A browser-based tool for computing distribution of relaxation times (DRT) functions from measured impedance spectroscopy (EIS) data. No installation, no Python backend - just open it in your browser.
- In-depth analysis of EIS data - Deconvolute your impedance spectra to obtain valuable insights into the underlying capacitive-resistive processes.
- Automatic process separation - As the DRTs are approximated using dispersed basis functions, the resulting functions can easily be dissected. This, in turn, yields the precise contribution of singular processes, simplifying aging analysis significantly.
- Interactive and real-time visualization - Real-time plot updates when settings are adjusted (e.g., when shape parameters are tuned).
- Data export - The DRTs, the reconstructed process impedance spectra, and the plots can easily be exported for use in PowerPoint, etc.
- Runs everywhere - QuickDRT works offline (e.g., on lab computers), on mobile, and without any external dependencies.
- Gamry .dta support - Native support for Gamry impedance spectra.
Online: Open the live demo and drop your EIS file onto the upload area.
Offline: Download or clone this repository and open index.html in your browser.
- Gamry .DTA - Native support for most Gamry EIS files.
- Generic CSV - You can also use QuickDRT with *.csv files with the following generic header:
frequency_Hz,z_real_Ohm,z_imag_Ohm. Optionally, a JSON metadata header can be prepended to the CSV data (i.e., at line 1, followed by the CSV data).
See the in-app "Supported data types" information for the CSV specs.
QuickDRT reconstructs the DRT by discretizing the impedance data using analytical basis functions (Cole-Cole, Havriliak-Negami, and Gauss). This approach yields clean per-process separation while mitigating the need for Tikhonov regularization.
For more background information on the process and the used basis functions, see the underlying publication and the PyDRT documentation.
If QuickDRT is useful to your research, please cite:
Leonhardt, et al. (2025). "Reconstructing the distribution of relaxation times with analytical basis functions" Journal of Power Sources 652, DOI: 10.1016/j.jpowsour.2025.237403 DOI:10.1016/j.jpowsour.2025.237403
Wan, T. H., et al. (2015). "Influence of the Discretization Methods on the Distribution of Relaxation Times Deconvolution: Implementing Radial Basis Functions with DRTtools." Electrochimica Acta 184: 483-499.
and, as the main source for the implementation of the Cole-Cole and Havriliak-Negami bases,
T. Tichter. https://github.com/Polarographica/Polarographica_program