Anthropogenic CO2 emissions are a major driver of climate change, highlighting the urgent need for effective mitigation strategies. Carbon Capture, Utilization, and Storage (CCUS) offers a promising approach, particularly through CO2-enhanced gas recovery (EGR) in shale reservoirs, which enables simultaneous hydrocarbon production and CO2 sequestration. This study employs a numerical simulation model to compare two injection strategies: CO2 flooding and huff-and-puff (H&P). The results indicate that, without accounting for key mechanisms such as adsorption and molecular diffusion, CO2 H&P provides minimal improvement in methane recovery. When adsorption is included, methane recovery increases by 9%, with 14% of the injected CO2 stored over 40 years. Incorporating diffusion enhances recovery by 19%, although with limited storage potential. In contrast, CO2 flooding improves methane production by 26% and retains up to 94% of the injected CO2. Higher storage efficiency is observed in reservoirs with high porosity and low permeability, particularly in nano-scale pore systems. Overall, CO2 H&P may be a viable EGR option when adsorption and diffusion are considered, while CO2 flooding demonstrates greater effectiveness for both enhanced gas recovery and long-term CO2 storage in shale formations. © 2025 by the authors.

The bottom sediment of reservoirs has many functions. Among them, matter sorption is a very important one, and results in many side-effects on the reservoir sediment forming the water–bottom sediment system. As a result, bottom sediment can also be an indicator of anthropogenic water pollution. There is only very little knowledge of this situation in the study area. The main objective was the analysis of heavy metal accumulation in bottom sediment, as well as their ability to migrate throughout the water–bottom sediment system and their spatial distribution in the Kapshagay Reservoir in Kazakhstan. Heavy metal concentrations, in the both water samples and the bottom sediment, were determined using the atomic absorption spectrophotometric method. Surfer software was used to visualize the processes of migration and accumulation. Another objective was the development of model maps of the spatial distribution of metals in the reservoir water area, which indicated significant anthropogenic loads. It is obvious that both the transboundary inflow of the Ili River and the inflow from small rivers in the territory of Kazakhstan are the reasons for the anthropogenic water and sediment load. The results of the spectrometric analysis verify the water pollution in the reservoir, revealing increased concentrations of zinc reaching up to 10.8 µg/L and lead up to 32.7 µg/L, transported by the transboundary runoff of the Ili River and by the small rivers on the left bank into the Kapshagay Reservoir. Sediment concentrations close to the central part and dam zone of the reservoir reached the following values: zinc up to 37.0 mg/kg and lead up to 8.8 mg/kg. The results of this study indicate a significant anthropogenic load of the ecological conditions of the Kapshagay Reservoir. This is discussed and compared with other relevant studies. © 2022 by the authors.

In this work, optical properties of perovskite solar cells (PSCs) with planar and nanorod-based SnO2 electron transport layers (ETLs) are studied and their photovoltaic parameters are compared using computer simulation methods. It is found that nanorod-based SnO2 ETLs improve the light harvesting ability of device. However, their power conversion efficiencies (PCEs) are still lower than those with thin planar SnO2 ETLs. © 2023 IEEE.

This study aims to enhance terrorism financing detection mechanisms by analyzing existing patterns in financial transactions. Utilizing advanced data analysis techniques and machine learning models, we identified significant transaction patterns indicative of terrorism financing activities. The proposed models demonstrated improved accuracy and efficiency over traditional detection methods. The findings have substantial implications for financial institutions and regulatory bodies in strengthening financial security and preventing illicit activities. © 2024 IEEE.

Herein, a comprehensive validation of the catalytic and sensing capabilities of gallium sulfide (GaS). This study focuses on the self-assembled heterostructure formed by GaS with its native oxide, revealing novel insights into the crucial role of defects, strain, and surface oxide phases in optimizing the behavior of 2D materials for catalytic and sensing applications. Although the energy barrier for water dissociation on pristine GaS surfaces is prohibitive (+419.3 kJ mol−1), surface sulfur vacancies considerably reduce this barrier, transforming defective GaS (GaSx) into an efficient catalyst for the hydrogen evolution reaction (HER) in alkaline media. Water dissociation is energetically favorable at room temperature on GaS0.96 surfaces (−147.6 kJ mol−1). Correspondingly, the differential free energy for HER on GaS0.96 in an alkaline medium is found to be −1.56 eV for the hydroxyl adsorption step and +1.28 eV for the desorption step, while all reaction steps are exothermic for its implementation as a catalyst for oxygen evolution reaction (OER). These theoretical models and surface-science experiments confirm that exposure of GaS surfaces to ambient conditions leads to the inevitable formation of a self-assembled nanoscale (≈3 nm thick) oxide skin. This native oxide layer stabilizes the surface and, moreover, it also significantly enhances its catalytic and sensing properties by providing additional active sites and improving charge transfer dynamics. The exceptional sensitivity (response of 18% at T = 150 °C) and selectivity for detecting ammonia (NH3) are attributed to both its high affinity for chemisorption and the significant charge-transfer interactions that enhance the sensor response.

The scientific research investigates the neutralization and purification process of harmful microorganisms present in surface water using an ozonator device, which operates based on a pilot electric discharge method. A pilot ozonator based on a special high-frequency electric discharge has been developed for disinfection and cleaning of harmful microorganisms found in surface water. In order to conduct practical tests on scientific research work, special water was taken from the Ili floodplain and an examination of the water composition was carried out. The examination results revealed the presence of several harmful microorganisms in the source water, surpassing the maximum allowable concentration (MPC). Effective economic indicators of ozone content (mg/l), contact time (t, minutes) and the like were determined for disinfection and removal of microorganisms from the water composition. In addition, an algorithm for theoretical calculations for the destruction of harmful microorganisms in 1m3 surface water was compiled and a mathematical model was given. © 2024, Zibeline International Publishing Sdn. Bhd.. All rights reserved.

