GrapheneMetamaterial.ipynb

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   "source": [
    "# Graphene metamaterial absorber"
   ]
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    "Graphene, a single atomic sheet of carbon atoms arranged in a hexagonal lattice, has shown great promise for functional optical and optoelectronic devices. Compared to devices made of conventional materials, graphene-based devices have a unique tunability advantage since graphene's conductivity can be drastically modulated by electrostatic gating. \n",
    "\n",
    "Due to its atomic thickness, it is usually very difficult to model graphene in an FDTD simulation without using a large number of grid points. Fortunately, Tidy3D natively supports a surface conductivity model such that thin material layers can be accurately simulated even with grids much larger than the actual layer thickness. More specifically, you can model graphene directly using Tidy3D's [Material Library](../material_library.html?highlight=material%20ibrary). The graphene's conductivity is described by the well established Kubo formula, which includes the  contributions from the intraband and interband electronic transitions. To define graphene, a few parameters, namely the scattering rate, chemical potential, and temperature, are required as user inputs.\n",
    "\n",
    "This notebook demonstrates how to model a graphene fishnet metamaterial absorber in the THz frequency range. By forming a Fabry-Perot resonator between the graphene layer and a metal mirror, high absorption is achieved across a bandwidth of ~ 2 THz. The design is adapted from the seminal work [Andrei Andryieuski and Andrei V. Lavrinenko, \"Graphene metamaterials based tunable terahertz absorber: effective surface conductivity approach,\" Opt. Express 21, 9144-9155 (2013)](https://opg.optica.org/oe/fulltext.cfm?uri=oe-21-7-9144&id=252404&ibsearch=false).\n",
    "\n",
    "<img src=\"img/graphene_metamaterial_schematic.png\" width=\"400\" alt=\"Schematic of the graphene metamaterial absorber\">\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. For more simulation examples, please visit our [examples page](https://www.flexcompute.com/tidy3d/examples/). FDTD simulations can diverge due to various reasons. If you run into any simulation divergence issues, please follow the steps outlined in our [troubleshooting guide](https://www.flexcompute.com/tidy3d/examples/notebooks/DivergedFDTDSimulation/) to resolve it."
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   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import tidy3d as td\n",
    "import tidy3d.web as web\n"
   ]
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   "source": [
    "The overall design of the absorber involves two layers of graphene sheets embedded in TOPAS polymer. The bottom of the device is a metallic mirror, which forms a Fabry-Perot resonator with graphene. This resonator greatly amplifies the absorption in graphene and achieves perfect absorption when the resonance condition is met. Two designs are explored in this notebook. The first one is a simple uniform graphene layer. When the chemical potential of graphene is tuned to 0.5 eV, perfect absorption is achieved but only within a narrow frequency band. Then, we test a fishnet structure, which shows a much wider absorption band. "
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   "source": [
    "## Uniform Graphene Sheet Absorber"
   ]
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   "source": [
    "We start with a simpler case where the absorber is made of two uniform graphene layers embedded in TOPAS polymer above a ground plate. \n",
    "\n",
    "First, define the basic simulation parameters."
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   "source": [
    "THz = 1e12  # 1 THz = 1e12 Hz\n",
    "\n",
    "freq0 = 2.5 * THz  # central frequency\n",
    "freqs = np.linspace(0.1, 5, 300) * THz  # frequency range of interest\n",
    "\n",
    "lda0 = td.C_0 / freq0  # central wavelength\n"
   ]
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   "source": [
    "The TOPAS polymer has a refractive index of 1.53 in the THz range with little absorption. "
   ]
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   "source": [
    "n_topas = 1.53  # refractive index of the polymer\n",
    "topas = td.Medium(permittivity=n_topas**2)\n"
   ]
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   "source": [
    "To define graphene conductivity, we need to specify a few parameters. Here, we consider a relaxation time of $\\tau$=0.1 ps, which translates to a scattering rate $\\Gamma=\\frac{1}{2\\tau}=\\frac{6.58e-16}{2 \\times 1e-13}=$0.0033 eV, where 6.58e-16 is $\\hbar$ in the unit of eV*s. The temperature is at room temperature. Since there are two layers of graphene, the scaling parameter is set to 2. Note that this only works for graphene layers separated by a small distance. For real bilayer graphene or few-layer graphene in general, the conductivity is more complex as interlayer coupling and stacking order play an important role."
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    "gamma = 0.0033  # scattering rate\n",
    "temp = 300  # temperature\n",
    "scaling = 2  # number of layers.\n"
   ]
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   "source": [
    "Furthermore, we consider a unit cell size of 15 $\\mu m$. In the uniform graphene sheet absorber, the distance between the graphene and the mirror is 35.9 $\\mu m$."
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    "a = 15  # unit cell size\n",
    "h = 35.9  # distance between graphene and the ground plate\n",
    "offset = lda0 / 2  # distance between the flux monitor and the graphene\n"
   ]
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    "The periodic boundary condition is applied in both the $x$ and $y$ directions. In the $z$ direction, PML is applied in the plus direction and PEC is applied in the minus direction. The PEC mimics the metal mirror. For the grids, we use automatic nonuniform grids in all directions. The same [BoundarySpec](../api/_autosummary/tidy3d.BoundarySpec.html?highlight=BOUNDARYSPEC) and [GridSpec](../api/_autosummary/tidy3d.GridSpec.html?highlight=gridspec) will be used through the notebook."
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    "# define a BoundarySpec\n",
    "boundary_spec = td.BoundarySpec(\n",
    "    x=td.Boundary.periodic(),\n",
    "    y=td.Boundary.periodic(),\n",
    "    z=td.Boundary(minus=td.PECBoundary(), plus=td.PML()),\n",
    ")\n",
    "\n",
    "# define a GridSpec\n",
    "grid_spec = td.GridSpec.auto(min_steps_per_wvl=200, wavelength=lda0)\n",
    "\n",
    "# simulation run time\n",
    "run_time = 1e-11\n"
   ]
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   "source": [
    "Next we define a function that returns a simulation at a given graphene chemical potential. This function will later be called repeatedly to construct a simulation batch to investigate how the chemical potential affects the absorption spectrum."
