Liu Chang, Lin Oliver, Pidaparthy Saran, Ni Haoyang, Lyu Zhiheng, Zuo Jian-Min, Chen Qian
Department of Materials Science and Engineering, University of Illinois, Urbana, Illinois 61801, United States.
Department of Chemistry, University of Illinois, Urbana, Illinois 61801, United States.
Nano Lett. 2024 Apr 3;24(13):3890-3897. doi: 10.1021/acs.nanolett.3c05015. Epub 2024 Mar 25.
Chemical reaction kinetics at the nanoscale are intertwined with heterogeneity in structure and composition. However, mapping such heterogeneity in a liquid environment is extremely challenging. Here we integrate graphene liquid cell (GLC) transmission electron microscopy and four-dimensional scanning transmission electron microscopy to image the etching dynamics of gold nanorods in the reaction media. Critical to our experiment is the small liquid thickness in a GLC that allows the collection of high-quality electron diffraction patterns at low dose conditions. Machine learning-based data-mining of the diffraction patterns maps the three-dimensional nanocrystal orientation, groups spatial domains of various species in the GLC, and identifies newly generated nanocrystallites during reaction, offering a comprehensive understanding on the reaction mechanism inside a nanoenvironment. This work opens opportunities in probing the interplay of structural properties such as phase and strain with solution-phase reaction dynamics, which is important for applications in catalysis, energy storage, and self-assembly.
纳米尺度下的化学反应动力学与结构和组成的不均匀性相互交织。然而，在液体环境中描绘这种不均匀性极具挑战性。在此，我们将石墨烯液体池（GLC）透射电子显微镜和四维扫描透射电子显微镜相结合，以成像反应介质中金纳米棒的蚀刻动力学。我们实验的关键在于GLC中较小的液体厚度，这使得能够在低剂量条件下收集高质量的电子衍射图案。基于机器学习对衍射图案进行数据挖掘，可绘制三维纳米晶体取向图，对GLC中各种物质的空间域进行分组，并识别反应过程中新生成的纳米微晶，从而全面了解纳米环境中的反应机制。这项工作为探究诸如相和应变等结构性质与溶液相反应动力学之间的相互作用开辟了机会，这对于催化、能量存储和自组装等应用具有重要意义。
