Abstract: This dataset contains 1000 simulated nanoparticle-like 3D structures and noisy EDX-like elemental maps based on them. These data are intended to be used for quantitative analysis of data processing methods in (EDX) tomography of nanoparticles and training the data-driven approaches for these tasks. The dataset is structured as follows: voxel_data/clean 3D voxel grid representation of the simulated nanoparticles. Voxel intensities are adjusted so that the total intensity equals 103. All 3D structures have unique identifiers in 0..999 range. The data derived from a 3D structure preserves this unique identifier. sinograms/clean Tilt series of projection images obtained from the corresponding 3D structures over an angular range of -75..75 degrees with a tilt step of 10 degrees to simulate a typical tilt series used in EDX tomography. Total intensity in each projection image equals 103. sinograms/noisy Tilt series of projection images corrupted with Poisson noise and an additional spatially uniform background noise. projections/clean Projection images extracted from the clean tilt series at 0 degrees tilt angle. projections/noisy Projection images extracted from the noisy tilt series at 0 degrees tilt angle. images/clean Visualizations of the clean projections as PNG images with the intensity range adjusted to 0..255 images/noisy Visualizations of the noisy projections as PNG images with the intensity range adjusted to 0..255

Abstract: Metal halide perovskite (MHP) quantum dots (QDs) offer immense potential for several areas of photonics research due to their easy and low-cost fabrication and excellent optoelectronic properties. However, practical applications of MHP QDs are limited by their poor stability and, in particular, their tendency to aggregate. Here, we develop a two-step double-solvent strategy to grow and confine CsPbBr3 QDs within the three-dimensional (3D) cavities of a mesoporous SBA-16 silica scaffold (CsPbBr3@SBA-16). Strong confinement and separation of the MHP QDs lead to a relatively uniform size distribution, narrow luminescence, and good ambient stability over 2 months. In addition, the CsPbBr3@SBA-16 presents a high activity and stability for visible-light-driven photocatalytic toluene C(sp(3))-H bond activation to produce benzaldehyde with similar to 730 mu mol g(-1) h(-1) yield rate and near-unity selectivity. Similarly, the structural stability of CsPbBr3@SBA-16 QDs is superior to that of both pure CsPbBr3 QDs and those confined in MCM-41 with 1D channels.

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.

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

Abstract: In situ TEM is a valuable technique to offer novel insights in the behavior of nanomaterials under various conditions. However, interpretation of in situ experiments is not straightforward since the electron beam can impact the outcome of such measurements. For example, ligands surrounding metal nanoparticles transform into a protective carbon layer upon electron beam irradiation and may impact the apparent thermal stability during in situ heating experiments. In this work, we explore the effect of different treatments typically proposed to remove such ligands. We found that plasma treatment prior to heating experiments for Au nanorods and nanostars increased the apparent thermal stability of the nanoparticles, while an activated carbon treatment resulted in a decrease of the observed thermal stability. Treatment with HCl barely changed the experimental outcome. These results demonstrate the importance of carefully selecting pre-treatments procedures during in situ heating experiments.

Abstract: In this work, the magnetic properties of superparamagnetic iron oxide nanoparticles (SPIONs) submitted to an external magnetic field are studied using a Metropolis algorithm. The influence on the M(B) curves of the size distribution of the nanoparticles, of uniaxial anisotropy, and of dipolar interaction between the cores are examined, as well as the influence of drying the samples under a zero or non-zero magnetic field. It is shown that the anisotropy impacts the shape of the magnetization curves, which then deviate from a pure Langevin behaviour, whereas the dipolar interaction has no influence on the curves at 300 K for small particles (with a radius of 3 nm). The fitting of the magnetization curves of particles with magnetic anisotropy to a Langevin model (including a size distribution of the particles) can then lead to erroneous values of the distribution parameters. The simulation results are qualitatively compared to experimental results obtained for iron oxide nanoparticles (with a 3.21 nm median radius).

Abstract: Chiral ligands are considered a required ingredient during the synthesis of dissymmetric plasmonic metal nanocrystals. The mechanism behind the generation of chiral structures involves the formation of high Miller index chiral facets, induced by the adsorption of such chiral ligands. We found however that, chirality can also evolve spontaneously, without the involvement of any chiral ligands, during the co-deposition of Au and Ag on Au nanorods. When using a specific Au/Ag ratio, phase segregation of the two metals leads to an interface within the obtained AuAg shell, which can be exposed by removing the Ag component via oxidative etching. Although a close-to-racemic mixture of chiral Au nanorods with right and left handedness is found in solution, electron tomography analysis evidences left- and righthanded helicities, both at the Au-Ag interface and at the exposed surface of Au NRs after Ag etching. The helicity profile of the NRs indicates dominating inclination angles in a range from 30° to 60°. Single-particle optical characterization also reveals random handedness in the plasmonic response of individual nanorods. We hypothesize that, the origin of chirality is related with symmetry breaking during the co-deposition of Au and Ag, through an initial perturbation in a small region on the Au-Ag interface that eventually leads to chiral segregation throughout the nanocrystal.

Abstract: Sample holders for transmission electron microscopy (TEM) based on micro-electro-mechanical systems (MEMS) have recently become popular for investigating the behavior of nanomaterials under in situ or environmental conditions. The accuracy and reproducibility of these in situ holders are essential to ensure the reliability of experimental results. In addition, the uniformity of an applied temperature trigger across the MEMS chip is a crucial parameter. In this work, it is measured the temperature homogeneity of MEMS-based heating sample supports by locally analyzing the dynamics of heat-induced alloying of Au@Ag nanoparticles located in different regions of the support through quantitative fast high-angle annular dark-field scanning TEM tomography. These results demonstrate the superior temperature homogeneity of a microheater design based on a heating element shaped as a circular spiral with a width decreasing outwards compared to a double spiral-shaped designed microheater. The proposed approach to measure the local temperature homogeneity based on the thermal properties of bimetallic nanoparticles will support the future development of MEMS-based heating supports with improved thermal properties and in situ studies where high precision in the temperature at a certain position is required. This schematic delineates an approach to quantifying potential localized temperature deviation within a nanochip. Employing two comparable nanoparticles as thermal probes in discrete nanochip regions, the alloying kinetics of these nanoparticles are monitorable using in situ quantitative high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) tomography, thus enabling the precise estimation of local temperature deviations.image