Abstract: Single atom detection is of key importance to solving a wide range of scientific and technological problems. The strong interaction of electrons with matter makes transmission electron microscopy one of the most promising techniques. In particular, aberration correction using scanning transmission electron microscopy has made a significant step forward toward detecting single atoms. However, to overcome radiation damage, related to the use of high-energy electrons, the incoming electron dose should be kept low enough. This results in images exhibiting a low signal-to-noise ratio and extremely weak contrast, especially for light-element nanomaterials. To overcome this problem, a combination of physics-based model fitting and the use of a model-order selection method is proposed, enabling one to detect single atoms with high reliability.

Abstract: Recently, the maximum a posteriori (MAP) probability rule has been proposed as an objective and quantitative method to detect atom columns and even single atoms from high-resolution high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) images. The method combines statistical parameter estimation and model-order selection using a Bayesian framework and has been shown to be especially useful for the analysis of the structure of beam-sensitive nanomaterials. In order to avoid beam damage, images of such materials are usually acquired using a limited incoming electron dose resulting in a low contrast-to-noise ratio (CNR) which makes visual inspection unreliable. This creates a need for an objective and quantitative approach. The present paper describes the methodology of the MAP probability rule, gives its step-by-step derivation and discusses its algorithmic implementation for atom column detection. In addition, simulation results are presented showing that the performance of the MAP probability rule to detect the correct number of atomic columns from HAADF STEM images is superior to that of other model-order selection criteria, including the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). Moreover, the MAP probability rule is used as a tool to evaluate the relation between STEM image quality measures and atom detectability resulting in the introduction of the so-called integrated CNR (ICNR) as a new image quality measure that better correlates with atom detectability than conventional measures such as signal-to-noise ratio (SNR) and CNR.

Abstract: A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials.

Abstract: The atomic lensing model has been proposed as a promising method facilitating atom-counting in heterogeneous nanocrystals [1]. Here, image simulations will validate the model, which describes dynamical diffraction as a superposition of individual atoms focussing the incident electrons. It will be demonstrated that the model is reliable in the annular dark field regime for crystals having columns containing dozens of atoms. By using the principles of statistical detection theory, it will be shown that this model gives new opportunities for detecting compositional differences.

Abstract: In quantitative scanning transmission electron microscopy (STEM), scattering cross-sections have been shown to be very sensitive to the number of atoms in a column and its composition. They correspond to the integrated intensity over the atomic column and they outperform other measures. As compared to atomic column peak intensities, which saturate at a given thickness, scattering cross-sections increase monotonically. A study of the electron wave propagation is presented to explain the sensitivity of the scattering cross-sections. Based on the multislice algorithm, we analyse the wave propagation inside the crystal and its link to the scattered signal for the different probe positions contained in the scattering cross-section for detector collection in the low-, middle- and high-angle regimes. The influence to the signal from scattering of neighbouring columns is also discussed.

Abstract: We present the ASTRA Toolbox as an open platform for 3D image reconstruction in tomography. Most of the software tools that are currently used in electron tomography offer limited flexibility with respect to the geometrical parameters of the acquisition model and the algorithms used for reconstruction. The ASTRA Toolbox provides an extensive set of fast and flexible building blocks that can be used to develop advanced reconstruction algorithms, effectively removing these limitations. We demonstrate this flexibility, the resulting reconstruction quality, and the computational efficiency of this toolbox by a series of experiments, based on experimental dual-axis tilt series.

