External Quantum Efficiency Current Density Calculator

The Solar Cell Jsc Calculator is a simple script designed to calculate the short-circuit current density (Jsc) of solar cells based on input external quantum efficiency (EQE) and spectral irradiance data. 

Features:

• EQE Analysis: Load EQE data to compute solar cell response.
• Multiple Spectra Support: Import multiple light spectrum files at once to calculate and compare the Jsc for each spectrum.
• Dynamic Visualization: Generate plots of the EQE and normalized spectra for easy comparison and analysis.

How to Use:

1. Open the software and load your EQE file (in .txt format).
2. Load one or more spectral irradiance files (in .txt format).
3. Click "Calculate Current" to compute the Jsc for each spectrum.
4. View the calculated Jsc values and corresponding plots in an easy-to-understand graphical format.

Output:

• Plots showing EQE and normalized spectra.
• Calculated Jsc values for each spectrum, displayed on the figure and console.

Requirements:

• The input files must be in .txt format with two columns:
  • EQE File: Wavelength (nm) and EQE values (0–1). Version 2.0 accepts EQE in %
  • Spectrum File: Wavelength (nm) and irradiance (W/m²/nm).

Version:

1.0: Basic functionality of integrating EQE to calculate Jsc from a given spectrum

1.1: Multiple spectra can be added at once

1.2: Urbach energy and inflection point calculations in the EQE

1.4: COrrected a bug where numbers would overlap when a large amount of spectra were loaded. Added support for UTF-16 .txt files (UTF-32 unsupported, but who needs that?). Added a button to export the data in a .txt file

2.0:  Key Updates and Improvements
1. New Bandgap Attribute
o A dedicated attribute for the bandgap energy (Eg) has been introduced to
enhance usability and clarity in calculations.

2. Improved File Handling
o Files are now read using pandas.read_csv from the Pandas library for more
efficient data handling.
o Data is stored in Pandas DataFrames instead of Numpy arrays, offering
improved functionality and compatibility.
o EQE data in percentage format (%) is now accepted and automatically
converted to the 0-1 range.
3. Enhanced Current Calculation
o Linspace Resolution: The wavelength grid (linspace) has been expanded to
3000 points, improving precision in calculations.
o Interpolation: The EQE interpolation method has been upgraded from linear
interpolation to cubic spline interpolation for smoother and more accurate
results.
o Inflection Point Determination:
▪ The calculation method for the inflection point has been significantly
improved.
▪ Instead of relying on the second derivative, the following approach is
now used:
1. Calculate the first derivative of the EQE curve.
2. Identify the minimum of the first derivative.
3. Fit a Gaussian function to the region surrounding the minima
to improve accuracy.

▪ The bandgap energy (Eg) is also calculated and displayed.
▪ The following plots are generated for visual analysis:
▪ EQE Curve
▪ First Derivative
▪ Gaussian Fitting
4. Refined Urbach Energy Calculation
o The Urbach energy calculation now uses the formula:

ln (− ln(1 − EQE))

Urbach Energy doesn't always work and will be refined in a future version

o Improved Linear Fit:
▪ A linear fit is applied to the tail of the EQE data.

▪ The process includes an iterative method that adjusts the fit until the R-
squared value exceeds 0.995.

o Visualization:
▪ The resulting linear fit is plotted alongside the data for visual
verification.
Summary of Changes
• Bandgap energy (Eg) attribute added.

• Files are loaded with Pandas, and data is stored in DataFrames.
• EQE interpolation upgraded to cubic splines.
• Inflection point calculation now uses the first derivative and Gaussian fitting.
• Urbach energy calculation refined with an iterative linear fit and R-squared
validation.

Note: Description partially written by an AI.