Search Results (559)

Allogeneic blood transfusion is frequently performed in critically ill patients, but accumulating evidence demonstrates that it is not a biologically neutral intervention. Transfusion-associated immunomodulation (TRIM) encompasses the immunological effects of transfusion, ranging from immune suppression to proinflammatory activation and cancer recurrence, with potential impact on morbidity and mortality in the intensive care unit. We conducted a narrative review of recent experimental and clinical evidence on TRIM to describe the molecular pathways involved. We reviewed, randomized trials, metaanalyses, and large observational cohorts to evaluate the clinical relevance of TRIM in critically ill populations. TRIM arises from multiple converging mechanisms. These pathways alter innate and adaptive immunity, leading to increased risk of healthcare-associated infections, transfusion-related acute lung injury, acute kidney injury, multiorgan dysfunction, prolonged length of stay, and cancer recurrence in surgical patients. Blood-sparing strategies, including patient blood management (PBM), mitigate exposure. The impact of storage duration and novel processing technologies remains unclear. There is still a gap in research that needs to be addressed. Transfusion-associated immunomodulation (TRIM) is a phenomenon in which donor leukocytes, extracellular vesicles, microparticles, bioactive lipids, and cytokines interact with the host immune system to produce a spectrum of immunological effects. In critically ill patients, the immune system is already fragile, and these mechanisms predispose patients to infections, pulmonary complications, organ dysfunction, prolonged recovery, and even cancer recurrence. Although TRIM cannot currently be diagnosed through a single biomarker or clinical test, its existence is strongly supported by mechanistic studies and consistent clinical associations between transfusion exposure and adverse outcomes. Full article

The dual imperative of mitigating carbon emissions and maximizing hydrocarbon recovery has amplified global interest in carbon capture, utilization, and storage (CCUS) technologies. These integrated processes hold significant promise for achieving net-zero targets while extending the productive life of mature oil reservoirs. However, their effectiveness hinges on a nuanced understanding of the complex interactions between geological formations, reservoir characteristics, and injection strategies. In this study, a comprehensive machine learning-based framework is presented for estimating CO₂ storage capacity and enhanced oil recovery (EOR) performance simultaneously in subsurface reservoirs. The methodology combines simulation-driven uncertainty quantification with supervised machine learning to develop predictive surrogate models. Simulation results were used to generate a diverse dataset of reservoir and operational parameters, which served as inputs for training and testing three machine learning models: Random Forest, Extreme Gradient Boosting (XGBoost), and Artificial Neural Networks (ANN). The models were trained to predict three key performance indicators (KPIs): cumulative oil production (bbl), oil recovery factor (%), and CO₂ sequestration volume (SCF). All three models exhibited exceptional predictive accuracy, achieving coefficients of determination (R²) greater than 0.999 across both training and testing datasets for all KPIs. Specifically, the Random Forest and XGBoost models consistently outperformed the ANN model in terms of generalization, particularly for CO₂ sequestration volume predictions. These results underscore the robustness and reliability of machine learning models for evaluating and forecasting the performance of CO₂-EOR and sequestration strategies. To enhance model interpretability and support decision-making, SHapley Additive exPlanations (SHAP) analysis was applied. SHAP, grounded in cooperative game theory, offers a model-agnostic approach to feature attribution by assigning an importance value to each input parameter for a given prediction. The SHAP results provided transparent and quantifiable insights into how geological and operational features such as porosity, injection rate, water production rate, pressure, etc., affect key output metrics. Overall, this study demonstrates that integrating machine learning with domain-specific simulation data offers a scalable approach for optimizing CCUS operations. The insights derived from the predictive models and SHAP analysis can inform strategic planning, reduce operational uncertainty, and support more sustainable oilfield development practices. Full article