   ]
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    "def make_sim_uniform(mu_c):\n",
    "\n",
    "    # define graphene\n",
    "    graphene = td.material_library[\"graphene\"](\n",
    "        gamma=gamma, mu_c=mu_c, temp=temp, scaling=scaling\n",
    "    ).medium\n",
    "\n",
    "    # define graphene structure\n",
    "    graphene_layer = td.Structure(\n",
    "        geometry=td.Box(center=(0, 0, h), size=(td.inf, td.inf, 0)), medium=graphene\n",
    "    )\n",
    "\n",
    "    # define a plane wave source\n",
    "    plane_wave = td.PlaneWave(\n",
    "        center=(0, 0, h + 0.1 * offset),\n",
    "        size=(td.inf, td.inf, 0),\n",
    "        source_time=td.GaussianPulse(freq0=freq0, fwidth=freq0 / 2),\n",
    "        direction=\"-\",\n",
    "    )\n",
    "\n",
    "    # define a flux monitor to measure reflection\n",
    "    flux_monitor = td.FluxMonitor(\n",
    "        center=(0, 0, h + offset),\n",
    "        size=(td.inf, td.inf, 0),\n",
    "        freqs=freqs,\n",
    "        name=\"R\",\n",
    "    )\n",
    "\n",
    "    # simulation domain size in z\n",
    "    Lz = h + 1.1 * offset\n",
    "\n",
    "    # define simulation\n",
    "    sim = td.Simulation(\n",
    "        center=(0, 0, Lz / 2),\n",
    "        size=(a, a, Lz),\n",
    "        grid_spec=grid_spec,\n",
    "        structures=[graphene_layer],\n",
    "        sources=[plane_wave],\n",
    "        monitors=[flux_monitor],\n",
    "        run_time=run_time,\n",
    "        medium=topas,\n",
    "        boundary_spec=boundary_spec,\n",
    "        shutoff=1e-7,\n",
    "        symmetry=(-1, 1, 0),  # symmetry is used to reduce the computational load\n",
    "    )\n",
    "\n",
    "    return sim\n"
   ]
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   "source": [
    "Specifically, we study $\\mu_c=$0, 0.1, 0.2, and 0.5 eV. "
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       "\u001B[2;36m           \u001B[0m\u001B[31moutside of `Medium.frequency_range` = \u001B[0m\u001B[1;31m(\u001B[0m\u001B[1;36m1000000000000.0\u001B[0m\u001B[31m, \u001B[0m \u001B[2m            \u001B[0m\n",
       "\u001B[2;36m           \u001B[0m\u001B[1;36m1000000000000000.0\u001B[0m\u001B[1;31m)\u001B[0m\u001B[31m                                     \u001B[0m \u001B[2m            \u001B[0m\n"
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       "\u001B[2;36m          \u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: frequency passed to `\u001B[0m\u001B[1;35mMedium.eps_model\u001B[0m\u001B[1;31m(\u001B[0m\u001B[1;31m)\u001B[0m\u001B[31m`is     \u001B[0m \u001B]8;id=581308;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py\u001B\\\u001B[2mmedium.py\u001B[0m\u001B]8;;\u001B\\\u001B[2m:\u001B[0m\u001B]8;id=735365;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py#64\u001B\\\u001B[2m64\u001B[0m\u001B]8;;\u001B\\\n",
       "\u001B[2;36m           \u001B[0m\u001B[31moutside of `Medium.frequency_range` = \u001B[0m\u001B[1;31m(\u001B[0m\u001B[1;36m1000000000000.0\u001B[0m\u001B[31m, \u001B[0m \u001B[2m            \u001B[0m\n",
       "\u001B[2;36m           \u001B[0m\u001B[1;36m1000000000000000.0\u001B[0m\u001B[1;31m)\u001B[0m\u001B[31m                                     \u001B[0m \u001B[2m            \u001B[0m\n"
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   "source": [
    "mu_cs = [0, 0.1, 0.2, 0.5]  # values of mu_c to be simulated\n",
    "\n",
    "# define a simulation batch\n",
    "sims = {f\"mu_c={mu_c:.2f}\": make_sim_uniform(mu_c) for mu_c in mu_cs}\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4b6fb5c",
   "metadata": {},
   "source": [
    "Submit the simulation batch to the server."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5a706f2c",
   "metadata": {
    "execution": {
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     "iopub.status.busy": "2023-08-18T18:28:59.562728Z",
     "iopub.status.idle": "2023-08-18T18:29:37.537121Z",
     "shell.execute_reply": "2023-08-18T18:29:37.534743Z"
    }
   },
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-e7f9c895-55f6-411b-9941-8f6e30852b7av1'</span>.          <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
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       "\u001B[2;36m           \u001B[0m\u001B[32m'fdve-e7f9c895-55f6-411b-9941-8f6e30852b7av1'\u001B[0m.          \u001B[2m             \u001B[0m\n"
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       "\u001B[2;36m           \u001B[0m\u001B[32m'fdve-f2d0defb-9bf8-4085-9a71-23505ffd1ea7v1'\u001B[0m.          \u001B[2m             \u001B[0m\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>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'mu_c=0.20'</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-095e3ae5-0053-4177-829c-e820b2a53350v1'</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'\u001B[0m\u001B[32mmu_c\u001B[0m\u001B[32m=\u001B[0m\u001B[32m0\u001B[0m\u001B[32m.20'\u001B[0m with task_id                   \u001B]8;id=451627;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=97816;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-095e3ae5-0053-4177-829c-e820b2a53350v1'\u001B[0m.          \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>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-095e3ae5-0053-4177-829c-e820b2a53350v1\" 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-095e3ae5-0053-4177-829c-e820b2a53350v1\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">095e3ae5-0053-4177-829c-e820b2a53350v1'</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=567390;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=725002;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=784361;https://tidy3d.simulation.cloud/workbench?taskId=fdve-095e3ae5-0053-4177-829c-e820b2a53350v1\u001B\\\u001B[32m'https://tidy3d.simulation.cloud/workbench?\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=809329;https://tidy3d.simulation.cloud/workbench?taskId=fdve-095e3ae5-0053-4177-829c-e820b2a53350v1\u001B\\\u001B[32mtaskId\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=784361;https://tidy3d.simulation.cloud/workbench?taskId=fdve-095e3ae5-0053-4177-829c-e820b2a53350v1\u001B\\\u001B[32m=\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=847594;https://tidy3d.simulation.cloud/workbench?taskId=fdve-095e3ae5-0053-4177-829c-e820b2a53350v1\u001B\\\u001B[32mfdve\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=784361;https://tidy3d.simulation.cloud/workbench?taskId=fdve-095e3ae5-0053-4177-829c-e820b2a53350v1\u001B\\\u001B[32m-\u001B[0m\u001B]8;;\u001B\\ \u001B[2m             \u001B[0m\n",
