Abstract: By using the full 3D generalized time-dependent Ginzbug-Landau equation, we study a long superconducting film of finite width and thickness under an applied transport current. We show that, for sufficiently large thickness, the vortices and the antivortices become curved before they annihilate each other. As they approach the center of the sample, their ends combine, producing a single closed vortex. We also determine the critical values of the thickness for which the closed vortex sets in for different values of the Ginzburg-Ladau parameter. Finally, we propose a model of how to detect a closed vortex experimentally.

Abstract: The DFT-1/2 method is a band-gap correction with GW precision at a density functional theory (DFT) computational cost. The method was also extended to correct the gap between defect levels, allowing for the calculation of optical transitions. However, this method fails when the atomic character of the occupied and unoccupied defect levels is similar as we illustrate by two examples, the tetrahedral hydrogen interstitial and the negatively charged vacancy in diamond. We solve this problem by decoupling the effect of the occupied and unoccupied defect levels and call this the decoupled DFT-1/2 method for defects.

Abstract: technologies have been expanding, and one of the most exciting and rapidly growing
applications is in biology and medicine. Most biomedical studies with DBD plasma systems are performed in vitro, which include cells grown on the surface of plastic well plates, or in vivo, which include animal research models (e.g. mice, pigs). Since many DBD systems use the biological target as the secondary electrode for direct plasma generation and treatment, they are sensitive to the surface properties of the target, and thus can be altered based on the in vitro or in vivo system used. This could consequently affect biological response from plasma treatment. Therefore, in this study, we investigated the DBD plasma behavior both in vitro (i.e. 96-well flat bottom plates, 96-well U-bottom plates, and 24-well flat bottom plates), and in vivo (i.e. mouse skin). Intensified charge coupled device (ICCD) imaging was performed and the plasma discharges were visually distinguishable between the different systems. The geometry of the wells did not affect DBD plasma generation for low application distances (≤ 2 mm), but differentially affected plasma uniformity on the bottom of the well at greater distances. Since DBD plasma treatment in vitro is rarely performed in dry wells for plasma medicine experiments, the effect of well wetness was also investigated. In all in vitro cases, the uniformity of the DBD plasma was affected when comparing wet versus dry wells, with the plasma in the wide-bottom wells appearing the most similar to plasma generated on mouse skin. Interestingly, based on quantification of ICCD images, the DBD plasma intensity per surface area demonstrated an exponential one-phase decay with increasing application distance, regardless of the in vitro or in vivo system. This trend is similar to that of the energy per pulse of plasma, which is used to determine the total plasma treatment energy for biological systems. Optical emission spectroscopy performed on the plasma revealed similar trends in radical species generation between the plastic well plates and mouse skin. Therefore, taken together, DBD plasma intensity per surface area may be a valuable parameter to be used as a simple method for in situ monitoring during biological treatment and active plasma treatment control, which can be applied for in vitro and in vivo systems.

Abstract: Since the onset of pattern transfer technologies for chip manufacturing, various strategies have been developed to circumvent or overcome aspect ratio dependent etching (ARDE). These methods have, however, their own limitations in terms of etch non-idealities, throughput or costs. Moreover, they have mainly been optimized for individual in-device features and die-scale patterns, while occasionally ending up with poor patterning of metrology marks, affecting the alignment and overlay in lithography. Obtaining a better understanding of the underlying mechanisms of ARDE and how to mitigate them therefore remains a relevant challenge to date, for both marks and advanced nodes. In this work, we accordingly assessed the neutral transport mechanisms in ARDE by means of experiments and multiscale modeling for SiO₂etching with CHF₃/Ar and CF₄/Ar plasmas. The experiments revealed a local maximum in the etch rate for an aspect ratio around unity, i.e. the simultaneous occurrence of regular and inverse reactive ion etching lag for a given etch condition. We were able to reproduce this ARDE trend in the simulations without taking into account charging effects and the polymer layer thickness, suggesting shadowing and diffuse reflection of neutrals as the primary underlying mechanisms. Subsequently, we explored four methods with the simulations to regulate ARDE, by varying the incident plasma species fluxes, the amount of polymer deposition, the ion energy and angular distribution and the initial hardmask sidewall angle, for which the latter was found to be promising in particular. Although our study focusses on feature dimensions characteristic to metrology marks and back-end-of-the-line integration, the obtained insights have a broader relevance, e.g. to the patterning of advanced nodes. Additionally, this work supports the insight that physisorption may be more important in plasma etching at room temperature than originally thought, in line with other recent studies, a topic on which we recommend further research.

