Baseline for Dielectric Analysis (DEA) Data
In the case of DEA data, Prepare Data includes also the possibility to define an interpolated baseline that is subtracted from the data. There are five possibilities:
Baseline: None
None means that no baseline is applied.
Baseline: Left Horizontal (DEA Isothermal)
A horizontal baseline is used where the constant value of the baseline is the data point at the left cursor. Typical application: The temperature dependence of the ion viscosity is unknown and the temperature is constant (isothermal).
Baseline: Left Tangential (DEA Dynamic):
This temperature-dependent baseline is calculated according to η ~ exp(Ea/RT) assuming thermal activation of the ion viscosity η. The parameters (offset, activation energy Ea for the temperature dependence of η) are determined at the left cursor. Typical application: Dynamic temperature program (heating) before the reaction and constant temperature (isothermal) after the reaction.
Baseline: Right Tangential (DEA Dynamic):
This temperature-dependent baseline is also calculated according to η ~ exp(Ea/RT) assuming thermal activation of the ion viscosity η. The parameters (offset, activation energy Ea for the temperature dependence of η) are determined at the right cursor for the product. However, the parameters of η of the baseline vary continuously so that the baseline always starts horizontally at the left cursor. Typical application: Entirely dynamic temperature program and no defined behavior or unknown temperature dependence of the ion viscosity before the start of the reaction.
Baseline: Tangential (DEA Dynamic)
Tangential (DEA Dynamic) baseline is also used for an entirely dynamic temperature program. This temperature-dependent baseline is also calculated according to η ~ exp(Ea/RT) assuming thermal activation of the ion viscosity η. However, the parameters (offset, activation energy Ea for the temperature dependence of η) are determined at the left cursor for the educt and at the right cursor for the product. The parameters of η of the baseline vary continuously between the educt’s and the product’s parameters where the interpolation is calculated utilizing the deviation of the data from educt behavior to product behavior as a weight function.