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This study reviews the metal corrosion problem regarding the carbon capture, utilization, and storage (CCUS) technology and aims to deepen the understanding and research on this problem and thus deal with the severe material corrosion failures in the capture, transportation, utilization, and storage systems. Based on the novel corrosion environments, the uniqueness of corrosion behaviors, limited cognition, and relative lack of protective measures in CCUS technology systems, this study analyzes the possible types of metal corrosion and its major influencing factors, explores the challenges it brings, and draws the following conclusions. For the CO2 organic amine capture system, the degradation mechanism of absorbents and the impact of degradation products on the corrosion process are complex, and some degradation products have a inhibitory effect on metal corrosion. The internal corrosion issue of dense-phase CO2 transmission pipelines cannot be ignored, and controlling the moisture content is the key to controlling this corrosion problem. The risk of corrosion failures leading to CO2 leakage is high in the wellbore tubing of CO2 enhanced oil recovery utilization and storage systems under the long-term coupled effects of ultra-high CO2 partial pressure, carbon source impurities, high mineralized formation water, microorganisms, and stress. Finally, the research that needs to be conducted urgently in the future is prospected, including the corrosion impact of different carbon source impurities on each subsystem, the material degradation law in the wellbore area under long-term storage conditions, and corrosion protection technologies of CCUS systems.

Power sales business stands on reasonable assessment of power users by power sales enterprises. The present assessment methods are incomprehensive and less applied. Therefore， a power user classification model is proposed based on WRSR （weighted rank-sum ratio） and Catboost algorithm. Firstly， the existing power users are graded and labeled using WRSR. Then， the Catboost algorithm is used to learn the classification law and construct a classifier. The hyperparameters of Catboost are optimized using BOA （Bayesian optimization algorithm） to improve the classification effect. Finally， the importance of each feature is analyzed according to the model， and the user features are filtered by the importance scores. The experimental results show that the method can reasonably classify power users， and the proposed classification model is superior to other machine learning models in accuracy and interpretability.

Nitrate plays a crucial role in marine ecosystems, as it influences primary productivity. Despite its ecological significance, accurately mapping its three-dimensional (3D) concentration on a large scale remains a considerable challenge due to the inherent limitations of existing methodologies. To address this issue, this study proposes a continual learning-based multilayer perceptron (MLP) model to reconstruct the 3D ocean nitrate concentrations above 2000 m depth over the pan-European coast. The continual learning strategy enhances the model generalization by integrating knowledge from CMEMS nitrate data, effectively overcoming the spatial limitations of BGC-Argo observations in comprehensive nitrate characterization. The proposed approach integrates the advantages of extensive spatial remote sensing observations, the precision of Biogeochemical Argo (BGC-Argo) measurements, and the broad knowledge from simulated nitrate datasets, exploiting the capacity of neural networks to model their nonlinear relationships between multi-source sea surface environmental variables and subsurface nitrates. The model achieves excellent performance in profile cross-validation (R 2 = 0.98, RMSE=0.522 µmol · kg −1), and maintains robustness across diverse 3D validation scenarios, suggesting its effectiveness in filling observational gaps and reconstructing the 3D nitrate field. Then, the spatiotemporal distribution of the reconstructed 3D nitrate field from 2010 to 2023 reveals a spatial distribution pattern, an interannual upward trend, and the degree of consistency in vertical variation. The contributions of all 22 input features to the model's estimation were respectively quantified by using Shapley additive explanations values. This study reveals the potential of the proposed approach to overcoming observational limitations and enrich further insights into the 3D ocean condition. The reconstructed 3D nitrate dataset is freely available at https://doi.org/10.5281/zenodo.14010813 (Yu et al., 2024). [ABSTRACT FROM AUTHOR]

