MXenes have emerged as promising two-dimensional (2D) materials for catalytic applications in energy production due to their exceptional structural, electronic, and chemical properties. Their high surface area, tunable surface terminations, and excellent electrical conductivity make them ideal candidates for facilitating surface reactions and enhancing charge transfer processes. Additionally, the ability to modify their composition and structure at the atomic level allows for the design of tailored MXene-based catalysts suited for various energy-related reactions. This review highlights recent advancements in MXene-based catalysts, focusing on novel synthesis techniques, including selective etching, CVD and ALD, as well as advanced characterization methods such as XRD, Raman spectroscopy, TEM, FTIR, and In-situ/Operando techniques. Their applications in key catalytic processes, including the Fischer-Tropsch synthesis of hydrocarbons, CO₂ hydrogenation to methane, and hydrogen production via electrochemical water splitting, are discussed, as these reactions play a crucial role in carbon utilization, energy storage, and the transition to sustainable fuels. Notably, Mo₂C-based catalysts favor heavier hydrocarbon formation, while NiV oxycarbide electrocatalysts exhibit high durability and hydrogen selectivity. These findings emphasize MXenes’ potential in sustainable energy conversion and highlight the need for further optimization to enhance their catalytic efficiency and stability. © 2025 The Authors

The study covers a range of problems related to risk management, logistics, enterprise relocation, transport infrastructure and sustainable development of transport enterprises, especially in conditions of military threats. It is determined that modern trends in risk management demonstrate significant progress with the expansion of its boundaries by introducing new concepts such as risk management, risk economics, risk engineering, risk administration and risk production. New professional approaches to risk classification are proposed, and the elements of risk content - certainty and uncertainty, taking into account their limiting values - are specified. It is proven that the erroneous perception of complete certainty or complete uncertainty in management processes is a factor that reduces the effectiveness of organizational decisions. The illusion of complete certainty leads to excessive bureaucratization and loss of adaptability, while the idea of complete uncertainty stimulates impulsive, unfounded decisions without proper analysis and forecasting. The elimination of such illusions allows the formation of adaptive management strategies that are able to respond more effectively to changes in the external environment. To assess the readiness of enterprises for development, a two-component methodological approach is proposed, based on the analysis of investment adequacy and the balance of activity costs. An integral indicator of investment adequacy is determined, which allows assessing the resource capacity of enterprises. The testing of the approach at Ukrainian motor transport enterprises showed a low level of this indicator - a value in the range of 1.2-1.7 with a standard of 3 indicates limited resources for economic development and the dominance of survival strategies instead of development. © Author(s) 2025. All rights reserved.

This study applies machine learning to detect and classify anomalous minerals within a large mineralogical dataset, enhancing geological exploration and resource identification. Using Isolation Forest and One-Class SVM, we identified rare minerals with distinct physical and chemical properties that deviate from common mineral compositions. These anomalies were further grouped using KMeans clustering into three categories, each linked to different geological formation environments: evaporitic, metamorphic, and magmatic processes. The study also evaluates the reliability of these machine learning models using a statistical benchmark and explores the role of deep learning in improving anomaly detection. The findings demonstrate the potential of unsupervised learning to enhance mineral classification, reduce exploration costs, and improve predictive modeling for rare mineral deposits. Future research will refine these methods by integrating Deep Isolation Forest, Autoencoders, and Graph Neural Networks, further strengthening machine learning applications in geosciences.

