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: Scaling down the size of transistors has been a trend for several decades which has led to improved transistor performance, increased transistor density and hence the overall computation power of IC chips. The trend slowed in recent years due to reliability and power consumption issues at the nanoscale. Hence strain is introduced into transistor channels that has beneficial effects on improving the mobility of charge carriers, providing an alternative pathway for enhancing transistor performance. Therefore, monitoring strain is vital for the semiconductor industry. With the recent trend of decreasing device dimensions (FinFETS ~ 10-20nm) and strain modulation being used throughout, industry needs a reliable and fast method as quality control or defect characterisation. Such a universal strain measurement method does not exist, and one relies on a combination of quantitative in-line methods and complex off-line approaches. In this thesis, I investigated TEM and Raman spectroscopy-based methodologies for strain measurement. In terms of TEM methodologies, advancements are made for the STEM moiré imaging, targeting strain spatial resolution enhancement. I introduce advanced quadrature demodulation and phase stepping interferometry applied to STEM moiré that greatly enhances the spatial resolution while providing enhanced field of view and sensitivity for strain measurement. We introduce ways to reduce scan distortions in strain maps using an alternative scan strategy called “Block scanning” and the non-linear regression applied for strain extraction. Prospects for 3D strain analysis using high-resolution tomography is also investigated which gives direct access for the full second order strain tensors calculation. Finally, we compare strain measurements from TEM techniques with inline techniques like Raman spectroscopy. Raman stress measurement involves sensitive identification of the TO and LO phonon peaks. Raman spectrum of strained Ge transistor channel consists of strongly overlapping peaks within the spectral resolution of the spectrometer. Hence, the process of deconvolution of the two peaks is rather challenging. Hence, we explore new polarisation geometries like radially polarised incoming light which was shown to ease the deconvolution problem resulting in improved precision for Raman stress–strain measurements.

Abstract: Precipitation is accompanied by the formation and migration of heterophase interfaces. Using the combined approach of advanced imaging and atomistic simulations, we studied the precipitate-matrix interfaces in various aluminium alloy systems, aiming to resolve their detailed atomic structures and illuminate their role in phase transformations.

Abstract: Exposure to volatile organic compounds (VOCs) remains a major public health concern. Indoor VOC concentrations typically far exceed outdoor levels due to a variety of emission sources and the stringent insulation measures that are imposed today. Many attempts have been made to use photocatalysis for indoor air purification. In an ideal situation, photocatalysis is capable of complete mineralization of VOCs to H2O and CO2, without any byproduct formation. Moreover, the process can take place at standard atmospheric conditions, i.e. ambient temperature and atmospheric pressure. However, successful exploitation is still impeded due to low conversion efficiency, significant pressure loss (and hence a high energy consumption) and byproduct formation. In the first part of this thesis an attempt was made to tackles these problems by designing a novel type of photocatalytic (PCO) reactor. The PCO device consists of a cylindrical vessel filled with TiO2-coated glass tubes and equipped with UV fluorescence lamps. It was investigated in terms of fluid dynamics, coating properties, UV-light distribution and photocatalytic activity. Experimental data was later used to develop and calibrate a Multiphysics model. The model proved to be a useful tool for designing and upscaling the PCO reactor. Consequently, an optimized prototype reactor was constructed and tested according the CEN-EN-16846-1 standard for VOC removal. Although the prototype showed promising results for lab-scale conditions, it struggled with byproduct formation when purifying ppb-level VOCs. In the second part of this thesis, activated carbon adsorption was investigated in order to combine it with photocatalysis. Activated carbon fiber was opted for its fast kinetics, high adsorption capacity and thermo-electrical regeneration. The filter was studied in detail regarding the adsorption of polar and apolar VOCs at indoor air concentration levels and regeneration capabilities. Experimental data was used to develop a Multiphysics model for activated carbon adsorption as well. Consequently, a novel type of ACF filter was developed using the Multiphysics model, which was equipped with electrodes in the tips of the pleats for effective thermal regeneration. In the last part, the combination of both ACF and PCO was studied using a realistic case study. Based on the Multiphysics model, the feasibility of a so-called hybrid air purification device could be investigated. The Multiphysics model shows promising results for this hybrid PCO-ACF system and hence, a demo setup was constructed for future research.

