AI Article Synopsis
- Automation has greatly improved productivity in liquid handling research like organic synthesis but has struggled to impact materials laboratories due to the need for sample prep and solid-state characterization techniques.
- A fully autonomous workflow for powder X-ray diffraction (PXRD) is presented, which can achieve data quality that matches or exceeds manual methods, despite the complexities of solid powder handling.
- This workflow consists of 12 steps and is executed by three multipurpose robots, showcasing how modular automation can effectively manage complex laboratory tasks.
Article Abstract
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, encompassing crystal growth, sample preparation, and automated data capture. 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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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10866346 | PMC |
| http://dx.doi.org/10.1039/d3sc06206f | DOI Listing |
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