Energy & Fuels最新文献

CO₂ storage in geological formations, particularly deep saline aquifers, is a critical component of carbon capture and storage technology, offering significant potential for mitigating greenhouse gas emissions. However, high salinity of these aquifers poses the risk of salt precipitation, leading to pressurization and injectivity reduction. Developing a method to prevent salt precipitation remains a challenge, and this is an area that this study is focused on. Dissolved-water CO₂ injection (dwCO₂ injection) is proposed here as a novel method to prevent salt precipitation where water is dissolved in CO₂ before injection into an aquifer. Presence of water in the CO₂ stream prevents more dissolution of water into CO₂ (evaporation) and, hence, prevents salt precipitation. Before presenting this method and in order to provide a good mechanistic understanding of the interactions involved in a CO₂ storage process, six different scenarios are examined using the CMG-GEM simulator within a carbonate aquifer. The results showed that saturating CO₂ with water reduced the precipitation nearly to zero, and dissolving 2000 ppmv water decreased the salt precipitation to one-third. It should be noted that injection of humid CO₂ requires special methods to tackle the potential challenges, including corrosion and hydrate formation risks, and the paper also discusses them.

This study investigates the ignition characteristics of hydrogen double injection under a split-injection schedule with varying dwell times, focusing on their influence on ignition delay and flame development. Experiments were conducted in a constant-volume combustion chamber (CVCC) with optical access, replicating compression-ignition engine-like conditions. The baseline environment featured a quasi-quiescent ambient with a 23.8 kg/m³ gas density, a 21 vol.% O₂ concentration, and a core temperature of 1000 K. High-speed Schlieren imaging, pressure trace analysis, jet mixing modeling, and constant-pressure homogeneous reactor (CHR) simulations were utilized to characterize the combustion process. Single-injection cases were also analyzed for comparison. The results revealed that, at the baseline 1000 K condition, the first injection advanced the ignition delay of the second injection significantly, reducing the ignition delay time from 9.66 ms for a single injection to as low as 0.62 ms relative to its start of injection, depending on dwell time. However, excessively short dwell times (e.g., 1 ms) led to reduced ignition events, attributed to interactions between closely spaced injections. Longer dwell times facilitated a more robust ignition. CHR simulations highlighted the role of elevated local temperatures and flame intermediates from the pilot injection in influencing the subsequent ignition processes. Temperature variation studies at 1030 and 970 K revealed that, while trends at 1030 K aligned with the baseline, ignition was not achieved at 970 K for either single-injection or split-injection cases with the same injection schedules as other temperature cases. However, increasing the first injection quantity and extending the dwell time enabled ignition at lower temperature, emphasizing the sensitivity of the strategy to ambient conditions. These findings highlight the potential of double injection strategies for robust hydrogen ignition in compression-ignition engines while underscoring the need for optimized injection parameters tailored to the operating conditions.

The electrochemical CO₂ reduction reaction (CO₂RR) in a zero-gap electrolyzer is a promising pathway for carbon fixation via utilizing intermittent renewable energies to produce synthetic fuels and feedstocks, contributing to climate change mitigation. As a critical component of the electrolyzer, the flow field affects its performance by influencing the CO₂ transport. A 3D numerical model of the electrolyzer is critical for flow field optimization. However, numerical studies on the flow field in zero-gap electrolyzers are currently lacking. This study established a 3D model for CO₂ electrolyzers and validated it by experiments under acidic conditions. Based on this model, we investigated the effects of flow field designs on the performance of zero-gap electrolyzers. Two typical flow fields used in zero-gap CO₂ electrolyzers, including serpentine and parallel flow field designs, were evaluated, with the serpentine flow field demonstrating better CO₂ transport characteristics and performance. Then, the serpentine flow field was designed by further optimizing the channel-to-rib ratio and the channel depth within the flow field. The results indicate that a larger channel-to-rib ratio and shallower flow channels facilitate an increased average CO₂ flux and average CO₂ concentration within the catalyst layer. This research provides insights into flow field designs for zero-gap electrolyzers.

