Resolving the structure of active sites on platinum catalytic nanoparticles

Atomic-Scale 3D Structure of a Supported Pd Nanoparticle Revealed by Electron Tomography with Convolution Neural Network-Based Image Inpainting

Electron tomography based on scanning transmission electron microscopy (STEM) is used to analyze 3D structures of metal nanoparticles on the atomic scale. However, in the case of supported metal nanoparticle catalysts, the supporting material may interfere with the 3D reconstruction of metal nanoparticles. In this study, a deep learning-based image inpainting method is applied to high-angle annular dark field (HAADF)-STEM images of a supported metal nanoparticle to predict and remove the background image of the support. The inpainting method can separate an 11 nm Pd nanoparticle from the θ-Al2O3 support in HAADF-STEM images of the θ-Al2O3-supported Pd catalyst. 3D reconstruction of the extracted images of the Pd nanoparticle reveals that the Pd nanoparticle adopts a deformed structure of the cuboctahedron model particle, resulting in high index surfaces, which account for the high catalytic activity for methane combustion. Using the xyz coordinate of each Pd atom, the local Pd-Pd bond distance and its variance in a real supported Pd nanoparticle are visualized, showing large strain and disorder at the Pd-Al2O3 interface. The results demonstrate that 3D atomic-scale analysis enables atomic structure-based understanding and design of supported metal catalysts.

Catalyst Supraparticles: Tuning the Structure of Spray-Dried Pt/SiO2 Supraparticles via Salt-Based Colloidal Manipulation to Control their Catalytic Performance

The structure of supraparticles (SPs) is a key parameter for achieving advanced functionalities arising from the combination of different nanoparticle (NP) types in one hierarchical entity. However, whenever a droplet-assisted forced assembly approach is used, e.g., spray-drying, the achievable structure is limited by the inherent drying phenomena of the method. In particular, mixed NP dispersions of differently sized colloids are heavily affected by segregation during the assembly. Herein, the influence of the colloidal arrangement of Pt and SiO2 NPs within a single supraparticulate entity is investigated. A salt-based electrostatic manipulation approach of the utilized NPs is proposed to customize the structure of spray-dried Pt/SiO2 SPs. By this, size-dependent separation phenomena of NPs during solvent evaporation, that limit the catalytic performance in the reduction of 4-nitrophenol, are overcome by achieving even Pt NP distribution. Additionally, the textural properties (pore size and distribution) of the SiO2 pore framework are altered to improve the mass transfer within the material leading to increased catalytic activity. The suggested strategy demonstrates a powerful, material-independent, and universally applicable approach to deliberately customize the structure and functionality of multi-component SP systems. This opens up new ways of colloidal material combinations and structural designs in droplet-assisted forced assembly approaches like spray-drying.

Size-dependent shape distributions of platinum nanoparticles

While it is well established that nanoparticle shape can depend on equilibrium thermodynamics or growth kinetics, recent computational work has suggested the importance of thermal energy in controlling the distribution of shapes in populations of nanoparticles. Here, we used transmission electron microscopy to characterize the shapes of bare platinum nanoparticles and observed a strong dependence of shape distribution on particle size. Specifically, the smallest nanoparticles (<2.5 nm) had a truncated octahedral shape, bound by 〈111〉 and 〈100〉 facets, as predicted by lowest-energy thermodynamics. However, as particle size increased, the higher-energy 〈110〉 facets became increasingly common, leading to a large population of non-equilibrium truncated cuboctahedra. The observed trends were explained by combining atomistic simulations (both molecular dynamics and an empirical square-root bond-cutting model) with Boltzmann statistics. Overall, this study demonstrates experimentally how thermal energy leads to shape variation in populations of metal nanoparticles, and reveals the dependence of shape distributions on particle size. The prevalence of non-equilibrium facets has implications for metal nanoparticles applications from catalysis to solar energy.

