Abstract: This dataset comprises a large collection of atom probe tomography datasets collected from DIN 1.4970 alloy that was irradiated with Fe ions at different conditions. The DIN 1.4970 alloy is an austenitic stainless steel with 15 wt% Cr, 15 wt% Ni, a small addition of Ti. The full composition and characterization of our material can be found published elsewhere [1,2]. Some of our material was subjected to ageing heat treatments at different temperatures for different times. Small samples of our original material and aged material was irradiated at the Michigan Ion Beam Laboratory in 2017 with 4.5 MeV Fe ions up to 40 dpa at an average dose rate of 2×10−4 dpa/s. This was done at three different temperatures: 300, 450, and 600 ºC. Atom probe samples were made of the irradiated layers (approximately 1.5 micron deep) with focused ion beam and mounted on Microtip coupons. APT measurements took place on three CAMECA LEAP-HR systems located at CAES in Idaho Falls, USA (files beginning with R33), at Montanuniversität Leoben in Leoben, Austria (R21) and at Friedrich–Alexander University in Erlangen, Germany (R56).

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: Nanomaterialen kunnen uiterst interessante eigenschappen vertonen voor een verscheidenheid aan veelbelovende toepassingen, gaande van zonnecrème tot batterijen voor elektrische auto’s. Een nanometer is een miljard keer kleiner dan een meter. Op deze schaal kunnen de materiaaleigenschappen volledig verschillen van bulkmaterialen op grotere schaal. Bovendien hangen de eigenschappen van nanomaterialen sterk af van hun exacte grootte en vorm. Kleine verschillen in de posities van de atomen, in de grootte-orde van een picometer (nog eens duizend maal kleiner dan een nanometer), kunnen de fysische eigenschappen al drastisch beïnvloeden. Daarom is een betrouwbare kwantificering van de atomaire structuur van kritisch belang om de evolutie naar materiaalontwerp mogelijk te maken en inzicht te verwerven in de relatie tussen de fysische eigenschappen en de structuur van nanomaterialen. Daarnaast kan de atomaire structuur van nanomaterialen ook veranderen in de loop van de tijd ten gevolge van verschillende fysische processen. Het onderzoek dat in deze thesis gepresenteerd wordt, maakt het mogelijk om de dynamische structuurveranderingen van nanomaterialen betrouwbaar te kwantificeren op atomaire schaal door gebruik te maken van raster transmissie elektronenmicroscopie (STEM). Ik heb dit gerealiseerd door methodes te ontwikkelen waarmee ik het aantal atomen “achter elkaar” kan tellen in elke atoomkolom van een nanomateriaal, en dit op basis van beelden opgenomen met een elektronenmicroscoop. Een belangrijk verschil met telmethodes voor de analyse van een enkel beeld is het schatten van de kans dat een atoomkolom atomen zal verliezen of bijkrijgen van het ene naar het andere beeld in de tijdreeks. Deze kwantitatieve methode kan het ontrafelen van de tijdsafhankelijke structuur-eigenschappen relatie van een nanomateriaal mogelijk maken, wat uiteindelijk kan leiden tot efficiënter design en productie van nanomaterialen voor innovatieve toepassingen.

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: 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.