Optoelectronic-Processes-in-Organic-Solar-Cells-Under-Short-Circuit-Conditions

Please reference the following work:

A Simple Approach for Unraveling Optoelectronic Processes in Organic Solar Cells under Short-Circuit Conditions

N. Schopp, V. Brus*, J. Lee, G. C. Bazan, T.-Q. Nguyen*

Adv. Energy Mater. 2021, 11, 2002760

https://doi.org/10.1002/aenm.202002760

The python-based software created for this work operates in conjunction with the transfer matrix method software that was developed by George F. Burkhard, Eric T. Hoke at Stanford University.

Our part of the code includes:

visualization of the 3D Generation rate
calculation of the EQE in dependence on the position x in the device, the wavelengths, and the
fitting of the calculated EQEs to the experimental EQE and the output of the
calculation of the J_sc from measured EQE for AM1.5 illumination
visualization of the extraction efficiency of electrons and holes at 0 V in dependence of the position in the device based on the determined μτ
visualization of the extraction efficiency of electrons and holes at -3 V in dependence of the position in the device based on the determined μτ
the average extraction efficiency for different active layer thicknesses (required for device optimization)

To use the code for device optimization, follow the step-by-step guide below.

Recommendations for Python Beginners

Install Anaconda and Spyder, import the .py (code) file into Spyder. Download the required nk data in one of your folders, as well as the AM1.5 file and the EQE file. You can replace the EQE file with your own EQE file and use your own optical properties as desired. Please keep in mind that your files need to be exactly in the same format for the code to work without modification (eg. csv or tab delimiter, number of lines in header, no empty line at the bottom of the file).

By default, running the code will output the graphs into the root directory of the repository.

Alternative using `pipenv`

To install pipenv (a Python package and virtual environment manager), follow the instructions for your operating system here.

Download the repository from Github, then navigate to the root directory in a terminal prompt. Run pipenv install to automatically create the virtual environment and install the packages from Pipfile. After installing, run pipenv shell to activate the environment.

Step-by Step Guide for the Application of our Approach to the Device Optimization

After obtaining the optical constants of the active layer and of other layers that are not provided in this work or other literature, the following steps lead to the prediction of the thickness-dependent J_sc.

Experimental steps:

Fabrication of at least one solar cell (thickness measurement should be done after completing the other experimental steps)

Measurement of the JV characteristics at 1 sun and in the dark (to obtain V_bi)

Measurement of the EQE

Measuring JV-characteristics under monochromatic illumination

Simulation and calculation steps:

Simulating the J_sc

theo under the monochromatic illumination used in step 4. (It is important to set other wavelengths to zero in the spectral distribution file.)

Calculation of Pg

Using the provided software (see below) to obtain μτ and the extraction efficiency η by fitting to measured EQE.

Calculation of the extraction probability η(x) for each thickness L of interest, then averaging η(x) to get extraction efficiency for each L. Simulation of the Jsc, ideal for each L (no losses) with TMM under 1 sun AM 1.5 or the spectrum of your interest. (blue curve)

Product of Pg, η(L) and simulated J_sc,ideal give predicted J_sc. (red curve)

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