Dataset for article "Characterization of Mobile Ions in Perovskite Solar Cells with Capacitance and Current Measurements by Approximating Drift-Diffusion Simulations"

Fuente: Zenodo
Guardado en:
Detalles Bibliográficos
Autores principales: Schmidt, Moritz Christian, Alvarez, Agustin O., Seid, Biruk A., de Boer, Jeroen J., Lang, Felix, Ehrler, Bruno
Formato: Recurso digital
Lenguaje:inglés
Publicado: Zenodo 2025
Materias:
Acceso en línea:
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866902146248605696
author Schmidt, Moritz Christian
Alvarez, Agustin O.
Seid, Biruk A.
de Boer, Jeroen J.
Lang, Felix
Ehrler, Bruno
author_facet Schmidt, Moritz Christian
Alvarez, Agustin O.
Seid, Biruk A.
de Boer, Jeroen J.
Lang, Felix
Ehrler, Bruno
contents <p>The migration of mobile ions is one of the leading causes of the degradation of perovskite solar cells. However, quantifying mobile ions in complete perovskite solar cells is challenging due to the complex device stacks and the impact of charge transport layers on the measurement techniques. Here, we develop a simple and openly accessible step model that approximates drift-diffusion simulations. The step model is based on expressing the charge density in the ionic and electronic accumulation and depletion layers as step functions. We can then accurately determine the impact of mobile ions on the DC potential distribution of perovskite solar cells. Furthermore, we can simulate electrical measurement techniques commonly used to quantify mobile ions: capacitance transient, current transient, and capacitance frequency measurements. By validating the step model with drift-diffusion simulations, we show that an accurate extraction of ion density, diffusion coefficient, and activation energy is possible in an accessible range. We finally apply the developed step model to estimate the ionic conductivity and activation energy of perovskite solar cells.</p> <p>This dataset includes all experimental and simulation data used for the article.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_16890531
institution Zenodo
language eng
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Dataset for article "Characterization of Mobile Ions in Perovskite Solar Cells with Capacitance and Current Measurements by Approximating Drift-Diffusion Simulations"
Schmidt, Moritz Christian
Alvarez, Agustin O.
Seid, Biruk A.
de Boer, Jeroen J.
Lang, Felix
Ehrler, Bruno
Perovskite
Solar Cells
Drift-Diffusion Simulations
Mobile Ions
<p>The migration of mobile ions is one of the leading causes of the degradation of perovskite solar cells. However, quantifying mobile ions in complete perovskite solar cells is challenging due to the complex device stacks and the impact of charge transport layers on the measurement techniques. Here, we develop a simple and openly accessible step model that approximates drift-diffusion simulations. The step model is based on expressing the charge density in the ionic and electronic accumulation and depletion layers as step functions. We can then accurately determine the impact of mobile ions on the DC potential distribution of perovskite solar cells. Furthermore, we can simulate electrical measurement techniques commonly used to quantify mobile ions: capacitance transient, current transient, and capacitance frequency measurements. By validating the step model with drift-diffusion simulations, we show that an accurate extraction of ion density, diffusion coefficient, and activation energy is possible in an accessible range. We finally apply the developed step model to estimate the ionic conductivity and activation energy of perovskite solar cells.</p> <p>This dataset includes all experimental and simulation data used for the article.</p>
title Dataset for article "Characterization of Mobile Ions in Perovskite Solar Cells with Capacitance and Current Measurements by Approximating Drift-Diffusion Simulations"
topic Perovskite
Solar Cells
Drift-Diffusion Simulations
Mobile Ions
url https://doi.org/10.5281/zenodo.16890531