Аннотация. Мақала Қазақстанның уран провинциялары мен кенорындарындағы геологиялық және тау-кен-геологиялық жұмыстардың барлық кезеңдерінде ақпаратты геофизикалық технологияларды таңдау және пайдаланудың ғылыми-әдістемелік (физикалық-геологиялық) проблемаларын шешуге арналған. Уран кенорындары ұңғымаларында геофизикалық 212N E W S of the National Academy of Sciences of the Republic of Kazakhstan (қашықтық) әдістерді қолдану қажеттілігі уранның радиоактивті табиғатымен ғана негізделмейді. Маңызды өндірістік фактор – жерасты ұңғымалық сілтісіздендіру (ЖҰС) әдісін қолдана отырып, уран кенорындарын игеру мен өндірудің қауіпсіз және озық технологиясының қолданылуы. Проблеманы шешудің физикалық-геологиялық негіздері кенорындардағы геологиялық қималарды құрайтын таужыныстар мен кендердің неғұрлым көп физикалық қасиеттері мәндерін жүйелеу болып табылады. Ұңғыманың геофизикалық өрістерінің және таужыныстардың физикалық қасиеттерінің жиынтық мәндерін (мәндерінің өзгеру диапазонын) есептеуде статистикалық әдістер мен әдістемелелер қолданылды. Есептеулер үшін геологиялық қорлардың фактілік деректері және Шу-Сарысу уран провинциясы бойынша ғылыми басылымдардың мәліметтері пайдаланылды. Мақаланы жазуда авторлардың басқа кенорындардағы және басқа геологиялық мәселелерді шешудегі тәжірибесі де пайдаланылды. Алынған көппараметрлі петрофизикалық модельдік көрсеткіштер уран кенорындары бойынша өткізбейтін (сазды) және өткізетін (кенді және кенсіз құмдар) таужыныстарды дәл ажыратуға мүмкіндік беретін зерттеулер қажеттігін көрсетті. Оларға таужыныстарда сейсмикалық толқындардың тарау жылдамдықтары, таужыныстардың электрлік қасиеттері, тығыздықтары жатады. Осы физикалық қасиеттерді тақырыптық және неғұрлым нақты деңгейде зерттеулер геофизикалық әдістердің мәліметтілік деңгейін көтеруге және олардың салада шеше алатын мәселелерінің ауқымын кеңейтуге мүмкіндік береді. Уран кенорындарын барлау мен игеруде геофизикалық технологиялардың мүмкіндіктерін кеңейту және енгізу персоналдың еңбек қауіпсіздігінің деңгейін көтереді және жалпы саланың экономикалық тиімділігін арттырады. Түйін сөздер: Шу-Сарысу провинциясы, уран кенорындары, таужы- ныстардың физикалық өрістері мен қасиеттері, мәліметтерді статистикалық өңдеу, геофизикалық технологиялар

This study aimed to develop and evaluate the effectiveness of a new Savonius wind turbine scheme featuring a vertical fixed axle, which offers advantages in reducing metal intensity and operating time. The study employed theoretical analysis of existing wind turbine designs, a fixed-axle modular design, and aerodynamic modeling of the rotor profile to enhance the plant’s efficiency. As a result of the study, a new scheme of a Savonius wind turbine with a vertical fixed axle was developed. The proposed design helped significantly reduce the metal intensity of the plant by approximately 30%, resulting in lower manufacturing costs. The absence of a rotating shaft and its replacement with a fixed axle resulted in a reduction of friction in the support, thereby increasing the plant’s efficiency. Dynamic forces on the structure were also reduced, contributing to longer bearing life. The proposed design reduced metal consumption by approximately 1.5 times, resulting in a 35% reduction in production costs. Less frequent maintenance, once every two years instead of every six months, reduces operating costs by up to 40%. Reduced friction in the bearings and reduced dynamic loads increase reliability and extend bearing life by 25%. All in all, these factors increase the financial efficiency and competitiveness of the turbine in the renewable energy market. The practical benefits of the research for stakeholders are that engineers are able to implement simplified and reliable design solutions that reduce bearing loads and increase turbine efficiency. © 2025. The Author(s).

Heat pumps are widely recognized as energy-efficient technologies for domestic hot water production. However, conventional single-stage vapor compression heat pumps utilizing ambient air as the heat source are limited in delivering outlet water temperatures above 323 K under low ambient conditions. This limitation restricts their applicability in continental climates characterized by large diurnal and seasonal temperature variations. Two-stage cascade systems can achieve higher outlet temperatures exceeding 343 K, but they require two compressors, resulting in increased energy consumption and higher capital costs. To overcome these drawbacks, the present study proposes an auto-cascade compression heat pump system employing an environmentally friendly binary zeotropic refrigerant mixture to achieve water outlet temperatures above 343 K with improved efficiency and reduced system complexity. In addition, solar collectors are integrated to enhance low-grade heat extraction from the environment. A numerical simulation of the proposed auto-cascade system was conducted for binary zeotropic refrigerant mixtures including R32/R134a, R32/R1234yf, R32/R1234ze, and R32/R245fa within an ambient temperature range of 223–273 K. The results show that the coefficients of performance (COP) for R32/R134a, R32/R1234yf, and R32/R1234ze mixtures vary between 2.72 and 2.75, while that of R32/R600a reaches 2.55. Based on the comparative analysis, the R32/R134a mixture demonstrated the best performance and is recommended as a promising working fluid for auto-cascade heat pump systems designed for water heating applications in continental climate regions. © 2025 al-Farabi Kazakh National University.

