论文标题
用于数据驱动的组合合金薄膜研究的实验数据管理平台
Experimental data management platform for data-driven investigation of combinatorial alloy thin films
论文作者
论文摘要
实验材料数据是异质的，包括用于处理和表征条件的各种元数据，从而实施了数据驱动的方法，以开发新型材料的困难。在本文中，我们介绍了材料数据管理平台的薄膜合金数据库（TFADB），该平台旨在通过各种实验工具进行组合研究的薄膜合金。使用TFADB，研究人员可以轻松地上载，编辑和检索多维实验合金数据，例如组成，厚度，X射线衍射，电阻率，纳米凹痕和图像数据。此外，数据库中的组成依赖性属性可以很容易地以足够的格式来管理以进行机器学习分析的预处理。该软件的高灵活性允许管理新型材料数据，这些数据可以从新的组合实验中获取。
Experimental materials data are heterogeneous and include a variety of metadata for processing and characterization conditions, making the implementation of data-driven approaches for developing novel materials difficult. In this paper, we introduce the Thin-Film Alloy Database (TFADB), a materials data management platform, designed for combinatorially investigated thin-film alloys through various experimental tools. Using TFADB, researchers can readily upload, edit, and retrieve multidimensional experimental alloy data, such as composition, thickness, X-ray Diffraction, electrical resistivity, nanoindentation, and image data. Furthermore, composition-dependent properties from the database can easily be managed in a format adequate to be preprocessed for machine learning analyses. High flexibility of the software allows management of new types of materials data that can be potentially acquired from new combinatorial experiments.
