Tools for TL Glow Curves

This Python package provides tools for analyzing thermoluminescence (TL) glow curves.
It includes functions for calculating activation energies using various classical methods, extracting peak parameters, and generating informative visualizations of TL peaks.

Features

• Initial Rise Method (Initial_rise_TL)
  Estimates the activation energy (Ea) from the initial rise of the TL glow curve.
  Generates plots of TL vs Temperature and ln(TL) vs 1/(kT) with linear fit.

• Peak Parameters (TL_peak_parameters)
  Extracts key TL peak features:

  • Maximum intensity (Imax)
  • Half intensity (I½)
  • Temperatures (T1, T2, Tm)
  • Peak widths: left (τ), right (δ), total (ω)
  • Shape factor (μ)
    Generates plots with TL curve and marked peak points.

• Activation Energy from Peak Shape (energy_activation_peak_parameters)
  Calculates Ea using three methods based on peak geometry: τ, δ, and ω.
  Computes the geometric shape factor μ.
  Generates annotated TL plots.

• Activation Energy from Peak Position (energy_activation_peak_position)
  Estimates Ea from the peak temperature (Tm) using semi-empirical relations.
  Requires the frequency factor (s) as input.
  Produces a plot highlighting the peak position.

# Example: TL curve
T =   # Temperature in K
I =  # TL peak

# Apply Initial Rise method
Initial_rise_TL(T, I, Tini=100, Tfin=200)

# Extract peak parameters
TL_peak_parameters(T, I)

# Estimate activation energy from peak shape
energy_activation_peak_parameters(T, I)

# Estimate activation energy from peak position (requires frequency factor s)
energy_activation_peak_position(T, I, s=1e12)