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Linear Polarization

This page documents the Linear Polarization (LP) method.

pypalmsens.corrosion.LinearPolarization

Create linear polarization method parameters.

Linear polarization is typically used to study the corrosion response of metallic coatings. The method is equivalent to Linear Sweep Voltammetry.

Methods:

  • to_dict

    Return the technique instance as a new key/value dictionary mapping.

  • from_dict

    Structure technique instance from dict.

  • from_method_id

    Create new instance of appropriate technique from method ID.

Attributes:

material class-attribute instance-attribute

material: Material = Field(default_factory=Material)

Stores material settings for corrosion measurements.

general class-attribute instance-attribute

general: General = Field(default_factory=General)

Sets general/other settings.

multiplexer class-attribute instance-attribute

multiplexer: Multiplexer = Field(default_factory=Multiplexer)

Set the multiplexer settings.

data_processing class-attribute instance-attribute

data_processing: DataProcessing = Field(default_factory=DataProcessing)

Set the data processing settings.

measurement_triggers class-attribute instance-attribute

measurement_triggers: MeasurementTriggers = Field(default_factory=MeasurementTriggers)

Set the trigger at measurement settings.

equilibrion_triggers class-attribute instance-attribute

equilibrion_triggers: EquilibrationTriggers = Field(default_factory=EquilibrationTriggers)

Set the trigger at equilibration settings.

ir_drop_compensation class-attribute instance-attribute

ir_drop_compensation: IrDropCompensation = Field(default_factory=IrDropCompensation)

Set the iR drop compensation settings.

current_limits class-attribute instance-attribute

current_limits: CurrentLimits = Field(default_factory=CurrentLimits)

Set the current limit settings.

post_measurement class-attribute instance-attribute

post_measurement: PostMeasurement = Field(default_factory=PostMeasurement)

Set the post measurement settings.

bipot class-attribute instance-attribute

bipot: BiPot = Field(default_factory=BiPot)

Set the bipot settings.

versus_ocp class-attribute instance-attribute

versus_ocp: VersusOCP = Field(default_factory=VersusOCP)

Set the versus OCP settings.

pretreatment class-attribute instance-attribute

pretreatment: Pretreatment = Field(default_factory=Pretreatment)

Set the pretreatment settings.

current_range class-attribute instance-attribute

current_range: CurrentRange = Field(default_factory=CurrentRange)

Set the autoranging current.

equilibration_time class-attribute instance-attribute

equilibration_time: float = 0.0

Equilibration time in s.

Begin potential is applied during equilibration and the device switches to the appropriate current range.

begin_potential class-attribute instance-attribute

begin_potential: float = -0.5

Potential where the scan starts at in V.

end_potential class-attribute instance-attribute

end_potential: float = 0.5

Potential where the scan stops at in V.

step_potential class-attribute instance-attribute

step_potential: float = 0.1

Potential step size in V.

scanrate class-attribute instance-attribute

scanrate: float = 1.0

Scan rate in V/s.

The applicable range depends on the value of step_potential since the data acquisition rate is limited by the connected instrument.

enable_bipot_current class-attribute instance-attribute

enable_bipot_current: bool = False

Enable bipot current.

record_auxiliary_input class-attribute instance-attribute

record_auxiliary_input: bool = False

Record auxiliary input.

record_cell_potential class-attribute instance-attribute

record_cell_potential: bool = False

Record cell potential.

Counter electrode vs ground.

record_we_potential class-attribute instance-attribute

record_we_potential: bool = False

Record applied working electrode potential.

Reference electrode vs ground.

id class-attribute instance-attribute

id: Literal['lp'] = 'lp'

Unique method identifier.

to_dict

to_dict() -> dict[str, Any]

Return the technique instance as a new key/value dictionary mapping.

Source code in src/pypalmsens/_methods/base.py
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def to_dict(self) -> dict[str, Any]:
    """Return the technique instance as a new key/value dictionary mapping."""
    return self.model_dump()

from_dict classmethod

from_dict(obj: dict[str, Any]) -> BaseTechnique

Structure technique instance from dict.

Opposite of .to_dict()

Source code in src/pypalmsens/_methods/base.py
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@classmethod
def from_dict(cls, obj: dict[str, Any]) -> BaseTechnique:
    """Structure technique instance from dict.

    Opposite of `.to_dict()`"""
    return cls.model_validate(obj)

from_method_id classmethod

from_method_id(id: str) -> BaseTechnique

Create new instance of appropriate technique from method ID.

Source code in src/pypalmsens/_methods/base.py
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@classmethod
def from_method_id(cls, id: str) -> BaseTechnique:
    """Create new instance of appropriate technique from method ID."""
    new = cls._registry[id]
    return new()