A control volume finite element method for three-dimensional three-phase flows

A novel control volume finite element method with adaptive anisotropic unstructured meshes is presented for three-dimensional three-phase flows with interfacial tension. The numerical framework consists of a mixed control volume and finite element formulation with a new P₁DG-P₂ elements (linear discontinuous velocity between elements and quadratic continuous pressure between elements). A “volume of fluid” type method is used for the interface capturing, which is based on compressive control volume advection and second-order finite element methods. A force-balanced continuum surface force model is employed for the interfacial tension on unstructured meshes. The interfacial tension coefficient decomposition method is also used to deal with interfacial tension pairings between different phases. Numerical examples of benchmark tests and the dynamics of three-dimensional three-phase rising bubble, and droplet impact are presented. The results are compared with the analytical solutions and previously published experimental data, demonstrating the capability of the present method.     

Computational analysis of the SARS-CoV-2 and other viruses based on the Kolmogorov’s complexity and Shannon’s information theories

Nonlinear Dynamics - This paper tackles the information of 133 RNA viruses available in public databases under the light of several mathematical and computational tools. First, the formal concepts...     

K-line X-ray fluorescence from highly charged iron ions under dense astrophysical plasma conditions

In the present work, we report an investigation of plasma environment effects on the atomic parameters associated with the K-vacancy states in highly charged iron ions within the astrophysical context of accretion disks around black holes. More particularly, the sensitivity of K-line X-ray fluorescence parameters (wavelengths, radiative transition probabilities, and Auger rates) in Fe XVII–Fe XXV ions has been estimated for plasma conditions characterized by an electron temperature ranging from 10⁵ to 10⁷ K and an electron density ranging from 10¹⁸ to 10²² cm⁻³. In order to do this, relativistic multiconfiguration Dirac-Fock atomic structure calculations have been carried out by considering a time averaged Debye-Hückel potential for both the electron–nucleus and electron–electron interactions.     

Self-assembling and phase coexistence of SW trimers as complex amphiphile analogues. I. Simulations

We analyse by discrete molecular dynamics the self-assembly of SW trimer particles that contain a different number of attractive and repulsive spheres. They also have different geometries: linear, obtuse, rectangular and equilateral. We identify that some of these molecules exhibit liquid–vapour equilibria while others do not. For all of them, we show the morphological phase diagram built up from the different supra-molecular structures formed by each type of trimer. We simulated 14 different systems with a total of 321 states. The main features of the supra-molecular structures depend only on the composition and geometry of the trimer: triple SW trimers do not form supra-structures, double SW trimers and single SW trimers form monolayers, bilayers and worm-like micelles. The liquid–vapour coexistence properties are also exhibited. These trimers can be used to model complex amphiphiles beyond the standard ones, such as the Gemini and the Bola surfactants as well as colloidal particles.     

Simulation of the ion beam-plasma interaction processes for point-like ions in doped DT plasmas

The purpose of this work is to study the interaction between an ion beam and a doped deuterium-tritium (DT) plasma in a fast ignition nuclear fusion context. In order to analyze the influence of the dopants in the interaction process, we present a physical model to carry out spatial-temporal simulations of the stopping of an ion beam interacting with a doped plasma target, the plasma heating processes, and the formation of the ignition regions. We perform a set of numerical experiments where different concentrations of dopants are added to a fully ionized DT plasma. These simulations allow us to characterize the increase in the stopping power and the maximum temperatures achieved with the presence of impurities, as well as the reduction of the heated and ignition regions. This reduction in the ignition region indicates difficulties for the formation of an efficient hot spot when there are dopants in the DT plasma.     

