Two-component Mixture Research Articles

Environmentally Friendly Diesel Fuel Obtained from Vegetable Raw Materials and Hydrocarbon Crude

Currently, the global issue for countries is the search for raw materials and the production of bioenergy within their country; bioenergy also includes biodiesel fuels. One of the most promising biodiesel fuels is the green diesel fuel produced by the hydrogenation of vegetable oils. Three methods have been proposed to obtain high-quality biodiesel and environmentally friendly diesel fuel: compounding green diesel with hydro-treated diesel fuel, compositions of the improved fuel «green diesel» with bio-additives, and two-component mixtures of environmentally friendly diesel fuel with bio-additives. Using these methods, it is possible to produce fuel for diesel engines with improved lubricating properties, the wear scar diameter is reduced to 232 microns, according to EN 590: 2009, this value standard is up to 460 microns. The optimal quantitative composition of three-component environmentally friendly diesel fuel with improved lubricity was established. The dependence of the change in the lubricating properties of environmentally friendly diesel fuel on the quantitative and qualitative composition are established. A mathematical equation describing the dependence of the change in the corrected wear spot on the amount of anti-wear additive in the green diesel fuel is derived. Three-component compositions of environmentally friendly diesel fuel make it possible to obtain fuel that meets the requirements of the EN 590: 2009 standard and to expand the resources for obtaining fuel, as well as to improve the environmental and operational characteristics of the fuel.

Variation of Spin-Transition Temperature in the Iron(III) Complex Induced by Different Compositions of the Crystallization Solvent

We crystallized the Schiff-base iron(III) spin-crossover complex [Fe(3,5Cl-L5)(NCSe)] from different two-component solvent mixtures containing methanol and chloroform (Φ = V(CH3OH)/V(solvent) = 0.05, 0.25, 0.50, 0.83, and 1.00). The obtained crystalline products were characterized by X-ray diffraction, and it was confirmed that they are all composed of the same crystalline phase, and they do not contain any crystal solvent. However, significant differences in magnetic properties were observed, and thermal hysteresis changed from (in K) 121T↓ and 134T↑ for Φ = 0.05 and 0.25, down to 72T↓ and 96T↑ for Φ = 1.00. The crystal structures of the low-spin and high-spin phases were studied theoretically and experimentally.

Study of Cationic Surfactants Raw Materials for COVID-19 Disinfecting Formulations by Potentiometric Surfactant Sensor.

The behavior of a new 1,3-dioctadecyl-1H-imidazol-3-ium tetraphenylborate (DODI-TPB) surfactant sensor was studied in single and complex mixtures of technical grade QACs-benzalkonium chloride (BAC), N,N-didecyl-N,N-dimethylammonium chloride (DDAC), and N,N-dioctyl-N,N-dimethylammonium chloride (DOAC) usually used in COVID-19 disinfecting agents formulations. The results obtained with the new DODI-TPB sensor were in good agreement with data measured by a 1,3-dihexadecyl-1H-benzo[d]imidazol-3-ium-tetraphenylborate (DMI-TPB) surfactant sensor, as well as two-phase titration used as a reference method. The quantitative titrations of a two-component mixture of the cationic homologs (a) DDAC and DOAC; and (b) BAC and DOAC showed that the new DODI-TPB surfactant sensor can clearly distinguish two separate mixture components in a single potentiometric titration curve with two characteristic inflexion points. The consumption of SDS (used as a titrant) in the end-point 1 (EP 1) corresponded to the content of DDAC (or BAC), whereas the consumption in the end-point 2 (EP 2) corresponded to the total content of both cationic surfactants in the mixture. DOAC content in both mixtures can be calculated from the difference of the titrant used to achieve EP1 and EP2. The addition of nonionic surfactants resulted in the signal change decrease from 333.2 mV (1:0; no nonionic surfactant added) to 243.0 mV (1:10, w/w). The sensor was successfully tested in ten two-component COVID-19 disinfecting formulations.

