Measuring Dynamic Structural Changes of Nanoparticles at the Atomic Scale Using Scanning Transmission Electron Microscopy

Localization and segmentation of atomic columns in supported nanoparticles for fast scanning transmission electron microscopy

To accurately capture the dynamic behavior of small nanoparticles in scanning transmission electron microscopy, high-quality data and advanced data processing is needed. The fast scan rate required to observe structural dynamics inherently leads to very noisy data where machine learning tools are essential for unbiased analysis. In this study, we develop a workflow based on two U-Net architectures to automatically localize and classify atomic columns at particle-support interfaces. The model is trained on non-physical image simulations, achieves sub-pixel localization precision, high classification accuracy, and generalizes well to experimental data. We test our model on both in situ and ex situ experimental time series recorded at 5 frames per second of small Pt nanoparticles supported on CeO2(111). The processed movies show sub-second dynamics of the nanoparticles and reveal site-specific movement patterns of individual atomic columns.

Surface Rearrangement and Sublimation Kinetics of Supported Gold Nanoparticle Catalysts

Heterogeneous catalysts consisting of supported metallic nanoparticles typically derive exceptional catalytic activity from their large proportion of undercoordinated surface sites which promote adsorption of reactant molecules. Simultaneously, these high energy surface configurations are unstable, leading to nanoparticle growth or degradation and eventually a loss of catalytic activity. Surface morphology of catalytic nanoparticles is paramount to catalytic activity, selectivity, and degradation rates, however it is well-known that harsh reaction conditions can cause the surface structure to change. Still, limited research has focused on understanding the link between nanoparticle surface facets and degradation rates or mechanisms. Here, we study a model Au supported catalyst system over a range of temperatures using a combination of in situ transmission electron microscopy, kinetic Monte Carlo simulations, and density functional theory calculations to establish an atomistic picture of how variations in surface structures and atomic coordination environments lead to shifting evolution mechanisms as a function of temperature. By combining experimental results, which yield direct observation of dynamic shape changes and particle sublimation rates, with computational techniques, which enable understanding the fundamental thermodynamics and kinetics of nanoparticle evolution, we illustrate a two-step evolution mechanism in which mobile adatoms form through desorption from low-coordination facets and subsequently sublimate off the particle surface. By understanding the role of temperature in the competition between surface diffusion and sublimation, we are able to show how individual atomic movements lead to particle scale morphological changes and rationalize why sublimation rates vary between particles in a system of nearly identical nanoparticles.

Atomic-Scale Dynamics at Solid-Liquid Nanointerfaces Induced by Electron-Beam Irradiation

We report electron-beam induced dynamics at PbS-Pb solid-liquid interfaces. We fabricated PbS-Pb solid-liquid nanointerfaces by heating PbS nanocrystals under vacuum to observe the entire process of structural evolution at the atomic scale. We investigated the dynamics using time-resolved high-angle annular dark-field imaging. Electron-beam irradiation caused layer-by-layer dissolution of PbS at the interface, resulting in the formation of the Pb nanodroplet. Ordered liquid layers were observed adjacent to the interface even under continuous electron-beam irradiation and followed the movement of the interface. Instantaneous epitaxial growth of PbS was observed as a reverse process of the dissolution. The resultant Pb nanodroplet provides indisputable evidence for selective sputtering of sulfur atoms via electron-beam irradiation. This paper demonstrates atomic resolution in situ observations of selective and complete sputtering. The observed dynamics can be explained by the intermittent phase transition via nonequilibrium states of the solid-liquid nanointerface triggered by selective sputtering.

Recent Developments of Microscopic Study for Lanthanide and Manganese Doped Luminescent Materials

Luminescent materials are indispensable for applications in lighting, displays and photovoltaics, which can transfer, absorb, store and utilize light energy. Their performance is closely related with their size and morphologies, exact atomic arrangement, and local configuration about photofunctional centers. Advanced electron microscopy-based techniques have enabled the possibility to study nanostructures with atomic resolution. Especially, with the advanced micro-electro-mechanical systems, it is able to characterize the luminescent materials at the atomic scale under various environments, providing a deep understanding of the luminescent mechanism. Accordingly, this review summarizes the recent achievements of microscopic study to directly image the microstructure and local environment of activators in lanthanide and manganese (Ln/Mn²⁺ )-doped luminescent materials, including: 1) bulk materials, the typical systems are nitride/oxynitride phosphors; and 2) nanomaterials, such as nanocrystals (hexagonal-phase NaLnF₄ and perovskite) and 2D nanosheets (Ca₂ Ta₃ O₁₀ and MoS₂ ). Finally, the challenges and limitations are highlighted, and some possible solutions to facilitate the developments of advanced luminescent materials are provided.

