tidy3d.SemiconductorMedium#
- class SemiconductorMedium[source]#
Bases:
AbstractChargeMediumThis class is used to define semiconductors.
- Parameters:
name (Optional[str] = None) – Optional unique name for medium.
frequency_range (Optional[tuple[float, float]] = None) – [units = (Hz, Hz)]. Optional range of validity for the medium.
allow_gain (bool = False) – Allow the medium to be active. Caution: simulations with a gain medium are unstable, and are likely to diverge.Simulations where
allow_gainis set toTruewill still be charged even if diverged. Monitor data up to the divergence point will still be returned and can be useful in some cases.nonlinear_spec (Optional[Union[
NonlinearSpec,NonlinearSusceptibility]] = None) – Nonlinear spec applied on top of the base medium properties.modulation_spec (Optional[
ModulationSpec] = None) – Modulation spec applied on top of the base medium properties.viz_spec (Optional[
VisualizationSpec] = None) – Plotting specification for visualizing medium.heat_spec (Optional[Union[
FluidSpec,SolidSpec,SolidMedium,FluidMedium]] = None) – DEPRECATED: UseMultiPhysicsMedium. Specification of the medium heat properties. They are used for solving the heat equation via theHeatSimulationinterface. Such simulations can beused for investigating the influence of heat propagation on the properties of optical systems. Once the temperature distribution in the system is found usingHeatSimulationobject,Simulation.perturbed_mediums_copy()can be used to convert mediums with perturbation models defined into spatially dependent custom mediums. Otherwise, theheat_specdoes not directly affect the running of an opticalSimulation.permittivity (float = 1.0) – [units = None (relative permittivity)]. Relative permittivity.
N_c (Union[
ConstantEffectiveDOS,IsotropicEffectiveDOS,MultiValleyEffectiveDOS,DualValleyEffectiveDOS, PositiveFloat]) – [units = 1/cm^3]. \(N_c\) Effective density of states in the conduction band.N_v (Union[
ConstantEffectiveDOS,IsotropicEffectiveDOS,MultiValleyEffectiveDOS,DualValleyEffectiveDOS, PositiveFloat]) – [units = 1/cm^3]. \(N_v\) Effective density of states in the valence band.E_g (Union[
ConstantEnergyBandGap,VarshniEnergyBandGap, PositiveFloat]) – [units = eV]. \(E_g\) Band-gap energymobility_n (Union[
CaugheyThomasMobility,ConstantMobilityModel]) – Mobility model for electronsmobility_p (Union[
CaugheyThomasMobility,ConstantMobilityModel]) – Mobility model for holesR (tuple[Union[
AugerRecombination,DistributedGeneration,RadiativeRecombination,ShockleyReedHallRecombination,HurkxDirectBandToBandTunneling,SelberherrImpactIonization], …] = ()) – Array containing the R models to be applied to the material.delta_E_g (Optional[
SlotboomBandGapNarrowing] = None) – [units = eV]. \(\Delta E_g\) Bandgap narrowing model.N_a (Union[tuple[Union[
ConstantDoping,GaussianDoping,CustomDoping], …], list[Union[ConstantDoping,GaussianDoping,CustomDoping]], SpatialDataArray, NonNegativeFloat] = ()) – [units = 1/cm^3]. Concentration of acceptor impurities, which create mobile holes, resulting in p-type material. Can be specified as a single float for uniform doping, aSpatialDataArrayfor a custom profile, or a tuple/list of geometric shapes to define specific doped regions.N_d (Union[tuple[Union[
ConstantDoping,GaussianDoping,CustomDoping], …], list[Union[ConstantDoping,GaussianDoping,CustomDoping]], SpatialDataArray, NonNegativeFloat] = ()) – [units = 1/cm^3]. Concentration of donor impurities, which create mobile electrons, resulting in n-type material. Can be specified as a single float for uniform doping, aSpatialDataArrayfor a custom profile, or a tuple/list of geometric shapes to define specific doped regions.
