DRTtools

GitHub About

Data Input

.txt file or .csv file. Click "About" to see correct input file format.

Analysis Parameters

Options for RBF

Run DRT

Peak Analysis

Nyquist Plot

Bode Plot

Distribution of Relaxation Times (DRT)

Upload File and Run DRT Analysis

About DRTtools

DRTtools is a powerful open-source toolbox developed by Prof. Francesco CIUCCI's group for calculating the Distribution of Relaxation Times (DRT) from Electrochemical Impedance Spectroscopy (EIS) data.

This web interface is created by Zilong WANG and Yuhao WANG from Prof. Francesco CIUCCI's group.

Key Features

  • Calculate DRT using Tikhonov regularization method
  • Flexible regularization parameter input
  • Optimize regularization parameter selection
  • Determine credible intervals for DRT
  • Fast DRT peak fitting
  • Visualized EIS data and DRT analysis results

Input File Format

Incorrect input file format will cause DRT fail to return results, please check input file prompt for correct input file format.

Citations

If you use DRTtools, please cite the following papers:

  1. Wan, T. H., Saccoccio, M., Chen, C., & Ciucci, F. (2015). Influence of the discretization methods on the distribution of relaxation times deconvolution: implementing radial basis functions with DRTtools. Electrochimica Acta, 184, 483-499.

If you want to add more details about standard regularization methods for computing the regularization parameter used in ridge regression, you should also cite the following references:

  1. Maradesa, A., Py, B., Wan, T. H., Effat, M. B., & Ciucci, F. (2023). Selecting the Regularization Parameter in the Distribution of Relaxation Times. Journal of The Electrochemical Society, 170, 030502.

If you are presenting the Bayesian credible intervals generated by the DRTtools in any of your academic works, you should cite the following references also:

  1. Ciucci, F., & Chen, C. (2015). Analysis of electrochemical impedance spectroscopy data using the distribution of relaxation times: A Bayesian and hierarchical Bayesian approach. Electrochimica Acta, 167, 439-454.
  1. Effat, M. B., & Ciucci, F. (2017). Bayesian and hierarchical Bayesian based regularization for deconvolving the distribution of relaxation times from electrochemical impedance spectroscopy data. Electrochimica Acta, 247, 1117-1129.

If you are using the DRTtools to compute the Hilbert Transform, you should cite:

  1. Liu, J., Wan, T. H., & Ciucci, F. (2020). Bayesian and hierarchical Bayesian based regularization for deconvolving the distribution of relaxation times from electrochemical impedance spectroscopy dataA Bayesian view on the Hilbert transform and the Kramers-Kronig transform of electrochemical impedance data: Probabilistic estimates and quality scores. Electrochimica Acta, 357, 136864.

Collaboration

For business cooperation, please send email to: francesco.ciucci@uni-bayreuth.de.

For academic cooperation, please send email to:

francesco.ciucci@uni-bayreuth.de;

or yuhao.wang@connect.ust.hk (for fuel cell field);

or zl.wang@connect.ust.hk (for battery field).

Theoretical Background

DRT analysis is a powerful technique for interpreting EIS data without assuming an equivalent circuit model. It deconvolutes the impedance response into a distribution of time constants, providing insights into the electrochemical processes occurring at different timescales.

Data Privacy

To improve our service and optimize algorithms, we collect:

  • Basic visitor information (IP, browser version)
  • Uploaded EIS data (periodically cleaned)
  • DRT fitting results (for algorithm optimization)

All data is used solely for service improvement and research purposes.