To optimize enhanced oil recovery (EOR) techniques for pre-fractured heavy oil reservoirs, this research conducted long-core flooding experiments using three distinct injection media: CO₂, water, and CO₂/water alternate huff-n-puff. A 35 cm composite core was employed to simulate the reservoir conditions after pre-fracturing. Experimental results indicated that the CO₂ huff-n-puff process yielded the highest oil production, enhancing the overall recovery factor by 33.0% compared to depletion production, with a total recovery factor of 43.8% after four optimized cycles. The CO₂/water alternate huff-n-puff process increased the recovery factor by 28.3%, achieving a total of 41.9% after four cycles. In contrast, water injection improved the recovery factor by only 15.2%, reaching a total of 26.2% after three cycles. By evaluating both oil recovery efficiency and oil exchange ratio, the optimal cycle numbers were determined as four cycles for CO₂ huff-n-puff, four cycles for CO₂/water alternate huff-n-puff, and three cycles for water huff-n-puff. Based on these optimized parameters, the CO₂/water alternate huff-n-puff process was identified as the most effective EOR method for the target reservoir. Furthermore, this study assessed the potential for CO₂ storage in the reservoir post-production. Calculations of CO₂ storage ratios during the huff-n-puff process demonstrated the feasibility of integrating enhanced oil recovery with carbon sequestration. The findings provide a practical strategy for improving heavy oil recovery in low-permeability reservoirs while concurrently exploring the benefits of CO₂ storage. Full article

How to economically and effectively mobilize remaining oil and achieve carbon sequestration after water flooding in low-permeability, high-water-cut reservoirs is an urgent challenge. This study, focusing on Block Y of the Daqing Oilfield, employs numerical simulation to systematically reveal the synergistic influencing mechanisms of CO₂ flooding and geological storage. A three-dimensional compositional model characterizing this reservoir was constructed, with a focus on analyzing the controlling effects of key geological (depth, heterogeneity, physical properties) and engineering (gas injection rate, gas injection volume, bottom-hole flowing pressure) parameters on the displacement and storage processes. Simulation results indicate that the low-permeability characteristics of Block Y effectively suppress gas channeling, enabling a CO₂ flooding enhanced oil recovery (EOR) increment of 15.65%. Increasing reservoir depth significantly improves both oil recovery and storage efficiency by improving the mobility ratio and enhancing gravity segregation. Parameter optimization is key to achieving synergistic benefits: the optimal gas injection rate is 700–900 m³/d, the economically reasonable gas injection volume is 0.4–0.5 PV, and the optimal bottom-hole flowing pressure is 9–10 MPa. This study confirms that for Block Y and similar high-water-cut, low-permeability reservoirs, CO₂ flooding is a highly promising replacement technology; through optimized design, it can simultaneously achieve significant crude oil production increase and efficient CO₂ storage. Full article

The exponential growth of lithium-ion batteries (LIBs) in electric vehicles and energy storage systems has amplified the urgent need for sustainable recycling strategies. Conventional pyrometallurgical and hydrometallurgical methods for LIB recycling are energy-intensive, chemically demanding, and fail to preserve the structural integrity of cath-ode materials. Closed-loop recycling, in contrast, enables the recovery of layered oxides with minimal processing steps, reducing environmental footprint and supporting a circular economy. This study provides a systematic comparison of two regeneration approaches—sol–gel synthesis and hydroxide co-precipitation—for closed-loop recycling of layered NCM (LiNi_xCo_yMn_zO₂) cathode materials recovered from spent LIBs. Spent cells were mechani-cally processed and leached using malic acid to recover Ni, Co, Mn, which were subsequently used to synthesize NCM622 cathode powders. The regenerated materials were characterized using SEM/EDX, XRD, and electrochemical testing in CR2032 coin cells. Both methods successfully produced phase-pure layered oxides with the R-3m structure, with distinct differences in structural ordering and electrochemical behavior. The sol–gel-derived NCM622 displayed higher crystallinity and reduced cation mixing, evidenced by an I(003)/I(104) ratio of 1.896 compared to 1.720 for the co-precipitated sample, and delivered a high initial discharge capacity of 170 mAh/g at 0.1 C. However, it exhibited significant capacity fade, retaining only 60 mAh/g after 40 cycles. In contrast, the co-precipitation route produced hierarchical porous spherical agglomerates that offered superior cycling stability, maintaining ~150 mAh/g after 40 cycles with lower polarization (ΔE_p = 0.16 V). Both materials demonstrated electrochemical performance comparable to commercial NCM. Overall, hydroxide co-precipitation emerged as the most industrially viable method due to scalable processing, compositional robustness, and improved long-term stability of regenerated cathodes. This work highlights the critical influence of synthesis route selection in LIB closed-loop recycling and provides a technological framework for industrial recovery of high-value NCM cathode materials. Full article