Metrology of convex-shaped nanoparticles via soft classification machine learning of TEM images

The shape of nanoparticles is a key performance parameter for many applications, ranging from nanophotonics to nanomedicines. However, the unavoidable shape variations, which occur even in precision-controlled laboratory synthesis, can significantly impact on the interpretation and reproducibility of nanoparticle performance. Here we have developed an unsupervised, soft classification machine learning method to perform metrology of convex-shaped nanoparticles from transmission electron microscopy images. Unlike the existing methods, which are based on hard classification, soft classification provides significantly greater flexibility in being able to classify both distinct shapes, as well as non-distinct shapes where hard classification fails to provide meaningful results. We demonstrate the robustness of our method on a range of nanoparticle systems, from laboratory-scale to mass-produced synthesis. Our results establish that the method can provide quantitative, accurate, and meaningful metrology of nanoparticle ensembles, even for ensembles entailing a continuum of (possibly irregular) shapes. Such information is critical for achieving particle synthesis control, and, more importantly, for gaining deeper understanding of shape-dependent nanoscale phenomena. Lastly, we also present a method, which we coin the "binary DoG", which achieves significant progress on the challenging problem of identifying the shapes of aggregated nanoparticles.

Correlating Surface Structures and Electrochemical Activity Using Shape-Controlled Single-Pt Nanoparticles

We report a method for synthesizing and studying shape-controlled, single Pt nanoparticles (NPs) supported on carbon nanoelectrodes. The key advance is that the synthetic method makes it possible to produce single, electrochemically active NPs with a vast range of crystal structures and sizes. Equally important, the NPs can be fully characterized, and, therefore, the electrochemical properties of the NPs can be directly correlated to the size and structure of a single shape. This makes it possible to directly correlate experimental results to first-principles theory. Because just one well-characterized NP is analyzed at a time, the difficulty of applying a theoretical analysis to an ensemble of NPs having different sizes and structures is avoided. In this article, we report on two specific Pt NP shapes having sizes on the order of 200 nm: concave hexoctahedral (HOH) and concave trapezohedral (TPH). The former has {15 6 1} facets and the latter {10 1 1} facets. The electrochemical properties of these single NPs for the formic acid oxidation (FAO) reaction are compared to those of a single, spherical polycrystalline Pt NP of the same size. Finally, density functional theory, performed prior to the electrochemical studies, were used to interpret the experimental results of the FAO experiments.

Statistically Representative Metrology of Nanoparticles via Unsupervised Machine Learning of TEM Images

The morphology of nanoparticles governs their properties for a range of important applications. Thus, the ability to statistically correlate this key particle performance parameter is paramount in achieving accurate control of nanoparticle properties. Among several effective techniques for morphological characterization of nanoparticles, transmission electron microscopy (TEM) can provide a direct, accurate characterization of the details of nanoparticle structures and morphology at atomic resolution. However, manually analyzing a large number of TEM images is laborious. In this work, we demonstrate an efficient, robust and highly automated unsupervised machine learning method for the metrology of nanoparticle systems based on TEM images. Our method not only can achieve statistically significant analysis, but it is also robust against variable image quality, imaging modalities, and particle dispersions. The ability to efficiently gain statistically significant particle metrology is critical in advancing precise particle synthesis and accurate property control.

Exsolution of Embedded Nanoparticles in Defect Engineered Perovskite Layers

Exsolution phenomena are highly debated as efficient synthesis routes for nanostructured composite electrode materials for the application in solid oxide cells (SOCs) and the development of next-generation electrochemical devices for energy conversion. Utilizing the instability of perovskite oxides, doped with electrocatalytically active elements, highly dispersed nanoparticles can be prepared at the perovskite surface under the influence of a reducing heat treatment. For the systematic study of the mechanistic processes governing metal exsolution, epitaxial SrTi_0.9Nb_0.05Ni_0.05O_3-δ thin films of well-defined stoichiometry are synthesized and employed as model systems to investigate the interplay of defect structures and exsolution behavior. Spontaneous phase separation and the formation of dopant-rich features in the as-synthesized thin film material is revealed by high-resolution transmission electron microscopy (HR-TEM) investigations. The resulting nanostructures are enriched by nickel and serve as preformed nuclei for the subsequent exsolution process under reducing conditions, which reflects a so far unconsidered process drastically affecting the understanding of nanoparticle exsolution phenomena. Using an approach of combined morphological, chemical, and structural analysis of the exsolution response, a limitation of the exsolution dynamics for nonstoichiometric thin films is found to be correlated to a distortion of the perovskite host lattice. Consequently, the incorporation of defect structures results in a reduced particle density at the perovskite surface, presumably by trapping of nanoparticles in the oxide bulk.

