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人工智能驱动的闪闪发光用于并行高场核磁共振
Moritz Becker1, Yen-Tse Cheng1, Achim Voigt1
1Institute of Microstructure Technology (IMT), Karlsruhe Institute of Technology (KIT), Eggenstein-Leopoldshafen, 76344, Karlsruhe, Germany.
Scientific reports
|October 20, 2023
概括
在核磁共振 (NMR) 中并行检测现在是可行的. 一种新的深度学习方法可以快速校准多个NMR探测器,克服高吞吐量查之前的技术障碍.
科学领域:
- 磁共振成像是一种磁共振成像技术.
- 频谱学是一种光谱学.
- 药物发现技术 药物发现技术
背景情况:
- 高吞吐量查对于快速药物开发至关重要.
- 核磁共振 (NMR) 提供了并行检测的潜力,但面临着重大的技术挑战.
- 在多个检测站点实现每亿分之一 (ppb) 的磁场均性是并行NMR的主要障碍.
研究的目的:
- 为了克服当前闪技术的局限性,用于并行NMR检测.
- 为平行NMR探测器开发一种快速校准方法.
- 为了使NMR磁体内的检测点能够进行升级.
主要方法:
- 为每个探测器实施单独的磁性闪光系统.
- 应用深度学习算法来管理重叠的,非直角的闪场.
- 使用原始画技术开发最小的NMR条纹探测器.
主要成果:
- 证明了并行NMR探测器的快速校准成功.
- 开发的shim系统和深度学习方法有效地弥补了现场重叠.
- 该研究报告了迄今为止最小的NMR条纹检测器,促进了可扩展性.
结论:
- 开发的技术克服了平行NMR检测中的关键障碍.
- 这一进步支持开发用于药物发现的高吞吐量选技术.
- 基于Origami的条纹检测器为NMR系统的检测密度显著增加铺平了道路.
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