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Author |
Cioni, M.; Delle Piane, M.; Polino, D.; Rapetti, D.; Crippa, M.; Arslan Irmak, E.; Van Aert, S.; Bals, S.; Pavan, G.M. |
![goto web page (via DOI) doi](http://nano.uantwerpen.be/nanorefs/img/doi.gif)
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Title |
Sampling real-time atomic dynamics in metal nanoparticles by combining experiments, simulations, and machine learning |
Type |
A1 Journal article |
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Year |
2024 |
Publication |
Advanced Science |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
1-13 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT) |
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Abstract |
Even at low temperatures, metal nanoparticles (NPs) possess atomic dynamics that are key for their properties but challenging to elucidate. Recent experimental advances allow obtaining atomic-resolution snapshots of the NPs in realistic regimes, but data acquisition limitations hinder the experimental reconstruction of the atomic dynamics present within them. Molecular simulations have the advantage that these allow directly tracking the motion of atoms over time. However, these typically start from ideal/perfect NP structures and, suffering from sampling limits, provide results that are often dependent on the initial/putative structure and remain purely indicative. Here, by combining state-of-the-art experimental and computational approaches, how it is possible to tackle the limitations of both approaches and resolve the atomistic dynamics present in metal NPs in realistic conditions is demonstrated. Annular dark-field scanning transmission electron microscopy enables the acquisition of ten high-resolution images of an Au NP at intervals of 0.6 s. These are used to reconstruct atomistic 3D models of the real NP used to run ten independent molecular dynamics simulations. Machine learning analyses of the simulation trajectories allow resolving the real-time atomic dynamics present within the NP. This provides a robust combined experimental/computational approach to characterize the structural dynamics of metal NPs in realistic conditions. Experimental and computational techniques are bridged to unveil atomic dynamics in gold nanoparticles (NPs), using annular dark-field scanning transmission electron microscopy and molecular dynamics simulations informed by machine learning. The approach provides unprecedented insights into the real-time structural behaviors of NPs, merging state-of-the-art techniques to accurately characterize their dynamics under realistic conditions. image |
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Wos |
001206888000001 |
Publication Date |
2024-04-24 |
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Edition |
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ISSN |
2198-3844 |
ISBN |
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Additional Links |
UA library record; WoS full record |
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Impact Factor |
15.1 |
Times cited |
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Open Access |
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Notes |
This work was supported by the funding received by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement no. 818776- DYNAPOL, no. 770887 PICOMETRICS and no. 815128 REALNANO). The authors also acknowledge the computational resources provided by the Swiss National Supercomputing Center (CSCS), by CINECA, and the Research Foundation Flanders (FWO, Belgium) G.0346.21N. |
Approved ![sorted by Approved field, ascending order (up)](img/sort_asc.gif) |
Most recent IF: 15.1; 2024 IF: 9.034 |
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Call Number |
UA @ admin @ c:irua:205442 |
Serial |
9171 |
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Author |
Pedrazo-Tardajos, A.; Arslan Irmak, E.; Kumar, V.; Sánchez-Iglesias, A.; Chen, Q.; Wirix, M.; Freitag, B.; Albrecht, W.; Van Aert, S.; Liz-Marzán, L.M.; Bals, S. |
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Title |
Thermal Activation of Gold Atom Diffusion in Au@Pt Nanorods |
Type |
A1 Journal article |
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Year |
2022 |
Publication |
ACS nano |
Abbreviated Journal |
Acs Nano |
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Pages |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT) |
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Abstract |
Understanding the thermal stability of bimetallic nanoparticles is of vital importance to preserve their functionalities during their use in a variety of applications. In contrast to well-studied bimetallic systems such as Au@Ag, heat-induced morphological and compositional changes in Au@Pt nanoparticles are insufficiently understood, even though Au@Pt is an important material for catalysis. To investigate the thermal instability of Au@Pt nanorods at temperatures below their bulk melting point, we combined in situ heating with two- and three-dimensional electron microscopy techniques, including three-dimensional energy-dispersive X-ray spectroscopy. The experimental results were used as input for molecular dynamics simulations, to unravel the mechanisms behind the morphological transformation of Au@Pt core–shell nanorods. We conclude that thermal stability is influenced not only by the degree of coverage of Pt on Au but also by structural details of the Pt shell. |