       "\u001B[2;36m           \u001B[0m\u001B]8;id=784361;https://tidy3d.simulation.cloud/workbench?taskId=fdve-095e3ae5-0053-4177-829c-e820b2a53350v1\u001B\\\u001B[32m095e3ae5-0053-4177-829c-e820b2a53350v1'\u001B[0m\u001B]8;;\u001B\\.                \u001B[2m             \u001B[0m\n"
      ]
     },
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    {
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       "Output()"
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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"
      ],
      "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\">[11:29:01] </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'mu_c=0.50'</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-d6b08b2f-efef-4cb0-864d-19c302858c67v1'</span>.          <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001B[2;36m[11:29:01]\u001B[0m\u001B[2;36m \u001B[0mCreated task \u001B[32m'\u001B[0m\u001B[32mmu_c\u001B[0m\u001B[32m=\u001B[0m\u001B[32m0\u001B[0m\u001B[32m.50'\u001B[0m with task_id                   \u001B]8;id=455725;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=525999;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-d6b08b2f-efef-4cb0-864d-19c302858c67v1'\u001B[0m.          \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>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-d6b08b2f-efef-4cb0-864d-19c302858c67v1\" 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-d6b08b2f-efef-4cb0-864d-19c302858c67v1\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">d6b08b2f-efef-4cb0-864d-19c302858c67v1'</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=463043;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=568770;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=393766;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d6b08b2f-efef-4cb0-864d-19c302858c67v1\u001B\\\u001B[32m'https://tidy3d.simulation.cloud/workbench?\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=724624;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d6b08b2f-efef-4cb0-864d-19c302858c67v1\u001B\\\u001B[32mtaskId\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=393766;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d6b08b2f-efef-4cb0-864d-19c302858c67v1\u001B\\\u001B[32m=\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=436357;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d6b08b2f-efef-4cb0-864d-19c302858c67v1\u001B\\\u001B[32mfdve\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=393766;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d6b08b2f-efef-4cb0-864d-19c302858c67v1\u001B\\\u001B[32m-\u001B[0m\u001B]8;;\u001B\\ \u001B[2m             \u001B[0m\n",
       "\u001B[2;36m           \u001B[0m\u001B]8;id=393766;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d6b08b2f-efef-4cb0-864d-19c302858c67v1\u001B\\\u001B[32md6b08b2f-efef-4cb0-864d-19c302858c67v1'\u001B[0m\u001B]8;;\u001B\\.                \u001B[2m             \u001B[0m\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\"></pre>\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\">\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\">[11:29:02] </span>Started working on Batch.                            <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">container.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py#475\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">475</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001B[2;36m[11:29:02]\u001B[0m\u001B[2;36m \u001B[0mStarted working on Batch.                            \u001B]8;id=27534;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py\u001B\\\u001B[2mcontainer.py\u001B[0m\u001B]8;;\u001B\\\u001B[2m:\u001B[0m\u001B]8;id=66503;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py#475\u001B\\\u001B[2m475\u001B[0m\u001B]8;;\u001B\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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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\">[11:29:30] </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.100</span> for the whole batch.  <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">container.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py#479\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">479</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>Use <span style=\"color: #008000; text-decoration-color: #008000\">'Batch.real_cost()'</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 the Batch has completed.                  <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001B[2;36m[11:29:30]\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m0.100\u001B[0m for the whole batch.  \u001B]8;id=582905;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py\u001B\\\u001B[2mcontainer.py\u001B[0m\u001B]8;;\u001B\\\u001B[2m:\u001B[0m\u001B]8;id=42621;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py#479\u001B\\\u001B[2m479\u001B[0m\u001B]8;;\u001B\\\n",
       "\u001B[2;36m           \u001B[0mUse \u001B[32m'Batch.real_cost\u001B[0m\u001B[32m(\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 the Batch has completed.                  \u001B[2m                \u001B[0m\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\">[11:29:37] </span>Batch complete.                                      <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">container.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py#522\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">522</span></a>\n",
       "</pre>\n"
      ],
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       "\u001B[2;36m[11:29:37]\u001B[0m\u001B[2;36m \u001B[0mBatch complete.                                      \u001B]8;id=590092;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py\u001B\\\u001B[2mcontainer.py\u001B[0m\u001B]8;;\u001B\\\u001B[2m:\u001B[0m\u001B]8;id=600276;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py#522\u001B\\\u001B[2m522\u001B[0m\u001B]8;;\u001B\\\n"
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   "source": [
    "batch = web.Batch(simulations=sims, folder_name=\"default\")\n",
    "batch_results = batch.run(path_dir=\"data\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b14e5299",
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   "source": [
    "After the batch of jobs is complete, we want to plot the absorption spectra. Since the bottom ground plane is a perfect mirror, absorption is simply $A=1-R$, where $R$ is the reflection. A function `plot_absorption` is defined to do this plotting. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "75eb91f2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T18:29:37.757989Z",
     "iopub.status.busy": "2023-08-18T18:29:37.757669Z",
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     "shell.execute_reply": "2023-08-18T18:29:37.776842Z"
    }
   },
   "outputs": [],
   "source": [
    "def plot_absorption(batch_results):\n",