In the Republic of Kazakhstan, there is a noticeable shortage of water resources, which is a consequence of the natural features of its territory and climate. In particular, there are big problems in the water supply to the Mangystau region. The main source of water in the region is the Samskoye groundwater field. In this work, the conditions of the Samskoye field are typified, the method and technological parameters for drilling a typical well are selected and substantiated. It has been established that rotary drilling with reverse circulation in the conditions of the Samskoye field has significant advantages. The maximum possible production rate of drilling with reverse circulation, taking into account the limited thickness of the aquifer, is 4.3 times higher than with rotary drilling with direct circulation and 2.5 times higher than with percussion drilling. With the same filter pipe diameter, the greatest possible thickness of the gravel pack layer in reverse circulation drilling is 15 times greater than for conventional rotary drilling and 3.7 times greater than for percussion drilling. Thus, the use of rotary drilling with reverse circulation will solve an important problem - the provision of domestic and drinking water supply to the area. © Published under licence by IOP Publishing Ltd.

This scientific research focuses on the study of the disinfection process of harmful microorganisms found in the Vyacheslav Reservoir using the ETRO-02 ozonator installation based on pilot electrical corona discharge and ozone technology. The objective of the research is to determine the effectiveness of ozone technology in eliminating microorganisms in water and compare it with other disinfection methods. The materials and methods section reveals that ozone eliminates total coliform bacteria within 2-4 minutes at a rate of 99-100%, which is significantly faster than chloramine (which takes 15-30 minutes). Additionally, it was found that ozone decomposes into oxygen after use, leaving no harmful residues. The research results showed that ozone eliminates Clostridium spores by 85-90% within 10-15 minutes, while chloramine requires more time to reach the same efficiency. Ozone technology demonstrated an effectiveness of 95-99% at a pH range of 4.0-5.0, proving its suitability for different water conditions. Moreover, ozone works effectively under high temperatures and pressure. The findings indicated that at an ozone concentration of 1.0 mg/L, all harmful microorganisms in water are completely eliminated within 20 minutes. The research was conducted both theoretically and experimentally, with the mathematical model of water disinfection coded in Python. Mathematical calculations were performed using the SMath Solver software. In conclusion, ozone technology has been proven to be an effective, safe, and environmentally friendly method for water purification. The primary objective of this study is to evaluate the effectiveness of ozone technology for water disinfection and to compare its efficiency with other disinfection methods. © 2025, Zibeline International Publishing Sdn. Bhd.. All rights reserved.

The destabilization of the geopolitical, socio-economic and security situation in the world has exacerbated the issue of sustainable development of regional economies and deepening their interaction. Ensuring the growth of the national economy as a whole and individual regions in particular makes the search for mechanisms aimed specifically at internal sources relevant. Spatial development is gaining particular importance due to the increasing role of transport infrastructure in ensuring the economic growth of regions. The socio-economic heterogeneity of regional systems plays a decisive role in the formation of mechanisms for ensuring economic growth, which determines the diversity and contradictions of the effects of transport infrastructure on them. This is expressed in the fact that similar infrastructure facilities in different regions can have different organizational and economic effects. Thus, the appearance of a road can lead to the acceleration of material flows, thereby contributing to the development of the region's economy, and on the other hand, can stimulate an accelerated outflow of population. At the same time, the principles of managing social development and economic growth of regions obtained in practice do not allow to take into account the functional diversity and inconsistency of the effects of transport infrastructure and thereby complicate the search for effective mechanisms for ensuring regional development. growth based on the development of transport infrastructure. Therefore, the study focuses on the actualization of the need to introduce innovative mechanisms into the economy of regions by determining the conditions necessary and sufficient for the implementation of the role of transport infrastructure as one of the sources of sustainable economic growth. In this regard, the knowledge of the essence and patterns of the mutual influence of transport and regional economic development is of great theoretical and practical interest. © Author(s) 2025. © Author(s) 2025. All rights reserved.

Sustainable copper extraction presents significant challenges due to waste generation and environmental impacts, requiring advanced predictive methodologies to optimize production processes. This study addresses a gap in applying deep learning to forecast hydrometallurgical copper production by comparing six recurrent neural network architectures: Vanilla LSTM, Stacked LSTM, Bidirectional LSTM, GRU, CNN-LSTM, and Attention LSTM. Using time-series data from a full-scale industrial operation, we implemented a data augmentation approach to overcome data scarcity limitations. The models were evaluated through rigorous metrics and multi-step forecasting tests. The results demonstrated remarkable performance from five architectures, with Bidirectional LSTM and Attention LSTM achieving the highest accuracy (RMSE < 0.004, R2 > 0.999, MAPE < 1%). These models successfully captured and reproduced complex cyclical patterns in copper mass production for up to 500 time steps ahead. The findings validate our data augmentation strategy for enabling models to learn complex known cyclical patterns from limited initial data and establish a promising foundation for implementing AI-driven predictive systems that can enhance process control, reduce waste, and advance sustainability in hydrometallurgical operations. However, these performance metrics reflect the models’ ability to reproduce patterns inherent in the augmented dataset derived from a single operational cycle; validation on entirely independent operational data is crucial for assessing true generalization and is a critical next step.