Nanoscale Chemical and Structural Analysis during In Situ Scanning/Transmission Electron Microscopy in Liquids.
Rui F Serra-MaiaPawan KumarAndrew C MengAlexandre C FoucherYijin KangKhim KarkiDeep JariwalaEric A StachPublished in: ACS nano (2021)
Liquid-cell scanning/transmission electron microscopy (S/TEM) has impacted our understanding of multiple areas of science, most notably nanostructure nucleation and growth and electrochemistry and corrosion. In the case of electrochemistry, the incorporation of electrodes requires the use of silicon nitride membranes to confine the liquid. The combined thickness of the liquid layer and the confining membranes prevents routine atomic-resolution characterization. Here, we show that by performing electrochemical water splitting in situ to generate a gas bubble, we can reduce the thickness of the liquid to a film approximately 30 nm thick that remains covering the sample. The reduced thickness of the liquid allows the acquisition of atomic-scale S/TEM images with chemical and valence analysis through electron energy loss spectroscopy (EELS) and structural analysis through selected area electron diffraction (SAED). This contrasts with a specimen cell entirely filled with liquid, where the broad plasmon peak from the liquid obscures the EELS signal from the sample and induces beam incoherence that impedes SAED analysis. The gas bubble generation is fully reversible, which allows alternating between a full cell and thin-film condition to obtain optimal experimental and analytical conditions, respectively. The methodology developed here can be applied to other scientific techniques, such as X-ray scattering, Raman spectroscopy, and X-ray photoelectron spectroscopy, allowing for a multi-modal, nanoscale understanding of solid-state samples in liquid media.
Keyphrases
- electron microscopy
- ionic liquid
- solid state
- optical coherence tomography
- high resolution
- cell therapy
- single molecule
- mesenchymal stem cells
- deep learning
- quantum dots
- public health
- convolutional neural network
- mass spectrometry
- photodynamic therapy
- liquid chromatography
- carbon nanotubes
- contrast enhanced
- reduced graphene oxide