    "    for i, mu_c in enumerate(mu_cs):\n",
    "        sim_data = batch_results[f\"mu_c={mu_c:.2f}\"]\n",
    "        A = 1 - sim_data[\"R\"].flux\n",
    "        plt.plot(freqs / THz, A, label=f\"{mu_c:.2f} eV\")\n",
    "        plt.xlim(0, 5)\n",
    "        plt.ylim(0, 1)\n",
    "        plt.xlabel(\"Frequency (THz)\")\n",
    "        plt.ylabel(\"Absorption\")\n",
    "        plt.legend()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6516c046",
   "metadata": {},
   "source": [
    "At 0.5 eV chemical potential, perfect absorption is observed around 2.3 THz. However, the bandwidth is rather small."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "77f7b725",
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     "iopub.status.idle": "2023-08-18T18:29:40.179648Z",
     "shell.execute_reply": "2023-08-18T18:29:40.179210Z"
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_absorption(batch_results)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f49c61a9",
   "metadata": {},
   "source": [
    "## Graphene Fishnet Absorber"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3ae8df1",
   "metadata": {},
   "source": [
    "To enhance the absorption bandwidth, a fishnet design is explored, as discussed in the [reference](https://opg.optica.org/oe/fulltext.cfm?uri=oe-21-7-9144&id=252404&ibsearch=false).\n",
    "\n",
    "Similarly, we define a function here that returns a simulation at a given graphene chemical potential. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9fe6635e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T18:29:40.209007Z",
     "iopub.status.busy": "2023-08-18T18:29:40.208872Z",
     "iopub.status.idle": "2023-08-18T18:29:40.230467Z",
     "shell.execute_reply": "2023-08-18T18:29:40.229988Z"
    }
   },
   "outputs": [],
   "source": [
    "# fishnet parameters\n",
    "b = 2\n",
    "w = 12\n",
    "\n",
    "h = 17.6  # distance between the graphene and the ground plate\n",
    "inf_eff = 1e3  # effective infinity\n",
    "\n",
    "\n",
    "def make_sim_fishnet(mu_c):\n",
    "    # define graphene\n",
    "    graphene = td.material_library[\"graphene\"](\n",
    "        gamma=gamma, mu_c=mu_c, temp=temp, scaling=scaling\n",
    "    ).medium\n",
    "\n",
    "    # define the fishnet structure\n",
    "    graphene_finishnet_center = td.Structure(\n",
    "        geometry=td.Box.from_bounds(rmin=(0, 0, h), rmax=(w / 2, w / 2, h)),\n",
    "        medium=graphene,\n",
    "    )\n",
    "    graphene_finishnet_right = td.Structure(\n",
    "        geometry=td.Box.from_bounds(rmin=(w / 2, 0, h), rmax=(inf_eff, b / 2, h)),\n",
    "        medium=graphene,\n",
    "    )\n",
    "    graphene_finishnet_top = td.Structure(\n",
    "        geometry=td.Box.from_bounds(rmin=(0, w / 2, h), rmax=(b / 2, inf_eff, h)),\n",
    "        medium=graphene,\n",
    "    )\n",
    "\n",
    "    # define a plane wave source\n",
    "    plane_wave = td.PlaneWave(\n",
    "        center=(0, 0, h + 0.1 * offset),\n",
    "        size=(td.inf, td.inf, 0),\n",
    "        source_time=td.GaussianPulse(freq0=freq0, fwidth=freq0 / 2),\n",
    "        direction=\"-\",\n",
    "    )\n",
    "\n",
    "    # define a flux monitor to measure reflection\n",
    "    flux_monitor = td.FluxMonitor(\n",
    "        center=(0, 0, h + offset),\n",
    "        size=(td.inf, td.inf, 0),\n",
    "        freqs=freqs,\n",
    "        name=\"R\",\n",
    "    )\n",
    "\n",
    "    # simulation domain size in z\n",
    "    Lz = h + 1.1 * offset\n",
    "\n",
    "    # define simulation\n",
    "    sim = td.Simulation(\n",
    "        center=(0, 0, Lz / 2),\n",
    "        size=(a, a, Lz),\n",
    "        grid_spec=grid_spec,\n",
    "        structures=[\n",
    "            graphene_finishnet_center,\n",
    "            graphene_finishnet_right,\n",
    "            graphene_finishnet_top,\n",
    "        ],\n",
    "        sources=[plane_wave],\n",
    "        monitors=[flux_monitor],\n",
    "        run_time=run_time,\n",
    "        medium=topas,\n",
    "        boundary_spec=boundary_spec,\n",
    "        shutoff=1e-7,\n",
    "        symmetry=(-1, 1, 0),\n",
    "    )\n",
    "\n",
    "    return sim\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62d74707",
   "metadata": {},
   "source": [
    "To make sure the structures are defined correctly, use the `plot` method to visualize the fishnet. Due to symmetry, only a quarter of it needs to be defined."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "cfc44984",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T18:29:40.232399Z",
     "iopub.status.busy": "2023-08-18T18:29:40.232263Z",
     "iopub.status.idle": "2023-08-18T18:29:40.863478Z",
     "shell.execute_reply": "2023-08-18T18:29:40.862978Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #800000; text-decoration-color: #800000\">outside of `Medium.frequency_range` = </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1000000000000.0</span><span style=\"color: #800000; text-decoration-color: #800000\">, </span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">            </span>\n",
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       "</pre>\n"
      ],
      "text/plain": [
       "\u001B[2;36m[11:29:40]\u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: frequency passed to `\u001B[0m\u001B[1;35mMedium.eps_model\u001B[0m\u001B[1;31m(\u001B[0m\u001B[1;31m)\u001B[0m\u001B[31m`is     \u001B[0m \u001B]8;id=625809;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py\u001B\\\u001B[2mmedium.py\u001B[0m\u001B]8;;\u001B\\\u001B[2m:\u001B[0m\u001B]8;id=472692;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py#64\u001B\\\u001B[2m64\u001B[0m\u001B]8;;\u001B\\\n",
       "\u001B[2;36m           \u001B[0m\u001B[31moutside of `Medium.frequency_range` = \u001B[0m\u001B[1;31m(\u001B[0m\u001B[1;36m1000000000000.0\u001B[0m\u001B[31m, \u001B[0m \u001B[2m            \u001B[0m\n",
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     "metadata": {},
     "output_type": "display_data"
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     "data": {
