The increasing depletion of high-grade nickel sulfide deposits and the growing demand for nickel have intensified global interest in oxidized nickel ores (ONOs), particularly those located in Kazakhstan. This study presents a comprehensive review of the mineralogical and chemical characteristics of ONOs from the Shevchenkovskoye cobalt–nickel ore deposit and other Kazakhstan deposits, highlighting the challenges they pose for conventional beneficiation and metallurgical processing. Current industrial practices are analyzed, including pyrometallurgical, hydrometallurgical, and pyro-hydrometallurgical methods, with an emphasis on their efficiency, environmental impact, and economic feasibility. Special attention is given to the potential of hydro-catalytic leaching as a flexible, energy-efficient alternative for treating low-grade ONOs under atmospheric conditions. The results underscore the necessity of developing cost-effective and sustainable technologies tailored to the unique composition of Kazakhstani ONOs, particularly those rich in iron and magnesium. This work provides a strategic framework for future research and the industrial application of advanced leaching techniques to unlock the full potential of Kazakhstan’s nickel resources. © 2025 by the authors.

The main aim of this study is to determine the efficiency of enhancement of the strength and heat-resistant characteristics of cementing mortars by addition of metallurgical sludge in the form of iron oxide powder, which is a waste product in steel production, to the composition of a finely dispersed fraction. The use of stabilizing strengthening additives is due to the need to increase the strength properties of cementing solutions, especially those that are used in extreme conditions, at high temperatures and high loads, creating pressure on the formations. At the same time, the use of expensive strengthening stabilizers increases the cost of manufacturing cementing solutions, which in turn leads to an increase in the cost of the entire process of creating oil wells. According to the data presented, the use of finely dispersed and ultra-finely dispersed fractions of metallurgical sludge in the form of hematite powder leads to an increase in the strength properties of cementing solutions, and also increases resistance to long-term thermal heating due to an increase in resistance to high-temperature degradation associated with cracking and embrittlement. It was also determined that the transition from a finely dispersed fraction and an ultrafinely dispersed fraction leads to an increase in strength properties, which makes it possible to reduce the consumption of the stabilizing strengthening additive powder while maintaining strength characteristics.

In-situ uranium recovery features high economic efficiency and low environmental impact as compared with other uranium production techniques. The article presents the experimental results on the application of new geophysical logging methods at a uranium deposit of hydrogenetic type. Complex hydrogenetic uranium deposits have a nonuniform lithology, varied permeability and alternation of permeable and water-resistant rocks. The development of such deposits is often complicated by a number of factors affecting the production process. The common methods of geophysical research in wells provide insufficiently reliable information about the geological structure of interwell space. As a result, it is difficult to control and monitor the production process, which can lead to inefficient consumption of chemical reagents, undesirable leakage beyond the limits of production blocks, incomplete extraction of uranium reserves, etc. To solve the problem of insufficient studies of interwell space, the method of radiowave geointroscopy was tested. This method is based on the measurement of electrical resistance. The tests were carried out in two stages, during the periods of high-rate production. By comparing the measurement results in different dimensions, the electrical resistance maps were plotted. The interpretation of the measurement results made it possible to obtain reliable data on the actual distribution of solutions in the interwell space in a given period of time, to identify areas of excessive concentrations of solutions (stagnant zones), to assess acidification dynamics in production blocks, and to delineate potentially difficult areas of the blocks. © 2022, Ore and Metals Publishing house. All rights reserved.

