Artificial intelligence based analysis of nanoindentation load–displacement data using a genetic algorithm
Artificial intelligence based analysis of nanoindentation load–displacement data using a genetic algorithm
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DOI：
10.1016/j.apsusc.2022.155734
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发表时间：
2022-11
影响因子：
6.7
通讯作者：
Abraham Burleigh;Miu Lun Lau;Megan Burrill;D. Olive;J. Gigax;Nan Li;T. Saleh;Frederique Pellemoine-Frederique
中科院分区：
文献类型：
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作者：
Abraham Burleigh;Miu Lun Lau;Megan Burrill;D. Olive;J. Gigax;Nan Li;T. Saleh;Frederique Pellemoine-Frederique
我们开发了一种自动化工具，纳米压痕Neopackage，用于使用应用于Oliver-Pharr方法的遗传算法（GA）分析纳米压痕载荷-位移曲线（奥利弗等人，1992年）。对于某些材料，如多晶各向同性石墨，卸载曲线的最小二乘拟合（LSF）可能会产生不切实际的拟合参数。这些石墨表现出尖锐的峰值卸载曲线不容易拟合使用LSF，这往往会高估压头尖端的几何参数。为了解决这个问题，我们扩展了我们的通用材料表征工具Neo用于EXAFS分析（Terry等人，Nanoindentation Neo自动处理和分析纳米压痕数据，只需最少的用户输入，同时生成有意义的拟合参数。GA，一个强大的元启发式方法，开始与人口的临时解决方案，使用模型参数称为染色体;从这些我们评估每个解决方案的适应值，并选择最佳的解决方案与随机解决方案混合产生下一代。然后，变异算子通过随机扰动修改现有解，并选择最优解。我们使用二氧化硅和Al参比标准品测试了GA方法。我们适合石墨和高熵合金（HEA）的BCC和FCC相组成的样品。
We developed an automated tool,Nanoindentation Neopackage for the analysis of nanoindentation load–displacement curves using a Genetic Algorithm (GA) applied to the Oliver-Pharr method (Oliver et al.,1992). For some materials, such as polycrystalline isotropic graphites, Least Squares Fitting (LSF) of the unload curve can produce unrealistic fit parameters. These graphites exhibit sharply peaked unloading curves not easily fit using the LSF, which tends to overestimate the indenter tip geometry parameter. To tackle this problem, we extended our general materials characterization toolNeofor EXAFS analysis (Terry et al., 2021) to fit nanoindentation data.Nanoindentation Neoautomatically processes and analyzes nanoindentation data with minimal user input while producing meaningful fit parameters. GA, a robust metaheuristic method, begins with a population of temporary solutions using model parameters called chromosomes; from these we evaluate a fitness value for each solution, and select the best solutions to mix with random solutions producing the next generation. A mutation operator then modifies existing solutions by random perturbations, and the optimal solution is selected. We tested the GA method using Silica and Al reference standards. We fit samples of graphite and a high entropy alloy (HEA) consisting of BCC and FCC phases.