Arbitrary Composition Research Articles

Testing the accretion scenario of λ Boo stars

Context. The existence of a group of λ Boo stars has been known for years, however, the origin of its chemical peculiarity is still a matter of debate. Aims. Our aim is to test the accretion scenario of λ Boo stars. This model predicts that in a binary system with two early-type stars passing through a diffuse cloud, both stars ought to display the same superficial peculiarity. Methods. Via spectral synthesis, we carried out a detailed abundance determination of three multiple systems hosting a candidate λ Boo star: the remarkable triple system HD 15164/65/65C and the two binary systems HD 193256/281 and HD 198160/161. The stellar parameters were initially estimated using Strömgren photometry or literature values and then refined by requiring excitation and ionization balances for Fe lines. The abundances were determined iteratively for 24 different species by fitting synthetic spectra using the SYNTHE program together with local thermodynamic equilibrium (LTE) ATLAS12 model atmospheres. Specific opacities were calculated for each star, depending on its arbitrary composition and microturbulence velocity, υmicro, through the opacity sampling method. The abundances of the light elements C and O were corrected by non-LTE effects. The complete chemical patterns of the stars were then compared to those of λ Boo stars. Results. The abundance analysis of the triple system HD 15164/65/65C shows a clear λ Boo object (HD 15165) and two objects with a near-solar composition (HD 15164 and 15165C). Notably, the presence of a λ Boo star (HD 15165) together with a near-solar early-type object (HD 15164) is difficult to explain under the accretion scenario. Also, the solar-like composition derived for the late-type star of the system (HD 15165C) could be used, for the first time, as a proxy for the initial composition of the λ Boo stars. This could help to constrain any model of λ Boo stars formation – not only the accretion scenario. The abundance analysis of the binary system HD 193256/281 shows no clear λ Boo components, while the analysis of HD 198160/161 shows two mild-λ Boo stars. Then, by carefully reviewing the abundance analysis of all known binary systems with candidate λ Boo stars from literature and including the systems analyzed here, we find no binary or multiple system having two clear bona fide λ Boo stars, as would expected from the accretion scenario. The closest candidates to exhibiting two λ Boo-like stars are the binary systems HD 84948, HD 171948, and HD 198160; however we find that they show mild, rather than clear, λ Boo patterns. Conclusions. We performed, for the first time, a complete analysis of a triple system that includes a λ Boo candidate. Our results brings little support to the accretion scenario of λ Boo stars. Furthermore, there is an urgent need for additional binary and multiple systems to be analyzed via a detailed abundance analysis in order to test the accretion model of λ Boo stars.

Implementation of multi-component Zhdanov closure in SOLEDGE3X

The multi-component fluid closure derived by Zhdanov (2002 Transport Processes in Multicomponent Plasma (London: Taylor and Francis)) is implemented in the fluid code SOLEDGE3X-EIRENE to deal with arbitrary edge plasma composition. The closure assumes no distinction between species such as light versus heavy species separation. The work of Zhdanov is rewritten in a matricial form in order to clearly link friction forces and heat fluxes to the different species velocities and temperature gradients.

Temperature-responsive mixed-mode column for the modulation of multiple interactions

In this study, mixed-mode chromatography columns have been investigated using multiple analyte interactions. A mixed-mode chromatography column was developed using poly(N-isopropylacrylamide) (PNIPAAm) brush-modified silica beads and poly(3-acrylamidopropyl trimethylammonium chloride) (PAPTAC) brush-modified silica beads. PNIPAAm brush-modified silica beads and PAPTAC brush-modified silica beads were prepared by atom transfer radical polymerization. The beads were then packed into a stainless-steel column in arbitrary compositions. The elution studies evaluated the column performance on hydrophobic, electrostatic, and therapeutic drug samples using steroids, adenosine nucleotide, and antiepileptic drugs as analytes, respectively. Steroids exhibited an increased retention time when the column temperature was increased. The retention of adenosine nucleotides increased with the increasing composition of the PAPTAC-modified beads in the column. The antiepileptic drugs were separated using the prepared mixed-mode columns. An effective separation of antiepileptic drugs was observed on a 10:1 PNIPAAm:PAPTAC column because the balance between the hydrophobic and electrostatic interactions with antiepileptic drugs was optimized for the bead composition. Oligonucleotides were also separated using mixed-mode columns through multiple hydrophobic and electrostatic interactions. These results demonstrate that the developed mixed-mode column can modulate multiple hydrophobic and electrostatic interactions by changing the column temperature and composition of the packed PNIPAAm and PAPTAC beads.