The pure and representative types of disordered platinum nanoparticles from machine learning

The development of interpretable structure/property relationships is a cornerstone of nanoscience, but can be challenging when the structural diversity and complexity exceeds our ability to characterise it. This is often the case for imperfect, disordered and amorphous nanoparticles, where even the nomenclature can be unspecific. Disordered platinum nanoparticles have exhibited superior performance for some reactions, which makes a systematic way of describing them highly desirable. In this study we have used a diverse set of disorder platinum nanoparticles and machine learning to identify the pure and representative structures based on their similarity in 121 dimensions. We identify two prototypes that are representative of separable classes, and seven archetypes that are the pure structures on the convex hull with which all other possibilities can be described. Together these nine nanoparticles can explain all of the variance in the set, and can be described as either single crystal, twinned, spherical or branched; with or without roughened surfaces. This forms a robust sub-set of platinum nanoparticle upon which to base further work, and provides a theoretical basis for discussing structure/property relationships of platinum nanoparticles that are not geometrically ideal.

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.

Versatile Homebuilt Gas Feed and Analysis System for Operando TEM of Catalysts at Work

Understanding how catalysts work during chemical reactions is crucial when developing efficient catalytic materials. The dynamic processes involved are extremely sensitive to changes in pressure, gas environment and temperature. Hence, there is a need for spatially resolved operando techniques to investigate catalysts under working conditions and over time. The use of dedicated operando techniques with added detection of catalytic conversion presents a unique opportunity to study the mechanisms underlying the catalytic reactions systematically. Herein, we report on the detailed setup and technical capabilities of a modular, homebuilt gas feed system directly coupled to a quadrupole mass spectrometer, which allows for operando transmission electron microscopy (TEM) studies of heterogeneous catalysts. The setup is compatible with conventional, commercially available gas cell TEM holders, making it widely accessible and reproducible by the community. In addition, the operando functionality of the setup was tested using CO oxidation over Pt nanoparticles.

The structure of gold nanoparticles: molecular dynamics modeling and its verification by X-ray diffraction

Noble metal nanoparticles exhibit unique physical, chemical, biomedical, catalytic and optical properties. Understanding these properties and further development of production methods entail detailed knowledge of the structure at the atomic scale. Gold nanoparticles with multimodal size distribution were synthesized on porous silica and their atomic scale structure was studied by X-ray diffraction. The obtained experimental data are compared with molecular dynamics simulations. Spherical models of the Au nanoparticles, defined by ensembles of the Cartesian coordinates of constituent atoms, were generated and their geometry was optimized by applying theLAMMPSsoftware. The comparison was performed in both reciprocal and real space. A good agreement is achieved for the models with disorder that can be related to surface relaxation effects and vacancy defects. The approach adopted here may have wider applications for further structural studies of other nanomaterials, offering direct verification of simulation results by experiment.

Dislocation Engineered PtPdMo Alloy With Enhanced Antioxidant Activity for Intestinal Injury

Radiotherapy is the mainstay for abdomen and pelvis cancers treatment. However, high energy ray would inflict gastrointestinal (GI) system and adversely disrupt the treatment. The anti-oxidative agents provide a potential route for protecting body from radiation-induced injuries. Herein, highly catalytic nanocubes with dislocation structure are developed for treatment of intestinal injury. Structural and catalytic properties show that Mo incorporation can enhance antioxidant activity by dislocation structure in the alloy. In vitro studies showed that PtPdMo improved cell survival by scavenging radiation-induced ROS accumulation. Furthermore, after animals were exposed to lethal dose of radiation, the survival was increased by 50% with the PtPdMo i.p. treatment. Radioprotection mechanism revealed that PtPdMo alleviated the oxidative stress in multi-organs especially the small intestine by inhibiting intestinal epithelium apoptosis, reducing DNA strands breaks and enhancing repairing ability. In addition, PtPdMo protected hematopoietic system by improving the number of bone marrow and peripheral blood cells.

