Managing dose-, damage- and data-rates in multi-frame spectrum-imaging

As an instrument, the scanning transmission electron microscope is unique in being able to simultaneously explore both local structural and chemical variations in materials at the atomic scale. This is made possible as both types of data are acquired serially, originating simultaneously from sample interactions with a sharply focused electron probe. Unfortunately, such scanned data can be distorted by environmental factors, though recently fast-scanned multi-frame imaging approaches have been shown to mitigate these effects. Here, we demonstrate the same approach but optimized for spectroscopic data; we offer some perspectives on the new potential of multi-frame spectrum-imaging (MFSI) and show how dose-sharing approaches can reduce sample damage, improve crystallographic fidelity, increase data signal-to-noise, or maximize usable field of view. Further, we discuss the potential issue of excessive data-rates in MFSI, and demonstrate a file-compression approach to significantly reduce data storage and transmission burdens

Targeted T1 Magnetic Resonance Imaging Contrast Enhancement with Extraordinarily Small CoFe2O4 Nanoparticles

Extraordinarily small (2.4 nm) cobalt ferrite nanoparticles (ESCIoNs) were synthesized by a one-pot thermal decomposition approach to study their potential as magnetic resonance imaging (MRI) contrast agents. Fine size control was achieved using oleylamine alone, and annular dark-field scanning transmission electron microscopy revealed highly crystalline cubic spinel particles with atomic resolution. Ligand exchange with dimercaptosuccinic acid rendered the particles stable in physiological conditions with a hydrodynamic diameter of 12 nm. The particles displayed superparamagnetic properties and a low r2/r1 ratio suitable for a T1 contrast agent. The particles were functionalized with bile acid, which improved biocompatibility by significant reduction of reactive oxygen species generation and is a first step toward liver-targeted T1 MRI. Our study demonstrates the potential of ESCIoNs as T1 MRI contrast agents

Quantitative structural and compositional studies of catalyst nanoparticles using imaging and spectroscopy in STEM

The thesis aims to develop methods to explore how catalyst structure and composition affect catalytic performance of nanoparticles used in Proton Exchange Membrane Fuel Cell (PEMFC)applications. Using Scanning Transmission Electron Microscopy (STEM), the structure and composition of Pt and Pt-Co catalysts are explored with the intent of designing better catalysts. Catalysts such as pure Pt and alloyed Pt-Co ensembles are hugely popular in the PEMFC industry due to their catalytic activity and stability. Out of the two ensembles, the bimetallic Pt-Co catalysts exhibit better performance and are cheaper to manufacture. The addition of a secondary element reduces the overall Pt loading making the catalyst cheaper. Introducing a secondary alloy also results in enhanced catalytic activity for reasons not well explained. To study the effects of enhanced activity, a thorough characterisation at the atomic scale is required. This means studying a catalystâs size, shape, strain and composition simultaneously, at high throughput, and linking this to catalytic activity. Full characterisation of this detail is challenging, but not impossible. Using STEM, it is possible to obtain catalyst size, shape, strain and composition simultaneously. However due to the nature of the technique is it challenging to characterise industrially relevant materials at high throughput. This thesis develops upon current methods for characterising nanoparticles in STEM to obtain nanoparticle size, shape, strain and composition at high throughput. In STEM, the size, shape and strain information is obtained from the Annular Dark Field (ADF) signal, whereas the composition information is obtained from Energy Dispersive X-ray Spectroscopy (EDS) and Electron Energy Loss Spectroscopy (EELS). One of the challenges is combining the information from ADF, EDS and EELS signals into one quantifiable unit and building an analysis framework for catalyst nanoparticles. This can be achieved by converting the measured STEM signal into scattering cross-sections. The scattering cross-section describes the effective area corresponding to the probability of scattering from a sample. With careful microscope calibration, the scattering cross-section can be converted to number of atoms. Atom counts from the STEM signals provide the structure and composition information from a nanoparticle. The thesis will explore the minimum requirements needed to develop new automated methods to characterise structure and composition of nanoparticles using scattering cross-sections at high throughput. In addition, limitations and capabilities of current hardware and software are explored. The three-dimensional models obtained from the quantitative analysis can be used as inputs for Density Functional Theory (DFT) simulations to understand molecule adsorption mechanics better. Combining high throughput technique development, STEM quantification and high scale DFT simulation together unlocks a detailed insight in understanding catalyst activity. Such detailed description of a system is the stepping stone towards reducing cost and time for better catalyst design.</p