Notes
Semiconductors are associated with
Chargesimulations. During these simulations the Drift-Diffusion (DD) equations will be solved in semiconductors. In what follows, a description of the assumptions taken and its limitations is put forward.The iso-thermal DD equations are summarized here
\[\begin{equation} - \nabla \cdot \left( \varepsilon_0 \varepsilon_r \nabla \psi \right) = q \left( p - n + N_d^+ - N_a^- \right) \end{equation}\]\[\begin{equation} q \frac{\partial n}{\partial t} = \nabla \cdot \mathbf{J_n} - qR \end{equation}\]\[\begin{equation} q \frac{\partial p}{\partial t} = -\nabla \cdot \mathbf{J_p} - qR \end{equation}\]The system defaults to isothermal conditions at \(T=300 \text{K}\). Non-isothermal (self-heating) simulations can be enabled via appropriate analysis specifications (e.g.,
SteadyChargeDCAnalysis).The above system requires the definition of the flux functions (free carrier current density), \(\mathbf{J_n}\) and \(\mathbf{J_p}\). We consider the usual form
\[\begin{equation} \mathbf{J_n} = q \mu_n \mathbf{F_{n}} + q D_n \nabla n \end{equation}\]\[\begin{equation} \mathbf{J_p} = q \mu_p \mathbf{F_{p}} - q D_p \nabla p \end{equation}\]where we simplify the effective field defined in [1] to
\[\begin{equation} \mathbf{F_{n,p}} = \nabla \psi \end{equation}\]i.e., we are not considering the effect of band-gap narrowing and degeneracy on the effective electric field \(\mathbf{F_{n,p}}\). This is a good approximation for non-degenerate semiconductors.
Let’s explore how material properties are defined as class parameters or other classes.
Symbol
Parameter Name
Description
\(N_a\)
N_aIonized acceptors density
\(N_d\)
N_dIonized donors density
\(N_c\)
N_cEffective density of states in the conduction band.
\(N_v\)
N_vEffective density of states in valence band.
\(R\)
RGeneration-Recombination term.
\(E_g\)
E_gBandgap Energy.
\(\Delta E_g\)
delta_E_gBandgap Narrowing.
\(\sigma\)
conductivityElectrical conductivity.
\(\varepsilon_r\)
permittivityRelative permittivity.
\(q\)
tidy3d.constants.Q_eFundamental electron charge.
Example
>>> import tidy3d as td >>> default_Si = td.SemiconductorMedium( ... N_c=td.ConstantEffectiveDOS(N=2.86e19), ... N_v=td.ConstantEffectiveDOS(N=3.1e19), ... E_g=td.ConstantEnergyBandGap(eg=1.11), ... mobility_n=td.CaugheyThomasMobility( ... mu_min=52.2, ... mu=1471.0, ... ref_N=9.68e16, ... exp_N=0.68, ... exp_1=-0.57, ... exp_2=-2.33, ... exp_3=2.4, ... exp_4=-0.146, ... ), ... mobility_p=td.CaugheyThomasMobility( ... mu_min=44.9, ... mu=470.5, ... ref_N=2.23e17, ... exp_N=0.719, ... exp_1=-0.57, ... exp_2=-2.33, ... exp_3=2.4, ... exp_4=-0.146, ... ), ... R=([ ... td.ShockleyReedHallRecombination( ... tau_n=3.3e-6, ... tau_p=4e-6 ... ), ... td.RadiativeRecombination( ... r_const=1.6e-14 ... ), ... td.AugerRecombination( ... c_n=2.8e-31, ... c_p=9.9e-32 ... ), ... ]), ... delta_E_g=td.SlotboomBandGapNarrowing( ... v1=6.92 * 1e-3, ... n2=1.3e17, ... c2=0.5, ... min_N=1e15, ... ), ... N_a=[td.ConstantDoping(concentration=1e15)], ... N_d=[td.ConstantDoping(concentration=1e15)] ... )
Warning
Current limitations of the formulation include:
Boltzmann statistics by default; Fermi-Dirac statistics available
Isothermal by default at T=300K; self-heating available through analysis spec
Steady-state DC and small-signal AC analyses supported
Dopants are considered to be fully ionized
Note
Both \(N_a\) and \(N_d\) can be either a positive number or an
xarray.DataArray.Default values for parameters and models are those appropriate for Silicon.
The current implementation is a good approximation for non-degenerate semiconductors.
Attributes
permittivitynamefrequency_rangeallow_gainnonlinear_specmodulation_specviz_specheat_specMethods
check_eg_uses_model(val)Issue deprecation warning if float is provided
check_na_uses_model(val)Issue deprecation warning if float is provided
check_nc_uses_model(val)Issue deprecation warning if float is provided
check_nd_uses_model(val)Issue deprecation warning if float is provided
check_nv_uses_model(val)Issue deprecation warning if float is provided
- N_c#
- N_v#
- E_g#
- mobility_n#
- mobility_p#
- R#
- delta_E_g#
- N_a#
- N_d#