As global warming intensifies, geological carbon storage (GCS) in saline aquifers could play a vital role in mitigating CO₂ emissions. CO₂ trapping occurs mainly through solubility and residual trapping, requiring an accurate prediction using solubility trapping (STI) and residual trapping (RTI) indices. Machine learning shows promise for estimating CO₂ trapping in saline aquifers, but current models often lack effective feature selection, parameter optimization, and advanced deep learning techniques, limiting their performance. This study develops predictive models for RTI and STI using CNN, LSTM, and hybrid algorithms by combining them with growth optimization (GO) and cuckoo optimization (COA). An extensive data set of 6,811 global data points was analyzed, with feature selection using the nondominated sorting genetic algorithm and random forest analysis. Model performance was based on independent testing data, and Shapley additive explanation (SHAP) analysis identified key features. For RTI, residual gas saturation (RGS), injection rate (IR), permeability (Perm), elapsed time (Te), porosity (Por), and salinity (Sal) were the most influential. Conversely, RGS, thickness (Th), Te, Perm, Sal, and Por were most critical for STI. The results confirm that hybrid DL models outperformed standard DL models, with metaheuristic optimization enhancing accuracy and generalization. The CNN-COA model achieved the lowest root-mean-square error (RMSE) for RTI (0.0011 for training; 0.0035 for testing) and STI (0.0005 for training; 0.0028 for testing) predictions. SHAP analysis revealed RGS and Perm as the most and least influential features for RTI predictions and Th and Perm as the most and least influential features, respectively, for STI predictions. This study is innovative in its integration of advanced feature selection methods and hybrid deep learning algorithms with effective optimization and feature selection. This integration leads to improved GCS model prediction performance, robustness, and adaptability to diverse geological conditions.

Supercritical CO₂ (SC-CO₂) fracturing is a key technology for the development of unconventional tight reservoirs. With an increase in the extraction depth, both the temperature and the in situ stress of the reservoirs rise rapidly. Understanding and characterizing the effects of high temperature and in situ stress on fracture propagation during SC-CO₂ fracturing are crucial for optimizing this technique. However, few SC-CO₂ fracturing experiments under true triaxial loading conditions with temperatures up to 200 °C have been conducted. In this study, true triaxial fracturing tests were conducted on artificial tight reservoir sandstone specimens to explore the influence of different high temperatures and in situ stress differentials on SC-CO₂ fracturing behaviors. Using computed tomography and the U-net artificial intelligence algorithm, the 3D morphology of fracture networks and the breakdown pressure were quantitatively analyzed. Experimental results show that thermal shock induced by the temperature difference between the fracturing fluid and the rock matrix significantly affected the breakdown pressure and enhanced the complexity of fracture networks. Compared to conventional hydraulic fracturing, SC-CO₂ fracturing generated more complex and tortuous fracture networks, reducing the breakdown pressure by 16–24%. As the temperature increased, the number of branch fractures within the SC-CO₂ fracture network substantially increased, boosting fracture complexity by 8–9%, approximately. In contrast, as the horizontal stress differential increased, the complexity of SC-CO₂ fractures gradually decreased by 4–6%. These findings provide important insights into the mechanisms of fracture network propagation in SC-CO₂ fracturing of unconventional tight reservoirs at different depths.

The solid oxide electrolyzer with perovskite as the cathode can electrolyze CO₂ to produce a valuable chemical resource, revealing the great potential of direct electrolysis of CO₂ at high temperatures. However, its insufficient electrocatalytic activity limits the performance of a solid oxide electrolysis cell. In the present work, we successfully anchored metal nanoparticles, such as nickel and copper, on the perovskite cathode surface to form a composite cathode, thereby creating an active electrochemical interface for CO₂ cleavage to improve the electrocatalytic activity for CO₂ electrolysis and Faraday efficiency improvement. The perovskite cathode based on metal nanoparticles can increase the conductivity of the composite cathode compared to an undoped perovskite cathode, and it can be considered that the improved CO₂ electrolytic performance is attributed to the synergistic effect of the metal nanocatalysts with the La_0.8Sr_0.2CrO_3−δ ceramic electrodes. The electrochemical properties remained stable after 100 h of high-temperature testing, suggesting that the construction of metal–oxide active interfaces can improve the electrocatalytic performance and durability of the materials.