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000819246800001 |
Publication Date |
2022-06-10 |
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Edition |
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ISSN |
1936-0851 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
17.1 |
Times cited |
8 |
Open Access |
OpenAccess |
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Notes |
S.B., S.V.A., L.M.L.-M. and A.P.-T. acknowledge financial support from the European Commission under the Horizon 2020 Programme by grant nos. 731019 (EUSMI) and 823717 (ESTEEM3) and ERC Consolidator grant nos. 815128 (REALNANO) and 770887 (PICOMETRICS). L.M.L.-M. acknowledges funding from MCIN/AEI/10.13039/501100011033 through grants no. PID2020-117779RB-I00 and Maria de Maeztu Unit of Excellence no. MDM-2017-0720. The authors acknowledge the resources and services used for the simulations in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation – Flanders (FWO) and the Flemish Government.; esteem3reported; esteem3JRA |
Approved ![sorted by Approved field, ascending order (up)](img/sort_asc.gif) |
Most recent IF: 17.1 |
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Call Number |
EMAT @ emat @c:irua:188540 |
Serial |
7072 |
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Author |
Albrecht, W.; Arslan Irmak, E.; Altantzis, T.; Pedrazo‐Tardajos, A.; Skorikov, A.; Deng, T.‐S.; van der Hoeven, J.E.S.; van Blaaderen, A.; Van Aert, S.; Bals, S. |
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Title |
3D Atomic‐Scale Dynamics of Laser‐Light‐Induced Restructuring of Nanoparticles Unraveled by Electron Tomography |
Type |
A1 Journal article |
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Year |
2021 |
Publication |
Advanced Materials |
Abbreviated Journal |
Adv Mater |
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Volume |
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Issue |
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Pages |
2100972 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT); Applied Electrochemistry & Catalysis (ELCAT) |
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Abstract |
Understanding light–matter interactions in nanomaterials is crucial for
optoelectronic, photonic, and plasmonic applications. Specifically, metal
nanoparticles (NPs) strongly interact with light and can undergo shape
transformations, fragmentation and ablation upon (pulsed) laser excitation.
Despite being vital for technological applications, experimental insight into
the underlying atomistic processes is still lacking due to the complexity of
such measurements. Herein, atomic resolution electron tomography is performed
on the same mesoporous-silica-coated gold nanorod, before and after
femtosecond laser irradiation, to assess the missing information. Combined
with molecular dynamics (MD) simulations based on the experimentally
determined 3D atomic-scale morphology, the complex atomistic rearrangements,
causing shape deformations and defect generation, are unraveled.
These rearrangements are simultaneously driven by surface diffusion, facet
restructuring, and strain formation, and are influenced by subtleties in the
atomic distribution at the surface. |
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Wos |
000671662000001 |
Publication Date |
2021-07-11 |
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Series Volume |
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Edition |
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ISSN |
0935-9648 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
19.791 |
Times cited |
8 |
Open Access |
OpenAccess |
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Notes |
W.A. and E.A.I. contributed equally to this work. The authors acknowledge funding from the European Research Council under the European Union’s Horizon 2020 research and innovation program (ERC Consolidator Grants No. 815128 – REALNANO and No. 770887 – PICOMETRICS), the European Union’s Seventh Framework Programme (ERC Advanced Grant No. 291667 – HierarSACol), and the European Commission (EUSMI). W.A. acknowledges an Individual Fellowship funded by the Marie Sklodowska-Curie Actions (MSCA) in the Horizon2020 program (Grant 797153, SOPMEN). T.-S.D. acknowledges financial support from the National Science Foundation of China (NSFC, Grant No. 61905056). The authors also acknowledge financial support by the Research Foundation Flanders (FWO Grant G.0267.18N).; sygmaSB |
Approved ![sorted by Approved field, ascending order (up)](img/sort_asc.gif) |
Most recent IF: 19.791 |
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Call Number |
EMAT @ emat @c:irua:179781 |
Serial |
6805 |
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Author |
Liu, P.; Arslan Irmak, E.; De Backer, A.; De wael, A.; Lobato, I.; Béché, A.; Van Aert, S.; Bals, S. |
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Title |
Three-dimensional atomic structure of supported Au nanoparticles at high temperature |
Type |
A1 Journal article |
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Year |
2021 |
Publication |
Nanoscale |
Abbreviated Journal |
Nanoscale |
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Volume |
13 |
Issue |