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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><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: frequency passed to `</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Medium.eps_model</span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">()</span><span style=\"color: #800000; text-decoration-color: #800000\">`is     </span> <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">medium.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py#64\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">64</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #800000; text-decoration-color: #800000\">outside of `Medium.frequency_range` = </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1000000000000.0</span><span style=\"color: #800000; text-decoration-color: #800000\">, </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\">1000000000000000.0</span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">)</span><span style=\"color: #800000; text-decoration-color: #800000\">                                     </span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">            </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001B[2;36m          \u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: frequency passed to `\u001B[0m\u001B[1;35mMedium.eps_model\u001B[0m\u001B[1;31m(\u001B[0m\u001B[1;31m)\u001B[0m\u001B[31m`is     \u001B[0m \u001B]8;id=807625;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py\u001B\\\u001B[2mmedium.py\u001B[0m\u001B]8;;\u001B\\\u001B[2m:\u001B[0m\u001B]8;id=778418;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py#64\u001B\\\u001B[2m64\u001B[0m\u001B]8;;\u001B\\\n",
       "\u001B[2;36m           \u001B[0m\u001B[31moutside of `Medium.frequency_range` = \u001B[0m\u001B[1;31m(\u001B[0m\u001B[1;36m1000000000000.0\u001B[0m\u001B[31m, \u001B[0m \u001B[2m            \u001B[0m\n",
       "\u001B[2;36m           \u001B[0m\u001B[1;36m1000000000000000.0\u001B[0m\u001B[1;31m)\u001B[0m\u001B[31m                                     \u001B[0m \u001B[2m            \u001B[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim = make_sim_fishnet(0.5)\n",
    "ax = sim.plot(z=h)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24fe60ce",
   "metadata": {},
   "source": [
    "A batch of simulations at different chemical potentials is defined and submitted to the server. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6c616915",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T18:29:40.865473Z",
     "iopub.status.busy": "2023-08-18T18:29:40.865327Z",
     "iopub.status.idle": "2023-08-18T18:30:18.965218Z",
     "shell.execute_reply": "2023-08-18T18:30:18.964319Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[11:29:41] </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: frequency passed to `</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Medium.eps_model</span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">()</span><span style=\"color: #800000; text-decoration-color: #800000\">`is     </span> <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">medium.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py#64\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">64</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #800000; text-decoration-color: #800000\">outside of `Medium.frequency_range` = </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1000000000000.0</span><span style=\"color: #800000; text-decoration-color: #800000\">, </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\">1000000000000000.0</span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">)</span><span style=\"color: #800000; text-decoration-color: #800000\">                                     </span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">            </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001B[2;36m[11:29:41]\u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: frequency passed to `\u001B[0m\u001B[1;35mMedium.eps_model\u001B[0m\u001B[1;31m(\u001B[0m\u001B[1;31m)\u001B[0m\u001B[31m`is     \u001B[0m \u001B]8;id=11023;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py\u001B\\\u001B[2mmedium.py\u001B[0m\u001B]8;;\u001B\\\u001B[2m:\u001B[0m\u001B]8;id=177409;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py#64\u001B\\\u001B[2m64\u001B[0m\u001B]8;;\u001B\\\n",
       "\u001B[2;36m           \u001B[0m\u001B[31moutside of `Medium.frequency_range` = \u001B[0m\u001B[1;31m(\u001B[0m\u001B[1;36m1000000000000.0\u001B[0m\u001B[31m, \u001B[0m \u001B[2m            \u001B[0m\n",
       "\u001B[2;36m           \u001B[0m\u001B[1;36m1000000000000000.0\u001B[0m\u001B[1;31m)\u001B[0m\u001B[31m                                     \u001B[0m \u001B[2m            \u001B[0m\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><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: frequency passed to `</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Medium.eps_model</span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">()</span><span style=\"color: #800000; text-decoration-color: #800000\">`is     </span> <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">medium.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py#64\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">64</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #800000; text-decoration-color: #800000\">outside of `Medium.frequency_range` = </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1000000000000.0</span><span style=\"color: #800000; text-decoration-color: #800000\">, </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\">1000000000000000.0</span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">)</span><span style=\"color: #800000; text-decoration-color: #800000\">                                     </span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">            </span>\n",
       "</pre>\n"
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       "\u001B[2;36m          \u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: frequency passed to `\u001B[0m\u001B[1;35mMedium.eps_model\u001B[0m\u001B[1;31m(\u001B[0m\u001B[1;31m)\u001B[0m\u001B[31m`is     \u001B[0m \u001B]8;id=703321;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py\u001B\\\u001B[2mmedium.py\u001B[0m\u001B]8;;\u001B\\\u001B[2m:\u001B[0m\u001B]8;id=115012;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py#64\u001B\\\u001B[2m64\u001B[0m\u001B]8;;\u001B\\\n",
       "\u001B[2;36m           \u001B[0m\u001B[31moutside of `Medium.frequency_range` = \u001B[0m\u001B[1;31m(\u001B[0m\u001B[1;36m1000000000000.0\u001B[0m\u001B[31m, \u001B[0m \u001B[2m            \u001B[0m\n",
       "\u001B[2;36m           \u001B[0m\u001B[1;36m1000000000000000.0\u001B[0m\u001B[1;31m)\u001B[0m\u001B[31m                                     \u001B[0m \u001B[2m            \u001B[0m\n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #800000; text-decoration-color: #800000\">outside of `Medium.frequency_range` = </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1000000000000.0</span><span style=\"color: #800000; text-decoration-color: #800000\">, </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\">1000000000000000.0</span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">)</span><span style=\"color: #800000; text-decoration-color: #800000\">                                     </span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">            </span>\n",