Reverse Monte Carlo modeling for low-dimensional systems

Reverse Monte Carlo (RMC) is one of the commonly used approaches for modeling total scattering data. However, to extend the capability of the RMC method for refining the structure of nanomaterials, the dimensionality and finite size need to be considered when calculating the pair distribution function (PDF). To achieve this, the simulation box must be set up to remove the periodic boundary condition in one, two or three of the dimensions. This then requires a correction to be applied for the difference in number density between the real system and the simulation box. In certain circumstances an analytical correction for the uncorrelated pairings of atoms is also applied. The validity and applicability of our methodology is demonstrated by applying the algorithms to simulate the PDF patterns of carbon systems with various dimensions, and also by using them to fit experimental data of CuO nanoparticles. This alternative approach for characterizing the local structure of nano-systems with the total scattering technique will be made available via the RMCProfile package. The theoretical formulation and detailed explanation of the analytical corrections for low-dimensional systems – 2D nanosheets, 1D nanowires and 0D nanoparticles – is also given.

Predicting archetypal nanoparticle shapes using a combination of thermodynamic theory and machine learning

Machine learning is a useful way of identifying representative or pure nanoparticle shapes as part of a larger ensemble, but its predictive capabilities can be limited when a large dataset of candidate structures must already exist. Ideally one would like to use machine learning to define the ideal dataset for future, more computationally intensive, studies before a significant amount of resources are consumed. In this work we combine an established analytical phenomenological model and statistical machine learning to predict the archetypes and prototypes of a diverse ensemble of 2380 platinum nanoparticle morphologies developed with less than twenty input electronic structure simulations. By parameterising a size- and shape-dependent thermodynamic model, probabilities are assigned to seventeen different shapes between three and thirty nanometres, which together with structural features such as nanoparticle diameter, surface area, sphericity and facet configuration form the basis for archetypal analysis and K-means clustering. Using this approach we rapidly identify six "pure" archetypes and twelve "representative" prototypes that can be used in future computational studies of properties such as catalysis.

Improving the engine power of a catalytic Janus-sphere micromotor by roughening its surface

Microspheres with catalytic caps have become a popular model system for studying self-propelled colloids. Existing experimental studies involve predominantly "smooth" particle surfaces. In this study we determine the effect of irregular surface deformations on the propulsive mechanism with a particular focus on speed. The particle surfaces of polymer microspheres were deformed prior to depositing a layer of platinum which resulted in the formation of nanoscopic pillars of catalyst. Self-propulsion was induced upon exposure of the micromotors to hydrogen peroxide, whilst they were dispersed in water. The topological surface features were shown to boost speed (~2×) when the underlying deformations are small (nanoscale), whilst large deformations afforded little difference despite a substantial apparent catalytic surface area. Colloids with deformed surfaces were more likely to display a mixture of rotational and translational propulsion than their "smooth" counterparts.

Paracrystalline structure of gold, silver, palladium and platinum nanoparticles

Metallic nanoparticles are of great importance because of their unique physical, chemical, antimicrobial, diagnostic, therapeutic, biomedical, sensing, biosensing, catalytic and optical properties. Detailed knowledge of the atomic scale structure of these materials is essential for understanding their activities and for exploiting their potential. This paper reports structural studies of silica-supported silver, gold, palladium and platinum nanoparticles using X-ray diffraction and high-resolution transmission electron microscopy. Electron microscopy observation allowed the determination of nanoparticle sizes, which were estimated to be in the range of 45–470 Å, and their distribution. The obtained histograms exhibit a multimodal distribution of the investigated nanoparticle sizes. The X-ray diffraction data were analyzed using the Rietveld method in the form of Williamson–Hall plots, thePDFguifitting procedure and model-based simulation. The Williamson–Hall plots provide evidence for the presence of strain in all investigated samples. ThePDFguifitting results indicate that the investigated nanoparticles consist of atomic clusters with different sizes and degrees of disorder as well as slightly different lattice parameters. The detailed structural characterization performedviamodel-based simulations proves that all samples exhibit a face-centered cubic type structure with paracrystalline distortion. The degree of disorder predicted by the paracrystalline theory is correlated with the sizes of the nanoparticles. The catalytic properties of the investigated noble metals are discussed in relation to their disordered structure.