Physical determinants of multiphase organisation in multi-component protein/RNA condensates

The formation of biomolecular condensates via phase separation achieves spatiotemporal organisation within the cell by creating intracellular microenvironments that contribute to the regulation of chemical reactions. Internal subcompartmentalisation of biomolecules to form multiphase architectures has been observed in a number of biomolecular condensates, where immiscible liquid-like phases with different compositions coexist within the same compartment. Understanding the biophysical mechanisms that drive the formation of multiphase condensates is highly desirable since these condensates are responsible for mediating many fundamental biological processes. Here, we couple a genetic algorithm to our residue-resolution coarse-grained model, Mpipi, to evolve two-component protein mixtures towards increasing multiphasicity (i.e., demixing into two compositionally distinct liquid-like phases). Given a target protein, our method allows us to predict a partner protein that supports multiphasic compartmentalisation and investigate the underlying thermodynamics of the multiphasicity. We find that the balance of homo- and heterotypic interaction energies between the two components is important for controlling multiphase organisation: a large difference between homotypic interactions of the two components favours demixing, and the strength of heterotypic interactions should be small but comparable to that of the weaker homotypic interactions for multilayered condensates to form. Our approach for designing multilayered condensates achieves this balance of interaction energies by optimising the composition and patterning of the protein sequences. Lastly, since many multiphase condensates in cells contain RNA, we extend our approach to include RNA as a third component and investigate the role of protein-RNA interactions in stabilising condensates and multilayered architectures.

On the Spatial Distribution of Polarization and Color of a Distant Comet C/2017 K2 (PanSTARRS)

Comet C/2017 K2 (PanSTARRS) was observed at two wavelengths using two different-sized apertures in two measurement campaigns. We find that all the observations can be interpreted using a two-component mixture of dust composed of Mg-rich silicates and amorphous carbon. The modeling suggests a slight increase in the absorption of the refractory component at shorter wavelengths, which is consistent with the optical properties of Mg-rich silicates, and a change in the size distribution as a function of distance from the cometary nucleus, a result of smaller particles accelerating more rapidly from the expanding-gas and radiative-pressure forces.

Flood Frequency Analysis Using Mixture Distributions in Light of Prior Flood Type Classification in Norway

The fundamental assumption of flood frequency analysis is that flood samples are generated by the same flood generation mechanism (FGM). However, flood events are usually triggered by the interaction of meteorological factors and watershed properties, which results in different FMGs. To solve this problem, researchers have put forward traditional two-component mixture distributions (TCMD-T) without clearly linking each component distribution to an explicit FGM. In order to improve the physical meaning of mixture distributions in seasonal snow-covered areas, the ratio of rainfall to flood volume (referred to as rainfall–flood ratio, RF) method was used to classify distinct FGMs. Thus, the weighting coefficient of each component distribution was determined in advance in the rainfall–flood ratio based TCMD (TCMD-RF). TCMD-RF model was applied to 34 basins in Norway. The results showed that flood types can be clearly divided into rain-on-snow-induced flood, snowmelt-induced flood and rainfall-induced flood. Moreover, the design flood and associated uncertainties were also estimated. It is found that TCMD-RF model can reduce the uncertainties of design flood by 20% compared with TCMD-T. The superiority of TCMD-RF is attributed to its clear classification of FGMs, thus determining the weighting coefficients without optimization and simplifying the parameter estimation procedure of mixture distributions.