Probing atom dynamics of excited Co-Mo-S nanocrystals in 3D

Advances in electron microscopy have enabled visualizations of the three-dimensional (3D) atom arrangements in nano-scale objects. The observations are, however, prone to electron-beam-induced object alterations, so tracking of single atoms in space and time becomes key to unravel inherent structures and properties. Here, we introduce an analytical approach to quantitatively account for atom dynamics in 3D atomic-resolution imaging. The approach is showcased for a Co-Mo-S nanocrystal by analysis of time-resolved in-line holograms achieving ~1.5 Å resolution in 3D. The analysis reveals a decay of phase image contrast towards the nanocrystal edges and meta-stable edge motifs with crystallographic dependence. These findings are explained by beam-stimulated vibrations that exceed Debye-Waller factors and cause chemical transformations at catalytically relevant edges. This ability to simultaneously probe atom vibrations and displacements enables a recovery of the pristine Co-Mo-S structure and establishes, in turn, a foundation to understand heterogeneous chemical functionality of nanostructures, surfaces and molecules.

The authors introduce an analytical approach for quantitative analysis of 3D atom dynamics during electron microscopy. They image a Co-Mo-S nanocrystal with 1.5 Å resolution, and observe chemical transformations caused by beam-stimulated vibrations.

Disentangling Rotational Dynamics and Ordering Transitions in a System of Self-Organizing Protein Nanorods via Rotationally Invariant Latent Representations

The dynamics of complex ordering systems with active rotational degrees of freedom exemplified by protein self-assembly is explored using a machine learning workflow that combines deep learning-based semantic segmentation and rotationally invariant variational autoencoder-based analysis of orientation and shape evolution. The latter allows for disentanglement of the particle orientation from other degrees of freedom and compensates for lateral shifts. The disentangled representations in the latent space encode the rich spectrum of local transitions that can now be visualized and explored via continuous variables. The time dependence of ensemble averages allows insight into the time dynamics of the system and, in particular, illustrates the presence of the potential ordering transition. Finally, analysis of the latent variables along the single-particle trajectory allows tracing these parameters on a single-particle level. The proposed approach is expected to be universally applicable for the description of the imaging data in optical, scanning probe, and electron microscopy seeking to understand the dynamics of complex systems where rotations are a significant part of the process.

Combining quantitative ADF STEM with SiNx membrane-based MEMS devices: A simulation study with Pt nanoparticles

Computer simulations are used to assess the influence of a 20-nm-thick SiN_x membrane on the quantification of atomic-resolution annular dark-field (ADF) scanning transmission electron microscopy images of Pt nanoparticles. The discussions include the effect of different nanoparticle/membrane arrangements, accelerating voltage, nanoparticle thickness and the presence of adjacent atomic columns on the accuracy with which the number of Pt atoms in each atom column can be counted. The results, which are based on the use of ADF scattering cross-sections, show that an accuracy of better than a single atom is attainable at 200 and 300 kV. At 80kV, the scattering in a typical SiN_x membrane is sufficiently strong that the best possible atom counting accuracy is reduced to +/- 2 atoms. The implications of the work for quantitative studies of Pt nanoparticles imaged through SiN_x membranes are discussed.

Single-atom level determination of 3-dimensional surface atomic structure via neural network-assisted atomic electron tomography

Functional properties of nanomaterials strongly depend on their surface atomic structures, but they often become largely different from their bulk structures, exhibiting surface reconstructions and relaxations. However, most of the surface characterization methods are either limited to 2D measurements or not reaching to true 3D atomic-scale resolution, and single-atom level determination of the 3D surface atomic structure for general 3D nanomaterials still remains elusive. Here we demonstrate the measurement of 3D atomic structure at 15 pm precision using a Pt nanoparticle as a model system. Aided by a deep learning-based missing data retrieval combined with atomic electron tomography, the surface atomic structure was reliably measured. We found that <\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$100$$\end{document}100> and <\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$111$$\end{document}111> facets contribute differently to the surface strain, resulting in anisotropic strain distribution as well as compressive support boundary effect. The capability of single-atom level surface characterization will not only deepen our understanding of the functional properties of nanomaterials but also open a new door for fine tailoring of their performance.