Simulation of the Impact of Point Defects and Edge Dislocations on X‐Ray Diffraction in Hexagonal (Ni,Co)1+2xTi1−xO3 Thin Films

A computer code for simulating high‐resolution X‐ray diffraction (XRD) data from disordered crystals with arbitrary spatial composition and local lattice parameters is developed. Simulated patterns are compared with the experimental data collected on a single phase, highly crystalline (Ni0.42Co0.58)2.22Ti0.39O3 solid‐solution thin film exhibiting a large number of subsidiary minima. As a case study, the edge dislocations in hexagonal (Ni,Co)3O3 thin films with Burgers vector parallel and perpendicular to the a‐axis and c‐axis, respectively, are modeled. No peak profiles are assumed and thus issues related to profile fitting are avoided. Both macroscopic features, such as film thickness, and atomic‐scale structure, such as dislocations, are simultaneously modeled. Simulations are run on a desktop machine. Commonly applied database‐based phase identification routines can result in wrong phase identification, unless intensities are properly modeled. Modeling tools of diffractometer manufacturers are compared with the present approach. An example of how simulated reciprocal lattice patterns can be used to choose relevant measurement geometries in defected thin films is given.

Optimum distribution of materials for functionally graded rectangular plates considering thermal buckling

Metal–ceramic functionally graded (FG) materials are suitable for constructing structures subjected to a very high-temperature gradient. The composition of the FG materials constituents impacts the thermal buckling of the FG plates. Different forms of the composition for the FG plates have been proposed in the literature. In this paper, using the Carrera unified formulation, a higher-order plate theory, in the finite element method framework, the thermal buckling of rectangular FG plates with arbitrary composition distribution along thickness has been formulated using the linearized buckling analysis method. Three different composition forms: power, bilinear, and piecewise cubic interpolation polynomials (PCHIP), have been adopted for optimization. The optimization results show that the higher the degrees of freedom associated with the composition distribution, the higher the critical buckling temperature of the plate. In addition, the obtained optimum distributions are independent of the geometric ratios and the boundary conditions of the FG plates.

Mori-Tanaka experimental-analytical model for predicting engineering elastic moduli of composite materials

An experimental-analytical model of homogenised elastic moduli of matrix composites has been developed based on the Mori-Tanaka analytical model. The fitting parameter of the model is the ratio of the constrained strains of the experimental sample matrix and the model composite and is determined by one experimental point for the basic composition of the composite. A linear dependence of the fitting parameter on the volume fraction of inclusions is used for composites of arbitrary composition. Good agreement is obtained between the calculation results and experimental data for isotropic and transversally isotropic composites.

Математическая модель для имитационной реализации функционирования системы противовоздушной обороны соединения надводных кораблей

The article considers the stages of the logical-time cyclogram of detection and maintenance of groups of controlled objects by means of the air defense system of a naval surface force. An algorithm for forming arrays of detected objects is implemented, taking into account the impulse volume, the coverage sector to accompany all detected objects and other configuration factors, considering probabilistic estimates of the detection of controlled objects. A mathematical model of the functioning of the naval surface force air defense system has been created, taking into account various parameters of active means affecting the groups of controlled objects, as well as taking into account firing strategies in the presence of network-centric control of the order of controlled objects. An algorithm for evaluating the results of fire counteraction of a network-centric group of controlled objects on the part of the air defense system of a naval surface force has been considered. A variant of the simulation implementation of the logical-time cyclogram of the operation of air defense system fire channels has been developed, and examples of the implementation of a logical-time cyclogram for an arbitrary composition of the air defense system are given, taking into account the strategic actions of active means of a naval surface force. Additional conditions for embedding the developed version of the algorithm of the air defense system logical-time cyclogram into the system for simulating the conflict interaction of systems are listed

