grapa.datatypes.curveCV.CurveCV

class grapa.datatypes.curveCV.CurveCV(data, attributes, silent=False)

Bases: Curve

CurveCV offer basic treatment of C-V capacitance versus voltage curves of solar cells. Input units must be [V] and [nF] (or [nF cm-2]).

__init__(data, attributes, silent=False)

Methods

`CurveCV_0V`([volt])	Creates a curve with require data to compute doping at volt=0 V
`CurveCV_fitVbiN`([Vlim, silent])	Fits the linear segment on the Mott-Schottky plot.
`CurveCV_fitVbiN_smart`([Vrange, window, silent])	Returns a Curve based on a fit on Mott-Schottky plot, after first guessing the best possible range for fifting (where N_CV is lowest).
`__init__`(data, attributes[, silent])
`alterListGUI`()	Determines the possible curve visualisations.
`fit_MottSchottky`([Vlim])	Fits the C-V data on Mott-Schottky plot, in ROI Vlim[0] to Vlim[0].
`funcListGUI`(**kwargs)	Fills in the Curve actions specific to the Curve type. Retuns a list, which elements are instances of FuncGUI, or (old style): ::.
`func_MottSchottky`(volts, v_bi, n_cv)	Computes C(V) which will appear linear on a Mott-Schottky plot.
`getArea`()	Return cell area, using dedicated keyword
`getEpsR`()
`setArea`(value)	Normalizes the device area.
`setEpsR`(value)	Set the epsilon_r (relative permittivity) value of the material of interest.
`smartVlim_MottSchottky`([Vlim, window])	Returns Vlim [Vmin, Vmax] offering a possible best range for Mott- Schottky fit.
`x_CVdepth_nm`(**kwargs)	apparent probing depth, assuming planar capacitor.
`y_CV_Napparent`([xyValue])	apparent carrier density N_CV
`y_ym2`([xyValue])	Mott-Schottky plot: 1 / C**2

Attributes

`AXISLABELS_X`
`AXISLABELS_Y`
`CST_MottSchottky_Vlim_adaptative`
`CST_MottSchottky_Vlim_def`
`CST_epsilonR`
`CURVE`
`FORMAT_AUTOLABEL`
`UNIT_LOOKUP_Y`

CurveCV_0V(volt=0)

Creates a curve with require data to compute doping at volt=0 V

Parameters:: volt – a voltage value different than 0 V

CurveCV_fitVbiN(Vlim=None, silent=False)

Fits the linear segment on the Mott-Schottky plot.

Parameters:

Vlim – [V_min, V_max] range of interest for the fit.
silent – if False, prints additional information.

Returns:

a Curve based on a fit on Mott-Schottky plot.

CurveCV_fitVbiN_smart(Vrange=None, window=[-2, 2], silent=False)

Returns a Curve based on a fit on Mott-Schottky plot, after first guessing the best possible range for fifting (where N_CV is lowest).

Parameters:

Vrange – voltage limits [V_min, V_max]
window
silent – if False, prints additional information

Returns:

a Curve object containing the Mott-Schottky fit

alterListGUI(): Determines the possible curve visualisations. One element has the form: AlterListItem(‘Label GUI’, [‘alter_x’, ‘alter_y’], ‘semilogx’, “print help doc”) By default only neutral (i.e. raw data) is provided

fit_MottSchottky(Vlim=None): Fits the C-V data on Mott-Schottky plot, in ROI Vlim[0] to Vlim[0]. Returns built-in voltage Vbi [V], apparent doping density N_CV [cm-3].

funcListGUI(**kwargs)

Fills in the Curve actions specific to the Curve type. Retuns a list, which elements are instances of FuncGUI, or (old style):

[func,
 'Button text',
 ['label 1', 'label 2', ...],
 ['value 1', 'value 2', ...],
 {'hiddenvar1': 'value1', ...}, (optional)
 [dictFieldAttributes, {}, ...]] (optional)

By default, returns quick modifs for offset and muloffset (if already set), and a help for some plot types (errorbar, scatter).

Parameters:: kwargs – this function should be called specifying kwargs[‘graph’] the graph self is embedded in, and kwargs[‘graph_i’] as position of self in graph.

func_MottSchottky(volts, v_bi, n_cv): Computes C(V) which will appear linear on a Mott-Schottky plot. - v_bi: built-in voltage [V] - n_CV: apparent doping density [cm-3] Returns: C [nF cm-2]

getArea(): Return cell area, using dedicated keyword

setArea(value)

Normalizes the device area. Modifies the y capacitance data. This module is designed for input units as [nF cm-2].

Parameters:: value – new value for device area, presumably in cm-2.

setEpsR(value)

Set the epsilon_r (relative permittivity) value of the material of interest. The value affects the different data transformation (apparent doping, apparent depth etc.) For CIGS, suitable values may be 10 to 13.

Parameters:: value – the new value for relative permittivity

smartVlim_MottSchottky(Vlim=None, window=[-2, 2]): Returns Vlim [Vmin, Vmax] offering a possible best range for Mott- Schottky fit. Assumes V in monotoneous increasing/decreasing. Window: how many points around best location are taken. Default [-2,2]

x_CVdepth_nm(**kwargs): apparent probing depth, assuming planar capacitor.

y_CV_Napparent(xyValue=None, **kwargs): apparent carrier density N_CV

y_ym2(xyValue=None, **kwargs): Mott-Schottky plot: 1 / C**2