Abstract: Dielectric barrier discharges (DBDs) are commonly used to generate cold plasmas at
atmospheric pressure. Whatever their configuration (tubular or planar), the presence of a dielectric barrier is mandatory to prevent too much charge build up in the plasma and the formation of a thermal arc. In this article, the role of the barrier thickness (2.0, 2.4 and 2.8 mm) and of the kind of dielectric material (alumina, mullite, pyrex, quartz) is investigated on the filamentary behavior in the plasma and on the CO2 conversion in a tubular flowing DBD, by means of mass spectrometry measurements correlated with electrical characterization and IR imaging. Increasing the barrier thickness decreases the capacitance, while preserving the electrical charge. As a result, the voltage over the dielectric increases and a larger number of microdischarges is generated, which enhances the CO2 conversion. Furthermore, changing the dielectric material of the barrier, while keeping the same geometry and dimensions, also affects the CO2 conversion. The highest CO2 conversion and energy efficiency are obtained for quartz and alumina, thus not following the trend of the relative permittivity. From the
electrical characterization, we clearly demonstrate that the most important parameters are the somewhat higher effective plasma voltage (yielding a somewhat higher electric field and electron energy in the plasma) for quartz, as well as the higher plasma current (and thus larger electron density) and the larger number of microdischarge filaments (mainly for alumina, but also for quartz). The latter could be correlated to the higher surface roughness for alumina and to the higher voltage over the dielectric for quartz.

Abstract: In this experimental study, a flowing dielectric barrier discharge operating at atmospheric pressure is used for the splitting of CO2 into O2 and CO. The influence of the applied frequency and plasma power on the microdischarge properties is investigated to understand their role on the CO2 conversion. Electrical measurements are carried out to explain the conversion trends and to characterize the microdischarges through their number, their lifetime,
their intensity and the induced electrical charge. Their influence on the gas and electrode temperatures is also evidenced through optical emission spectroscopy and infrared imaging. It is shown that, in our configuration, the conversion depends mostly on the charge delivered in the plasma and not on the effective plasma voltage when the applied power is modified. Similarly, at constant total current, a better conversion is observed at low frequencies, where a less filamentary discharge regime with a higher effective plasma voltage than that at a higher
frequency is obtained.

Abstract: The present contribution gives a review of recent quantification work of atom displacements, atom site occupations and level of crystallinity in various systems and based on aberration corrected HR(S)TEM images. Depending on the case studied, picometer range precisions for individual distances can be obtained, boundary widths at the unit cell level determined or statistical evolutions of fractions of the ordered areas calculated. In all of these cases, these quantitative measures imply new routes for the applications of the respective materials.

Abstract: In recent years, the ability of cold atmospheric pressure plasmas (CAPS) to selectively induce cell death in cancer cells has been widely established. This selectivity has been assigned to the reactive oxygen and nitrogen species (RONS) created in CAPs. To provide new insights in the search for an explanation
for the observed selectivity, we calculate the transfer free energy of multiple ROS across membranes containing a varying amount of cholesterol. The cholesterol fraction is investigated as a selectivity parameter because membranes of cancer cells are known to contain lower fractions of cholesterol compared to healthy cells. We find that cholesterol has a significant effect on the permeation of
reactive species across a membrane. Indeed, depending on the specific reactive species, an increasing cholesterol fraction can lead to (i) an increase of the transfer free energy barrier height and width, (ii) the formation of a local free energy minimum in the center of the membrane and (iii) the creation of extra free energy barriers due to the bulky sterol rings. In the context of plasma oncology, these observations suggest that the increased ingress of RONS in cancer cells can be explained by the decreased cholesterol fraction of their cell membrane.

Abstract: Aberration correction in scanning transmission electron microscopy (STEM) has greatly improved the lateral and depth resolution. When using depth sectioning, a technique during which a series of images is recorded at different defocus values, single impurity atoms can be visualised in three dimensions. In this paper, we investigate new possibilities emerging when combining depth sectioning and precise atom-counting in order to reconstruct nanosized particles in three dimensions. Although the depth resolution does not allow one to precisely locate each atom within an atomic column, it will be shown that the depth location of an atomic column as a whole can be measured precisely. In this manner, the morphology of a nanoparticle can be reconstructed in three dimensions. This will be demonstrated using simulations and experimental data of a gold nanorod.