Abstract: We placed crystals of different compounds to explore the possibility of fingerprinting them through EELS. Here are representative datasets of 7 different compounds: b-cyclodextrin hexacarboxy cyclohexane tannin TH-15 peptide TH-27 peptide two different forms of piroxicam The datasets were collected at EMAT, using a monochromated FEI Titan3 TEM, within the scope of an EUSMI request. More information as well as analysis methodologies adopted for the data are detailed in the paper: Das et al. “Reliable Characterization of Organic & Pharmaceutical Compounds with High Resolution Monochromated EEL Spectroscopy”, Polymers 2020, 12(7), 1434.

Abstract: Electron microscopy is an excellent tool which provides resolution down to the atomic scale with up to pm precision in locating atoms. The characterization of materials in these length scales is of utmost importance to answer questions in biology, chemistry and material science. The successful implementation of aberration-corrected microscopes made atomic resolution imaging relatively easy, this could give the impression that the development of novel electron microscopy techniques would stagnate and only the application of these instruments as giant magnifying tools would continue. This is of course not true and a multitude of problems still exist in electron microscopy. Two of such issues are discussed below. One of the biggest problems in electron microscopy is the presence of beam damage which occurs due the fact that the highly energetic incoming electrons have sufficient kinetic energy to change the structure of the material. The amount of damage induced depends on the dose, hence minimizing this dose during an experiment is beneficial. This minimizing of the total dose comes at the expense of more noise due to the counting nature of the electrons. For this reason, the implementation of four dimensional scanning transmission electron microscopy (4D STEM) experiments has reduced the total dose needed per acquisition. However, the current cameras used to measure the diffraction patterns are still two orders of magnitude slower than to the conventional STEM methods. Improving the acquisition speed would make the 4D STEM technique more feasible and is of utmost importance for the beam sensitive materials since less dose is used during the acquisition. In TEM there is not only the possibility to perform imaging experiments but also spectroscopic measurements. There are two frequently used methods: electron energy-loss spectroscopy (EELS) and energy dispersive x-ray spectroscopy (EDX). EELS measures the energy-loss spectrum of the incoming electron which gives information on the available excitations in the material providing elemental sensitivity. In EDX, the characteristic x-rays, arising from the decay of an atom which is initially excited due to the incoming electrons, are detected providing similar elemental analysis. Both methods are able to provide comparable elemental information where in certain circumstances one outperforms the other. However, both methods have a detection limit of approximately 100-1000 ppm which is not sufficient for some materials. In this thesis, two novel techniques which can make significant progress for the two problems discussed above.

Abstract: This dataset contains individual EEL and EDX events where for every event (electron or X-ray), their energy and time of arrival is stored. The experiment was performed in a transmission electron microscope (Tecnai Osiris) at 200 keV. The material investigated is an Al-Mg-Si-Cu alloy. The 'full_dataset.mat' contains the full dataset and the 'subset.mat' has the first five frames of the full dataset. The attached 'EELS-EDX.ipynb' is a jupyter notebook file. This file describes the data processing in order to observe the temporal correlation between the electrons and X-rays.

Abstract: The stress corrosion cracking (SCC) mechanism is investigated in high Si duplex stainless steel in a simulated PWR environment based on TEM analysis of FIB-extracted SCC crack tips. The microstructural investigation in the near vicinity of SCC crack tips illustrates a strain-rate dependence in SCC mechanisms. Detailed analysis of the crack tip morphology, that includes crack tip oxidation and surrounding deformation field, indicates the existence of an interplay between corrosion- and deformation-driven failure as a function of the strain rate. Slow strain-rate crack tips exhibit a narrow cleavage failure which can be linked to the film-induced failure mechanism, while rounded shaped crack tips for faster strain rates could be related to the strain-induced failure. As a result, two nominal strain-rate-dependent failure regimes dominated either by corrosion or deformation-driven cracking mechanisms can be distinguished.