The significant impact of shape deviations of atmospheric aerosols on light monitoring networks

ABSTRACT Aerosol particles are important modulators of night sky brightness (NSB) due to their manifold impacts on spectral and angular properties of scattered light. The majority of radiative transfer models currently in use are based on rigorous Mie theory for spherical homogeneous particles. This fundamental concept enables significant simplifications in theoretical formulae and numerical modelling. However, as known from many studies, spherical shapes are rare for both natural and anthropogenic aerosols. Therefore, the aim of this paper is to analyse the potential magnitude of the subsequent effect in skyglow modelling assuming that the aerosol particles are of different aspect ratios. The zero-order approximation to tackle the problem is to characterize the non-sphericity by the ratio of the largest to smallest size of an ellipsoidal particle. We use T-matrix formalism to perform light scattering calculations on spheroidal particles of arbitrary size, composition, and orientation in respect to the incident light. Results indicate that the particle-shape impact on NSB can be of significant size leading to both positive and negative amplitudes around the zenith. In the most extreme case, an increase of up to 70 per cent in zenithal luminance was displayed. As a consequence, especially light monitoring devices like the sky quality meter, usually measuring the NSB around the zenith, are particularly influenced by this effect. In summary, the paper underlines both the importance of treating non-spherical aerosols in theoretical modelling of skyglow and also the significance of including atmospheric parameters to analyses of light monitoring networks.

Computational Indicator Approach for Assessment of Nanotoxicity of Two-Dimensional Nanomaterials.

The increasing growth in the development of various novel nanomaterials and their biomedical applications has drawn increasing attention to their biological safety and potential health impact. The most commonly used methods for nanomaterial toxicity assessment are based on laboratory experiments. In recent years, with the aid of computer modeling and data science, several in silico methods for the cytotoxicity prediction of nanomaterials have been developed. An affordable, cost-effective numerical modeling approach thus can reduce the need for in vitro and in vivo testing and predict the properties of designed or developed nanomaterials. We propose here a new in silico method for rapid cytotoxicity assessment of two-dimensional nanomaterials of arbitrary chemical composition by using free energy analysis and molecular dynamics simulations, which can be expressed by a computational indicator of nanotoxicity (CIN2D). We applied this approach to five well-known two-dimensional nanomaterials promising for biomedical applications: graphene, graphene oxide, layered double hydroxide, aloohene, and hexagonal boron nitride nanosheets. The results corroborate the available laboratory biosafety data for these nanomaterials, supporting the applicability of the developed method for predictive nanotoxicity assessment of two-dimensional nanomaterials.

Quantum Machine Learning Approach for Studying Atmospheric Cluster Formation

Quantum chemical (QC) calculations can yield direct insight into an atmospheric cluster formation mechanism and cluster formation rates. However, such calculations are extremely computationally demanding as more than millions of cluster configurations might exist and need to be computed. We present an efficient approach to produce high quality QC data sets for applications in cluster formation studies and how to train an accurate quantum machine learning model on the generated data. Using the two-component sulfuric acid─water system as a proof of concept, we demonstrate that a kernel ridge regression machine learning model with Δ-learning can be trained to accurately predict the binding energies of cluster equilibrium configurations with mean absolute errors below 0.5 kcal mol–1. Additionally, we enlarge the training data set with nonequilibrium configurations and show the possibility of predicting the binding energies of new structures of clusters several molecules larger than those in the training set. Applying the trained machine learning model leads to a drastic reduction in the number of relevant clusters that need to be explicitly evaluated by QC methods. The presented approach is directly transferable to clusters of arbitrary composition and will lead to faster and more efficient exploration of the configurational space of new cluster systems.