Methenamine, a urinary antiseptic with antimicrobial properties, decomposes into toxic formaldehyde under acidic conditions. Its use is prohibited in dairy cattle in Korea to prevent harmful residues in milk. This study was designed to develop and validate a sensitive and reliable LC–MS/MS method for determining methenamine in raw milk and bovine muscle in compliance with the Positive List System (PLS) regulations. Samples were extracted with acetonitrile (ACN)–methanol (MeOH) (7:3, v/v) containing ammonia water, followed by defatting with n-hexane and purification with primary secondary amine (PSA). Chromatographic separation was performed on a hydrophilic interaction liquid chromatography (HILIC) column, and quantification was conducted using matrix-matched calibration to minimize matrix effects. The method showed excellent linearity (R² > 0.999), low limits of quantification (LOQ) (0.49 μg/kg for raw milk; 0.64 μg/kg for bovine muscle), and acceptable recoveries (78.1–102.8%) with precision (CV ≤ 8.75%), meeting Codex CAC/GL 71-2009 criteria. Stability studies demonstrated that methenamine remained stable in stock solutions, working standards and processed extracts under the storage and handling conditions used. Application to incurred samples resulted in the detection of methenamine in 2 of 32 raw milk samples (0.65 and 1.14 μg/kg) but in none of the 25 bovine muscle samples, with all detected levels below the Korean PLS limit. These findings confirm that the developed method is accurate, sensitive, and applicable for routine surveillance of methenamine residues to ensure consumer safety. Full article

The global food industry is undergoing a critical shift toward sustainability, driven by high postharvest losses—reaching up to 40% for fruits and vegetables—and the need to reduce environmental impact. Sustainable postharvest innovations focus on improving quality, extending shelf life, and minimizing waste through eco-efficient technologies. Advances in non-thermal and minimal processing, including ultrasound, pulsed electric fields, and edible coatings, support nutrient preservation and food safety while reducing energy consumption. Although integrated postharvest technologies can reduce deterioration and microbial spoilage by 70–92%, significant challenges remain, including global losses of 20–40% and the high implementation costs of certain nanostructured materials. Simultaneously, eco-friendly packaging solutions based on biodegradable biopolymers and bio-composites are replacing petroleum-based plastics and enabling intelligent systems capable of monitoring freshness and detecting spoilage. Energy-efficient storage, smart sensors, and optimized cold-chain logistics further contribute to product integrity across distribution networks. In parallel, the circular bioeconomy promotes the valorization of agro-food by-products through the recovery of bioactive compounds with antioxidant and anti-inflammatory benefits. Together, these integrated strategies represent a promising pathway toward reducing postharvest losses, supporting food security, and building a resilient, environmentally responsible fresh produce system. Full article