Statistical modeling of the sea surface in the presence of abnormal waves

A wide range of fundamental and applied problems requires a detailed description of the statistics of abnormal sea waves (freak waves or rouge waves). These waves are characterized not only by a change in ener-gy, but also by strong nonlinearity, leading to extreme values of the higher cumulants. The possibilities and limitations of modeling the probability density function (PDF) of sea surface elevations by a two-component Gaussian mixture at extreme values of skewness and excess kurtosis are analyzed. The parameters of a two-component Gaussian mixture are calcu-lated from known values of statistical moments. Model PDFs in the form of a two-component Gaussian mixture are compared with PDFs based on direct wave measurement data, and also compared with the known Gram-Charlier distribution. It is shown that with positive values of the excess kurtosis, the PDF in the form of a two-component Gaussian mixture can be constructed at the limit values of the skewness and excess kurtosis ob-tained in different regions of the World Ocean. With large negative values of the kurtosis, the shape of the probability density function is strongly dis-torted, which indicates the limit of applicability of a two-component Gaussian mixture to the description of such situations.

Оптимизация газовых смесей многополосных эксиламп

The paper considers the problem of optimizing gas-discharge sources of multiband UV radiation – excilamps. A method is proposed for estimating the ratio of partial pressures of the components of a gas mixture, which makes it possible to simplify the process of developing a multiband excilamp with the desired power ratio of the emission bands. It is shown that the optimization of a multiband excilamp on a mixture of one noble gas with several halogen carriers can be reduced to the problem of optimizing an excilamp on a two-component mixture. If, in addition to the radiation of exciplex molecules, the radiation of excimer molecules is of importance, then the method makes it possible to control the relative contribution of the powers emitted by these molecules.

Development and investigating parameters of fermented milk products based on various types of vegetable milk

Plant-based milks and fermented plant-based milk products are gaining popularity but may not possess the same physicochemical characteristics as the traditional fermented dairy products. The different chemical composition of plant-based milk affects the physicochemical and consumer acceptability of fermented plant-based milk. To compare their characteristics to the traditional dairy yoghurt and consumer acceptability, different fermented plant-based milk products were prepared as well as their two-component mixtures and their physicochemical and consumer acceptability evaluated. The single component fermented plant-based milk sample (soy milk) did not vary in terms of physicochemical parameters with respect to the traditional fermented dairy product, yoghurt. The physicochemical parameters including pH, water holding capacity, syneresis improved when the milk samples were composited and are comparable to the traditional fermented dairy product (yogurt). The results indicated that the use of two-component plant-based milk for fermentation provides the best nutritional and energy values for consumers rather than using just one component. Also, the high consumer acceptability for fermented plant-based milk was demonstrated from the findings.

Optimization of gas mixtures of multiband excilamps

The paper considers the problem of optimizing gas-discharge sources of multiband UV radiation --- excilamps. A method is proposed for estimating the ratio of partial pressures of the components of a gas mixture, which makes it possible to simplify the process of developing a multiband excilamp with the desired power ratio of the emission bands. It is shown that the optimization of a multiband excilamp on a mixture of one noble gas with several halogen carriers can be reduced to the problem of optimizing an excilamp on a two-component mixture. If, in addition to the radiation of exciplex molecules, the radiation of excimer molecules is of importance, then the method makes it possible to control the relative contribution of the powers emitted by these molecules. Keywords: gas discharge, sources of ultraviolet radiation, kinetics of plasma-chemical processes, excimer and exciplex molecules.

ANTIADHESION FLUOROCARBON COATINGS WITH INDUCED SURFACE CHARGE FOR PROTECTION AGAINST BIODEGRADATION

This paper analyzes the results of studying the antimicrobial properties of nanostructured fluorocarbon films deposited on polymers by ion-plasma technology. For the first time, the dependence of the surface charge and antimicrobial properties over time was established. As the negative charge drains, the number of colonies of the studied bacteria and fungi increases. Fluorocarbon films were formed using a two-component gas mixture (CF<sub>4</sub> + C<sub>6</sub>H<sub>12</sub>) with different ratios of components. Antimicrobial activity on fluorocarbon coatings is maintained for 12 months.

