Optical Resolution of the Morphological Change of Single Nanoparticles at Native Conditions: A Nonsuper-Resolution...

Area of Science:

• Nanoscience and Nanotechnology
• Optical Microscopy
• Materials Science

Background:

• Label-free imaging of single nanoparticle morphology under native conditions is difficult.
• Understanding nanoparticle morphology is crucial for synthesis, properties, and applications.

Purpose of the Study:

• To develop a novel method for label-free imaging of single nanoparticle morphology.
• To enable high-throughput, in situ monitoring of nanoparticle dynamics.

Main Methods:

• Developed angular scanning dark-field scattering microscopy (ASDFSM).
• Utilized angle-dependent scattering intensities to identify morphology.
• Integrated a random forest machine learning algorithm for morphology identification.
• Applied the technique for in situ monitoring of nanoparticle corrosion and growth in high-temperature solutions.

Main Results:

• ASDFSM can resolve nanoparticle morphologies down to 1/5 wavelength of incident light.
• Achieved simultaneous imaging of numerous nanoparticles in a large field of view.
• Morphology identification accuracy reached an average of 96% when coupled with machine learning.
• Demonstrated in situ monitoring of nanoparticle kinetics.

Conclusions:

• ASDFSM offers a high-throughput, noninvasive, and dynamic method for nanoparticle morphology analysis.
• The technique simplifies nanoparticle characterization compared to existing methods.
• ASDFSM shows significant potential for broad applications in nanoscience.