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Pages |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT) |
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Abstract |
Au nanoparticles (NPs) deposited on CeO2 are extensively used as thermal catalysts since the morphology of the NPs is expected to be stable at elevated temperatures. Although it is well known that the activity of Au NPs depends on their size and surface structure, their three-dimensional (3D) structure at the atomic scale has not been completely characterized as a function of temperature. In this paper, we overcome the limitations of conventional electron tomography by combining atom counting applied to aberration-corrected scanning transmission electron microscopy images and molecular dynamics relaxation. In this manner, we are able to perform an atomic resolution 3D investigation of supported Au NPs. Our results enable us to characterize the 3D equilibrium structure of single NPs as a function of temperature. Moreover, the dynamic 3D structural evolution of the NPs at high temperatures, including surface layer jumping and crystalline transformations, has been studied. |
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000612999200029 |
Publication Date |
2020-12-29 |
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ISSN |
2040-3364 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
7.367 |
Times cited |
13 |
Open Access |
OpenAccess |
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Notes |
This work was supported by the European Research Council (Grant 815128 REALNANO to SB, Grant 770887 PICOMETRICS to SVA, Grant 823717 ESTEEM3). The authors acknowledge financial support from the Research Foundation Flanders (FWO, Belgium) through grants to A. D. w. and A. D. B. and project funding G.0267.18N.; sygma; esteem3JRA; esteem3reported |
Approved ![sorted by Approved field, ascending order (up)](img/sort_asc.gif) |
Most recent IF: 7.367 |
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Call Number |
EMAT @ emat @c:irua:174858 |
Serial |
6665 |
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Permanent link to this record |
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Author |
Arslan Irmak, E.; Liu, P.; Bals, S.; Van Aert, S. |
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Title |
3D Atomic Structure of Supported Metallic Nanoparticles Estimated from 2D ADF STEM Images: A Combination of Atom – Counting and a Local Minima Search Algorithm |
Type |
A1 Journal article |
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Year |
2021 |
Publication |
Small methods |
Abbreviated Journal |
Small Methods |
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Issue |
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Pages |
2101150 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT) |
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Abstract |
Determining the three-dimensional (3D) atomic structure of nanoparticles (NPs) is critical to understand their structure-dependent properties. It is hereby important to perform such analyses under conditions relevant for the envisioned application. Here, we investigate the 3D structure of supported Au NPs at high temperature, which is of importance to understand their behavior during catalytic reactions. To overcome limitations related to conventional high-resolution electron tomography at high temperature, 3D characterization of NPs with atomic resolution has been performed by applying atom-counting using atomic resolution annular darkfield scanning transmission electron microscopy (ADF STEM) images followed by structural relaxation. However, at high temperatures, thermal displacements, which affect the ADF STEM intensities, should be taken into account. Moreover, it is very likely that the structure of a NP investigated at elevated temperature deviates from a ground state configuration, which is difficult to determine using purely computational energy minimization approaches. In this paper, we therefore propose an optimized approach using an iterative local minima search algorithm followed by molecular dynamics (MD) structural relaxation of candidate structures associated with each local minimum. In this manner, it becomes possible to investigate the 3D atomic structure of supported NPs, which may deviate from their ground state configuration. |
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000716511600001 |
Publication Date |
2021-11-10 |
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ISSN |
2366-9608 |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
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Times cited |
12 |
Open Access |
OpenAccess |
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Notes |
This work was supported by the European Research Council (Grant 815128 REALNANO to SB, Grant 770887 PICOMETRICS to SVA, Grant 823717 ESTEEM3). The authors acknowledge financial support from the Research Foundation Flanders (FWO, Belgium) through project funding (G.0267.18N, G.0502.18N, G.0346.21N).; sygmaSB; esteem3jra; esteem3reported |
Approved ![sorted by Approved field, ascending order (up)](img/sort_asc.gif) |
Most recent IF: NA |
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Call Number |
EMAT @ emat @c:irua:183289 |
Serial |
6820 |
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Permanent link to this record |
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Author |