A dual number abstraction for static analysis of Clarke Jacobians

We present a novel abstraction for bounding the Clarke Jacobian of a Lipschitz continuous, but not necessarily differentiable function over a local input region. To do so, we leverage a novel abstract domain built upon dual numbers, adapted to soundly over-approximate all first derivatives needed to compute the Clarke Jacobian. We formally prove that our novel forward-mode dual interval evaluation produces a sound, interval domain-based over-approximation of the true Clarke Jacobian for a given input region. Due to the generality of our formalism, we can compute and analyze interval Clarke Jacobians for a broader class of functions than previous works supported – specifically, arbitrary compositions of neural networks with Lipschitz, but non-differentiable perturbations. We implement our technique in a tool called DeepJ and evaluate it on multiple deep neural networks and non-differentiable input perturbations to showcase both the generality and scalability of our analysis. Concretely, we can obtain interval Clarke Jacobians to analyze Lipschitz robustness and local optimization landscapes of both fully-connected and convolutional neural networks for rotational, contrast variation, and haze perturbations, as well as their compositions.

ESSAY AS A PRIORITY GENRE OF ACADEMIC WRITING

The article is devoted to the understanding of the essay as a genre, which is of exceptional importance for the "Academic Writing" course. It is noted that the origins of the essay genre can be traced in the works of ancient authors (Plato, Isocrates, Marcus Aurelius), famous philosophers of the past (J. Addison, Voltaire, D. Diderot, H.-E. Lessing, J. Locke, O. Goldsmith, G. Frying pan, etc.). Later, the genre received its logical continuation in the work of foreign artists (H. Wells, J. Galsworthy, T.-S. Eliot, A. Camus, G. and T. Mann, J. P. Sartre, B. Shaw, etc.) and Ukrainian authors representing various literary periods and currents (Yu. Andruhovych, V. Vynnycheko, O. Honchar, I. Drach, M. Dochynets, E. Malanyuk, Yu. Lypa, U. Samchuk, T. Shevchenko, Yu. Shereh, etc.). It was determined that in the scientific discourse, an essay is traditionally understood as a prose work with an arbitrary composition, which is characterized by the fictionalization of recorded individual impressions, associations or information obtained from various fields of knowledge, an unsystematic combination of philosophical, literary-critical, popular science, and sometimes specifically scientific elements. The research emphasizes the desire of modern researchers to distinguish the meaning of the terms “essay” and “academic essay”, which is explained by practical needs, since the concepts function in different planes (fiction and teaching methods). The article focuses attention on the integration of the literary concept into the field of methodology. It has been found that in modern scientific studios, attention to the essay as a priority type of work in classes on the “Academic Writing” is increasing. This is explained by the orientation towards foreign models of the organization of the educational process. It is noted that at Sumy State University, during classes on the “Fundamentals of Academic Writing” course, studying the features of the essay genre is a priority. After acquiring theoretical knowledge, students represent creative work, thanks to which written and oral scientific communication is activated, and, therefore, the goal of the educational discipline is realized.

Multi-material additive manufacturing of thermocouples by laser-based powder bed fusion

Multi-material additive manufacturing by laser-based powder bed fusion (PBF-LB) enables arbitrary material composition in components and thus enables the manufacturing of so-called smart parts. By combining different materials sensoric structures can be implemented into components. This paper investigates the possibilities to manufacture thermocouples (TC) consisting of two nickel-based alloys by the means of PBF-LB. These alloys are qualified to achieve sufficient relative densities for the thermocouples. Furthermore, the electrical conductivity of the parts is measured and compared to literature values. Finally, additively manufactured thermocouples are tested in comparison to conventional thermocouples in the temperature range from 50 to 350°C.