Crystallographic orientation of facets and planar defects in functional nanostructures elucidated by nano-focused coherent diffractive X-ray imaging

The physical and chemical properties of nanostructures depend on their surface facets. Here, we exploit a pole figure approach to determine the three-dimensional orientation matrix of a nanostructure from a single Bragg reflection measured with a coherent nano-focused X-ray beam. The signature of any truncated (faceted) crystal produces a crystal truncation rod, which corresponds to a streak of intensity in reciprocal space normal to the surface. When two or more non-parallel facets are present, both the crystal orientation and the crystal facets can be identified. This enables facets to be rapidly indexed and uncommon facets, and planar defects, that have been difficult to study before to be identified. We demonstrate the technique with (i) epitaxial core-shell InGaN/GaN multiple quantum-wells grown on GaN nanowires, where surface facets and planar defects are determined, and (ii) single randomly oriented highly faceted tetrahedrahexal Pt nanoparticles. The methodology is applicable to a broad range of nanocrystals and provides a unique insight into the connection between structure and properties of nanomaterials.

Three-dimensional atomic models from a single projection using Z-contrast imaging: verification by electron tomography and opportunities

In order to fully exploit structure-property relations of nanomaterials, three-dimensional (3D) characterization at the atomic scale is often required. In recent years, the resolution of electron tomography has reached the atomic scale. However, such tomography typically requires several projection images demanding substantial electron dose. A newly developed alternative circumvents this by counting the number of atoms across a single projection. These atom counts can be used to create an initial atomic model with which an energy minimization can be applied to obtain a relaxed 3D reconstruction of the nanoparticle. Here, we compare, at the atomic scale, this single projection reconstruction approach with tomography and find an excellent agreement. This new approach allows for the characterization of beam-sensitive materials or where the acquisition of a tilt series is impossible. As an example, the utility is illustrated by the 3D atomic scale characterization of a nanodumbbell on an in situ heating holder of limited tilt range.

Beamstop-based low-background ptychography to image weakly scattering objects

In recent years, X-ray ptychography has been established as a valuable tool for high-resolution imaging. Nevertheless, the spatial resolution and sensitivity in coherent diffraction imaging are limited by the signal that is detected over noise and over background scattering. Especially, coherent imaging of weakly scattering specimens suffers from incoherent background that is generated by the interaction of the central beam with matter along its propagation path in particular close to and inside of the detector. Common countermeasures entail evacuated flight tubes or detector-side beamstops, which improve the experimental setup in terms of background reduction or better coverage of high dynamic range in the diffraction patterns. Here, we discuss an alternative approach: we combine two ptychographic scans with and without beamstop and reconstruct them simultaneously taking advantage of the complementary information contained in the two scans. We experimentally demonstrate the potential of this scheme for hard X-ray ptychography by imaging a weakly scattering object composed of catalytic nanoparticles and provide the analysis of the signal-to-background ratio in the diffraction patterns.

Capturing Solvation Effects at a Liquid/Nanoparticle Interface by Ab Initio Molecular Dynamics: Pt201 Immersed in Water

Solvation can substantially modify the adsorption properties of heterogeneous catalysts. Although essential for achieving realistic theoretical models, assessing such solvent effects over nanoparticles is challenging from a computational standpoint due to the complexity of those liquid/metal interfaces. This effect is investigated by ab initio molecular dynamics simulations at 350 K of a large platinum nanoparticle immersed in liquid water. The first solvation layer contains twice as much physisorbed water molecules above the terraces, than chemisorbed ones located only at edges and corners. The solvent stabilizes the binding energy of chemisorbates: 66% of the total gain comes from interactions with physisorbed molecules and 34% from the influence of bulk liquid.

Strain Field in Ultrasmall Gold Nanoparticles Supported on Cerium-Based Mixed Oxides. Key Influence of the Support Redox State

Using a method that combines experimental and simulated Aberration-Corrected High Resolution Electron Microscopy images with digital image processing and structure modeling, strain distribution maps within gold nanoparticles relevant to real powder type catalysts, i.e., smaller than 3 nm, and supported on a ceria-based mixed oxide have been determined. The influence of the reduction state of the support and particle size has been examined. In this respect, it has been proven that reduction even at low temperatures induces a much larger compressive strain on the first {111} planes at the interface. This increase in compression fully explains, in accordance with previous DFT calculations, the loss of CO adsorption capacity of the interface area previously reported for Au supported on ceria-based oxides.