Arslan Irmak, E. |
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Title |
Modelling three-dimensional nanoparticle transformations based on quantitative transmission electron microscopy |
Type |
Doctoral thesis |
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Year |
2022 |
Publication |
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Abbreviated Journal |
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Volume |
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Issue |
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Pages |
169 p. |
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Keywords |
Doctoral thesis; Electron microscopy for materials research (EMAT) |
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Abstract |
Nanomaterials are materials that have at least one dimension in the nanometer length scale, which corresponds to a billionth of a meter. When three dimensions are confined to the nanometer scale, these materials are referred to as nanoparticles. These materials are of great interest since they exhibit unique physical and chemical properties that cannot be observed for bulk systems. Due to their unique and often superior properties, nanomaterials have become central in the field of electronics, catalysis, and medicine. Moreover, they are expected to be one of the most promising systems to tackle many challenges that our society is facing, such as reducing the emission of greenhouse gases and finding effective treatments for cancer. The unique properties of nanomaterials are linked to their size, shape, structure, and composition. If one is able to measure the positions of the atoms, their chemical nature, and the bonding between them, it becomes possible to predict the physicochemical properties of nanomaterials. In this manner, the development of novel nanostructures can be triggered. However, the morphology and structure of nanomaterials are highly sensitive to the conditions for relevant applications, such as elevated temperatures or intense light illumination. Furthermore, any small change in the local structure at higher temperatures or pressures may significantly modify their performance. Hence, three-dimensional (3D) characterization of nanomaterials under application-relevant conditions is important in designing them with desired functional properties for specific applications. Among different structural characterization approaches, transmission electron microscopy (TEM) is one of the most efficient and versatile tools to investigate the structure and composition of nanomaterials since it can provide atomically resolved images, which are sensitive to the local 3D structure of the investigated sample. However, TEM only provides two-dimensional (2D) images of the 3D nanoparticle, which may lead to an incomplete understanding of their structure-property relationship. The most known and powerful technique for the 3D characterization of nanomaterials is electron tomography, where the images of a nanostructured material taken from different directions are mathematically combined to retrieve its 3D structure. Although these experiments are already state-of-the-art, 3D characterization by TEM is typically performed under ultra-high vacuum conditions and at room temperature. Such conditions are unfortunately not sufficient to understand transformations during synthesis or applications of nanomaterials. This limitation can be overcome by in situ TEM where external stimuli, such as heat, gas, and liquids, can be controllably introduced inside the TEM using specialized holders. However, there are some technical limitations to successful perform 3D in situ electron tomography experiments. For example, the long acquisition time required to collect a tilt series limits this technique when one wants to observe 3D dynamic changes with atomic resolution. A solution for this problem is the estimation of the 3D structure of nanomaterials from 2D projection images acquired along a single viewing direction. For this purpose, annular dark field scanning TEM (ADF STEM) imaging mode provides a valuable tool for quantitative structural investigation of nanomaterials from single 2D images due to its thickness and mass sensitivity. For quantitative analysis, an ADF STEM image is considered as a 2D array of pixels where relative variation of pixel intensity values is proportional to the total number of atoms and the atomic number of the elements in the sample. By applying advanced statistical approaches to these images, structural information, such as the number or types of atoms, can be retrieved with high accuracy and precision. The outcome can then be used to build a 3D starting model for energy minimization by atomistic simulations, for example, molecular dynamics simulations or the Monte Carlo method. However, this methodology needs to be further evaluated for in situ experiments. This thesis is devoted to presenting robust approaches to accurately define the 3D atomic structure of nanoparticles under application-relevant conditions and understand the mechanism behind the atomic-scale dynamics in nanoparticles in response to environmental stimuli. |
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Approved ![sorted by Approved field, ascending order (up)](img/sort_asc.gif) |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:188295 |
Serial |
7063 |
