工作流程
自动化
模块化设计
粉末衍射
固态
工艺工程
机器人
计算机科学
表征(材料科学)
样品制备
材料科学
纳米技术
系统工程
机械工程
工程类
化学
人工智能
数据库
色谱法
结晶学
工程物理
操作系统
作者
A. Lunt,Hatem Fakhruldeen,Gabriella Pizzuto,Louis Longley,Alexander E. White,Nicola Rankin,Rob Clowes,Ben M. Alston,Andrew I. Cooper,Samantha Y. Chong
出处
期刊:Cornell University - arXiv
日期:2023-01-01
被引量:6
标识
DOI:10.48550/arxiv.2309.00544
摘要
Automation can transform productivity in research activities that use liquid handling, such as organic synthesis, but it has made less impact in materials laboratories, which require sample preparation steps and a range of solid-state characterization techniques. For example, powder X-ray diffraction (PXRD) is a key method in materials and pharmaceutical chemistry, but its end-to-end automation is challenging because it involves solid powder handling and sample processing. Here we present a fully autonomous solid-state workflow for PXRD experiments that can match or even surpass manual data quality. The workflow involves 12 steps performed by a team of three multipurpose robots, illustrating the power of flexible, modular automation to integrate complex, multitask laboratories.
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