HAADF-STEM Electron Tomography in Catalysis Research

Hungría, Ana B.; Calvino, José J.; Hernández‐Garrido, Juan C.

doi:10.1007/s11244-019-01200-2

Cited by 23 publications

(13 citation statements)

References 73 publications

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“…Although most of the beam could be diffracted at small angles some could be scattered through much larger ones, this component being collected by an annular detector and used to form the so-called Z-contrast image. As the cross-section for this type of scattering depends upon the square of the atomic number (Z) of analyzed atoms (i.e., Z 2 ), corresponding micrographs could enable chemical composition profiling based on image contrast (Hungría et al, 2019). Thus, in HAADF-STEM images heavier atoms (i.e., Pt ones) appear brighter than lighter ones (as those of Ti or Si).…”

Section: High-resolution Tem (Hr-tem) and High Angle Annular Dark Field-stem (Haadf-stem)mentioning

confidence: 99%

Improving platinum dispersion on SBA-15 by titania addition

Morales-Hernández¹,

Ujat²,

Pacheco-Sosa³

et al. 2019

Rev.Mex.Ing.Quim.

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Section: High-resolution Tem (Hr-tem) and High Angle Annular Dark Field-stem (Haadf-stem)mentioning

confidence: 99%

Improving platinum dispersion on SBA-15 by titania addition

Morales-Hernández¹,

Ujat²,

Pacheco-Sosa³

et al. 2019

Rev.Mex.Ing.Quim.

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“…The potential of Electron Tomography to unveil the 3D structure of catalysts, with spatial resolution in the subnanometer scale, has been widely explored and reviewed in recent works [1,2]. A variety of experimental techniques, based either on Transmission Electron Microscopy (TEM) but reconstruction and segmentation are those with major contribution.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Evaluation of Supported Catalysts Key Properties from Electron Tomography Studies: Assessing Accuracy Using Material-Realistic 3D-Models

et al. 2022

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Electron Tomography (ET) reconstructions can be analysed, via segmentation techniques, to obtain quantitative, 3D-information about individual nanoparticles in supported catalysts. This includes values of parameters out of reach for any other technique, like their volume and surface, which are required to determine the dispersion of the supported particle system or the specific surface area of the support; two figures that play a major role in the performance of this type of catalysts.However, both the experimental conditions during the acquisition of the tilt series and the limited fidelity of the reconstruction and segmentation algorithms, restrict the quality of the ET results and introduce an undefined amount of error both in the qualitative features of the reconstructions and in all the quantitative parameters measured from them.Here, a method based on the use of well-defined 3D geometrical models (phantoms), with morphological features closely resembling those observed in experimental images of an Au/CeO2 catalyst, has been devised to provide a precise estimation of the accuracy of the reconstructions. Using this approach, the influence of noise and the number of projections on the errors of reconstructions obtained using a Total Variation Minimization in 3D (TVM-3D) algorithm have been determined. Likewise, the benefits of using smart denoising techniques based on Undecimated Wavelet Transforms (UWT) have been also evaluated.The results clearly reveal a large impact of usual noise levels on both the quality of the reconstructions and nanometrological measurement errors. Quantitative clues about the key role of UWT to largely compensate them are also provided.

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“…Composition mapping by electron energy loss spectroscopy (EELS) and energy dispersive X-ray spectroscopy (EDX) can also be acquired for electron tomography ( Haberfehlner et al, 2014 ; Slater et al, 2016 ). In such scenario, tilt increment is sometimes increased to reduce electron dose and reconstruction quality is compromised ( Midgley and Dunin-Borkowski, 2009 ; Hungría et al, 2019 ). The acquired tilt series are then reconstructed using different algorithms, such as classic back projection or weighted back projection, iterative procedure, and more advanced compressive sensing, atomic electron tomography (AET) or deep-learning assisted algorithms ( Midgley and Dunin-Borkowski, 2009 ; Zečević et al, 2013 ; Bals et al, 2014 ; Miao et al, 2016 ; Ding et al, 2019 ; Hovden and Muller, 2020 ; Wang, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

“…3D electron tomography has then been rapidly developed in the past decade due to the booming research in functional (nano)materials ( Leary et al, 2012a ; Bals et al, 2014 ; Ersen et al, 2015 ; Hovden and Muller, 2020 ). 3D electron tomography helps reveal the nanostructures in 3D, and thus contributes to activity and degradation study for electrocatalysis ( Hungría et al, 2019 ; Hovden and Muller, 2020 ). Despite much progress has been achieved in studying catalysts and related nanomaterials by using 3D electron tomography ( Zečević et al, 2013 ; Thomas, 2017 ; Zhang et al, 2017 ; Hungría et al, 2019 ), a dedicated review of electrocatalysts’ investigation by 3D electron tomography is lacking.…”

Section: Introductionmentioning

confidence: 99%

“…3D electron tomography helps reveal the nanostructures in 3D, and thus contributes to activity and degradation study for electrocatalysis ( Hungría et al, 2019 ; Hovden and Muller, 2020 ). Despite much progress has been achieved in studying catalysts and related nanomaterials by using 3D electron tomography ( Zečević et al, 2013 ; Thomas, 2017 ; Zhang et al, 2017 ; Hungría et al, 2019 ), a dedicated review of electrocatalysts’ investigation by 3D electron tomography is lacking. Therefore, in this mini-review, we summarize recent applications of electron tomography towards the developments of electrocatalysts.…”

Section: Introductionmentioning

confidence: 99%

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Recent Progress on Revealing 3D Structure of Electrocatalysts Using Advanced 3D Electron Tomography: A Mini Review

Wang

2022

Front. Chem.

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Electrocatalysis plays a key role in clean energy innovation. In order to design more efficient, durable and selective electrocatalysts, a thorough understanding of the unique link between 3D structures and properties is essential yet challenging. Advanced 3D electron tomography offers an effective approach to reveal 3D structures by transmission electron microscopy. This mini-review summarizes recent progress on revealing 3D structures of electrocatalysts using 3D electron tomography. 3D electron tomography at nanoscale and atomic scale are discussed, respectively, where morphology, composition, porous structure, surface crystallography and atomic distribution can be revealed and correlated to the performance of electrocatalysts. (Quasi) in-situ 3D electron tomography is further discussed with particular focus on its impact on electrocatalysts’ durability investigation and post-treatment. Finally, perspectives on future developments of 3D electron tomography for eletrocatalysis is discussed.

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HAADF-STEM Electron Tomography in Catalysis Research

Cited by 23 publications

References 73 publications

Improving platinum dispersion on SBA-15 by titania addition

Improving platinum dispersion on SBA-15 by titania addition

Quantitative Evaluation of Supported Catalysts Key Properties from Electron Tomography Studies: Assessing Accuracy Using Material-Realistic 3D-Models

Recent Progress on Revealing 3D Structure of Electrocatalysts Using Advanced 3D Electron Tomography: A Mini Review

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