CO₂-enhanced oil recovery (CO₂-EOR) with water-alternating-gas (WAG) injection offers the dual benefit of boosted oil production and CO₂ storage, addressing both energy needs and climate goals. However, designing CO₂-WAG schemes is challenging; maximizing oil recovery, CO₂ storage, and economic returns (net present value, NPV) simultaneously under a limited simulation budget leads to conflicting trade-offs. We propose a novel closed-loop multi-objective framework that integrates high-fidelity reservoir simulation with stacking surrogate modeling and active learning for multi-objective CO₂-WAG optimization. A high-diversity stacking ensemble surrogate is constructed to approximate the reservoir simulator. It fuses six heterogeneous models (gradient boosting, Gaussian process regression, polynomial ridge regression, k-nearest neighbors, generalized additive model, and radial basis SVR) via a ridge-regression meta-learner, with original control variables included to improve robustness. This ensemble surrogate significantly reduces per-evaluation cost while maintaining accuracy across the parameter space. During optimization, an NSGA-II genetic algorithm searches for Pareto-optimal CO₂-WAG designs by varying key control parameters (water and CO₂ injection rates, slug length, and project duration). Crucially, a decision-space diversity-controlled active learning scheme (DCAF) iteratively refines the surrogate: it filters candidate designs by distance to existing samples and selects the most informative points for high-fidelity simulation. This closed-loop cycle of “surrogate prediction → high-fidelity correction → model update” improves surrogate fidelity and drives convergence toward the true Pareto front. We validate the framework of the SPE5 benchmark reservoir under CO₂-WAG conditions. Results show that the integrated “stacking + NSGA-II + DCAF” approach closely recovers the true tri-objective Pareto front (oil recovery, CO₂ storage, NPV) while greatly reducing the number of expensive simulator runs. The method’s novelty lies in combining diverse stacking ensembles, NSGA-II, and active learning into a unified CO₂-EOR optimization workflow. It provides practical guidance for economically aware, low-carbon reservoir management, demonstrating a data-efficient paradigm for coordinated production, storage, and value optimization in CO₂-WAG EOR. Full article

This review critically examines photoresponsive supercapacitors based on TiO₂/graphene hybrids, with a particular focus on their emerging dual role as energy-storage devices and environmental sensors. We first provide a concise overview of the electronic structure of TiO₂ and the key attributes of graphene and related nanocarbons that enable efficient charge separation, transport, and interfacial engineering. We then summarize and compare reported device architectures and electrode designs, highlighting how morphology, graphene integration strategies, and illumination conditions govern specific capacitance, cycling stability, rate capability, and light-induced enhancement in performance. Particular attention is given to the underlying mechanisms of photo-induced capacitance enhancement—including photocarrier generation, interfacial polarization, and photodoping—and to how these processes can be exploited to embed sensing functionality in working supercapacitors. We review representative studies in which TiO₂/graphene systems operate as capacitive sensors for humidity, gases, and volatile organic compounds, emphasizing quantitative figures of merit such as sensitivity, response/recovery times, and stability under repeated cycling. Finally, we outline current challenges in materials integration, device reliability, and benchmarking, and propose future research directions toward scalable, multifunctional TiO₂/graphene platforms for self-powered and environmentally aware electronics. This work is intended as a state-of-the-art summary and critical guide for researchers developing next-generation photoresponsive supercapacitors with integrated sensing capability. Full article

Current CO₂-based energy storage systems still face several unsolved technical challenges, including strong thermal destruction between the multi-stage compression and expansion processes, significant exergy destruction in heat exchange units, limited utilization of low-grade heat, and the lack of an integrated comprehensive performance framework capable of simultaneously evaluating thermodynamic, economic, and environmental performance. Although previous studies have explored various compressed CO₂ energy storage (CCES) configurations and CCES–Organic Rankine Cycle (ORC) couplings, most works treat the two subsystems separately, neglect interactions between the heat exchange loops, or overlook the combined effects of exergy losses, cost trade-offs, and CO₂-emission reduction. These gaps hinder the identification of optimal operating conditions and limit the system-level understanding needed for practical application. To address these challenges, this study proposes an innovative system that integrates a multi-stage CCES system with ORC. The system introduces ethylene glycol as a dual thermal carrier, coupling waste-heat recovery in the CCES with low-temperature energy utilization in the ORC, while liquefied natural gas (LNG) provides cold energy to improve cycle efficiency. A comprehensive 4E (energy, exergy, economic, and environmental) assessment framework is developed, incorporating thermodynamic modeling, exergy destruction analysis, CEPCI-based cost estimation, and environmental metrics including primary energy saved (PES) and CO₂ emission reduction. Sensitivity analyses on the high-pressure tank (HPT) pressure, heat exchanger pinch temperature difference, and pre-expansion pressure of propane (P₃₀) reveal strong nonlinear effects on system performance. A multi-objective optimization combining NSGA-II and TOPSIS identifies the optimal operating condition, achieving 69.6% system exergy efficiency, a 2.07-year payback period, and 1087.3 kWh of primary energy savings. The ORC subsystem attains 49.02% thermal and 62.27% exergy efficiency, demonstrating synergistic effect between the CCES and ORC. The results highlight the proposed CCES–ORC system as a technically and economically feasible approach for high-efficiency, low-carbon energy storage and conversion. Full article

