Azerbaijan State Oil and Industry University

Composite materials based on a mixture of high- and low-pressure polyethylenes with additives of finely dispersed cobalt oxide are studied using X-ray phase analysis (XRD), differential thermal analysis (DTA), and scanning electron microscopy (SEM). An improvement in the strength, deformation properties, and thermal-oxidative stability of the composite is revealed when finely dispersed cobalt oxide is introduced, which is apparently related to the formation of interphase bonds between cobalt-containing nanoparticles (NPs) and the components of the polymer composition. It is shown that nanocomposites based on a mixture of high- and low-density polyethylenes with finely dispersed cobalt oxide additives can be processed using both pressing and injection molding and extrusion, which expands their areas of application. Small amounts of nanofiller being introduced into the polymer act as the structure formers (artificial crystallization nuclei), which contribute to the appearance of a finely spherulitic structure in the polymer characterized by improved physical, mechanical, and thermal properties of the resulted nanocomposite.

Remarkable durability in combination with electrical conductivity, as well as large surface area, makes graphene and its composites an appealing prospect as Lithium-ion battery electrode material (LIBs). With specific emphasis on graphene composites with layered double hydroxide (LDH), metal-organic frameworks (MOFs), Silicon (Si), and metal oxides (MO), this paper presents the advances in graphene-based composites in Li-ion batteries. This review article specifically focused on the various synthesis methods of graphene and its composites with LDH, MOF, Si and metal oxides. As lithium-ion batteries continue to face limitations in charge storage, power performance, and long-term stability, there remains a strong need for further advancement. This article explores the potential of incorporating graphene-based composite materials into lithium-ion battery electrode as a promising strategy to address these challenges. In conclusion, this study provides a comprehensive summary of performance of various graphene based composites, current challenges and recommendations for future research in LIBs.

This article investigates the influence of oxygenated compounds on the antiknock properties of gasoline. Various oxygenate additives, including acetone, ethylene glycol ethyl ether, diethylene glycol ethyl ether, and diethylene glycol butyl ether, were blended with base gasoline at concentrations ranging from 0.5% to 5%. The physicochemical properties of the resulting fuel blends were evaluated using standard methods established by the American Society for Testing and Materials (ASTM). The results indicate that acetone has only a minimal effect on improving antiknock performance, although a 5% addition increases the octane number by 4.5 units. In contrast, ethylene glycol ethyl ether significantly enhances fuel quality, raising the octane rating from 78.5 to 88.5 across the tested concentration range. Diethylene glycol ethyl ether shows an even stronger effect, increasing the octane number up to 91.5. Among all tested additives, diethylene glycol butyl ether demonstrates the highest performance, substantially improving the octane rating to 93.1. Overall, the study confirms that diethylene glycol butyl ether is the most effective additive for enhancing the antiknock characteristics of gasoline among the examined oxygenated compounds.

В исследовании задача оптимального управления стационарными режимами функционирования ректификационной колонны формулируется как оптимизация энергетического или экономического критерия при нелинейных ограничениях модели. Стационарное поведение колонны описывается материальными и компонентными балансами, соотношениями потока на тарелках, фазовым равновесием и энергетическими уравнениями, что приводит к многомерной нелинейной системе уравнений. В связи с сильной нелинейностью, вызванной зависимостью фазового равновесия от температуры и состава, предлагается аппроксимация этого блока с использованием нейронной сети в рамках гибридной модели. Для поддержания оптимального режима при наличии возмущений применяется механизм на основе скользящего режима в реальном масштабе времени. Такой подход позволяет отслеживать экстремумы без измерения производной целевой функции и повышает энергетическую и экономическую эффективность работы колонны In this study, the problem of optimal control of the steady-state operating modes of a distillation column is formulated as the optimization of an energy or economic criterion under nonlinear model constraints. The steady-state behavior of the column is described by material and component balances, tray flow relations, phase equilibrium, and energy equations, resulting in a high-dimensional nonlinear system of equations. Due to the strong nonlinearity caused by temperature–composition dependence in phase equilibrium, the approximation of this block using a neural network is proposed within a hybrid modeling framework. To maintain the optimal mode in the presence of disturbances, a mechanism based on a sliding mode in real time is used. This approach enables extremum tracking without measuring the derivative of the objective function and improves the energy and economic efficiency of the column’s operation