Abstract: We report an innovative method to explore the optimal experimental settings to detect light atoms from scanning transmission electron microscopy (STEM) images. Since light elements play a key role in many technologically important materials, such as lithium-battery devices or hydrogen storage applications, much effort has been made to optimize the STEM technique in order to detect light elements. Therefore, classical performance criteria, such as contrast or signal-to-noise ratio, are often discussed hereby aiming at improvements of the direct visual interpretability. However, when images are interpreted quantitatively, one needs an alternative criterion, which we derive based on statistical detection theory. Using realistic simulations of technologically important materials, we demonstrate the benefits of the proposed method and compare the results with existing approaches.

Abstract: 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.

Abstract: We introduce a Bayesian genetic algorithm for reconstructing atomic models of monotype crystalline nanoparticles from a single projection using Z-contrast imaging. The number of atoms in a projected atomic column obtained from annular dark field scanning transmission electron microscopy images serves as an input for the initial three-dimensional model. The algorithm minimizes the energy of the structure while utilizing a priori information about the finite precision of the atom-counting results and neighbor-mass relations. The results show promising prospects for obtaining reliable reconstructions of beam-sensitive nanoparticles during dynamical processes from images acquired with sufficiently low incident electron doses.

Abstract: Understanding nanostructures down to the atomic level is the key to optimizing the design of advancedmaterials with revolutionary novel properties. This requires characterization methods capable of quantifying the three-dimensional (3D) atomic structure with the highest possible precision. A successful approach to reach this goal is to count the number of atoms in each atomic column from 2D annular dark field scanning transmission electron microscopy images. To count atoms with single atom sensitivity, a minimum electron dose has been shown to be necessary, while on the other hand beam damage, induced by the high energy electrons, puts a limit on the tolerable dose. An important challenge is therefore to develop experimental strategies to optimize the electron dose by balancing atom-counting fidelity vs the risk of knock-on damage. To achieve this goal, a statistical framework combined with physics-based modeling of the dose-dependent processes is here proposed and experimentally verified. This model enables an investigator to theoretically predict, in advance of an experimental measurement, the optimal electron dose resulting in an unambiguous quantification of nanostructures in their native state with the highest attainable precision.

Abstract: To gain insights into the underlying mechanisms of NTP therapy sensitivity and resistance, using the firstever
NTP-resistant cell line derived from sensitive melanoma cells (A375).
Methods: Melanoma cells were exposed to NTP and re-cultured for 12 consecutive weeks before evaluation
against the parental control cells. Whole transcriptome sequencing analysis was performed to identify differentially
expressed genes and enriched molecular pathways. Glucose uptake, extracellular lactate, media acidification,
and mitochondrial respiration was analyzed to determine metabolic changes. Cell death inhibitors were
used to assess the NTP-induced cell death mechanisms, and apoptosis and ferroptosis was further validated via
Annexin V, Caspase 3/7, and lipid peroxidation analysis.
Results: Cells continuously exposed to NTP became 10 times more resistant to NTP compared to the parental cell
line of the same passage, based on their half-maximal inhibitory concentration (IC50). Sequencing and metabolic
analysis indicated that NTP-resistant cells had a preference towards aerobic glycolysis, while cell death analysis
revealed that NTP-resistant cells exhibited less apoptosis but were more vulnerable to lipid peroxidation and
ferroptosis.
Conclusions: A preference towards aerobic glycolysis and ferroptotic cell death are key physiological changes in
NTP-resistance cells, which opens new avenues for further, in-depth research into other cancer types.

Abstract: This chapter provides an overview of statistical and quantitative methodologies that have pushed (scanning) transmission electron microscopy ((S)TEM) toward accurate and precise measurements of unknown structure parameters for understanding the relation between the structure of a material and its properties. Hereby, statistical parameter estimation theory has extensively been used which enabled not only measuring atomic column positions, but also quantifying the number of atoms, and detecting atomic columns as accurately and precisely as possible from experimental images. As a general conclusion, it can be stated that advanced statistical techniques are ideal tools to perform quantitative electron microscopy at the atomic scale. In the future, statistical methods will continue to be developed and novel quantification procedures will open up new possibilities for studying material structures at the atomic scale.