The oil and gas industry is a significant consumer of water and a major producer of wastewater, particularly in the form of produced water. To achieve sustainable development, it is essential to treat, recycle, and reuse produced water. A critical step in produced water treatment involves the removal of impurities including suspended and dissolved solids. Clathrate hydrate desalination (CHD) has emerged as a promising technology for reducing total dissolved salts in produced water. In this study, the full-scale CHD process was simulated using Aspen HYSYS, employing three hydrate formers: 1,1,1,2-tetrafluoroethane, tetra-n-butyl ammonium bromide (TBAB), and cyclopentane. For a water recovery of 40%, the specific energy consumption (SEC) of the CHD process was determined to be 64.47 kWh/m³ for 1,1,1,2-tetrafluoroethane, 48.04 kWh/m³ for TBAB, and 52.79 kWh/m³ for cyclopentane. The results also indicated that as water recovery increases, the SEC decreases. Among the formers studied, CP emerged as the most efficient option for CHD of produced water. A significant portion of the energy demand in the CHD process arises from external refrigeration requirements. However, integrating waste energy streams from oil and gas operations could enhance the energy efficiency and viability of a CHD as a sustainable alternative for treating produced water.

The influence of the concentration of the water-soluble Fe(NO₃)₃ catalyst precursor (from 0.2 to 0.6 wt % by metal) on the properties of heavy oil during the process of aquathermolysis at 300 °C for 24 h was studied. An increase in catalyst active sites leads to a reduction in viscosity by 58.3–85.3% relative to crude oil due to the growth of the light hydrocarbons by 9.9–19.5 wt % according to SARA analysis results. Additionally, there is an active release of gases, with CO₂ being released most intensively due to the water–gas shift reaction and hydrocarbon oxidation. One of the most significant upgrading processes is hydrodesulfurization, which occurs during the thermal decomposition of resins and asphaltenes of heavy oil. Secondary processes involving the transformation of light hydrocarbons also occur, including C–C bond breaking, as evidenced by the decrease in the amount of C₁₀–C₁₅ n-alkanes. The maximum positive effect of the catalyst is observed at 0.4 wt % by the metal concentration of Fe(NO₃)₃ because the presence of 0.6 wt % catalyst under aquathermolysis conditions intensifies oxidation and carbon formation processes.

In this study, we have successfully incorporated a small molecular acceptor, Y-LC, with conjugated π-extension as a secondary acceptor in the PM6:BTP-eC9-based organic photovoltaics. The performance of the device was significantly promoted from 18.45% in the binary system of PM6:BTP-eC9 to over 19% in the ternary system with a minimal Y-LC loading. This enhancement in performance can be attributed to the alloy-like structures of acceptors and the optimized active layer morphology, which leads to improved hole and electron mobilities, thereby suppressing charge recombination, and finally resulting in a higher photocurrent in the solar cells. Furthermore, a complementary absorption of Y-LC is observed with PM6 and BTP-eC9, which can broaden the absorption spectrum of the photoactive layer and enable more photons from sunlight to be absorbed. Additionally, Y-LC facilitates efficient charge transfer from the donor to the acceptor by forming cascade energy levels between PM6 and BTP-eC9. These advantages collectively contribute to the superior performance obtained in the ternary solar cells. This work also highlights that the adoption of a nonfullerene acceptor with suitable conjugated π-extensions as a minor additive in ternary photovoltaics is a powerful approach for achieving the state-of-the-art organic solar cells.

Cerium oxide facilitates redox reactions due to the presence of a reversible redox couple, but its conductivity is not high. The presence of manganese–cobalt sulfide (MnCoS) as a transition metal sulfide, along with cerium oxide, boosts the electrical conductivity and electrochemical properties. Herein, MnCoS hollow nanorods were synthesized on cerium oxide nanosheets (MnCoS/CeO₂) using a hydrothermal technique. The specific capacitance is 772.5 F g^–1 at 1 A g^–1 for MnCoS/CeO₂. It also demonstrated high cyclic stability, maintaining an 89% capacitance after 2500 cycles. Additionally, a battery-type asymmetric supercapacitor (MnCoS/CeO₂//activated carbon) was constructed with an energy density of 24.9 Wh kg^–1 at 407.6 W kg^–1. The device capacitance is retained at 75% after 5000 cycles, showing good cyclic stability. These findings suggest that the MnCoS/CeO₂ composite offers significant potential for enhancing supercapacitor performance and energy storage devices in general.