• Energy Research
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Deep eutectic solvents (DESs) are an alternative to traditional organic solvents and ionic liquids and meet the requirements of "green" chemistry. They are easy to prepare using low-cost constituents, are non-toxic and biodegradable. The review analyzes literature on the use of DES in various fields of biotechnology, provides data on the types of DESs, methods for their preparation, and properties. The main areas of using DESs in biotechnology include extraction of physiologically active substances from natural resources, pretreatment of lignocellulosic biomass to improve enzymatic hydrolysis of cellulose, production of bioplastics, as well as a reaction medium for biocatalytic reactions. The aim of this review is to summarize available information on the use of new solvents for biotechnological purposes.

Abstract The variation of properties with temperature have many practical applications in the area of chemical engineering and metallurgy, in the process of extrusion, the materials moving between a feed roll and on carrier belt. Here our intention is to explore the consequences of temperature dependent viscosity and variable thermal conductivity on flow of nanoliquid in a rotating system. Fluid between parallel plates is taken. Energy expression incorporates the exponential heat source. This analysis also explores the attributes of modified Arrhenius energy function with chemical reaction. Boundary layer problems have been computed via NDSolve approach. The obtained solutions are sketched for various estimations of embedded variables of interest. Results pointed out that both axial and transverse velocities show decaying behavior for higher rotation parameter. Thermal field boosts up with an enhancement of thermophoretic and space dependent heat source variables. Moreover the rate of mass transport decays through dimensionless activation energy.

In this study, the freshwater microalgae Selenastrum sp. was assessed for the effective degradation of pyrene and simultaneous production of biodiesel from pyrene-tolerant biomass. The growth of algae was determined based on the cell dry weight, cell density, chlorophyll content, and biomass productivity under different pyrene concentrations. Further, lipids from pyrene tolerant culture were converted into biodiesel by acid-catalyzed transesterification, which was characterized for the total fatty acid profile by gas chromatography. Increased pyrene concentration revealed less biomass yield and productivity after 20 days of treatment, indicating potent pyrene biodegradation by Selenastrum sp. Biomass yield was unaffected till the 20 mg/L pyrene. A 95% of pyrene bioremediation was observed at 20 days of culturing. Lipid accumulation of 22.14%, as evident from the estimation of the total lipid content, indicated a marginal increase in corroborating pyrene stress in the culture. Fatty acid methyl esters yield of 63.06% (% per 100 g lipids) was noticed from the pyrene tolerant culture. Moreover, fatty acid profile analysis of biodiesel produced under 10 mg/L and 20 mg/L pyrene condition showed escalated levels of desirable fatty acids in Selenastrum sp., compared to the control. Further, Selenastrum sp. and other freshwater microalgae are catalogued for sustainable development goals attainment by 2030, as per the UNSDG (United Nations Sustainable Development Goals) agenda. Critical applications for the Selenastrum sp. in bioremediation of pyrene, along with biodiesel production, are enumerated for sustainable and renewable energy production and resource management.

AbstractNowadays, researchers are focusing on the methods of using recycled industrial/agricultural wastes as raw materials, which are not only economically but also environmentally useful. In the recent years, many scholars have conducted research on the rational use of rice husks (RHs) and found that RHs are rich in inorganic/organic components and used in combination with the certain building materials to produce new green composite building materials. This paper studies the method of using RH processed products and the sodium silicate solution (liquid glass) made from RH ash to produce cheap wood substitute composite materials, which can be improved the insulation performance of the wall greatly. Obtained results are determined by comparing with the properties of standard polymer composite materials such as particleboards, chipboards, and medium‐density fiberboards (MDF). The significance of the work is pointing out by solving the problem of recycling large‐tonnage agricultural waste and reproduce products with the consumer's value.

Abstract This study presents and evaluates the feasibility of a novel hybridization of modified Kalina cycle, reverse osmosis desalination, and low-temperature water electrolysis utilizing geothermal energy to yield power, distilled water, and hydrogen, respectively. The scientific impact of the current work has been improved considering the features of Sabalan flash-binary geothermal wells in Iran as a real model through a case study. In addition to designing a novel setup, the smart use of multi-heat recovery technique, modifying the base cycle, and utilizing a part of generated distilled water to produce hydrogen by the electrolyzer are the other structural originalities, distinguishing the current work from the previous studies. The suggested system is scrutinized via a parametric study and optimized based on a genetic algorithm. The parametric study demonstrated that the highest sensitivity of varying the performance criteria of the whole system is attributed to the change in flash tank pressure. Moreover, the multi-objective optimization led to achieving the exergy efficiency and trigeneration gain output ratio as 51.3% and 1.7 for the system, respectively. Furthermore, the system was able to produce 4795 kW of power, 5.3 kg/h of hydrogen, and 19.9 kg/s of distilled water.

The article describes the results of work on the creation of neural networks calculating the technical and economic parameters of all possible modes of operation of a thermal turbine unit with a steam turbine of type PT-60-130/13. In accordance with the objectives set, recommendations for the preparation of training data samples are formulated. The input and output parameters of the condensing and heating modes of operation of the steam turbine are determined. The results of research on determining the most optimal architecture of neural networks for calculating the energy characteristics of steam turbine plants of the heating type are presented. The results of calculations of the mean squared errors of neural network predictions from the results of calculations performed using a verified object-oriented model of a PT-60-130/13 turbine unit are tabulated.Graphs of the dependence of the specific heat consumption for the generation of electrical energy on the power of a PT-60-130/13 turbine unit for condensation and heating modes of operation using neural networks are plotted. The conclusion is formulated about the possibility of using neural networks for the development of energy characteristics and regulatory documentation on fuel use of equipment of thermal power plants.