Abstract: The rapid progress in materials science that enables the design of materials down to the nanoscale also demands characterization techniques able to analyze the materials down to the same scale, such as transmission electron microscopy. As Belgium’s foremost electron microscopy group, among the largest in the world, EMAT is continuously contributing to the development of TEM techniques, such as high-resolution imaging, diffraction, electron tomography, and spectroscopies, with an emphasis on quantification and reproducibility, as well as employing TEM methodology at the highest level to solve real-world materials science problems. The lab’s recent contributions are presented here together with specific case studies in order to highlight the usefulness of TEM to the advancement of materials science.

Abstract: The obstructive sleep apnea-hypopnea syndrome (OSAHS) is a sleep related breathing disorder. A popular treatment is the use of a mandibular repositioning appliance (MRA) which advances the mandibula during the sleep and decreases the collapsibility of the upper airway. The success rate of such a device is, however, limited and very variable within a population of patients. Previous studies using computational fluid dynamics have shown that there is a decrease in upper airway resistance in patients who improve clinically due to an MRA. In this article, correlations between patient-specific anatomical and functional parameters are studied to examine how MRA induced biomechanical changes will have an impact on the upper airway resistance. Low-dose computed tomography (CT) scans are made from 143 patients suffering from OSAHS. A baseline scan and a scan after mandibular repositioning (MR) are performed in order to study variations in parameters. It is found that MR using a simulation bite is able to induce resistance changes by changing the pharyngeal lumen. The change in minimal cross-sectional area is the best parameter to predict the change in upper airway resistance. Looking at baseline values, the ideal patients for MR induced resistance decrease seem to be women with short airways, high initial resistance and no baseline occlusion.

Abstract: The increasing need for precise determination of the atomic arrangement of non-periodic structures in materials design and the control of nanostructures explains the growing interest in quantitative transmission electron microscopy. The aim is to extract precise and accurate numbers for unknown structure parameters including atomic positions, chemical concentrations and atomic numbers. For this purpose, statistical parameter estimation theory has been shown to provide reliable results. In this theory, observations are considered purely as data planes, from which structure parameters have to be determined using a parametric model describing the images. As such, the positions of atom columns can be measured with a precision of the order of a few picometres, even though the resolution of the electron microscope is still one or two orders of magnitude larger. Moreover, small differences in average atomic number, which cannot be distinguished visually, can be quantified using high-angle annular dark-field scanning transmission electron microscopy images. In addition, this theory allows one to measure compositional changes at interfaces, to count atoms with single-atom sensitivity, and to reconstruct atomic structures in three dimensions. This feature article brings the reader up to date, summarizing the underlying theory and highlighting some of the recent applications of quantitative model-based transmisson electron microscopy.

Abstract: The development of new nanocrystals with outstanding physicochemical properties requires a full threedimensional (3D) characterization at the atomic scale. For homogeneous nanocrystals, counting the number of atoms in each atomic column from high angle annular dark field scanning transmission electron microscopy images has been shown to be a successful technique to get access to this 3D information. However, technologically important nanostructures often consist of more than one chemical element. In order to extend atom counting to heterogeneous materials, a new atomic lensing model is presented. This model takes dynamical electron diffraction into account and opens up new possibilities for unraveling the 3D composition at the atomic scale. Here, the method is applied to determine the 3D structure of Au@Ag core-shell nanorods, but it is applicable to a wide range of heterogeneous complex nanostructures.

Abstract: The agri-food value chain is a major cause of nitrogen (N) and phosphorus (P) emissions and associated environmental and health impacts. The EU's farm-to-fork strategy (F2F) demands an agri-food value chain approach to reduce nutrient emissions by 50% and fertilizer use by 20%. Substance flow analysis (SFA) is a method that can be applied to study complex systems such as the agri-food chain. A review of 60 SFA studies shows that they often lack detail by not sufficiently distinguishing between nodes, products and types of emissions. The present study aims to assess the added value of detail in SFAs and to illustrate that valuable indicators can be derived from detailed assessments. This aim will be attained by presenting a highly-detailed SFA for the livestock-intensive region of Flanders, Belgium. The SFA distinguishes 40 nodes and 1827 flows that are classified into eight different categories (e.g. by-products, point source emissions) following life cycle methods. Eight novel indicators were calculated, including indicators that assess the N and P recovery potential. Flanders has a low overall nutrient use efficiency (11% N, 18% P). About 55% of the N and 56% of the P embedded in recoverable streams are reused providing 35% and 37% of the total N and P input. Optimized nutrient recycling could replace 45% of N and 48% of P of the external nutrient input, exceeding the target set by the F2F strategy. Detailed accounting for N and P flows and nodes leads to the identification of more recoverable streams and larger N and P flows. More detailed flow accounting is a prerequisite for the quantification of technological intervention options. Future research should focus on including concentration and quality as a parameter in SFAs.