Metal halide perovskites (MHPs) have been demonstrated to exhibit mixed ionic and electron conductive properties, characterized by their remarkable soft lattice features. However, a full understanding of the complicated interplay between ion, lattice, and carrier recombination and the influence on the optoelectronic properties and performance of perovskite solar cells remains elusive. To this end, the present study utilized time-dependent photoluminescence (PL) spectroscopy to investigate the light-soaking effect of organic–inorganic perovskite solar cells doped with alkali metal ions (K+/Rb+) and undoped perovskite films under continuous illumination. Dynamic monitoring of the PL intensity and carrier lifetimes within 1–500 s of continuous illumination revealed significant influences of the alkali metal ions and light intensity on the performance, including the stability of the perovskite solar devices. The results reveal that K+/Rb+ doping in perovskite films induces more positive light-soaking effects. These effects include enhanced PL intensity, inhibited phase separation, and prolonged carrier lifetime. The synergistic combination of these effects leads to the improved photoelectric conversion efficiency and device stability of perovskite solar cells (PSCs). These findings offer novel insights into the roles of ions in MHPs and are pivotal for comprehending the mechanisms underlying MHP devices, particularly concerning the ionic properties of MHPs. [ABSTRACT FROM AUTHOR]

Atmospheric pressure and zenith wet delay (ZWD) are essential for global navigation satellite system (GNSS) tropospheric correction and precipitable water vapor (PWV) retrieval. As the development progresses of real-time GNSS kinematic technology, moving platforms, such as airborne and shipborne, require high-quality tropospheric delay information to pre-correct errors. Most existing tropospheric models are only applicable to the Earth's surface and exhibit poor accuracies in high-altitude areas due to simple vertical fitting functions and limited temporal resolution of the underlying parameters. Hence, an improved global empirical pressure and ZWD model is developed using 5-year ERA5 hourly reanalysis data, called IGPZWD, which takes seasonal and intraday variations into consideration. The vertical accuracy and applicability of IGPZWD model are further optimized by introducing the annual and semi-annual harmonics for pressure and ZWD height-scale factors of exponential function with three orders. Taking the ERA5 and radiosonde profile data in 2020 as reference, the pressure and ZWD of IGPZWD model show superior performance compared to those of three state-of-the-art models, i.e., GPT3, IGPT, and GTrop. Furthermore, IGPZWD-predicted zenith tropospheric delay (ZTD) yields improvements of up to 65.7 %, 2.4 %, and 7.8 % over that of GPT3, RGPT3, and GTrop models on a global scale, respectively. The proposed vertical correction algorithm effectively weakens the impact of accumulation error caused by excessive height difference, achieving optimal accuracy and feasibility in the high-altitude area. The IGPZWD model can be extensively applied in GNSS kinematic precision positioning, as well as atmospheric water vapor sounding. [ABSTRACT FROM AUTHOR]

Defect tolerance plays a crucial role in the outstanding photoelectric performance of hybrid organic–inorganic perovskites (HOIPs). Although the origin of defect tolerance has been extensively studied in the past few years through static density functional theory (DFT) calculations and experiments, the mechanism of photoinduced defect dynamic change has not yet been well revealed. In this study, we first demonstrate that defect tolerance is dynamically responsive to illumination. Continuous illumination can result in an increased defect tolerance, manifested as an increase in average carrier lifetime and photoluminescence (PL) efficiency, and the timescales involved are consistent with the reported ion activities. The results of DFT calculations and non-adiabatic molecular dynamics (NAMD) simulation suggest that the photoinduced dynamic PL enhancement can be attributed to the local structural reorganization caused by the defect trapping/detrapping, resulting in the formation of long-living structures with longer carrier lifetimes. The study reveals that the dynamic defect tolerance in HOIPs is powered by a unique interaction between the soft lattice, phonons, excited carriers, and defect sites. It has significant implications for the development of photostable optoelectronic devices based on HOIPs. [ABSTRACT FROM AUTHOR]