PH-metric method for determining the solubility and solubility products of slightly soluble hydroxides and acids

In this paper, original methods for determining such thermodynamic characteristics as solubility K S0 product (KS) or the activity product ( )of slightly soluble hydroxides and acids are communicated. Developed methods for determining KS and solubility S are based only on the pH values of the saturated aqueous solution for a known initial composition of the heterogeneous mixture and the equilibrium constants of an arbitrary set of possible side reactions in the aqueous natural systems. The determination of solubility S and solubility product KS is also possible in the presence of other hydroxides or acids of known concentrations. Deduced equations allow the calculation of such characteristics, as the equilibrium concentrations of the components of slightly soluble compounds in aqueous phase and the degree of precipitation γ of the solid phase for various initial concentrations of the components of the heterogeneous mixture which are known in the process of preparing the mixture, requiring only experimental pH values of a saturated solution. From the known experimental pH data, S and KS were calculated for a series of hydroxides and acids of arbitrary composition. The obtained results correlated well with the known tabular values. Analysis of a number of real systems illustrated the deduced expressions, including calculations and theoretical explanations.

PH-metric method determining the solubility and solubility products of slightly soluble salts of arbitrary composition

The developed method of determining KS from pH metric data has a number of advantages compared to those used traditionally. First, in place of the residual concentrations of the salt components, only the pH value of the saturated solution is used in the derived expressions. Thus, the number of independent variables, which need to be measured experimentally, is reduced. Furthermore, the potentiometric method, used to determine the pH, is sufficiently accurate, simple and universal and does not necessitate the use of ion-selective electrodes. At the same time, the residual concentrations are usually measured by chemical methods, which are inferior in most cases, for several reasons, compared to the potentiometric method. Second, the KS value calculated by the developed method has a thermodynamic character. The organization of the experiment must be appropriate to the applied equations. Therefore, it is necessary to draw attention to the need for high accuracy in the process of preparing the initial solutions, because the initial concentrations of the precipitate components are included in the calculation formulas. The developed method for determining Ks can be applied for systems of any degree of complexity, which contain additional complexing agents.

Wetting ridge assisted programmed magnetic actuation of droplets on ferrofluid-infused surface

Flexible actuation of droplets is crucial for biomedical and industrial applications. Hence, various approaches using optical, electrical, and magnetic forces have been exploited to actuate droplets. For broad applicability, an ideal approach should be programmable and be able to actuate droplets of arbitrary size and composition. Here we present an “additive-free” magnetic actuation method to programmably manipulate droplets of water, organic, and biological fluids of arbitrary composition, as well as solid samples, on a ferrofluid-infused porous surface. We specifically exploit the spontaneously formed ferrofluid wetting ridges to actuate droplets using spatially varying magnetic fields. We demonstrate programmed processing and analysis of biological samples in individual drops as well as the collective actuation of large ensembles of micrometer-sized droplets. Such model respiratory droplets can be accumulated for improved quantitative and sensitive bioanalysis - an otherwise prohibitively difficult task that may be useful in tracking coronavirus.

Self‐Assembly of All‐DNA Rods with Controlled Patchiness

AbstractDouble‐stranded DNA (dsDNA) fragments exhibit noncovalent attractive interactions between their tips. It is still unclear how DNA liquid crystal self‐assembly is affected by such blunt‐end attractions. It is demonstrated that stiff dsDNA fragments with moderate aspect ratio can specifically self‐assemble in concentrated aqueous solutions into different types of smectic mesophases on the basis of selectively screening of blunt‐end DNA stacking interactions. To this end, this type of attractions are engineered at the molecular level by constructing DNA duplexes where the attractions between one or both ends are screened by short hairpin caps. All‐DNA bilayer and monolayer smectic‐A type of phases, as well as a columnar phase, can be stabilized by controlling attractions strength. The results imply that the so far elusive smectic‐A in DNA rod‐like liquid crystals is a thermodynamically stable phase. The existence of the bilayer smectic phase is confirmed by Monte‐Carlo simulations of hard cylinders decorated with one attractive terminal site. This work demonstrates that DNA blunt‐ends behave as well‐defined monovalent attractive patches whose strength and position can be potentially precisely tuned, highlighting unique opportunities concerning the stabilization of nonconventional DNA‐based lyotropic liquid crystal phases assembled by all‐DNA patchy particles with arbitrary geometry and composition.

