ThermoElectric.fermi_level

ThermoElectric.fermi_level(carrier: numpy.ndarray, energy: numpy.ndarray, density: numpy.ndarray, Nc: Optional[float] = None, Ao: Optional[float] = None, temp: Optional[numpy.ndarray] = None) → numpy.ndarray[source]

This function uses Joice Dixon approximation to predict Ef and thereby the carrier concentration at each temperature A good reference book is “Principles of Semiconductor Devices” by Sima Dimitrijev.

Parameters

  • carrier (np.ndarray) – Total carrier concentration

  • energy (np.ndarray) – The electron energy level

  • density (np.ndarray) – The electron density of states

  • Nc (float) – The effective densities of states in the conduction band

  • Ao (float) – Experimentally fitted parameter (Nc ~ Ao*T^(3/2))

  • temp (np.ndarray) – Temperature range

Returns

output – The first row is the carrier concentration and the second one is the Fermi level

Return type

np.ndarray