Structure and morphology of shape-controlled Pd nanocrystals

Pd nanocrystals were produced with uniform truncated-cube shape and a narrow size distribution, yielding controlled surface area fractions from low Miller index ({100}, {110}, {111}) crystalline facets. Details on the structure and morphology of the nanocrystals were obtained by combining X-ray powder diffraction line profile analysis, high-resolution transmission electron microscopy and surface electrochemistry based on Cu underpotential deposition.

Porous single-crystalline palladium nanoflowers with enriched {100} facets for highly enhanced ethanol oxidation

Palladium porous single-crystalline nanoflowers (PSNFs) with enriched high catalytic activity {100} facets were synthesized using a mild and controllable seed mediated growth method. The growth mechanism of the Pd PSNFs was investigated using time dependent morphology evolution through TEM imaging. Due to the specific structure, Pd PSNFs show highly enhanced ethanol oxidation reaction (EOR) activity, high EOR anti-poisoning and stability, much better than Pd nanocubes, {111} facets dominated dendritic urchin-like Pd nanoparticles and Pd black.

Clarifying stability, probability and population in nanoparticle ensembles

Though theoretical and computational studies typically agree on the low energy, equilibrium structure of metallic nanoparticles, experimental studies report on samples with a distribution of shapes; including high-index, non-equilibrium morphologies. This apparent inconsistency is not due to inaccuracy on either side, nor the result of unquantifiable competition between thermodynamic and kinetic influences, but rather a lack of clarity about what is being inferred. The thermodynamic stability, statistical probability, and the observed population of a given structure are all straightforward to determine, provided an ensemble of possible configurations is included at the outset. To clarify this relationship, a combination of electronic structure simulations and mathematical models will be used to predict the relative stabilities, probability and population of various shapes of Ag, Au, Pd and Pt nanoparticles, and provide some explanation for the observation of high-index, non-equilibrium morphologies. As we will see, a nanoparticle can be in the ground-state, and therefore most thermodynamically stable, but can still be in the minority.

A power-transformed-and-managed triboelectric nanogenerator and its applications in a self-powered wireless sensing node

A power-transformed-and-managed triboelectric nanogenerator (PTM-TENG) is invented that is intended to give regulated power output for driving electronics. The design is based on a synchronized mechanical agitation that not only drives the TENG but also switches the connections for the capacitors for lowering the output voltage and increasing the output charges. An energy preservation efficiency of >95% was demonstrated. The PTM-TENG not only detected the external mechanical triggering action but also generated enough power for sending out an infrared signal.

Selecting the swimming mechanisms of colloidal particles: bubble propulsion versus self-diffusiophoresis

Bubble propulsion and self-diffusiophoresis are two common mechanisms that can drive autonomous motion of microparticles in hydrogen peroxide. Although microtubular particles, when coated with platinum in their interior concave surfaces, can propel due to the formation and release of bubbles from one end, the convex Janus particles usually do not generate any visible bubble. They move primarily due to the self-diffusiophoresis. Coincidentally, the platinum films on those particles were typically coated by physical evaporation. In this paper, we use a simple chemical deposition method to make platinum-polystyrene Janus dimers. Surprisingly, those particles are propelled by periodic growth and collapse of bubbles on the platinum-coated lobes. We find that both high catalytic activity and rough surface are necessary to change the propulsion mode from self-diffusiophoresis to bubble propulsion. Our Janus dimers, with combined geometric and interfacial anisotropy, also exhibit distinctive motions at the respective stages of bubble growth and collapse, which differ by 5-6 orders of magnitude in time. Our study not only provides insight into the link between self-diffusiophoresis and bubble propulsion but also reveals the intriguing impacts of the combined geometric and interfacial anisotropy on self-propulsion of particles.