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Permanent link to this record |
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Author |
De Backer, A.; Van Aert, S.; Faes, C.; Arslan Irmak, E.; Nellist, P.D.; Jones, L. |
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Title |
Experimental reconstructions of 3D atomic structures from electron microscopy images using a Bayesian genetic algorithm |
Type |
A1 Journal article |
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Year |
2022 |
Publication |
N P J Computational Materials |
Abbreviated Journal |
npj Comput Mater |
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8 |
Issue |
1 |
Pages |
216 |
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Keywords |
A1 Journal article; Electron microscopy for materials research (EMAT) |
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We introduce a Bayesian genetic algorithm for reconstructing atomic models of monotype crystalline nanoparticles from a single projection using Z-contrast imaging. The number of atoms in a projected atomic column obtained from annular dark field scanning transmission electron microscopy images serves as an input for the initial three-dimensional model. The algorithm minimizes the energy of the structure while utilizing a priori information about the finite precision of the atom-counting results and neighbor-mass relations. The results show promising prospects for obtaining reliable reconstructions of beam-sensitive nanoparticles during dynamical processes from images acquired with sufficiently low incident electron doses. |
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000866500900001 |
Publication Date |
2022-10-12 |
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2057-3960 |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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OpenAccess |
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Notes |
This work was supported by the European Research Council (Grant 770887 PICOMETRICS to S.V.A. and Grant 823717 ESTEEM3). The authors acknowledge financial support from the Research Foundation Flanders (FWO, Belgium) through project fundings (G.0267.18N, G.0502.18N, G.0346.21N) and a postdoctoral grant to A.D.B. L.J. acknowledges Science Foundation Ireland (SFI – grant number URF/RI/191637), the Royal Society, and the AMBER Centre. The authors acknowledge Aakash Varambhia for his assistance and expertise with the experimental recording and use of characterization facilities within the David Cockayne Centre for Electron Microscopy, Department of Materials, University of Oxford, and in particular the EPSRC (EP/K040375/1 South of England Analytical Electron Microscope).; esteem3reported; esteem3JRA |
Approved ![sorted by Approved field, ascending order (up)](img/sort_asc.gif) |
Most recent IF: NA |
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Call Number |
EMAT @ emat @c:irua:191398 |
Serial |
7114 |
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Author |
Cioni, M.; Delle Piane, M.; Polino, D.; Rapetti, D.; Crippa, M.; Arslan Irmak, E.; Pavan, G.M.; Van Aert, S.; Bals, S. |
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Title |
Data for Sampling Real‐Time Atomic Dynamics in Metal Nanoparticles by Combining Experiments, Simulations, and Machine Learning |
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Dataset |
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2024 |
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Dataset; Engineering sciences. Technology; Electron microscopy for materials research (EMAT) |
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Abstract |
Even at low temperatures, metal nanoparticles (NPs) possess atomic dynamics that are key for their properties but challenging to elucidate. Recent experimental advances allow obtaining atomic‐resolution snapshots of the NPs in realistic regimes, but data acquisition limitations hinder the experimental reconstruction of the atomic dynamics present within them. Molecular simulations have the advantage that these allow directly tracking the motion of atoms over time. However, these typically start from ideal/perfect NP structures and, suffering from sampling limits, provide results that are often dependent on the initial/putative structure and remain purely indicative. Here, by combining state‐of‐the‐art experimental and computational approaches, how it is possible to tackle the limitations of both approaches and resolve the atomistic dynamics present in metal NPs in realistic conditions is demonstrated. Annular dark‐field scanning transmission electron microscopy enables the acquisition of ten high‐resolution images of an Au NP at intervals of 0.6 s. These are used to reconstruct atomistic 3D models of the real NP used to run ten independent molecular dynamics simulations. Machine learning analyses of the simulation trajectories allows resolving the real‐time atomic dynamics present within the NP. This provides a robust combined experimental/computational approach to characterize the structural dynamics of metal NPs in realistic conditions. |
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Approved ![sorted by Approved field, ascending order (up)](img/sort_asc.gif) |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:205843 |
Serial |
9143 |
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