PhaseXplorer 创建高维相图,使用闭环主动学习
Stef A H Jansen1, Lasse S A Dreyer2, Jule van Basten1
1Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven 5612 AJ, The Netherlands.
ACS nano
|November 3, 2025
概括
PhaseXplorer加速了使用微流体,显微镜和机器学习研究材料相位分离的研究. 这个平台创建精确的相位图100倍更快,用1万倍更少的材料.
科学领域:
- 材料科学 材料科学 材料科学
- 生物物理学的生物物理.
- 化学工程是化学工程的重要组成部分.
背景情况:
- 阶段分离对于材料特性和细胞功能至关重要.
- 传统的实验方法是资源密集型的,并且仅限于低维度.
- 有效地研究复杂的相隔系统是一个重大挑战.
研究的目的:
- 开发一个自动化平台,对相隔系统进行高效和高通量研究.
- 以最小的实验资源创建高维相图.
- 克服传统,低维度调查的局限性.
主要方法:
- 微流体学,显微镜学和机器学习在闭环主动学习工作流程中的整合.
- 为平衡的勘探和开采开发一个采集函数的开发,以定位相位的边界.
- 使用卷积神经网络实时识别滴滴的图像和相位分离.
主要成果:
- PhaseXplorer自主生成和分析样本,以获得准确的相位图.
- 与传统方法相比,实现了100倍的速度增加和1万倍的材料消耗减少.
- 展示了为多元rA模型系统创建四维相位图的示例.
结论:
- PhaseXplorer提供了一种标准化,高效和节约资源的方法来确定相位图.
- 该平台能够在多个维度中快速探索复杂的相位行为.
- 这项技术显著推进了材料特性和由相位分离控制的细胞功能的研究.
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