以数据为导向,优化残留度变化,通过MATLAB估计的扩散系数和吸收
Luca Gritti1, Denny Coffetti1, Marina Cabrini1
1University of Bergamo, Bergamo, Italy.
Data in brief
|August 6, 2025
概括
这项研究引入了一种使用电化学技术测量金属中扩散参数的新方法. 开发的代码准确地从实验数据中估计了吸收和扩散系数.
科学领域:
- 材料科学 材料科学 材料科学
- 电化学 电化学 电化学
- 物理化学 物理化学
背景情况:
- 金属中的吸收对于材料的性能和安全至关重要.
- 精确测量扩散参数对于预测材料行为至关重要.
研究的目的:
- 呈现实验数据和开发代码来估计关键扩散参数.
- 建立一个数据驱动的优化方法来表征金属样本中的扩散.
主要方法:
- 一个两步电化学过程,涉及阴极充电和阳极放电.
- 在放电过程中对时间依赖的阳极电流进行分析,以确定流量.
- 使用MATLAB代码进行数据驱动优化以提取扩散参数.
主要成果:
- 该研究成功获得了扩散的特征参数,包括明显扩散系数,吸收和等待时间.
- 开发的方法适用于圆柱形几何形状,并通过模拟适应其他特定几何形状.
结论:
- 提出的实验和计算方法为量化金属中的扩散提供了一种可靠的方法.
- 这种技术为材料科学和工程应用提供了宝贵的见解,在这些应用中,由引起的降解是令人担忧的.
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