Electrocatalytic Water Oxidation with Cubane-Type Co(II) Complexes: Magnetic Susceptibility and AC Susceptibility Data Analysis

Overview This Jupyter Lab notebook provides a comprehensive data analysis and visualization of magnetic susceptibility and alternating current (AC) susceptibility measurements for cubane-type Co(II) complexes, as studied in the article "Electrocatalytic Water Oxidation with Cubane-Type Co(II) Complexes". The notebook includes raw data processing, model fitting (Cole-Cole and Curie-Weiss laws), and publication-ready plots for both DC and AC magnetic susceptibility. Key Features Data Processing: Loads and reshapes raw SQUID and AC susceptibility data. Corrects for diamagnetic contributions and normalizes by molar quantity. Model Fitting: Cole-Cole model: Fits frequency-dependent AC susceptibility data to extract relaxation times (τ) and distribution parameters (α). Curie-Weiss law: Fits inverse susceptibility data to determine Curie constants (C) and Weiss temperatures (θ). Visualization: Generates three-panel figures for: Real (χ') and imaginary (χ") susceptibility vs. frequency. Cole-Cole plots (real vs. imaginary susceptibility). Inverse susceptibility vs. temperature (Curie-Weiss fits). Uses LaTeX formatting for professional labels and viridis/Set1 colormaps for clarity. Reproducibility: All constants, models, and plotting parameters are explicitly defined. Saved figures are high-resolution (300–600 DPI) and labeled for direct use in publications. Outputs: Fitted parameters (e.g., U, τ₀, C, θ) are printed and saved for further analysis. Processed data files (e.g., Rxn66_AC_colecole_700G.dat) are generated for open access. Intended Use This notebook is designed for: Researchers studying magnetic properties of Co(II) complexes in electrocatalysis. Reproducibility and transparency in open science (e.g., Zenodo, Figshare, or institutional repositories). Educational purposes in magnetic susceptibility analysis and data visualization. Dependencies Python 3.x Libraries: numpy, matplotlib, scipy, pandas Input files: Raw .dat or .ac.dat files from SQUID/AC susceptibility measurements. License [Specify your preferred open license, e.g., CC-BY 4.0 or MIT License for code.]