论文标题
自主实验系统的高通量数据收集工作流的最佳选择框架
A Framework for the Optimal Selection for High-Throughput Data Collection Workflows by Autonomous Experimentation Systems
论文作者
论文摘要
自主实验系统已被用来极大地推进集成的计算材料工程（ICME）范式。本文概述了一个框架，该框架可以为自主实验系统设计和选择数据收集工作流程。该框架首先搜索数据收集工作流以生成高质量信息，然后根据用户定义的目标选择生成\ emph {最佳，最高值}信息的工作流程。我们采用此框架选择\ emph {用户定义的最佳}高通量工作流程，以在添加性制造的Ti-6al-4V样本上进行材料表征，以概述基本材料表征的表征，从而缩短了通过5次通过5次进行电子扫描的电子扫描案例来缩短对电子扫描的收集时间的收集时间与先前发表的研究中使用的工作流程相比，85倍。
Autonomous experimentation systems have been used to greatly advance the integrated computational materials engineering (ICME) paradigm. This paper outlines a framework that enables the design and selection of data collection workflows for autonomous experimentation systems. The framework first searches for data collection workflows that generate high-quality information and then selects the workflow that generates the \emph{best, highest-value} information as per a user-defined objective. We employ this framework to select the \emph{user-defined best} high-throughput workflow for material characterization on an additively manufactured Ti-6Al-4V sample for the purposes of outlining a basic materials characterization scenario, reducing the collection time of backscattered electron scanning electron scanning electron microscopy images by a factor of 5 times as compared to the benchmark workflow for the case study presented, and by a factor of 85 times as compared to the workflow used in the previously published study.