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       "\u001B[2;36m[11:29:42]\u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: frequency passed to `\u001B[0m\u001B[1;35mMedium.eps_model\u001B[0m\u001B[1;31m(\u001B[0m\u001B[1;31m)\u001B[0m\u001B[31m`is     \u001B[0m \u001B]8;id=251756;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py\u001B\\\u001B[2mmedium.py\u001B[0m\u001B]8;;\u001B\\\u001B[2m:\u001B[0m\u001B]8;id=827114;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py#64\u001B\\\u001B[2m64\u001B[0m\u001B]8;;\u001B\\\n",
       "\u001B[2;36m           \u001B[0m\u001B[31moutside of `Medium.frequency_range` = \u001B[0m\u001B[1;31m(\u001B[0m\u001B[1;36m1000000000000.0\u001B[0m\u001B[31m, \u001B[0m \u001B[2m            \u001B[0m\n",
       "\u001B[2;36m           \u001B[0m\u001B[1;36m1000000000000000.0\u001B[0m\u001B[1;31m)\u001B[0m\u001B[31m                                     \u001B[0m \u001B[2m            \u001B[0m\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><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: frequency passed to `</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Medium.eps_model</span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">()</span><span style=\"color: #800000; text-decoration-color: #800000\">`is     </span> <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">medium.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py#64\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">64</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #800000; text-decoration-color: #800000\">outside of `Medium.frequency_range` = </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1000000000000.0</span><span style=\"color: #800000; text-decoration-color: #800000\">, </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\">1000000000000000.0</span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">)</span><span style=\"color: #800000; text-decoration-color: #800000\">                                     </span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">            </span>\n",
       "</pre>\n"
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       "\u001B[2;36m          \u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: frequency passed to `\u001B[0m\u001B[1;35mMedium.eps_model\u001B[0m\u001B[1;31m(\u001B[0m\u001B[1;31m)\u001B[0m\u001B[31m`is     \u001B[0m \u001B]8;id=363512;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py\u001B\\\u001B[2mmedium.py\u001B[0m\u001B]8;;\u001B\\\u001B[2m:\u001B[0m\u001B]8;id=910785;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/components/medium.py#64\u001B\\\u001B[2m64\u001B[0m\u001B]8;;\u001B\\\n",
       "\u001B[2;36m           \u001B[0m\u001B[31moutside of `Medium.frequency_range` = \u001B[0m\u001B[1;31m(\u001B[0m\u001B[1;36m1000000000000.0\u001B[0m\u001B[31m, \u001B[0m \u001B[2m            \u001B[0m\n",
       "\u001B[2;36m           \u001B[0m\u001B[1;36m1000000000000000.0\u001B[0m\u001B[1;31m)\u001B[0m\u001B[31m                                     \u001B[0m \u001B[2m            \u001B[0m\n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-61224bd7-a026-4ce7-80e2-66f5162ad1f2v1'</span>.          <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
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       "\u001B[2;36m          \u001B[0m\u001B[2;36m \u001B[0mCreated task \u001B[32m'\u001B[0m\u001B[32mmu_c\u001B[0m\u001B[32m=\u001B[0m\u001B[32m0\u001B[0m\u001B[32m.00'\u001B[0m with task_id                   \u001B]8;id=540280;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=663539;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-61224bd7-a026-4ce7-80e2-66f5162ad1f2v1'\u001B[0m.          \u001B[2m             \u001B[0m\n"
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       "\u001B[2;36m           \u001B[0m\u001B]8;id=689381;https://tidy3d.simulation.cloud/workbench?taskId=fdve-61224bd7-a026-4ce7-80e2-66f5162ad1f2v1\u001B\\\u001B[32m'https://tidy3d.simulation.cloud/workbench?\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=188594;https://tidy3d.simulation.cloud/workbench?taskId=fdve-61224bd7-a026-4ce7-80e2-66f5162ad1f2v1\u001B\\\u001B[32mtaskId\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=689381;https://tidy3d.simulation.cloud/workbench?taskId=fdve-61224bd7-a026-4ce7-80e2-66f5162ad1f2v1\u001B\\\u001B[32m=\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=613250;https://tidy3d.simulation.cloud/workbench?taskId=fdve-61224bd7-a026-4ce7-80e2-66f5162ad1f2v1\u001B\\\u001B[32mfdve\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=689381;https://tidy3d.simulation.cloud/workbench?taskId=fdve-61224bd7-a026-4ce7-80e2-66f5162ad1f2v1\u001B\\\u001B[32m-\u001B[0m\u001B]8;;\u001B\\ \u001B[2m             \u001B[0m\n",
       "\u001B[2;36m           \u001B[0m\u001B]8;id=689381;https://tidy3d.simulation.cloud/workbench?taskId=fdve-61224bd7-a026-4ce7-80e2-66f5162ad1f2v1\u001B\\\u001B[32m61224bd7-a026-4ce7-80e2-66f5162ad1f2v1'\u001B[0m\u001B]8;;\u001B\\.                \u001B[2m             \u001B[0m\n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-100e69b5-312e-424f-95df-fb32aa20d691v1'</span>.          <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
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       "\u001B[2;36m[11:29:43]\u001B[0m\u001B[2;36m \u001B[0mCreated task \u001B[32m'\u001B[0m\u001B[32mmu_c\u001B[0m\u001B[32m=\u001B[0m\u001B[32m0\u001B[0m\u001B[32m.10'\u001B[0m with task_id                   \u001B]8;id=107965;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=538441;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-100e69b5-312e-424f-95df-fb32aa20d691v1'\u001B[0m.          \u001B[2m             \u001B[0m\n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-100e69b5-312e-424f-95df-fb32aa20d691v1\" 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-100e69b5-312e-424f-95df-fb32aa20d691v1\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">100e69b5-312e-424f-95df-fb32aa20d691v1'</span></a>.                <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