В данном исследовании представлена разработка моделей моделирования процесса выщелачивания урана на месте (ISL), включающей сложную кинетику растворения как тетравентных, так и шестивалентных соединений урана, а также взаимодействие выщелачивания раствора с рудосодержащей породой-хозяином. Для определения констант скорости реакции были получены экспериментальные данные с помощью системы проточного выщелачивания с использованием представительного образца руды. Анализ полученных кривых извлечения урана позволил определить постоянные скорости ключевых химических реакций между компонентами руды и реагентом выщелачивания. Эти параметры впоследствии использовались как входные данные для численного моделирования, направленных на прогнозирование временной динамики извлечения урана. Модель была проверена на основе полевых данных, собранных с месторождения Буденовского урана. Сравнение смоделированных и экспериментальных кривых извлечения показало сильное согласие, что подтвердило надёжность и надёжность модели. Результаты подчёркивают потенциал модели для практического применения в прогнозировании и оптимизации эффективности операций по выщелачиванию на месте для извлечения урана. © 2025, Казахско-Британский технический университет. Все права защищены.

In this paper, we investigate the global existence and blow-up phenomena of the solution to the fractional nonlinear porous medium equation on stratified groups, employing the concavity method. Specifically, we establish the necessary conditions for the existence of global solutions and blow-up solutions. Our findings not only contribute to the understanding of this equation on stratified groups but also extend the existing knowledge in the classical Euclidean setting to the fractional case. © 2025 the Author(s), licensee AIMS Press.

Thermal stratification strongly affects the efficiency and operational reliability of sensible thermal energy storage (TES) tanks in energy systems. This study numerically investigates the combined influence of inlet configuration and mass flow rate on the charging performance of a vertical cylindrical TES tank (H = 3 m, D = 1 m) using transient CFD simulations. Five inlet designs—open, orifice, groove, shower, and shower-groove are analyzed at three flow rates: (Formula presented.) = 0.0003 m3/s, (Formula presented.), and (Formula presented.). System performance is evaluated using key thermal and stratification metrics. Increasing the flow rate from (Formula presented.) to (Formula presented.) enhances convective heat transfer and energy and exergy efficiencies, but significantly intensifies mixing and degrades thermal stratification. At (Formula presented.), the groove inlet achieves the highest capacity ratio and exergy efficiency (0.87), while exhibiting increased mixing. Reducing the flow rate to (Formula presented.) and (Formula presented.) limits inlet-induced momentum, leading to improved stratification for all configurations. The shower-groove inlet reaches a maximum stratification level (tail factor) of 1.13 at (Formula presented.), indicating superior thermal layering, albeit with lower energetic efficiency (≈0.40–0.45). The groove inlet provides the best overall compromise at (Formula presented.), combining high efficiency with stable stratification. These results demonstrate a clear efficiency-stratification trade-off and highlight the importance of selecting inlet-flow combinations according to application-specific objectives. © 2026 by the authors.

The development of robotic systems for automated fruit harvesting in intensive orchards has emerged as a critical response to labor shortages, high production costs, and the need for efficiency in modern agriculture. This study presents the kinematic modeling and design of a robotic manipulator system integrated into a mobile platform with an articulated lift mechanism, dual manipulators, and compliant gripping devices equipped with vision-based perception. The proposed system was modeled and validated through simulation in SolidWorks, enabling analysis of workspace coverage, kinematic stability, and motion optimization. Results indicate that the dual-manipulator configuration achieved a harvesting rate of up to 12 trees per hour, reducing the average fruit cycle time to less than seven seconds while lowering fruit loss to 14.5%, compared to over 30% in manual harvesting. The gripping device demonstrated a success rate of 94% with safe detachment forces between 2.5 and 3.5 N, ensuring minimal fruit damage and consistent quality. The lift mechanism provided stable vertical translation with minimal lateral deflection, supporting precise manipulator operation. Overall, the study highlights the potential of robotic manipulators to enhance productivity, safety, and sustainability in orchard management, while outlining future directions for field implementation, adaptive vision algorithms, and autonomous navigation. © (2025), (Science and Information Organization). All rights reserved.