Abstract: Since its discovery 20 years ago, many studies have been performed to gain insight into the functional role of cytoglobin (Cygb). However, Cygb has been proven to be a promiscuous protein. Yet, there is a consensus that Cygb is a cytoprotective protein involved in redox homeostasis. CYGB is a ubiquitously expressed hexacoordinated globin that is highly expressed in melanocytes and is often found to be downregulated during melanocyte-to-melanoma transition. In Chapter III, we investigated the molecular mechanism through which CYGB could be involved in redox regulation. Here, we showed that CYGB contains two redox-sensitive cysteine residues and that the formation of an intramolecular disulfide bridge resulted in the heme group becoming more accessible to external ligands. This supports the hypothesis that Cys38 and Cys83 serve as sensitive redox sensors. In Chapter IV we showed that CYGB mRNA and protein levels were elevated upon exposure to hypoxia. Interestingly, this upregulation was most likely HIF-2α-dependent. We propose that in melanoma, HIF-2α, rather than HIF-1α, positively regulates CYGB under hypoxic conditions in a cell type specific way. In Chapter V, the cytotoxic effect of indirect NTP treatment in two melanoma cell lines with divergent endogenous CYGB expression levels was investigated. We confirmed that NTP endows cytotoxicity that induces cell death through apoptosis and that this was mediated through the production of ROS. Moreover, we showed that CYGB protects melanoma cells from ROS-induced apoptosis by the scavenging of ROS. Interestingly, CYGB expression influenced the expression of NRF2 and HO-1. We identified the lncRNA MEG3 as a possible mechanism through which NRF2 expression and its downstream target HO-1 can be regulated by CYGB. In chapter VI, increased basal ROS levels and higher degree of lipid peroxidation upon RSL3 treatment contributed to the increased sensitivity of CYGB knockdown G361 cells to ferroptosis. Furthermore, transcriptome analysis demonstrates the enrichment of multiple cancer malignancy pathways upon CYGB knockdown, supporting a tumor-suppressive role for CYGB. Remarkably, CYGB expression regulation was identified as a critical determinant of the ferroptosis–pyroptosis therapy response. This suggests that CYGB is involved in the regulation of multiple modes of programmed cell death. FInally, we sought to delineate the RONS that are responsible for plasma-induced ICD. Our results highlight the importance of the short-lived species. Furthermore, we are first to demonstrate that NTP-created vaccine is safely prepared and offers complete protection. Moreover, we provide conclusive evidence that direct application of NTP induces ICD in melanoma.

Abstract: 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 centredcubic crystal structures in the form of rafts, between 2 and 8 atoms thick, were formed after the initial wetting of the carbon support.

Abstract: Quantitative structure determination is needed in order to study and understand nanomaterials at the atomic scale. Materials characterisation resulting in precise structural information is a crucial point to understand the structure–property relation of materials. Counting the number of atoms and retrieving the 3D atomic structure of nanoparticles plays an important role here. In this paper, an overview will be given of the atom-counting methodology and its applications over the past decade. The procedure to count the number of atoms will be discussed in detail and it will be shown how the performance of the method can be further improved. Furthermore, advances toward mixed element nanostructures, 3D atomic modelling based on the atom-counting results, and quantifying the nanoparticle dynamics will be highlighted.

Abstract: Quantitative atomic resolution annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique for nanoparticle atom-counting. However, a lot of nanoparticles provide a severe characterisation challenge because of their limited size and beam sensitivity. Therefore, quantitative ADF STEM may greatly benefit from statistical detection theory in order to optimise the instrumental microscope settings such that the incoming electron dose can be kept as low as possible whilst still retaining single-atom precision. The principles of detection theory are used to quantify the probability of error for atom-counting. This enables us to decide between different image performance measures and to optimise the experimental detector settings for atom-counting in ADF STEM in an objective manner. To demonstrate this, ADF STEM imaging of an industrial catalyst has been conducted using the near-optimal detector settings. For this experiment, we discussed the limits for atomcounting diagnosed by combining a thorough statistical method and detailed image simulations.