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       "\u001B[2;36m          \u001B[0m\u001B[2;36m \u001B[0mView task using web UI at                               \u001B]8;id=899070;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=393394;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=859712;https://tidy3d.simulation.cloud/workbench?taskId=fdve-100e69b5-312e-424f-95df-fb32aa20d691v1\u001B\\\u001B[32m'https://tidy3d.simulation.cloud/workbench?\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=378708;https://tidy3d.simulation.cloud/workbench?taskId=fdve-100e69b5-312e-424f-95df-fb32aa20d691v1\u001B\\\u001B[32mtaskId\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=859712;https://tidy3d.simulation.cloud/workbench?taskId=fdve-100e69b5-312e-424f-95df-fb32aa20d691v1\u001B\\\u001B[32m=\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=481015;https://tidy3d.simulation.cloud/workbench?taskId=fdve-100e69b5-312e-424f-95df-fb32aa20d691v1\u001B\\\u001B[32mfdve\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=859712;https://tidy3d.simulation.cloud/workbench?taskId=fdve-100e69b5-312e-424f-95df-fb32aa20d691v1\u001B\\\u001B[32m-\u001B[0m\u001B]8;;\u001B\\ \u001B[2m             \u001B[0m\n",
       "\u001B[2;36m           \u001B[0m\u001B]8;id=859712;https://tidy3d.simulation.cloud/workbench?taskId=fdve-100e69b5-312e-424f-95df-fb32aa20d691v1\u001B\\\u001B[32m100e69b5-312e-424f-95df-fb32aa20d691v1'\u001B[0m\u001B]8;;\u001B\\.                \u001B[2m             \u001B[0m\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>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'mu_c=0.20'</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-40cd4b72-e67b-421e-aeec-88aa4d845b57v1'</span>.          <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
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       "\u001B[2;36m          \u001B[0m\u001B[2;36m \u001B[0mCreated task \u001B[32m'\u001B[0m\u001B[32mmu_c\u001B[0m\u001B[32m=\u001B[0m\u001B[32m0\u001B[0m\u001B[32m.20'\u001B[0m with task_id                   \u001B]8;id=677020;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=316522;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-40cd4b72-e67b-421e-aeec-88aa4d845b57v1'\u001B[0m.          \u001B[2m             \u001B[0m\n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-40cd4b72-e67b-421e-aeec-88aa4d845b57v1\" 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-40cd4b72-e67b-421e-aeec-88aa4d845b57v1\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">40cd4b72-e67b-421e-aeec-88aa4d845b57v1'</span></a>.                <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
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       "\u001B[2;36m          \u001B[0m\u001B[2;36m \u001B[0mView task using web UI at                               \u001B]8;id=926304;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=748288;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=467255;https://tidy3d.simulation.cloud/workbench?taskId=fdve-40cd4b72-e67b-421e-aeec-88aa4d845b57v1\u001B\\\u001B[32m'https://tidy3d.simulation.cloud/workbench?\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=510228;https://tidy3d.simulation.cloud/workbench?taskId=fdve-40cd4b72-e67b-421e-aeec-88aa4d845b57v1\u001B\\\u001B[32mtaskId\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=467255;https://tidy3d.simulation.cloud/workbench?taskId=fdve-40cd4b72-e67b-421e-aeec-88aa4d845b57v1\u001B\\\u001B[32m=\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=760020;https://tidy3d.simulation.cloud/workbench?taskId=fdve-40cd4b72-e67b-421e-aeec-88aa4d845b57v1\u001B\\\u001B[32mfdve\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=467255;https://tidy3d.simulation.cloud/workbench?taskId=fdve-40cd4b72-e67b-421e-aeec-88aa4d845b57v1\u001B\\\u001B[32m-\u001B[0m\u001B]8;;\u001B\\ \u001B[2m             \u001B[0m\n",
       "\u001B[2;36m           \u001B[0m\u001B]8;id=467255;https://tidy3d.simulation.cloud/workbench?taskId=fdve-40cd4b72-e67b-421e-aeec-88aa4d845b57v1\u001B\\\u001B[32m40cd4b72-e67b-421e-aeec-88aa4d845b57v1'\u001B[0m\u001B]8;;\u001B\\.                \u001B[2m             \u001B[0m\n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-6e529e36-0a18-41b9-a2ce-bc13a60623aev1'</span>.          <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
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       "\u001B[2;36m[11:29:44]\u001B[0m\u001B[2;36m \u001B[0mCreated task \u001B[32m'\u001B[0m\u001B[32mmu_c\u001B[0m\u001B[32m=\u001B[0m\u001B[32m0\u001B[0m\u001B[32m.50'\u001B[0m with task_id                   \u001B]8;id=542207;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=479291;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-6e529e36-0a18-41b9-a2ce-bc13a60623aev1'\u001B[0m.          \u001B[2m             \u001B[0m\n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-6e529e36-0a18-41b9-a2ce-bc13a60623aev1\" 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",
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       "</pre>\n"
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       "\u001B[2;36m           \u001B[0m\u001B]8;id=698723;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6e529e36-0a18-41b9-a2ce-bc13a60623aev1\u001B\\\u001B[32m'https://tidy3d.simulation.cloud/workbench?\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=266541;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6e529e36-0a18-41b9-a2ce-bc13a60623aev1\u001B\\\u001B[32mtaskId\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=698723;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6e529e36-0a18-41b9-a2ce-bc13a60623aev1\u001B\\\u001B[32m=\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=74262;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6e529e36-0a18-41b9-a2ce-bc13a60623aev1\u001B\\\u001B[32mfdve\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=698723;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6e529e36-0a18-41b9-a2ce-bc13a60623aev1\u001B\\\u001B[32m-\u001B[0m\u001B]8;;\u001B\\ \u001B[2m             \u001B[0m\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\">[11:29:45] </span>Started working on Batch.                            <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">container.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py#475\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">475</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001B[2;36m[11:29:45]\u001B[0m\u001B[2;36m \u001B[0mStarted working on Batch.                            \u001B]8;id=15034;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py\u001B\\\u001B[2mcontainer.py\u001B[0m\u001B]8;;\u001B\\\u001B[2m:\u001B[0m\u001B]8;id=275365;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py#475\u001B\\\u001B[2m475\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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[11:30:06] </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.100</span> for the whole batch.  <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">container.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py#479\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">479</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>Use <span style=\"color: #008000; text-decoration-color: #008000\">'Batch.real_cost()'</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 the Batch has completed.                  <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001B[2;36m[11:30:06]\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m0.100\u001B[0m for the whole batch.  \u001B]8;id=547832;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py\u001B\\\u001B[2mcontainer.py\u001B[0m\u001B]8;;\u001B\\\u001B[2m:\u001B[0m\u001B]8;id=298982;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py#479\u001B\\\u001B[2m479\u001B[0m\u001B]8;;\u001B\\\n",