Non-intrusive diagnostics of differentially-heated two-component immiscible fluid layer with phase change

Experiments on buoyancy-driven convective phenomena in a differentially-heated two component immiscible fluid layer with phase change phenomena have been reported. The real-time mapping of the transients associated with the process has been affected in a complete non-intrusive manner using rainbow schlieren deflectometry. Experiments have been performed for varying heat flux levels supplied to the lower horizontal surface of the cavity and for different heights of the secondary fluid layer. The two-component immiscible fluid mixture comprises of water as the (lighter) primary fluid layer and dichloromethane (DCM) as the (heavier) secondary fluid component. The supplied heat flux levels are sufficient enough to induce phase change in the secondary fluid layer through nucleate pool boiling. In addition to the real-time mapping of the buoyancy-induced convection in both the fluid layers, the process of vapor bubble inception, their growth and departure from the lower heated wall of the cavity have been recorded in the form of time-lapsed schlieren images. Conditions under which the continued interaction of the vapor phase of DCM with the interface leads to interface deformation and its final breakage have been investigated. Based on the force balance analysis, the critical volume of the DCM vapor phase required for interface breakage has been determined. Dependence of parameters such as neck breakage height, time required for interface breakage etc. on the supplied heat flux level and height of the secondary fluid has been investigated. The experimental observations revealed the importance of vapor bubbles-induced fluid agitation in the otherwise stagnant primary fluid layer, disruption of the thermal boundary layer in a completely passive manner as the upward rising vapor volume condenses at the top horizontal surface of the differentially-heated cavity and their implications in possible heat transfer enhancement.

The fractional composition calculation of two-component mixtures using direct and scattered X-rays: a new methodology testing

Continuous monitoring and control of hydrocarbon flow is not a new task. Today, there are many engineering solutions in flow measurement that are used in commercial applications. However, the search for other solutions continues and is associated with the emergence of new technical challenges of the oil and gas industry. There is also a constant request for optimization of already working flow-metering solutions. In the present work we propose a methodology to calculate the composition of a mixture using gamma densitometry methods with direct and scattered radiation tracking. Experiments were carried out on reference samples and ways of practical implementation of the proposed methodology are shown.

Sparse Estimation in Finite Mixture of Accelerated Failure Time and Mixture of Regression Models with R Package fmrs

Variable selection in large-dimensional data has been extensively studied in different settings over the past decades. In a recent article, Shokoohi et. al. [29, DOI:10.1214/18-AOAS1198] proposed a method for variable selection in finite mixture of accelerated failure time regression models for studies on time-to-event data to capture heterogeneity within the population and account for censoring. In this paper, we introduce the fmrs package, which implements the variable selection methodology for such models. Furthermore, as a byproduct, the fmrs package facilitates variable selection in finite mixture regression models. The package also incorporates a tuning parameter selection mechanism based on component-wise bic. Commonly used penalties, such as Least Absolute Shrinkage and Selection Operator, and Smoothly Clipped Absolute Deviation, are integrated into fmrs. Additionally, the package offers an option for non-mixture regression models. The C language is chosen to boost the optimization speed. We provide an overview of the fmrs principles and the strategies employed for optimization. Hands-on illustrations are presented to help users get acquainted with fmrs. Finally, we apply fmrs to a lung cancer dataset and observe that a two-component mixture model reveals a subgroup with a more aggressive form of the disease, displaying a lower survival time.

Methane gas hydrates of the Black Sea – environmental problem or energy source?