In this research paper, we delve into the transformative potential of integrating Big Data analytics with machine learning (ML) techniques, orchestrating a paradigm shift in production management methodologies. Traditional production systems, often marred by inefficiencies stemming from data opacity, have encountered bottlenecks that throttle scalability and adaptability, particularly in complex, fluctuating markets. By harnessing the voluminous streams of data-both structured and unstructured-generated in contemporary production environments, and subjecting these data lakes to advanced ML algorithms, we unveil profound insights and predictive patterns that remain elusive under conventional analytical methods. Our discourse juxtaposes the multidimensionality of Big Data-emphasizing velocity, variety, veracity, and volume-with the finesse of ML models, such as neural networks and reinforcement learning, which adapt iteratively to the dynamism inherent in production landscapes. This symbiosis underpins a more holistic, anticipatory decision-making process, empowering stakeholders to pinpoint and mitigate operational hiccups, optimize supply chain vectors, and streamline quality assurance protocols, thereby catalyzing a more resilient, responsive, and cost-effective production framework. Furthermore, we explore the ethical contours of data stewardship in this context, advocating for a judicious balance between technological ascendancy and responsible data governance. The culmination of this exploration is the conceptualization of a predictive, self-regulating production ecosystem that thrives on continuous learning and improvement, dynamically calibrating itself in response to an ever-evolving market tableau and thereby heralding a new era of optimal, sustainable, and intelligent production management. © 2023, Science and Information Organization. All rights reserved.

This article explores the efficiency of using the ETRO-02 ozonator, powered by solar energy, in the water purification process. The objective of the study is to find an environmentally friendly and economically efficient method for eliminating microorganisms in water by powering the ozonator with alternative energy sources. The research materials included water sourced from the Kapshagay reservoir, as well as solar panels and the ozonator device. During the study, solar panels with the capacity to produce 4.2 to 5.5 kWh of energy daily were used, which was sufficient to ensure the continuous operation of the ozonator. The total bacterial contamination in the water decreased from 12,000 CFU/ml to 45 CFU/ml, and coliform bacteria were reduced from 25 CFU/100 ml to 1 CFU/100 ml. Additionally, dangerous microorganisms such as Enterococcus, Salmonella, and Legionella were completely eliminated. The efficiency of the ozonator in removing bacteria and viruses was between 90-99%. In conclusion, the solar-powered ozonator proved to be an environmentally friendly and economically viable solution for effective water purification, particularly suitable for remote and rural areas. © 2025, Zibeline International Publishing Sdn. Bhd.. All rights reserved.

Artificial intelligence (AI) is an evolving set of technologies used for solving a wide range of applied issues. The core of AI is machine learning (ML)—a complex of algorithms and methods that address the problems of classification, clustering, and forecasting. The practical application of AI&ML holds promising prospects. Therefore, the researches in this area are intensive. However, the industrial applications of AI and its more intensive use in society are not widespread at the present time. The challenges of widespread AI applications need to be considered from both the AI (internal problems) and the societal (external problems) perspective. This consideration will identify the priority steps for more intensive practical application of AI technologies, their introduction, and involvement in industry and society. The article presents the identification and discussion of the challenges of the employment of AI technologies in the economy and society of resource-based countries. The systematization of AI&ML technologies is implemented based on publications in these areas. This systematization allows for the specification of the organizational, personnel, social and technological limitations. This paper outlines the directions of studies in AI and ML, which will allow us to overcome some of the limitations and achieve expansion of the scope of AI&ML applications. © 2022 by the authors.

This study explores the potential of oil sludge, a hazardous by-product of the oil industry, as a sustainable rejuvenator for restoring the physicochemical and rheological properties of aged bitumen. Aged binder samples were modified with different concentrations of oil sludge (1%, 3%, and 5%) and analyzed using dynamic shear rheometry (DSR), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). The incorporation of 5% oil sludge increased penetration from 60 to 71 mm and the softening point from 55 °C to 72 °C, indicating enhanced flexibility. DSR measurements showed a ~10% decrease in complex modulus (G*) and a slight increase in phase angle, confirming partial rheological recovery. FTIR spectra revealed partial restoration of aliphatic and aromatic functional groups, with a decrease in sulfoxide absorption bands, while SEM analysis indicated improved homogeneity and reduced microcracking. TGA confirmed enhanced thermal behavior and a reduction in residual mass. The novelty of this work lies in the first-time application of regionally sourced oil sludge as a rejuvenator, evaluated through a multiscale analytical framework. These findings demonstrate the dual benefits of performance recovery and hazardous waste valorization, contributing to sustainable road maintenance within a circular economy approach. © 2025 by the authors.