Abstract: Multimodal contrast agents, which take advantage of different imaging modalities, have emerged as an interesting approach to overcome the technical limitations of individual techniques. We developed hybrid nanoparticles comprising an iron oxide core and an outer gold spiky layer, stabilized by a biocompatible polymeric shell. The combined magnetic and optical properties of the different components provide the required functionalities for magnetic resonance imaging (MRI), surface-enhanced Raman scattering (SERS), and fluorescence imaging. The fabrication of such hybrid nanoprobes comprised the adsorption of small gold nanoparticles onto premade iron oxide cores, followed by controlled growth of spiky gold shells. The gold layer thickness and branching degree (tip sharpness) can be controlled by modifying both the density of Au nanoparticle seeds on the iron oxide cores and the subsequent nanostar growth conditions. We additionally demonstrated the performance of these hybrid multifunctional nanoparticles as multimodal contrast agents for correlative imaging of in vitro cell models and ex vivo tissues.

Abstract: Because of its unique properties, plasma technology has gained much prominence in the
microelectronics industry. Recently, environmental and energy applications of plasmas have gained a lot of attention. In this area, the focus is on converting CO 2 and reforming hydrocarbons, with the goal of developing an efficient single-step ‘gas-to-liquid’ (GTL) process. Here we show that applying tri-reforming principles to plasma—further called ‘plasma-based multi-reforming’—allows us to better control the plasma chemistry and thus the formed products. To demonstrate this, we used chemical kinetics calculations supported by experiments and reveal that better control of the plasma chemistry can be achieved by adding O 2 or H 2 O to a mixture containing CH 4 and CO 2 (diluted in N 2 ). Moreover, by adding O 2 and H 2 O simultaneously, we can tune the plasma chemistry even further, improving the conversions, thermal efficiency and methanol yield. Unlike thermocatalytic reforming, plasma-based reforming is capable of producing methanol in a single step; and compared with traditional plasma-based dry reforming, plasma-based multi-reforming increases the methanol yield by more than seven times and the thermal efficiency by 49%, as revealed by our model calculations. Thus, we believe that by using plasma-based multi-reforming, ‘gas-to-liquid’ conversion may be made efficient and scalable.

Abstract: Nowadays, aberration corrected transmission electron microscopy (TEM) is a popular method to characterise nanomaterials at the atomic scale. Here, atomically resolved images of nanomaterials are acquired, where the contrast depends on the illumination, imaging and detector conditions of the microscope. Visualization of light elements is possible when using low angle annular dark field (LAADF) STEM, annular bright field (ABF) STEM, integrated differential phase contrast (iDPC) STEM, negative spherical aberration imaging (NCSI) and imaging STEM (ISTEM). In this work, images of a NdGaO3-La0.67Sr0.33MnO3 (NGO-LSMO) interface are quantitatively evaluated by using statistical parameter estimation theory. For imaging light elements, all techniques are providing reliable results, while the techniques based on interference contrast, NCSI and ISTEM, are less robust in terms of accuracy for extracting heavy column locations. In term of precision, sample drift and scan distortions mainly limits the STEM based techniques as compared to NCSI. Post processing techniques can, however, partially compensate for this. In order to provide an outlook to the future, simulated images of NGO, in which the unavoidable presence of Poisson noise is taken into account, are used to determine the ultimate precision. In this future counting noise limited scenario, NCSI and ISTEM imaging will provide more precise values as compared to the other techniques, which can be related to the mechanisms behind the image recording.

Abstract: Nanoparticle assemblies can be investigated in 3 dimensions using electron tomography. However, it is not straightforward to obtain quantitative information such as the number of particles or their relative position. This becomes particularly difficult when the number of particles increases. We propose a novel approach in which prior information on the shape of the individual particles is exploited. It improves the quality of the reconstruction of these complex assemblies significantly. Moreover, this quantitative Sparse Sphere Reconstruction approach yields directly the number of particles and their position as an output of the reconstruction technique, enabling a detailed 3D analysis of assemblies with as many as 10 000 particles. The approach can also be used to reconstruct objects based on a very limited number of projections, which opens up possibilities to investigate beam sensitive assemblies where previous reconstructions with the available electron tomography techniques failed.