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Cyclic Voltammetry

This page documents the Cyclic Voltammetry (CV) method.

pypalmsens.CyclicVoltammetry

Create cyclic voltammetry method parameters.

In Cyclic Voltammetry, recurrent potential scans are performed between the potentials vertex1_potential and vertex2_potential going back the number of times determined by the n_scans. The scan starts at the begin_potential which can be at one of these vertex potentials or anywhere in between. The experiment will always terminate at the same potential set as the 'begin_potential'.

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:

general class-attribute instance-attribute

general: General = Field(default_factory=General)

Sets general/other 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.

id class-attribute instance-attribute

id: Literal['cv'] = 'cv'

Unique method identifier.

equilibration_time class-attribute instance-attribute

equilibration_time: float = 0.0

Equilibration time in s.

begin_potential class-attribute instance-attribute

begin_potential: float = -0.5

Potential where the scan starts and stops at in V.

vertex1_potential class-attribute instance-attribute

vertex1_potential: float = 0.5

First potential where direction reverses in V.

vertex2_potential class-attribute instance-attribute

vertex2_potential: float = -0.5

Second potential where direction reverses. 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.

n_scans class-attribute instance-attribute

n_scans: int = 1

Number of repetitions for this scan.

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.

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()