Theoretical Foundations of Chemical Engineering最新文献

The article provides data on the composition of solutions obtained on the basis of experimental laboratory modeling of physical-chemical interactions in the “water–material” waste dump system. Long-term storage of gold cyanidation cakes in the tailings of gold-processing factories can lead to the pollution of surface water bodies. This pollution is a result of active and passive interaction of atmospheric precipitation with the waste material. The solution in equilibrium with the leaching cakes has a pronounced alkaline reaction with a pH value of >9.0. During the first storage period the pH of the solutions increases as a result of hydrolysis reactions of excess reagent cyanides of alkali or alkaline-earth metals. Then the solution pH is observed to decrease gradually towards the end of the first month of experimental observation. Sulphate ions, formed by the oxidation of metal sulphides in an alkaline medium; cyanide ions; and heavy metal ions are accumulated in the solution due to the destruction of cyanide complexes with heavy metal ions, such as copper, zinc, cobalt, etc. The presence of arsenic in the drainage solutions in concentrations exceeding the maximum allowable concentration (MAC) is caused by oxidation of arsenopyrite contained in the source ore. Physical-chemical interactions result in exceeding of the MAC established for fisheries in the drainage water for copper, cobalt, zinc, vanadium, chromium, molybdenum, and wolframium. Taking into account that the majority of the water bodies in Kamchatka are spawning waters, it is recommended to treat drainage water using sorption methods. Local mineral aluminosilicate raw materials such as zeolites, which have an increased sorption capacity in neutral and slightly alkaline media, can be recommended to use as sorbents.

Quantum dots (QDs) are nanoscale semiconductor particles. They are promising objects of research in nanotechnology and materials science due to their special physical and chemical properties. An important role in the application of QD is played by the modification of their surface by specific substances to increase stability, change optical and magnetic properties, and give the particles improved characteristics. Therefore, the study of the interaction between QD and surface agents (SA) is an interesting task. Experimental analysis of such materials is complicated by the cost and complexity of their synthesis. Thus, quantum-chemical simulation methods are used to facilitate the studies. Such methods allow us to infer the molecular structure and physico-chemical properties of a substance with known accuracy. In this work, we use the Hartree–Fock method and density functional theory with different functionals and basis sets to simulate the molecular structure and some properties of SA. Semiempirical approaches are used for modeling the interactions between molecules of SA (thioglycolic, thiopropionic, and dihydrolepolic acids) and surface atoms of semiconductor ZnS and CdS QDs. Optimization of the geometry of surfactant molecules, calculations of their IR spectra, and calculation of the QD surface structure are carried out. Then, the energies of donor–acceptor bonds formed between the SA molecules and QD surface atoms are calculated. It is found that the values of the donor–acceptor bond energies in the case of a surfactant with a carboxyl group exceed the interaction energy of the QD surface with the surfactant with a thiol group by 0.3 eV. This effect is explained by the formation of two bonds of oxygen atoms of the carboxyl group and the bidentate coordination of the agent molecules on the QD surface.

The paper gives a brief review of publications on clustering (grouping) of variables in modeling complex systems. In particular, we consider a universal variable-selection model that takes into account the possible roles for each variable; two methods for partitioning data into similar clusters and selecting informative variables that contribute to clustering; a new variable-selection method for use in cluster and classification analysis that is both intuitive and computationally efficient; a clustering procedure for mixed-type data using a latent-variable model; a regularization method for variable selection; and a method for clustering variables that is both intuitive and computationally efficient. Methods and object of the study: the object of the study is a simple nested piecewise linear regression, the right side of which includes an external minimum and internal minimum and maximum. The process of forming the sets of independent variables is based on the methods of linear regression analysis and the apparatus of mathematical programming. Results: the problem of identification of parameters of a simple nested piecewise linear regression of the first type, the right part of which includes an external minimum and internal minimum and maximum, as well as the formation of sets of independent variables for them, is formulated. The cases of both empty and non-empty intersection of the corresponding index sets are considered. The problem of minimizing the sum of approximation error modules arising in this case is reduced to a linear–Boolean programming problem. An illustrative example is solved.

In this paper, the structure formation processes in Portland cement backfill materials containing solid technogenic (anhydrite gypsum and halite) mining waste as aggregates and a mixing fluid, bischofite lye (liquid mining waste), have been studied. The backfills are intended for filling mined-out spaces of potassium–magnesium salt deposits. The effect of the content and mass ratio of cement, hardening retarders, and mining waste on the technological properties of the backfill materials has been studied. After optimization of the compositions, backfills that are characterized by high viability, cohesion, structural homogeneity, controlled density, and strength properties have been obtained.