Precise determination of surface atomic structure of metallic nanoparticles is key to unlock their surface/interface properties. Here the authors introduce a neural network-assisted atomic electron tomography approach that provides a three-dimensional reconstruction of metallic nanoparticles at individual atom level.

Three-Dimensional Nanoparticle Transformations Captured by an Electron Microscope

ConspectusThree-dimensional (3D) morphology and composition govern the properties of nanoparticles (NPs). However, due to their high surface-to-volume ratio, the morphology and composition of nanomaterials are not as static as those for their bulk counterparts. One major influence is the increase in relative contribution of surface diffusion, which underlines rapid reshaping of NPs in response to changes in their environment. If not accounted for, these effects might affect the robustness of prospective NPs in practically relevant conditions, such as elevated temperatures, intense light illumination, or changing chemical environments. In situ techniques are promising tools to study NP transformations under relevant conditions. Among those tools, in situ transmission electron microscopy (TEM) provides an elegant platform to directly visualize NP changes down to the atomic scale. By the use of specialized holders or microscopes, external stimuli, such as heat, or environments, such as gas and liquids, can be controllably introduced inside the TEM. In addition, TEM is also a valuable tool to determine NP transformations upon ex situ stimuli such as laser excitation. However, standard TEM yields two-dimensional (2D) projection images of 3D objects. With the growing complexity of NP shapes and compositions, the information that is obtained in this manner is often insufficient to understand intricate diffusion dynamics.In this Account, we describe recent progress on measuring NP transformations in 3D inside the electron microscope. First, we discuss existing possibilities to obtain 3D information using either tomographic methods or the so-called atom counting technique, which utilizes single projection images. Next, we show how these techniques can be combined with in situ holders to quantify diffusion processes on a single nanoparticle level. Specifically, we focus on anisotropic metal NPs at elevated temperatures and in varying gas environments. Anisotropic metal NPs are important for plasmonic applications, because sharp tips and edges result in strong electromagnetic field enhancements. By electron tomography, surface diffusion as well as elemental diffusion can be tracked in monometallic and bimetallic NPs, which can then be directly related to changes in plasmonic properties of these systems. By atom counting, it has furthermore become possible to monitor the evolution of crystalline facets of metal NPs under gas and heat treatments, a change that influences catalytic properties. Next to in situ processes, we also demonstrate the value of electron tomography to assess external laser-induced NP transformations, making it viable to detect structural changes with atomic resolution. The application of the proposed methodologies is by far not limited to metal nanoparticles. In the final section, we therefore outline future material research that can benefit from tracking NP transformations from 3D techniques.

Three-dimensional atomic structure of supported Au nanoparticles at high temperature

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.

Correlating 3D Surface Atomic Structure and Catalytic Activities of Pt Nanocrystals

Active sites and catalytic activity of heterogeneous catalysts is determined by their surface atomic structures. However, probing the surface structure at an atomic resolution is difficult, especially for solution ensembles of catalytic nanocrystals, which consist of heterogeneous particles with irregular shapes and surfaces. Here, we constructed 3D maps of the coordination number (CN) and generalized CN (CN_) for individual surface atoms of sub-3 nm Pt nanocrystals. Our results reveal that the synthesized Pt nanocrystals are enclosed by islands of atoms with nonuniform shapes that lead to complex surface structures, including a high ratio of low-coordination surface atoms, reduced domain size of low-index facets, and various types of exposed high-index facets. 3D maps of CN_ are directly correlated to catalytic activities assigned to individual surface atoms with distinct local coordination structures, which explains the origin of high catalytic performance of small Pt nanocrystals in important reactions such as oxygen reduction reactions and CO electro-oxidation.

Dynamic Surface Reconstruction of Single-Atom Bimetallic Alloy under Operando Electrochemical Conditions

The atomic-level understanding of the dynamic evolution of the surface structure of bimetallic nanoparticles under industrially relevant operando conditions provides a key guide for improving their catalytic performance. Here, we exploit operando X-ray absorption fine structure spectroscopy to determine the dynamic surface reconstruction of Cu/Au bimetallic alloy where single-atom Cu was embedded on the Au nanoparticle, under electrocatalytic conditions. We identify the migration of isolated Cu atoms from the vertex position of the Au nanoparticle to the stable (100) plane of the Au first atom layer, when the reduction potential is applied. Density functional theory calculations reveal that the surface atom migration would significantly modulate the Au electronic structure, thus serving as the real active site for the catalytic performance. These findings demonstrate the real structural change under electrochemical conditions and provide guidance for the rational design of high-activity bimetallic nanocatalysts.