Abstract: Although traditional ferroelectric materials are usually dielectric and nonconductive, GeTe is a typical ferroelectric semiconductor, possessing both ferroelectric and semiconducting properties. GeTe is also a widely studied thermoelectric material, whose performance has been optimized by doping with various elements. However, the impact of the ferroelectric domains on the thermoelectric properties remains unclear due to the difficulty to directly observe the ferroelectric domains and their evolutions under actual working conditions where the material is exposed to high temperatures and electric currents. Herein, based on in-situ investigations of the ferroelectric domains and domain walls in both pure and Sb-doped GeTe crystals, we have been able to analyze the dynamic evolution of the ferroelectric domains and domain walls, exposed to an electric field and temperature. Local structural heterogeneities and nano-sized ferroelectric domains are generated due to the interplay of the Sb3+ dopant and the Ge-vacancies, leading to the increased number of charged domain walls and a much improved thermoelectric performance. This work reveals the fundamental mechanism of ferroelectric thermoelectrics and provides insights into the decoupling of previously interdependent properties such as thermo-power and electrical conductivity.

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.

Abstract: A real-time image reconstruction method for scanning transmission electron microscopy (STEM) is proposed. With an algorithm requiring only the center of mass of the diffraction pattern at one probe position at a time, it is able to update the resulting image each time a new probe position is visited without storing any intermediate diffraction patterns. The results show clear features at high spatial frequency, such as atomic column positions. It is also demonstrated that some common post-processing methods, such as band-pass filtering, can be directly integrated in the real-time processing flow. Compared with other reconstruction methods, the proposed method produces high-quality reconstructions with good noise robustness at extremely low memory and computational requirements. An efficient, interactive open source implementation of the concept is further presented, which is compatible with frame-based, as well as event-based camera/file types. This method provides the attractive feature of immediate feedback that microscope operators have become used to, for example, conventional high-angle annular dark field STEM imaging, allowing for rapid decision-making and fine-tuning to obtain the best possible images for beam-sensitive samples at the lowest possible dose.

Abstract: Although recent studies have advanced the understanding of pyrolyzed
Fe−N−C materials as oxygen reduction reaction (ORR) catalysts, the atomic and
electronic structures of the active sites and their detailed reaction mechanisms still remain unknown. Here, based on first-principles density functional theory (DFT) computations, we discuss the electronic structures of three FeN4 catalytic centers with different local topologies of the surrounding C atoms with a focus on unraveling the mechanism of their ORR activity in acidic electrolytes. Our study brings back a forgotten, synthesized pyridinic Fe−N coordinate to the community’s attention, demonstrating that this catalyst can exhibit excellent activity for promoting direct four-electron ORR through the addition of a fifth ligand such as −NH2, −OH, and −SO4. We also identify sites with good stability properties through the combined use of our DFT calculations and Mössbauer spectroscopy data.

Abstract: Structural analysis of metal clusters confined in nanoporous materials is typically performed by X-ray-driven techniques. Although X-ray analysis has proved its strength in the characterization of metal clusters, it provides averaged structural information. Therefore, we here present an alternative workflow for bringing the characterization of confined metal clusters towards the local scale. This workflow is based on the combination of aberration-corrected transmission electron microscopy (TEM), TEM image simulations, and powder X-ray diffraction (XRD) with advanced statistical techniques. In this manner, we were able to characterize the clustering of Pb atoms in Linde Type A (LTA) zeolites with Pb loadings as low as 5 wt%. Moreover, individual Pb clusters could be directly detected. The proposed methodology thus enables a local-scale characterization of confined metal clusters in zeolites. This is important for further elucidation of the connection between the structure and the physicochemical properties of such systems.