       "\u001B[2;36m           \u001B[0mUse \u001B[32m'Batch.real_cost\u001B[0m\u001B[32m(\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 the Batch has completed.                  \u001B[2m                \u001B[0m\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\">[11:30:18] </span>Batch complete.                                      <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">container.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py#522\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">522</span></a>\n",
       "</pre>\n"
      ],
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       "\u001B[2;36m[11:30:18]\u001B[0m\u001B[2;36m \u001B[0mBatch complete.                                      \u001B]8;id=930326;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py\u001B\\\u001B[2mcontainer.py\u001B[0m\u001B]8;;\u001B\\\u001B[2m:\u001B[0m\u001B]8;id=486959;file:///home/momchil/Drive/flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py#522\u001B\\\u001B[2m522\u001B[0m\u001B]8;;\u001B\\\n"
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   ],
   "source": [
    "mu_cs = [0, 0.1, 0.2, 0.5]  # values of mu_c to be simulated\n",
    "\n",
    "# define a simulation batch\n",
    "sims = {f\"mu_c={mu_c:.2f}\": make_sim_fishnet(mu_c) for mu_c in mu_cs}\n",
    "\n",
    "# submit the batch to the server\n",
    "batch = web.Batch(simulations=sims, folder_name=\"default\")\n",
    "batch_results = batch.run(path_dir=\"data\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9aea2ae0",
   "metadata": {},
   "source": [
    "At 0.5 eV, the absorber shows an absorption bandwidth (defined as absorption above 0.9) of ~2 THz, much better than the uniform graphene absorber case."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4c4965ac",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T18:30:19.235814Z",
     "iopub.status.busy": "2023-08-18T18:30:19.235675Z",
     "iopub.status.idle": "2023-08-18T18:30:21.625675Z",
     "shell.execute_reply": "2023-08-18T18:30:21.625120Z"
    }
   },
   "outputs": [
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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\"></pre>\n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>data/fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">61224bd7-a026-4ce7-80e2-66f5162ad1f2</span>v1.hdf5   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
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       "\u001B[2;36m           \u001B[0mdata/fdve-\u001B[93m61224bd7-a026-4ce7-80e2-66f5162ad1f2\u001B[0mv1.hdf5   \u001B[2m             \u001B[0m\n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>data/fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">100e69b5-312e-424f-95df-fb32aa20d691</span>v1.hdf5   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_absorption(batch_results)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72e4644e",
   "metadata": {},
   "source": [
    "## Additional Notes about Graphene "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d9b85e8",
   "metadata": {},
   "source": [
    "As briefly discussed in the introduction, graphene's conductivity includes the contributions from both the intraband and interband electronic transitions. The intraband transitions lead to a Drude-like response that is dominant at lower frequencies. The interband transitions give rise to the prominent feature around $f=2\\mu_c$.\n",
    "\n",
    "The conductivity of graphene can be inspected by using the `numerical_conductivity` method. Here we show an example of graphene conductivity at $\\Gamma$=0.0033 eV, $\\mu_c$=0.2 eV, and $T$=300 K. Below 20 THz, the conductivity is predominantly Drude-like, which comes from the intraband transitions. The interband transition feature shows up at around 100 THz (~0.4 eV). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fbd83cbf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T18:30:21.655310Z",
     "iopub.status.busy": "2023-08-18T18:30:21.655178Z",
     "iopub.status.idle": "2023-08-18T18:30:22.202021Z",
     "shell.execute_reply": "2023-08-18T18:30:22.201526Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gamma = 0.0033  # scattering rate\n",
    "mu_c = 0.2  # chemical potential\n",
    "temp = 300  # temperature\n",
    "\n",
    "freqs = np.linspace(10, 250, 100) * THz\n",
    "graphene = td.material_library[\"graphene\"](gamma=gamma, mu_c=mu_c, temp=temp)\n",
    "sigma_analytical = graphene.numerical_conductivity(freqs)\n",
    "plt.plot(freqs / THz, np.real(sigma_analytical * 1e6), label=\"Re($\\sigma$) ($\\mu$S)\")\n",
    "plt.plot(freqs / THz, np.imag(sigma_analytical * 1e6), label=\"Im($\\sigma$) ($\\mu$S)\")\n",
    "plt.xlabel(\"frequency (THz)\")\n",
    "plt.title(\"analytically calculated surface conductivity\")\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d66f68dd",
   "metadata": {},
   "source": [
    "Like other dispersive materials used in FDTD, graphene's conductivity needs to be fitted, which is automatically done when you define a graphene medium. The plot generated by `numerical_conductivity` above is the analytical result. To inspect the fitting, one can use the `plot_sigma` method as shown below. The fitted conductivity coincides well with the analytical result in this case."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c1591ef2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-18T18:30:22.204136Z",
     "iopub.status.busy": "2023-08-18T18:30:22.203948Z",
     "iopub.status.idle": "2023-08-18T18:30:22.845818Z",
     "shell.execute_reply": "2023-08-18T18:30:22.845183Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "graphene.medium.plot_sigma(freqs)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "32145119",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "description": "This notebook demonstrates how to model a graphene metamaterial absorber in Tidy3D FDTD.",
  "feature_image": "./img/graphene_metamaterial_schematic.png",
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "keywords": "graphene, 2D material, metamaterial absorber, 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": "3.10.9"
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  "title": "Graphene Metamaterial Absorber | Flexcompute",
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