;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#361\u001b\\\u001b[2m361\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
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    },
    {
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       "Output()"
      ]
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     "metadata": {},
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    },
    {
     "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\">[10:17:58] </span>status = preprocess                                     <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/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/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#355\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">355</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:17:58]\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                     \u001b]8;id=510631;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=295452;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#355\u001b\\\u001b[2m355\u001b[0m\u001b]8;;\u001b\\\n"
      ]
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    },
    {
     "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"
      ],
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     },
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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\">[10:18:03] </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Use                     <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/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/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#341\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">341</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed FlexCredit   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>cost after a simulation run.                            <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:18:03]\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.025\u001b[0m. Use                     \u001b]8;id=562408;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=566309;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#341\u001b\\\u001b[2m341\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m\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   \u001b[2m             \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mcost after a simulation run.                            \u001b[2m             \u001b[0m\n"
      ]
     },
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    },
    {
     "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>starting up solver                                      <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/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/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#377\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">377</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                      \u001b]8;id=975433;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=570869;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#377\u001b\\\u001b[2m377\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
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    },
    {
     "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                                          <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/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/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#386\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">386</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                          \u001b]8;id=970088;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=73522;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#386\u001b\\\u001b[2m386\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
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    },
    {
     "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   <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/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/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#387\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">387</span></a>\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   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>web UI. Terminating the Python script will not stop the <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>job running on the cloud.                               <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\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   \u001b]8;id=361088;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=821617;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\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   \u001b[2m             \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mweb UI. Terminating the Python script will not stop the \u001b[2m             \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mjob running on the cloud.                               \u001b[2m             \u001b[0m\n"
      ]
     },
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       "Output()"
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     },
     "metadata": {},
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    },
    {
     "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\">[10:18:20] </span>early shutoff detected, exiting.                        <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/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/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#404\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">404</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:18:20]\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected, exiting.                        \u001b]8;id=820660;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=178467;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#404\u001b\\\u001b[2m404\u001b[0m\u001b]8;;\u001b\\\n"
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       "</pre>\n"
      ],
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       "\n"
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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\">           </span>status = postprocess                                    <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/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/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#419\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">419</span></a>\n",
       "</pre>\n"
      ],
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                    \u001b]8;id=928548;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=300728;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#419\u001b\\\u001b[2m419\u001b[0m\u001b]8;;\u001b\\\n"
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     },
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       "Output()"
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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\">[10:18:24] </span>status = success                                        <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/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/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#426\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">426</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:18:24]\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                        \u001b]8;id=94370;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=289190;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#426\u001b\\\u001b[2m426\u001b[0m\u001b]8;;\u001b\\\n"
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     "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"
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       "model_id": "7be3f123d15c4526aa9a242621bc82de",
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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\"></pre>\n"
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     },
     "metadata": {},
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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"
      ],
      "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\">[10:18:25] </span>loading SimulationData from data/biosensor.hdf5         <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/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/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#590\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">590</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[10:18:25]\u001b[0m\u001b[2;36m \u001b[0mloading SimulationData from data/biosensor.hdf5         \u001b]8;id=134801;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=718447;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#590\u001b\\\u001b[2m590\u001b[0m\u001b]8;;\u001b\\\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)\n"
   ]
  },
  {
   "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()\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": {
    "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()\n"
   ]
  }
 ],
 "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": "Python 3 (ipykernel)",
   "language": "python",
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  "keywords": "grating, biosensor, Tidy3D, FDTD",
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   "name": "python",
   "nbconvert_exporter": "python",
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   "version": "3.9.16"
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