Azetidinium as Cation in Lead Mixed Halide Perovskite Nanocrystals of Optoelectronic Quality

The dataset is part of the research work submitted for publication titled "Azetidinium as Cation in Lead Mixed Halide Perovskite Nanocrystals of Optoelectronic Quality

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

We propose a new method to measure atomic scale dynamics of nanoparticles from experimental high-resolution annular dark field scanning transmission electron microscopy images. By using the socalled hidden Markov model, which explicitly models the possibility of structural changes, the number of atoms in each atomic column can be quantified over time. This newly proposed method outperforms the current atom-counting procedure and enables the determination of the probabilities and cross sections for surface diffusion. This method is therefore of great importance for revealing and quantifying the atomic structure when it evolves over time via adatom dynamics, surface diffusion, beam effects, or during in situ experiments

Measuring dynamic structural changes of nanoparticles at the atomic scale using scanning transmission electron microscopy

We propose a new method to measure atomic scale dynamics of nanoparticles from experimental high-resolution annular dark field scanning transmission electron microscopy images. By using the so-called hidden Markov model, which explicitly models the possibility of structural changes, the number of atoms in each atomic column can be quantified over time. This newly proposed method outperforms the current atom-counting procedure and enables the determination of the probabilities and cross sections for surface diffusion. This method is therefore of great importance for revealing and quantifying the atomic structure when it evolves over time via adatom dynamics, surface diffusion, beam effects, or during in situ experiments

Predicting the oxygen-binding properties of platinum nanoparticle ensembles by combining high-precision electron microscopy and density functional theory

Many studies of heterogeneous catalysis, both experimental and computational, make use of idealized structures such as extended surfaces or regular polyhedral nanoparticles. This simplification neglects the morphologicaldiversity in real commercial oxygen reduction reaction (ORR) catalysts used infuel-cell cathodes. Here we introduce an approach that combines 3Dnanoparticle structures obtained from high-throughput high-precision electronmicroscopy with density functional theory. Discrepancies between experimentalobservations and cuboctahedral/truncated-octahedral particles are revealed anddiscussed using a range of widely used descriptors, such as electron-density, d-band centers, and generalized coordination numbers. We use this new approach to determine the optimum particle size for which both detrimental surface roughness and particle shape effects are minimized

Quantifying a heterogeneous Ru catalyst on carbon black using ADF STEM

Ru catalysts are part of a set of late transition metal nanocatalysts that have garnered much interest for catalytic applications such as ammonia synthesis and fuel cell production. Their performance varies greatly depending on their morphology and size, these catalysts are widely studied using electron microscopy. Using recent developments in Annular Dark Field (ADF) Scanning Transmission Electron Microscopy (STEM) quantification techniques, a rapid atom counting procedure was utilized to document the evolution of a heterogeneous Ru catalyst supported on carbon black. Areas of the catalyst were imaged for approximately 15 minutes using ADF STEM. When the Ru clusters were exposed to the electron beam, the clusters changed phase from amorphous to crystalline. To quantify the thickness of the crystalline clusters, two techniques were applied (simulation and statistical decomposition) and compared. These techniques show that stable face centred cubic crystal structures in the form of rafts, between 2 and 8 atoms thick, were formed after the initial wetting of the carbon support

Strain effects in core-shell PtCo nanoparticles: a comparison of experimental observations and computational modelling

Strain in Pt nanoalloys induced by the secondary metal has long been suggested as a major contributor to the modification of catalytic properties. Here, we investigate strain in PtCo nanoparticles using a combination of computational modelling and microscopy experiments. We have used a combination of molecular dynamics (MD) and large-scale density functional theory (DFT) for our models, alongside experimental work using annular dark field scanning transmission electron microscopy (ADF-STEM). We have performed extensive validation of the interatomic potential against DFT using a Pt568Co18 nanoparticle. Modelling gives access to 3 dimensional structures that can be compared to the 2D ADF-STEM images, which we use to build an understanding of nanoparticle structure and composition. Strain has been measured for PtCo and pure Pt nanoparticles, with MD annealed models compared to ADF-STEM images. Our analysis was performed on a layer by layer basis, where distinct trends between the Pt and PtCo alloy nanoparticles are observed. To our knowledge, we show for the first time a way in which detailed atomistic simulations can be used to augment and help interpret the results of ADF-STEM strain mapping experiments, which will enhance their use in characterisation towards the development of improved catalysts