Purpose. The purpose of this paper is to substantiate the technological solution of equilibrium conditions in the system “methane – water phase – hydrate – R-2M”; to reveal existing ecological problems of methane gas hydrate extraction from the Black Sea bottom; to determine whether gas hydrate deposits of Black Sea methane are an ecological problem or should be considered as an energy source, to explain the necessity of introduction of the effect of forced self-preservation of methane gas hydrates into development of gas hydrates from the sea bottom.
 Results. This article analyses current research on gas hydrates specifically in the Black Sea. It shows that the necessary conditions exist for the accumulation of gas hydrates in certain areas of the deep Black Sea (one of the most favourable regions among modern sea basins). This article discusses some ideas for the development of experimental studies of the metastable state of methane gas hydrates at negative temperatures: stability and mechanisms of decomposition. Despite the great variety of technological solutions and schemes of gas hydrates application proposed by the leading researchers in the world, they have been tested practically on a small number of laboratory and model installations, mainly for water desalination and concentration of water solutions, separation of two-component gas mixtures. In fact, there is no data to calculate the processes of formation and melting of ice-gas hydrate methane. The effect of self-preservation of methane gas hydrates deserves special attention.
 Scientific novelty. An attempt was made to substantiate the issue of whether gas hydrate deposits of methane in the Black Sea are an environmental problem or should they be considered as an additional source of energy and even as a “fuel of the future”. The authors for the first time introduced the concept of “forced preservation (activation) effect of methane gas hydrates”, which makes it possible to stabilize methane hydrate decomposition when the system is transferred from the area of hydrate stability to the area of thermodynamic parameters, thus significantly reducing the environmental problems of the Black Sea.
 Practical value. This article offers a technological solution for stabilization of equilibrium conditions by hydrophobic material “Ramsinks-2M” in the system “methane-water phase-hydrate-R-2M” to regulate the self-preservation effect of methane gas hydrates

Murine Fibroblasts and Primary Hepatocytes as Tools When Studying the Efficacy of Potential Therapies for Mucopolysaccharidosis Type I

Mucopolysaccharidosis type I (MPS I) is a metabolic genetic disease caused by the deficiency of a lysosomal enzyme involved in glycosaminoglycans (GAGs) degradation. MPS I cells have a constant level of GAG synthesis, but disturbed degradation means that GAGs accumulate progressively, impairing cell metabolism. GAG metabolism can be modulated by flavonoids, and these are being studied as therapeutics for MPS. We have optimised the protocol for obtaining fibroblasts and hepatocytes from the MPS I murine model and characterised the cells for their suitability as an in vitro model for testing compounds with therapeutic potential. Methods: Murine primary hepatocytes and fibroblasts were used as a cellular model to study the effect of genistein, biochanin A, and kaempferol on the modulation of the GAG synthesis process. Flavonoids were used individually as well as in two-component mixtures. There were no statistically significant differences in GAG synthesis levels from cell types obtained from either wild-type or MPS I mice. We also showed that MPS I fibroblasts and hepatocytes store GAGs, which makes them useful in vitro models for testing the effectiveness of substrate reduction therapies. Furthermore, tested flavonoids had a different impact on GAG synthesis depending on cell type and whether they were used alone or in a mixture. The tested flavonoids reduce GAG synthesis more effectively in fibroblasts than in hepatocytes, regardless of whether they are used individually or in a mixture. Flavonoids modulate the level of GAG synthesis differently depending on cell types, therefore in vitro experiments performed to assess the effectiveness of potential therapies for metabolic diseases should be carried out using more than one cell model, and only such an approach will allow for full answering scientific questions.

AlPO-18 membranes for CO2/CH4 and N2/CH4 separations

Microporous aluminophosphates are promising materials for gas separation, but their industrial applications are still challenging due to the permeability-selectivity “trade-off” behavior. A new approach is now reported by the addition of single novel template N, N-diisopropylethylamine (DIPEA) into the gel precursor to prepare the pure AlPO-18 membrane with both high permeance and selectivity. It was identified that the AlPO-18 membrane possessed small plate-like crystals on support surface. The single and mixed CO2/CH4 and N2/CH4 gas separations were measured. The best membrane exhibited high CO2 and N2 permeances of 9.2, 0.91 × 10−7 mol m−2 s−1∙Pa−1 under the two-component gas mixture, and the mixture selectivities in CO2/CH4 and N2/CH4 were 93 and 6.0 at 303 K and 0.2 MPa, respectively. This strategy not only demonstrated a potential zeolite membrane material for gas separation but also furnished ideas for the preparation of high permeable thin films.

