化学
荧光
竞赛(生物学)
分辨率(逻辑)
超分辨率
纳米技术
生物物理学
生态学
人工智能
光学
图像(数学)
计算机科学
生物
物理
材料科学
作者
Xianwen Mao,Chunming Liu,Mahdi Hesari,Ningmu Zou,Peng Chen
出处
期刊:Nature Chemistry
[Nature Portfolio]
日期:2019-07-08
卷期号:11 (8): 687-694
被引量:122
标识
DOI:10.1038/s41557-019-0288-8
摘要
Super-resolved fluorescence microscopy techniques have enabled substantial advances in the chemical and biological sciences. However, they can only interrogate entities that fluoresce, and most chemical or biological processes do not involve fluorescent species. Here we report a competition-enabled imaging technique with super-resolution (COMPEITS) that enables quantitative super-resolution imaging of non-fluorescent processes. It is based on the incorporation of competition into a single-molecule fluorescence-detection scheme. We demonstrate COMPEITS by investigating a photoelectrocatalytic reaction; we map, with nanometre precision, a non-fluorescent surface reaction that is important for water decontamination on single photocatalyst particles. The subparticle-level quantitative information of reactant adsorption affinities unambiguously decouples size- and shape-scaling laws on specific particle facets and uncovers a surprising biphasic shape dependence, leading to catalyst design principles for optimal reactant adsorption efficacy. With its ability to provide spatially resolved information on the behaviours of unlabelled, non-fluorescent entities under operando conditions, COMPEITS could interrogate a variety of surface processes in fields ranging from heterogeneous catalysis and materials engineering to nanotechnology and energy sciences. Super-resolution fluorescence microscopy techniques can interrogate entities that fluoresce; however, most chemical or biological processes do not involve fluorescent species. Now, the incorporation of a competitive reaction into a single-molecule fluorescence detection scheme has been shown to enable quantitative super-resolution imaging of non-fluorescent reactions.
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