Solar thermochemical CeO2-based H2O splitting cycle was thermodynamically analyzed to ascertain the optimal thermal reduction (TH) and re-oxidation (TL) temperatures and evaluate the solar-to-fuel conversion efficiency (ηsolar−to−fuel) of the cycle. The equilibrium composition of CeO2, CeO1.72, CeO1.83 and O2 exhibited that the thermal reduction initiated at 1400 K thereby attaining 100 % TR at 2734 K. The observed variations in Gibbs free energy (ΔG) correspond to the feasibility of the re-oxidation step of CeO1.83 and CeO1.72 at 1050 K and 1200 K respectively. It was reported that the absorption efficiency of solar reactor (ηabs−solar−reactor−WS) decreases from 95.6 % to 37 %, as the TH increases from 1400 K to 2734 K. The results show that ηsolar−to−fuel reached the maximum value of 7.45 % for CeO1.72 and 7.69 % for CeO1.83 at 61.72 % TR of CeO2 without heat recuperation. Further, the ηsolar−to−fuel attained the maximum value of 14.92 % and 13.54 % for CeO1.83 and CeO1.72, respectively at the %TR of CeO2 of 80 % with 50 % heat recuperation. The solar-to-fuel conversion efficiency (ηsolar−to−fuel) further can be increased with the optimization of oxygen partial pressure (PO) and molar flow rate of reduction regents (Ar or N2). © 2023

Considerable interest in food packaging research has been prompted by the rising environmental impact of waste, customer awareness for readily accessible foods with extended shelf life, and ecological consciousness about the scarcity of natural resources. The utilization of plastic-based food packaging has resulted in a significant environmental concern due to the accumulation of substantial quantities of plastic in the surrounding areas. Research efforts are being motivated by ecological and health considerations in the pursuit of developing biodegradable films. Besides, poly(lactic acid) (PLA) has been suggested as a possible substitute for petroleum-based polymers because of its sustainability, simple accessibility, and biodegradability. PLA is a biodegradable plastic made from sugar beet or maize starch that may be fermented by bacteria to generate material with desirable qualities like transparency and rigidity. However, there is a need for further improvement in certain properties of PLA, such as flexibility, toughness, permeability, and thermal properties. One potential approach for enhancing these attributes involves the integration of nano-reinforcement. The utilisation of nanocellulose derived from biomass has garnered significant interest in recent times owing to its renewable nature, ability to biodegrade, impressive mechanical strength, low density, and considerable economic worth. In this study, we present a comprehensive overview of the most up-to-date methods for synthesising nanocellulose and its use as a filler material in the manufacture of PLA nanocomposites for food packaging. In addition, this study examines the emerging challenges and potential advantages associated with the utilization of PLA biocomposites incorporated with nanocellulose in the food packaging sector. © The Author(s) 2024.

In this work, we report a detailed scheme of computational optimization of solar cell structures and parameters using PC1D and AFORS-HET codes. Each parameter’s influence on the properties of the components of heterojunction silicon-based solar cells (HIT) has been thoroughly examined. The proposed approach follows a stringent sequence of steps to optimize various parameters of the studied HITs. Furthermore, we have revealed the effects of the metal-semiconductor contact, and a model of a photocell with an ohmic contact and a Schottky contact has been simulated. The optimal model of HIT for available materials has been proposed and fabricated based on the results of these simulations. A comparison of predicted and measured performance unequivocally demonstrates the efficiency of the proposed scheme in developing silicon-based HITs, providing reassurance about its practical application. © 2024 by the authors.