Abstract: We present a 48-element programmable phase plate for coherent electron waves produced by a combination of photolithography and focused ion beam. This brings the highly successful concept of wavefront shaping from light optics into the realm of electron optics and provides an important new degree of freedom to prepare electron quantum states. The phase plate chip is mounted on an aperture rod placed in the C2 plane of a transmission electron microscope operating in the 100-300 kV range. The phase plate's behavior is characterized by a Gerchberg-Saxton algorithm, showing a phase sensitivity of 0.075 rad/mV at 300 kV, with a phase resolution of approximately 3x10e−3π. In addition, we provide a brief overview of possible use cases and support it with both simulated and experimental results.

Abstract: Preston's equation is a general model describing the egg shape of birds. The parameters of Preston's equation are usually estimated after re-expressing it as the Todd-Smart equation and scaling the egg's actual length to two. This method assumes that the straight line through the two points on an egg's profile separated by the maximum distance (i.e., the longest axis of an egg's profile) is the mid-line. It hypothesizes that the photographed egg's profile is perfectly bilaterally symmetrical, which seldom holds true because of photographic errors and placement errors. The existing parameter estimation method for Preston's equation considers an angle of deviation for the longest axis of an egg's profile from the mid-line, which decreases prediction errors to a certain degree. Nevertheless, this method cannot provide an accurate estimate of the coordinates of the egg's center, and it leads to sub-optimal parameter estimation. Thus, it is better to account for the possible asymmetry between the two sides of an egg's profile along its mid-line when fitting egg-shape data. In this paper, we propose a method based on the optimization algorithm (optimPE) to fit egg-shape data and better estimate the parameters of Preston's equation by automatically searching for the optimal mid-line of an egg's profile and testing its validity using profiles of 59 bird eggs spanning a wide range of existing egg shapes. We further compared this method with the existing one based on multiple linear regression (lmPE). This study demonstrated the ability of the optimPE method to estimate numerical values of the parameters of Preston's equation and provide the theoretical egg length (i.e., the distance between two ends of the mid-line of an egg's profile) and the egg's maximum breadth. This provides a valuable approach for comparing egg shapes among conspecifics or across different species, or even different classes (e.g., birds and reptiles), in future investigations.

Abstract: Quantification of annular dark field (ADF) scanning transmission electron microscopy (STEM) images in terms
of composition or thickness often relies on probe-position integrated scattering cross sections (PPISCS). In
order to compare experimental PPISCS with theoretically predicted ones, expensive simulations are needed for
a given specimen, zone axis orientation, and a variety of microscope settings. The computation time of such
simulations can be in the order of hours using a single GPU card. ADF STEM simulations can be efficiently
parallelized using multiple GPUs, as the calculation of each pixel is independent of other pixels. However, most
research groups do not have the necessary hardware, and, in the best-case scenario, the simulation time will
only be reduced proportionally to the number of GPUs used. In this manuscript, we use a learning approach and
present a densely connected neural network that is able to perform real-time ADF STEM PPISCS predictions as
a function of atomic column thickness for most common face-centered cubic (fcc) crystals (i.e., Al, Cu, Pd, Ag,
Pt, Au and Pb) along [100] and [111] zone axis orientations, root-mean-square displacements, and microscope
parameters. The proposed architecture is parameter efficient and yields accurate predictions for the PPISCS
values for a wide range of input parameters that are commonly used for aberration-corrected transmission
electron microscopes.

Abstract: In this paper convexity constraints are derived for a background model of electron energy loss spectra (EELS) that is linear in the fitting parameters. The model outperforms a power-law both on experimental and simulated backgrounds, especially for wide energy ranges, and thus improves elemental quantification results. Owing to the model’s linearity, the constraints can be imposed through fitting by quadratic programming. This has important advantages over conventional nonlinear power-law fitting such as high speed and a guaranteed unique solution without need for initial parameters. As such, the need for user input is significantly reduced, which is essential for unsupervised treatment of large datasets. This is demonstrated on a demanding spectrum image of a semiconductor device sample with a high number of elements over a wide energy range.