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“3D characterization of the structural transformation undergone by Cu@Ag core-shell nanoparticles following CO₂, reduction reaction”. Arenas Esteban D, Pacquets L, Choukroun D, Hoekx S, Kadu AA, Schalck J, Daems N, Breugelmans T, Bals S, Chemistry of materials 35, 6682 (2023). http://doi.org/10.1021/ACS.CHEMMATER.3C00649
Abstract: The increasing use of metallic nanoparticles (NPs) is significantly advancing the field of electrocatalysis. In particular, Cu/Ag bimetallic interfaces are widely used to enhance the electrochemical CO2 reduction reaction (eCO(2)RR) toward CO and, more recently, C-2 products. However, drastic changes in the product distribution and performance when Cu@Ag core-shell configurations are used can often be observed under electrochemical reaction conditions, especially during the first few minutes of the reaction. Possible structural changes that generate these observations remain underexplored; therefore, the structure-property relationship is hardly understood. In this study, we use electron tomography to investigate the structural transformation mechanism of Cu@Ag core-shells NPs during the critical first minutes of the eCO(2)RR. In this manner, we found that the crystallinity of the Cu seed determines whether the formation of a complete and homogeneous Ag shell is possible. Moreover, by tracking the particles' transformations, we conclude that modifications of the Cu-Ag interface and Cu2O enrichment at the surface of the NPs are key factors contributing to the product generation changes. These insights provide a better understanding of how bimetallic core-shell NPs transform under electrochemical conditions.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Applied Electrochemistry & Catalysis (ELCAT)
Impact Factor: 8.6
Times cited: 1
DOI: 10.1021/ACS.CHEMMATER.3C00649
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“Real-time tilt undersampling optimization during electron tomography of beam sensitive samples using golden ratio scanning and RECAST3D”. Craig TM, Kadu AA, Batenburg KJ, Bals S, Nanoscale 15, 5391 (2023). http://doi.org/10.1039/D2NR07198C
Abstract: Electron tomography is a widely used technique for 3D structural analysis of nanomaterials, but it can cause damage to samples due to high electron doses and long exposure times. To minimize such damage, researchers often reduce beam exposure by acquiring fewer projections through tilt undersampling. However, this approach can also introduce reconstruction artifacts due to insufficient sampling. Therefore, it is important to determine the optimal number of projections that minimizes both beam exposure and undersampling artifacts for accurate reconstructions of beam-sensitive samples. Current methods for determining this optimal number of projections involve acquiring and post-processing multiple reconstructions with different numbers of projections, which can be time-consuming and requires multiple samples due to sample damage. To improve this process, we propose a protocol that combines golden ratio scanning and quasi-3D reconstruction to estimate the optimal number of projections in real-time during a single acquisition. This protocol was validated using simulated and realistic nanoparticles, and was successfully applied to reconstruct two beam-sensitive metal–organic framework complexes.
Keywords: A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT)
Impact Factor: 6.7
Times cited: 1
DOI: 10.1039/D2NR07198C
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“Low-dose 4D-STEM tomography for beam-sensitive nanocomposites”. Hugenschmidt M, Jannis D, Kadu AA, Grünewald L, De Marchi S, Perez-Juste J, Verbeeck J, Van Aert S, Bals S, ACS materials letters 6, 165 (2023). http://doi.org/10.1021/ACSMATERIALSLETT.3C01042
Abstract: Electron tomography is essential for investigating the three-dimensional (3D) structure of nanomaterials. However, many of these materials, such as metal-organic frameworks (MOFs), are extremely sensitive to electron radiation, making it difficult to acquire a series of projection images for electron tomography without inducing electron-beam damage. Another significant challenge is the high contrast in high-angle annular dark field scanning transmission electron microscopy that can be expected for nanocomposites composed of a metal nanoparticle and an MOF. This strong contrast leads to so-called metal artifacts in the 3D reconstruction. To overcome these limitations, we here present low-dose electron tomography based on four-dimensional scanning transmission electron microscopy (4D-STEM) data sets, collected using an ultrafast and highly sensitive direct electron detector. As a proof of concept, we demonstrate the applicability of the method for an Au nanostar embedded in a ZIF-8 MOF, which is of great interest for applications in various fields, including drug delivery.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
DOI: 10.1021/ACSMATERIALSLETT.3C01042
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“Quantitative 3D Investigation of Nanoparticle Assemblies by Volumetric Segmentation of Electron Tomography Data Sets”. Kavak S, Kadu AA, Claes N, Sánchez-Iglesias A, Liz-Marzán LM, Batenburg KJ, Bals S, The journal of physical chemistry: C : nanomaterials and interfaces 127, 9725 (2023). http://doi.org/10.1021/acs.jpcc.3c02017
Abstract: Morphological characterization of nanoparticle assemblies and hybrid nanomaterials is critical in determining their structure-property relationships as well as in the development of structures with desired properties. Electron tomography has become a widely utilized technique for the three-dimensional characterization of nanoparticle assemblies. However, the extraction of quantitative morphological parameters from the reconstructed volume can be a complex and labor-intensive task. In this study, we aim to overcome this challenge by automating the volumetric segmentation process applied to three-dimensional reconstructions of nanoparticle assemblies. The key to enabling automated characterization is to assess the performance of different volumetric segmentation methods in accurately extracting predefined quantitative descriptors for morphological characterization. In our methodology, we compare the quantitative descriptors obtained through manual segmentation with those obtained through automated segmentation methods, to evaluate their accuracy and effectiveness. To show generality, our study focuses on the characterization of assemblies of CdSe/CdS quantum dots, gold nanospheres and CdSe/CdS encapsulated in polymeric micelles, and silica-coated gold nanorods decorated with both CdSe/CdS or PbS quantum dots. We use two unsupervised segmentation algorithms: the watershed transform and the spherical Hough transform. Our results demonstrate that the choice of automated segmentation method is crucial for accurately extracting the predefined quantitative descriptors. Specifically, the spherical Hough transform exhibits superior performance in accurately extracting quantitative descriptors, such as particle size and interparticle distance, thereby allowing for an objective, efficient, and reliable volumetric segmentation of complex nanoparticle assemblies.
Keywords: A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT)
Impact Factor: 3.7
Times cited: 2
DOI: 10.1021/acs.jpcc.3c02017
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