As critical national energy arteries, long-distance large-scale cross-regional gas transmission networks are characterized by high operating pressures, extensive spatial coverage, and complex topological structures. Thus, the multi-hazard profiles threatening its safety and reliability operation differ significantly from those of local urban gas distribution networks. This research develops a resilience assessment framework capable of quantifying resistance, adaptation, and recovery capacities of such energy systems. The framework establishes performance indicator systems based on design parameters, installation environments, and construction methods for long-distance trunk pipelines and key facilities such as storage facilities. Furthermore, based on complex network theory, the size of the largest connected component and global efficiency of the transmission network are selected as core topological metrics to characterize functional scale retention and transmission efficiency under disturbances, respectively, with corresponding quantification methods proposed. A cross-regional pipeline transmission network within a representative municipal-level administrative region in China is used as a case for empirical analysis. The quantitative assessment results of pipeline and network resilience are analyzed. The research indicates that trunk pipeline resilience is significantly affected by characteristic parameters, the laying environment, and installation methods. It is notably observed that installation methods like jacking and directional drilling, used for road or river crossings, offer greater resistance than direct burial but considerably lower restoration capacity due to the complexity of both the environment and the repair processes, which increases time and cost. Moreover, simulation-based comparison of recovery strategies demonstrates that, in this case, a repair-time-prioritized strategy more effectively enhances overall adaptive capacity and restoration efficiency than a node-degree-prioritized strategy. The findings provide quantitative analytical tools and decision-support references for resilience assessment and optimization of cross-regional energy transmission networks. Full article

Lead-acid batteries (LAB) continue to be one of the most widely used energy storage technologies worldwide, especially in the automotive sector and in backup systems. However, their use is a significant source of lead and sulfuric acid pollution, with negative impacts on the environment and human health. This review analyzes the environmental and health effects of LAB manufacturing, use, and recycling, and evaluates sustainable alternatives through life cycle analysis. A search was conducted in the Multidisciplinary Digital Publishing Institute (MDPI), Science Direct, and Springer databases, yielding more than 247 documents, from which 84 technical and scientific articles were selected, mostly from the last five years, excluding duplicates and irrelevant texts or those in languages other than English. The results reveal that conventional pyrometallurgical processes release between 30 and 50 kg of lead fumes per ton processed, causing concentrations of up to 5000 mg/kg of Pb in soils near informal plants, exceeding international limits by more than 25 times. In contrast, closed-loop hydrometallurgical technologies reduce emissions by more than 70% and increase secondary lead recovery, making them an environmentally friendly option. It is concluded that the sustainability of the LAB system requires technological innovation, effective regulation, and extended responsibility within an eco-friendly circular economy model. Full article

Lithium has emerged as a critical energy metal due to its indispensable role in batteries, aerospace applications, new energy vehicles, and large-scale energy storage systems. The accelerated growth of electric mobility and renewable energy storage has led to a substantial increase in lithium demand, thereby exacerbating the prevailing global supply–demand imbalance. To address this challenge, it is imperative to diversify lithium resources and to advance extraction technologies that are both efficient and sustainable. In comparison with conventional hard-rock deposits, liquid resources such as salt lake brines, oilfield brines, and deep-well brines are gaining attention owing to their broad distribution, abundant reserves, and advantages of reduced land use, lower water consumption, and lower carbon emissions. This work presents a critical review of current lithium recovery strategies from brines, including precipitation, solvent extraction, adsorption, nanofiltration/electrodialysis, and electrochemical methods. Each approach is critically evaluated in terms of Li/Mg selectivity, extraction efficiency, operational stability, and environmental compatibility. Precipitation processes offer simplicity but suffer from low Li recovery and high chemical consumption; solvent extraction achieves high selectivity but faces phase and reagent loss; adsorption using Mn-based sieves yields high capacity with good regeneration stability, whereas membrane and electrochemical systems enable continuous lithium recovery with reduced energy input. Distinct advantages and existing gaps are systematically summarized to provide quantitative insights into performance trade-offs among these pathways. Key findings highlight that organophosphorus–FeCl₃ systems and Mn-based lithium-ion sieves show the best trade-off between selectivity and regeneration stability, whereas emerging membrane–electrochemical hybrids demonstrate promise for low-energy, continuous lithium recovery. The prospects for future development highlight highly selective functional materials, integrated multi-technology processes, and greener, low-energy extraction pathways. Full article

