Supplementary data for: Electrochemical corrosion analysis of Zr–Nb and Zr–Sn alloys using classical, noise, and wavelet-based methods

This dataset contains processed electrochemical data supporting the manuscript "Electrochemical corrosion analysis of Zr–Nb and Zr–Sn alloys using classical, noise, and wavelet-based methods" submitted to Journal of Nuclear Materials. Contents: Time-domain electrochemical noise (ECN) data for Zr-Nb (300, 400, 600 ppm Fe) and Zr-Sn (1100 ppm Fe) alloys Frequency-domain Power Spectral Density (PSD) data derived from ECN measurements Python Jupyter notebook (Wavelet Level 8 Code.ipynb) implementing Daubechies 4 (db4) wavelet decomposition for multiscale signal analysis File structure: *_Time.xlsx: Time-domain current and potential noise signals *_Frequency.xlsx: Frequency-domain PSD spectra and spectral noise resistance (Rsn) calculations Wavelet Level 8 Code.ipynb: Python code for wavelet decomposition (level 8) and statistical analysis Alloys studied: Zr-Nb with 300, 400, and 600 ppm Fe Zr-Sn with 1100 ppm Fe Experimental conditions: Electrolyte: 0.1 mol/L Na₂SO₄, pH 5.5 Temperature: ambient (25 ± 2°C) Sampling rate: 2 Hz (ECN) Frequency range: 100 kHz to 10 mHz (EIS) Raw time-series data (approximately 2 GB) are available from the corresponding author upon reasonable request. Corresponding author: Alexandre Roberto Soares ([e-mail])本数据集包含支撑已投稿至《Electrochimica Acta》的论文《采用经典方法、噪声分析方法及小波基方法对Zr-Nb与Zr-Sn合金开展电化学腐蚀分析》的经预处理电化学数据。 数据集内容： 1. 针对Zr-Nb（铁含量分别为300、400、600 ppm）与Zr-Sn（铁含量为1100 ppm）合金的时域电化学噪声（Electrochemical Noise, ECN）数据 2. 由ECN测量得到的频域功率谱密度（Power Spectral Density, PSD）数据 3. 用于实现Daubechies 4（db4）小波分解以开展多尺度信号分析的Python Jupyter记事本（Wavelet Level 8 Code.ipynb） 文件结构： - *_Time.xlsx：存储时域电流与电位噪声信号 - *_Frequency.xlsx：存储频域PSD谱图及谱噪声电阻（Rsn）计算结果 - Wavelet Level 8 Code.ipynb：用于完成8级小波分解与统计分析的Python代码 研究合金体系： - 铁含量分别为300、400、600 ppm的Zr-Nb合金 - 铁含量为1100 ppm的Zr-Sn合金 实验条件： - 电解质：0.1 mol/L 硫酸钠（Na₂SO₄）溶液，pH值为5.5 - 温度：室温（25 ± 2°C） - 采样速率：2 Hz（电化学噪声测试） - 频率范围：100 kHz至10 mHz（电化学阻抗谱，Electrochemical Impedance Spectroscopy, EIS） 原始时间序列数据（总大小约2 GB）可根据合理需求向通讯作者索取。 通讯作者：Alexandre Roberto Soares（邮箱：[e-mail]）