Adding the fourth dimension to nanomaterials analysis: electron energy loss spectroscopic tomography

Electron tomography is a widely spread technique for recovering the three dimensional (3D) shape of nanostructured materials. The use of electron energy-loss spectroscopy (EELS) spectrum-images (SI) for tomographic reconstruction retains all chemical information and adds a fourth chemical dimension to the 3D structure.

This research line involves the acquisition of EELS spectrum images in tomography series and the application of Multivariate Analysis (MVA) for noise reduction and identification of principal components to recover quantitative chemical information in 3D.

We have successfully demonstrated this approach in Co3O4 mesoporous template materials impregnated with FexCo(3-x)O4. EELS SI were acquired on a probe Cs corrected FEI Titan operated at 80 kV acceleration voltage. The whole data set consisted of 48 SI ranging from 68.99º to -64.74º. High angle annular dark field (HAADF) signal was acquired simultaneously. Afterwards, for data treatment, MVA methods were applied, namely principal component analysis (PCA) and independent component analysis (ICA). From the noisy raw spectra, enhanced chemical edges were retrieved after PCA analysis, and ICA successfully retrieved the Fe oxide and Co oxide signals as well as the background signal before the oxygen K edge. These components were useful to calculate composition maps and rendering volume reconstructions of chemical information.

a) Independent components used for reconstruction. b) Superposition of the voltex visualization of Co (blue) and Fe (orange) obtained from quantification, and c superposition of the voltex visualization of the HAADF signal (yellow) and thickness maps from ICA (violet).

 

 

 

Universitat de Barcelona