Computational chromatography: A machine learning strategy for demixing individual chemical components in complex mixtures

Surface-enhanced Raman spectroscopy (SERS) holds exceptional promise as a streamlined chemical detection strategy for biological and environmental contaminants compared with current laboratory methods. Priority pollutants such as polycyclic aromatic hydrocarbons (PAHs), detectable in water and soil worldwide and known to induce multiple adverse health effects upon human exposure, are typically found in multicomponent mixtures. By combining the molecular fingerprinting capabilities of SERS with the signal separation and detection capabilities of machine learning (ML), we examine whether individual PAHs can be identified through an analysis of the SERS spectra of multicomponent PAH mixtures. We have developed an unsupervised ML method we call Characteristic Peak Extraction, a dimensionality reduction algorithm that extracts characteristic SERS peaks based on counts of detected peaks of the mixture. By analyzing the SERS spectra of two-component and four-component PAH mixtures where the concentration ratios of the various components vary, this algorithm is able to extract the spectra of each unknown component in the mixture of unknowns, which is then subsequently identified against a SERS spectral library of PAHs. Combining the molecular fingerprinting capabilities of SERS with the signal separation and detection capabilities of ML, this effort is a step toward the computational demixing of unknown chemical components occurring in complex multicomponent mixtures.

Semi-supervised learning from coarse histopathology labels

ABSTRACT Ultrasound imaging is commonly used to guide sampling the prostate tissue in transrectal biopsies, followed by detection of cancer through histopathological analysis and coarse labelling of sampled tissue. Ideally, the procedure should be improved by developing machine learning solutions that can identify the presence of cancer in ultrasound images to guide the biopsy procedure. Training a fully supervised learning model using coarse histopathology labels suffers from weakly annotated data which introduce label noise for each image pixel. To address this challenge, we propose a semi-supervised framework for learning with noisy labels. We leverage a two-component mixture model to cluster the training data into clean and noisy label samples based on their loss values. Then, during the semi-supervised training phase, we utilise the well-known MixMatch algorithm which incorporates consistency regularisation, entropy minimisation, and the Mixup regularisation as well as the cross-entropy loss function for noisy and clean sets, respectively. We evaluate the proposed framework with prostate ultrasound data obtained from 71 subjects, while sampling 264 biopsy cores. We achieve balanced accuracy, sensitivity, and specificity of 78.6%, 80.0%, and 77.1%, respectively. In a detailed comparison study, we demonstrate that our proposed framework outperforms the fully supervised method with state-of-the-art robust loss functions.

Adsorption and diffusion behavior of two-component gases in coal particles at different temperatures

Oxygen (O2) plays a crucial role in the occurrence and progression of coal spontaneous combustion (CSC), but the diffusion behaviors of O2 and oxygen-containing gas mixtures (e.g., CO2-O2) in the microchannels of coal under different temperatures have involved little investigation. In this work, isothermal adsorption experiments of two-component gas mixtures at different temperatures (293 K-333 K) were first carried out. A two-component gas mixture adsorption model for coal particles based on the free gas density gradient (FGDG) diffusion was then developed. The cumulative gas adsorption was obtained by numerical solution and the microchannel diffusion coefficients (Fm) of single-component gases in gas mixtures were obtained by comparing the simulation results with the experimental data. The results show that: (i) the equilibrium cumulative adsorption of three types of gas mixtures decreases with the increase of temperature, and their cumulative adsorption satisfies our proposed empirical equation; (ii) the simulation results of strongly adsorbed single-component gases are in high agreement with the experimental data throughout the adsorption period, and the developed model is verified. It also indicates that the model can characterize the migration behavior of single-component gas in coal particles under different temperature conditions; (iii) the Fm of a single-component gas will gradually increase as the temperature increases, leading to further enhancement of diffusion behavior of the gas. This research is expected to provide some theoretical foundations for understanding the mechanisms of gas mixtures flowing in coal matrices under different temperature environments.