%0 Generic
%A Mohseni Armaki, Amir
%A Guo, Yaqi
%A Ahmadi, Majid
%A Streefland, Roan
%A Bäuerlein, Patrick S.
%A Mol, Arjan
%A Kumar, Sid
%A Taheri, Peyman
%D 2025
%T Source Data for: Ion Sensing based on Frequency-Dependent Physico-Chemical Processes at Electrode/Electrolyte Interfaces
%U 
%R 10.4121/fd5d845a-70aa-452f-b662-e72e1e057f34.v1
%K Electrochemical Impedance Spectroscopy (EIS)
%K Real-Time Sensing
%K Ion-specific Fingerprint
%K Electrode/Electrolyte Interfaces
%K water
%K water quality monitoring
%X <p>This dataset contains the complete set of experimental and processed data used in the study <em>"</em>Ion Sensing based on Frequency-Dependent Physico-Chemical Processes at Electrode/Electrolyte Interfaces<em>"</em>. It includes:</p><p><br></p><ul><li><strong>Raw data</strong>: Directly acquired from electrochemical impedance spectroscopy (EIS) measurements across a range of electrolyte compositions, concentrations, and experimental conditions.</li><li><strong>Model outputs</strong>: Results from the physicochemical model and machine learning predictions, including training, validation, and cross-validation outputs.</li><li><strong>Supporting materials</strong>: Code for preprocessing, model training, and figure generation, as used in the manuscript and supplementary information.</li></ul><p>The dataset is organized into clearly labeled folders for ease of navigation. All files are provided in formats suitable for direct use (e.g., <code>.csv</code>, <code>.mat</code>, <code>.py</code>, <code>.m</code>). Additional details about data acquisition, preprocessing, and analysis are described in the accompanying <em>README</em> and in the Methods section of the manuscript.</p>
%I 4TU.ResearchData