Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States.
Materials Science and Engineering Program, University of California San Diego, La Jolla, California 92093, United States.
J Phys Chem B. 2022 Sep 22;126(37):7192-7201. doi: 10.1021/acs.jpcb.2c05876. Epub 2022 Sep 13.
In this work, we determined the tilt angles of molecular units in hierarchical self-assembled materials on a single-sheet level, which were not available previously. This was achieved by developing a fast line-scanning vibrational sum frequency generation (VSFG) hyperspectral imaging technique in combination with neural network analysis. Rapid VSFG imaging enabled polarization resolved images on a single sheet level to be measured quickly, circumventing technical challenges due to long-term optical instability. The polarization resolved hyperspectral images were then used to extract the supramolecular tilt angle of a self-assembly through a set of spectra-tilt angle relationships which were solved through neural network analysis. This unique combination of both novel techniques offers a new pathway to resolve molecular level structural information on self-assembled materials. Understanding these properties can further drive self-assembly design from a bottom-up approach for applications in biomimetic and drug delivery research.
在这项工作中，我们确定了分层自组装材料中单分子单元的倾斜角度，这是以前无法获得的。这是通过开发一种快速线扫描振动和频产生（VSFG）高光谱成像技术与神经网络分析相结合来实现的。快速 VSFG 成像使我们能够快速测量单张水平的偏振分辨图像，避免了由于长期光学不稳定而导致的技术挑战。然后，通过一组通过神经网络分析解决的光谱-倾斜角关系，使用偏振分辨高光谱图像来提取自组装的超分子倾斜角。这两种新技术的独特结合为解决自组装材料的分子水平结构信息提供了新途径。了解这些特性可以进一步从底层设计自组装，以应用于仿生学和药物输送研究。