Semicomputational calculation of Bragg shift in stratified materials.

The fiber Bragg grating (FBG) may be viewed as a one dimensional photonic band-gap crystal by virtue of the periodic spatial perturbation imposed on the fiber core dielectric material. Similar to media supporting Bloch waves, the engraved weak index modulation, presenting a periodic "potential" to an incoming guided mode photon of the fiber, yields useful spectral properties that have been the basis for sensing applications and emerging quantum squeezing and solitons. The response of an FBG sensor to arbitrary external stimuli represents a multiphysics problem without a known analytical solution despite the growing use of FBGs in classical and quantum sensing and metrology. Here, we study this problem by first presenting a solid mechanics model for the thermal and elastic states of a stratified material. The model considers an embedded optical material domain that represents the Bragg grating, here in the form of an FBG. Using the output of this model, we then compute the optical modes and their temperature- and stress-induced behavior. The developed model is applicable to media of arbitrary shape and composition, including soft matter and materials with nonlinear elasticity and geometric nonlinearity. Finally, we employ the computed surface stress and temperature distributions along the grating to analytically calculate the Bragg shift, which is found to be in reasonable agreement with our experimental measurements.

Towards stacking fault energy engineering in FCC high entropy alloys

Stacking Fault Energy (SFE) is an intrinsic alloy property that governs much of the plastic deformation mechanisms observed in fcc alloys. While SFE has been recognized for many years as a key intrinsic mechanical property, its inference via experimental observations or prediction using, for example, computationally intensive first-principles methods is challenging. This difficulty precludes the explicit use of SFE as an alloy design parameter. In this work, we combine DFT calculations (with necessary configurational averaging), machine-learning (ML) and physics-based models to predict the SFE in the fcc CoCrFeMnNiV-Al high-entropy alloy space. The best-performing ML model is capable of accurately predicting the SFE of arbitrary compositions within this 7-element system. This efficient model along with a recently developed model to estimate intrinsic strength of fcc HEAs is used to explore the strength–SFE Pareto front, predicting new-candidate alloys with particularly interesting mechanical behavior.

On prediction of melting points without computer simulation: A focus on energetic molecular crystals

Melting point is one of the most important characteristics for molecular engineering of energetic materials. Therefore, methods for prediction of this physical property are essential to the field. In this paper, we have developed two models for prediction of melting point of energetic molecular crystals. The first one uses two parameters (lattice energy and crystal density) and grounds on the correlation of 200 compounds. The second model does not use any calculated quantities (only tabulated data) and is based on 1500 compounds. The first model needs separate calibrations for specific families of compounds; for nitroaromatic compounds, aliphatic nitro- and nitrato compounds and peroxides it provides R2 = 0.82–0.85 and RMSE ≥ 21–54 °C, respectively. Meanwhile, Model 2 is a more universal, but less accurate approach and it was tested for 747 energetic materials of different families providing R2 = 0.62 and RMSE ≥ 64 °C. This makes Model 2 a simple and convenient tool for a fast crude estimation of melting point of a desired energetic molecular crystal using a pocket calculator. Since Model 2 does not need quantum-chemical calculations, it can be effectively applied for any arbitrary composition. In the present work, however, we have considered compounds with a restricted number of constituting elements: C–H–N–O–S–F–Cl–Br–I. Nevertheless, extension of Model 2 is a simple procedure, which assumes estimation of so-called effective densities for other elements via regression analysis of experimentally available data on melting points.