In the long-hole stage open stoping with subsequent backfill mining of underground metal mines, the selection or optimization of stope dimension parameters is significant for safe and economic mining operations. To analyze the optimal stope sizes, the Mathews empirical graph method and FLAC3D numerical method can be used, but the analyzed safety results of the two methods are generally independent from each other. More importantly, economic indicators including production capacity and mining costs should be considered simultaneously to optimize the stope dimension which was mostly ignored in previous reports. In this paper, a new CRITIC-GRA model was proposed for the first time to build up a multi-factor quantitative optimization for stope dimension, which allows for a comprehensive analysis with preset influential safety and economic indicators. The indicators considered include the safety indicators such as stability probability for the side walls and roof of the open stope via the updated Mathews graph method, maximum displacement, plastic zones volume and maximum principal stress via FLAC3D simulations, as well as economic indicators such as mining costs and stope production capacity in mine operations. The model was then illustrated in an underground iron mine. With the given rockmass quality in the mine, the overall stability of the open stope can be improved instead of reduced to enlarge the single stage stope height (60 m) to a double stage height (120 m) by reducing the stope width from 20 m to 15 m, thereby significantly increasing the mineable ore amount and improving the stope safety. An integrated evaluation of open stope stability, mining capacity and costs objectively determined that scheme No. 10, with a slope length of 50 m, a width of 15 m and a height of 120 m, was the optimum out of the 20 preset schemes. The new CRITIC-GRA model offers a dependable reference tool for determining the optimal stope dimensions in similar underground mines. [ABSTRACT FROM AUTHOR]

Atmospheric pressure and Zenith wet delay (ZWD) are essential for GNSS tropospheric correction and precipitable water vapor (PWV) retrieval. As the development progresses of real-time GNSS kinematic technology, moving platforms such as airborne and shipborne require high-quality tropospheric delay information to pre-correct errors. Most existing tropospheric models are only applicable to the Earth surface, while exhibiting poor accuracies in high-altitude areas due to simple vertical fitting functions and limited temporal resolution of the underlying parameters. Hence, an improved global empirical pressure and ZWD model is developed using 5-years ERA5 hourly reanalysis data, called IGPZWD, which takes seasonal and intraday variations into consideration. The vertical accuracy and applicability of IGPZWD model are further optimized by introducing the annual and semi-annual harmonics for pressure and ZWD height scale factors of exponential function with three orders. Taking the ERA5 and radiosonde profiles data in 2020 as reference, the pressure and ZWD of IGPZWD model show superior performance than those of three state-of-the-art models, i.e., GPT3, IGPT and GTrop. Furthermore, IGPZWD-predicted ZTD yields improvements of up to 65.7 %, 2.4 % and 7.8 % over that of GPT3, RGPT3 and GTrop models on a global scale respectively. The proposed vertical correction algorithm effectively weakens the impact of accumulation error caused by excessive height difference, achieving optimal accuracy and feasibility in the high-altitude area. The IGPZWD model can be extensively applied in GNSS kinematic precision positioning as well as atmospheric water vapor sounding. [ABSTRACT FROM AUTHOR]

The stability of the cemented paste backfill is threatened by the dynamic disturbance during the excavation of the surrounding ore body. In this paper, the computerized tomography (CT) and Split Hopkinson Pressure Bar (SHPB) tests were conducted to explore the initial pore distribution characteristics of the cemented tailings backfill (CTB) and the development of the crack under low impact amplitude. SHPB tests were conducted with impact amplitudes of 34, 37, and 39 mV, respectively. Results show that the initial pores of CTB were steadily distributed with the height of CTB. The CTB contained many initial pores with similar pore size distribution characteristics, and the largest number of pores is between 0.1 and 0.3 mm. Most of the cracks in CTB after low impact amplitude develop and expand along the initial pores, and the damage of CTB mainly exists in shear cracks. A dependence has been established that the dynamic uniaxial compressive strength of the CTB increases, the total crack volume first increases and then decreases, and the number of cracks increases as the impact amplitude increases. The research results can provide a valuable reference for the dynamic performance of CTB under low impact amplitude and the design of mining backfill. [ABSTRACT FROM AUTHOR]