The work describes compositions of D-polylactic acid and corn starch as a fine filler, having both the ability to biodegrade and an electric field (corona electrets). The work explores the composition of D‑polylactic acid (PLA) combined with corn starch as a fine filler, both exhibiting biodegradability and acting as a corona electret under an electric field. The infrared (IR) spectrum of PLA reveals characteristic bands that reflect its chemical structure and functional groups: the bands in the 3200–3600 cm⁻¹ range correspond to O–H stretching, those in the 2950–2870 cm⁻¹ range correspond to C–H asymmetric and symmetric stretching, and the pronounced bands in the 1750–1800 cm⁻¹ range relate to C=O stretching of carbonyl groups, while the bands in the 1300–1450 cm⁻¹ range correspond to CO–C and C–C stretching. Bands indicative of ether group stretching are found in the 1000–1300 cm⁻¹ range. Similar bands are observed in the IR spectrum of starch, as it contains analogous functional groups. However, starch exhibits stronger absorption bands around 3300–3500 cm⁻¹, which are mirrored in the spectrum of the PLA–starch composites; specifically, higher starch content correlates with increased intensity in this region. Moreover, interactions between PLA and starch alter the IR spectrum of their compositions. Experimental data reveal that the surface potential of polymer matrices composed of 2–6% starch exceeds that of pure PLA. This enhancement in the accumulation and retention of electric charge carriers in the polymers is attributed to the formation of new trapping sites within the filler structure and at the polymer matrix interface. The high polarizability of starch contributes to local field effects, further facilitating charge retention, while its hygroscopic nature enables moisture retention, significantly influencing the electret characteristics of the polymer. The patterns observed in the surface potential of PLA and its starch composites over time align with typical behaviors seen in various polymer-based corona electrets. Two distinct phases are identified: an initial sharp decline in surface potential values followed by stabilization. These dynamics are controlled by the trapping of charge carriers in shallow, quickly depleting energy traps versus deeper traps that determine the electret’s longevity. The findings conclude that including 2–6% starch into polylactic acid enhances its electret properties, suggesting the potential for developing active packaging solutions that extend the shelf life of food products.

This paper presents an algorithm for the parametric identification of the heat transfer coefficient as a function of temperature in an evaporative heat exchanger operating under high vacuum conditions and subjected to a quasi-periodic specific heat flux. The problem is solved as a global minimization task by minimizing the mean squared error between the theoretical and experimental temperature fields at the locations of temperature sensors. To achieve this, the “direct” heat transfer problem is first solved in the chosen formulation with a given initial approximation of the heat transfer coefficient and its basis function, which accounts for its temperature dependence. The conjugate directions algorithm is selected as the minimization method, being the most accurate first-order gradient method with convergence. The second step involves finding the components of the gradient of the residual functional based on the solution of the adjoint heat transfer problem, obtained by differentiating the target formulation of the “direct” problem with respect to the parameterized heat transfer coefficient. The third step is to determine the descent step used in the proposed optimization method, based on the iterative regularization method. The systematic error in the measurements of the experimental temperature field is chosen as the stopping criterion for the iterative identification of the heat transfer coefficient.

The paper presents an experimental study on the residence time distribution (RTD) of a liquid-phase flow in a plate-type microfluidic reactor of a combined geometry, which includes a mixing zone and a meandering channel. The experiments are performed by stepwise tracer injection followed by UV detection within the volumetric flow rate range of 0.5–2.0 mL/min. Cumulative curves F(t) and differential curves E(t), characterizing the deviation of the actual flow from the ideal regime, are obtained. The average residence times are calculated, showing the expected dependence on the flow rate. Four one-parameter models are used to interpret the obtained data, specifically, axial dispersion, cascade, Y laminar, and M laminar models. The model parameters are determined by nonlinear regression analysis with minimization of the sum of squared deviations. It is found that with an increase in flow rate from 0.5 to 2.0 mL/min, the Peclet criterion increases from 37 to 125, while the Y model parameter decreases from 0.47 to 0.32, which indicates a change in the velocity profile. Based on the analysis of the model parameters, it is found that with increasing flow rate and Reynolds number, the flow approaches the ideal displacement mode. It is shown that all models satisfactorily describe the experimental curves; however, the smallest approximation errors are achieved for the axial-dispersion and cascade models, while the Y and M models, directly related to the shape of the velocity profile in the channel, demonstrate the greatest adequacy in terms of physical interpretation. The obtained results confirm the effectiveness and prospects of using a microfluidic reactor for processes requiring minimal longitudinal mixing and precise control of contact time in the fields of low-tonnage chemistry and specialized synthesis.

The study of rheokinetic characteristics is one of the most important stages in the development of new formulations of modified polymeric materials. Examining the specifics of the curing process of compositions makes it possible to assess component compatibility and the influence of various additives on a set of technological and performance properties. When developing polymer composite materials modeled after natural layered materials with weak interfaces (wood, shells, certain types of mica, etc.), an important technological task is to preserve, by means of applied modifiers, an original liquid aggregate state with the formation of an independent liquid phase within the composite structure (in this work, these modifiers are referred to as liquid-phase materials; triethylene glycol dimethacrylate and a silicone sealant are used as examples). The role of liquid-phase materials, arranged in the composite structure according to specified reinforcement schemes, is to avoid defect accumulation under deformation and to provide stress relaxation. Therefore, when designing a polymer composite composition with a two-phase reinforcement scheme, one of the key criteria for selecting a liquid-phase material is the absence of chemical interaction with the binder material. In this paper, using rotational viscometry, the influence of triethylene glycol dimethacrylate and a silicone sealant on changes in the rheokinetic characteristics of the ED-20 epoxy binder with the amine hardener PEPA is studied at +40, +60, and +80°C. It is found that adding these materials to the epoxy binder in the amount of 20 parts by mass per 100 parts by mass of the epoxy composition does not lead to a significant change in gelation time, viscosity growth constants, or activation energies, which indicates the absence of chemical interaction between the components.