Aquifer thermal energy storage (ATES) is a concept that can help to address heating and cooling needs through the use of the subsurface as a seasonal thermal energy storage (STES) system. Over 2800 ATES systems have been deployed with storage temperatures typically below 25 °C and only a few with higher temperatures (>40 °C), which would increase the energy density and utility of the stored thermal fluids. Until now, only a few high-temperature aquifer thermal energy storage (HT-ATES) projects have been initiated and are still in operation. These HT-ATES projects have encountered a range of technical and non-technical challenges. This study reviews ten such projects: four in Germany and six in the Netherlands. The non-technical issues include public acceptance, a lack of regulatory framework for these systems, managing overlapping uses of the subsurface, managing changes with the providers and off-takers of thermal energy, and obtaining financing to implement these projects. Common technical issues include geological factors such as incomplete characterization of the subsurface and reservoir heterogeneity; geochemical issues such as mineral scaling, corrosion, and biofouling; lower than expected thermal recovery; and issues with system design and reliability. This review highlights benefits and challenges faced by HT-ATES projects with the goal to use the lessons learned to improve the siting, design, development, and operation of such systems. Recommendations include improved initial subsurface site characterization, use of coupled process models to optimize system design and predict system performance, cascaded uses of stored thermal energy to better utilize the stored heat, monitoring networks to provide feedback on system performance, and expanded system scale to allow for continued operation even when maintenance of some system components is required. Techno-economic modeling and risk analysis could be used to optimize such HT-ATES project design and identify key factors that will affect sustained economic viability. In addition, design flexibility is important for these systems to allow for changing conditions regarding the supply and demand of thermal energy. Adopting these findings should improve the performance and reduce the risks for future HT-ATES projects worldwide. Full article

Background/Objectives: Adipose tissue (AT) plays significant roles in energy storage, metabolite signaling, and immunomodulation. The understanding of its underlying mechanisms of dysregulation can provide insight into complex disease processes through analysis with histology, flow cytometry, metabolomics, and proteomics. Tissue sampling in the clinical setting has largely shifted towards minimally invasive approaches to improve factors such as patient satisfaction, post-operative recovery, and procedure length. In contrast, preclinical animal models continue to rely on more invasive methods until refined, minimally invasive techniques are developed and systematically assessed. To improve animal welfare and enhance clinical translatability, there is a critical need to reverse translate these approaches into animal models. Methods: Our study evaluated the feasibility and performance of a commercially available vacuum-assisted biopsy (VAB) device for AT sampling in a preclinical nonhuman primate (NHP) model. Six rhesus NHPs successfully underwent three serial AT biopsies with a VAB device (n = 18). Results: All animals recovered without any serious or unexpected adverse events. The amount of adipose tissue collected per biopsy (0.5–2.7 g) was proportional to the number of individual tracks. Isolation of the stromal vascular fraction (SVF) from a subset of samples (n = 6) yielded 0.41 ± 0.12 × 10⁶ cells/g of tissue. Conclusions: The minimally invasive VAB technique is a safe and reliable method of AT collection in NHPs. This feasibility study demonstrated adequate volumes of tissue cores that are suitable for typical, downstream research applications including immunologic studies and pathology, while improving animal welfare. Full article