Porous dendritic platinum nanotubes with extremely high activity and stability for oxygen reduction reaction

Controlling the morphology of Pt nanostructures can provide opportunities to greatly increase their activity and stability. Porous dendritic Pt nanotubes were successfully synthesized by a facile, cost-effective aqueous solution method at room temperature in large scale. These unique structures are porous, hollow, hierarchical, and single crystalline, which not only gives them a large surface area with high catalyst utilization, but also improves mass transport and gas diffusion. These novel Pt structures exhibited significantly improved catalytic activity (4.4 fold) for oxygen reduction reaction (ORR) and greatly enhanced durability (6.1 fold) over that of the state-of-the-art commercial Pt/C catalyst. This work provides a promising approach to the design of highly efficient next-generation electrocatalysts.

A (S)TEM gas cell holder with localized laser heating for in situ experiments

The advent of aberration correction for transmission electron microscopy has transformed atomic resolution imaging into a nearly routine technique for structural analysis. Now an emerging frontier in electron microscopy is the development of in situ capabilities to observe reactions at atomic resolution in real time and within realistic environments. Here we present a new in situ gas cell holder that is designed for compatibility with a wide variety of sample type (i.e., dimpled 3-mm discs, standard mesh grids, various types of focused ion beam lamellae attached to half grids). Its capabilities include localized heating and precise control of the gas pressure and composition while simultaneously allowing atomic resolution imaging at ambient pressure. The results show that 0.25-nm lattice fringes are directly visible for nanoparticles imaged at ambient pressure with gas path lengths up to 20 μm. Additionally, we quantitatively demonstrate that while the attainable contrast and resolution decrease with increasing pressure and gas path length, resolutions better than 0.2 nm should be accessible at ambient pressure with gas path lengths less than the 15 μm utilized for these experiments.

Advanced electron microscopy for advanced materials

The idea of this Review is to introduce newly developed possibilities of advanced electron microscopy to the materials science community. Over the last decade, electron microscopy has evolved into a full analytical tool, able to provide atomic scale information on the position, nature, and even the valency atoms. This information is classically obtained in two dimensions (2D), but can now also be obtained in 3D. We show examples of applications in the field of nanoparticles and interfaces.

Atomic-scale determination of surface facets in gold nanorods

It is widely accepted that the physical properties of nanostructures depend on the type of surface facets. For Au nanorods, the surface facets have a major influence on crucial effects such as reactivity and ligand adsorption and there has been controversy regarding facet indexing. Aberration-corrected electron microscopy is the ideal technique to study the atomic structure of nanomaterials. However, these images correspond to two-dimensional (2D) projections of 3D nano-objects, leading to an incomplete characterization. Recently, much progress was achieved in the field of atomic-resolution electron tomography, but it is still far from being a routinely used technique. Here we propose a methodology to measure the 3D atomic structure of free-standing nanoparticles, which we apply to characterize the surface facets of Au nanorods. This methodology is applicable to a broad range of nanocrystals, leading to unique insights concerning the connection between the structure and properties of nanostructures.

Capping ligands as selectivity switchers in hydrogenation reactions

We systematically investigated the role of surface modification of nanoparticles catalyst in alkyne hydrogenation reactions and proposed the general explanation of effect of surface ligands on the selectivity and activity of Pt and Co/Pt nanoparticles (NPs) using experimental and computational approaches. We show that the proper balance between adsorption energetics of alkenes at the surface of NPs as compared to that of capping ligands defines the selectivity of the nanocatalyst for alkene in alkyne hydrogenation reaction. We report that addition of primary alkylamines to Pt and CoPt(3) NPs can drastically increase selectivity for alkene from 0 to more than 90% with ~99.9% conversion. Increasing the primary alkylamine coverage on the NP surface leads to the decrease in the binding energy of octenes and eventual competition between octene and primary alkylamines for adsorption sites. At sufficiently high coverage of catalysts with primary alkylamine, the alkylamines win, which prevents further hydrogenation of alkenes into alkanes. Primary amines with different lengths of carbon chains have similar adsorption energies at the surface of catalysts and, consequently, the same effect on selectivity. When the adsorption energy of capping ligands at the catalytic surface is lower than adsorption energy of alkenes, the ligands do not affect the selectivity of hydrogenation of alkyne to alkene. On the other hand, capping ligands with adsorption energies at the catalytic surface higher than that of alkyne reduce its activity resulting in low conversion of alkynes.