Comparison of two cold atmospheric pressure plasma jet configurations in argon

The present study compares the operation of two cold atmospheric plasma jet (CAPJ) configurations: needle-to-cylinder electrode configuration (CAPJ I) and single high-voltage cylinder electrode around the quartz tube (CAPJ II). The CAPJs were operated in argon flowing through a quartz capillary with 0.5-mm inner diameter into the ambient air, and the plasma was generated by sinusoidal kHz frequency AC power supplies. The main emphasis of the study was on the mechanism of the initiation of ionization waves for these two configurations. For both CAPJs, there appeared several ionization waves during one half-period of the applied voltage waveform, and the number of ionization waves increased at higher voltage amplitudes. However, we discovered marked differences in the initiation of the ionization waves for two different CAPJ configuration. The applied voltage controlled the initiation of consecutive ionization waves, which propagated from the grounded electrode towards the tube orifice in CAPJ I. In the case of CAPJ II, certain time had to pass for the initiation of a new ionization wave, and subsequent ionization waves within the same half-period started at the tube orifice. In addition to the differences in the initiation of the ionization waves, we observed that the CAPJ I was ignited and sustained at lower voltages, while CAPJ II produced a longer plasma jet. The observed advantages and deficiencies of investigated CAPJ configurations point out their potential in different applications.     

Optimization of STEM-HAADF Electron Tomography Reconstructions by Parameter Selection in Compressed Sensing Total Variation Minimization-Based Algorithms

A novel procedure to optimize the 3D morphological characterization of nanomaterials by means of high angle annular dark field scanning-transmission electron tomography is reported and is successfully applied to the analysis of a metal- and halogen-free ordered mesoporous carbon material. The new method is based on a selection of the two parameters (μ and β) which are key in the reconstruction of tomographic series by means of total variation minimization (TVM). The parameter-selected TVM reconstructions obtained using this approach clearly reveal the porous structure of the carbon-based material as consisting of a network of parallel, straight channels of ≈6 nm diameter ordered in a honeycomb-type arrangement. Such an unusual structure cannot be retrieved from a TVM 3D reconstruction using default reconstruction values. Moreover, segmentation and further quantification of the optimized 3D tomographic reconstruction provide values for different textural parameters, such as pore size distribution and specific pore volume that match very closely with those determined by macroscopic physisorption techniques. The approach developed can be extended to other reconstruction models in which the final result is influenced by parameter choice.     

Enhanced Growth of Nonpolar {001} Growth Sectors of Deuterated Triglycine Sulphate Doped with L-Alanine (LADTGS)

The crystals of deuterated triglycine sulphate substituted with L-alanine (LADTGS) were grown from nonpolar {001} growth sectors by four different methods. 35 mol% of L-alanine (LA) in the growth solution give a stable unipolarity of the crystals. A distribution of LA was measured by the electrical switching method using “hysteresis current” loops. A defect structure was observed in a microscope on the etched surface of crystals. Most uniform crystals have been obtained using an isothermal method without stirring of the growth solutions.     

Machine Learning Algorithm to Predict Acidemia Using Electronic Fetal Monitoring Recording Parameters

Background: Electronic fetal monitoring (EFM) is the universal method for the surveillance of fetal well-being in intrapartum. Our objective was to predict acidemia from fetal heart signal features using machine learning algorithms. Methods: A case–control 1:2 study was carried out compromising 378 infants, born in the Miguel Servet University Hospital, Spain. Neonatal acidemia was defined as pH < 7.10. Using EFM recording logistic regression, random forest and neural networks models were built to predict acidemia. Validation of models was performed by means of discrimination, calibration, and clinical utility. Results: Best performance was attained using a random forest model built with 100 trees. The discrimination ability was good, with an area under the Receiver Operating Characteristic curve (AUC) of 0.865. The calibration showed a slight overestimation of acidemia occurrence for probabilities above 0.4. The clinical utility showed that for 33% cutoff point, missing 5% of acidotic cases, 46% of unnecessary cesarean sections could be prevented. Logistic regression and neural networks showed similar discrimination ability but with worse calibration and clinical utility. Conclusions: The combination of the variables extracted from EFM recording provided a predictive model of acidemia that showed good accuracy and provides a practical tool to prevent unnecessary cesarean sections.