Search Results (7,383)

Achieving efficient demulsification of water-in-heavy oil (W/HO) emulsions remains a critical issue that urgently needs to be addressed in the heavy oil industry. Despite being a new generation of green demulsification materials, magnetic carbon nanoparticles still suffer from low demulsification efficiency when applied to water-in-heavy oil emulsions. Herein, polyethyleneimine-modified magnetic carbon nanoparticles (P-MCNs) were successfully prepared via a surface functionalization strategy. The demulsification performance of P-MCN in water-in-heavy oil (W/HO) emulsions was evaluated via the standard bottle test. The results demonstrated that P-MCN (500 ppm) achieved effective water removal within 60 min at 50 °C. Microscopic visualization characterization revealed that the efficient water removal from W/HO emulsions by P-MCN is attributed to its high interfacial activity. Specifically, P-MCN can rapidly migrate to the heavy oil–water interface and effectively disrupt the interfacial film through electrostatic interactions and hydrogen bonding, thereby achieving efficient demulsification of W/HO emulsions. This study provides a solid theoretical foundation for the further development of magnetic carbon nanoparticles with higher demulsification efficiency for applications in the petroleum industry. Full article

Essential oils are complex plant-derived volatile blends composed of a myriad of aromatic secondary metabolites. The volatile architecture of plant essential oils suggests a consistent trend under the experimental conditions evaluated, regardless of the distillation scale and methodology. This study presents a comparative chemometric evaluation of two integrated processing systems: laboratory-scale hydrodistillation (HD) of dried biomass versus semi-industrial-scale dry steam distillation (SD) of fresh biomass. Seven economically important botanical species spanning three families were analyzed: Lavandula angustifolia, Salvia officinalis, Hyssopus officinalis, Mentha piperita, Mentha spicata, Achillea millefolium, and Picea abies. Gas chromatography–mass spectrometry (GC-MS) profiling revealed that HD consistently yielded a more chemically diverse volatile profile than SD. Unsupervised Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) achieved absolute binary segregation between the HD and SD fractions for every species. Supervised Partial Least Squares Discriminant Analysis (PLS-DA) established robust predictive models (Q² cum > 0.98), isolating specific chemical markers responsible for the variance. The results prove a universal physical trend: HD significantly enriched low-boiling oxygenated derivatives (such as oxygenated monoterpene alcohols and oxides), while SD selectively preserved heavier, thermally sensitive hydrocarbon fractions across all taxonomic groups. Ultimately, combining GC-MS with multivariate chemometrics provides an objective, automated framework for quality control, authentication, and industrial process optimization in the essential oil sector. Full article

The reliable inspection of aging oil and gas pipelines is essential for preventing accidents and ensuring operational safety, yet the accuracy of RFID-based detection systems is often limited by noise-sensitive peak detection algorithms, motivating the need for more robust signal processing approaches. In this study, an improved Discrete Wavelet Transform (DWT)-based method is proposed, employing db6/db8 wavelets for signal denoising and reconstruction, followed by peak localization using derivative zero-crossing to enhance detection precision. Experimental validation was conducted through both simulations and physical tests, where the proposed method achieved zero false and missed detections in simulation environments and reduced relative error by 30–50% compared to conventional algorithms in practical scenarios. These results demonstrate that the proposed approach significantly improves detection reliability and accuracy. Overall, the method provides an effective and cost-efficient solution for pipeline surface defect inspection, offering strong potential for application in real-world industrial monitoring systems. Full article

Oil recovery from carbonate reservoirs is one of the critical challenges in the oil industry due to the strongly oil-wet nature, natural fractures, and the heterogeneity of carbonate rocks. Subsequently, waterflooding can only displace oil from large fractures, leaving the majority of oil trapped in the rock matrix. This work suggests that nanofluid flooding, as a predesigned flooding method, is an alternative to conventional waterflooding. Various concentrations of silica nanofluid at different nanoparticle concentrations were formulated and systematically investigated for their characteristics, stability at reservoir conditions, and their influence on wettability and oil recovery. Silica nanoparticles were sustainably synthesized from waste materials to ensure the feasibility and environmental friendliness of the process. Results indicated that the synthesized silica has an amorphous crystalline nature characterized by nano-sized particles. Additionally, treating silica nanoparticles with a silane group significantly enhances the stability of nanofluids in a high-salinity environment. Most interestingly, by comparing the amount of oil recovered, the results revealed that implementing nanofluid flooding as a secondary oil recovery, rather than waterflooding, can produce around 12% more oil, in addition to eliminating a whole waterflooding step. This is the first study to alter the traditional flooding scenario and directly conduct nanofluid flooding as secondary oil recovery, without being preceded by waterflooding, using sustainably synthesized nanoparticles. Considering the water crisis in the Middle East, this approach can save substantial amounts of water, which improves the sustainable development of communities. Full article

Bio-based polyurethane (PU) coatings offer sustainable alternatives to petrochemical coatings but often suffer from inferior mechanical performance, durability, and chemical resistance. This work addresses that challenge by integrating a trifunctional bio-based crosslinker (glycerol) and a silane-based additive (hexamethyldisilane (HMDS)) to simultaneously enhance structural robustness and hydrophobicity. Coatings were synthesized using a renewable soybean oil polyol (SOP), glycerol (5, 10, 15 and 20 wt.%), and methylene diphenyl diisocyanate (MDI), followed by the addition of HMDS (10, 20, 30, 40 and 50 wt.%). Mechanical tests identified 10 wt.% glycerol as the optimal content, yielding a maximum tensile strength of 47.18 MPa. Incorporating 10 wt.% HMDS into the optimized formulation greatly increased water contact angle (WCA, 95.76°) and chemical resistance with minimal loss of mechanical performance (38.19 MPa, tensile strength); higher HMDS loadings caused network disruption and reduced strength. Calorimetry and thermogravimetric analyses confirmed that the modified coatings retained high thermal stability. This synergistic crosslinker additive strategy produced a structurally robust, water-resistant bio-based coating, demonstrating a viable high-performance sustainable coating solution for industrial applications. Full article

Lubricating oil monitoring provides continuous health information for early fault warning and maintenance decision-making in industrial gas turbines. However, real-world multi-sensor monitoring streams exhibit pronounced nonstationary thermodynamic drifts that often obscure subtle high-frequency residuals containing critical incipient degradation signatures. Prevailing data-driven monitoring models typically struggle to separate these macroscopic trends from stochastic wear-related fluctuations, and their restrictive distributional assumptions are often inadequate for the heteroscedastic and heavy-tailed nature of industrial residuals. To address these challenges, this study proposes ResAD-Net, a framework for early fault warning in nonstationary multi-sensor oil monitoring that combines trend–residual decoupling, trend-conditioned residual modeling, and residual-domain dependency learning. Specifically, a signal trend–residual decoupling strategy is adopted to separate slowly varying operational trends from stochastic residual fluctuations captured by the sensors, thereby exposing residual information that is more sensitive to incipient degradation. On this basis, a trend-conditioned diffusion model is introduced to characterize state-dependent, skewed residual distributions and generate residual sample ensembles for nonstationary monitoring. Meanwhile, a graph-based variational autoencoder is employed to learn latent intersensor dependency structures from the residual domain, providing diagnostic cues for temporal risk evolution analysis and sensor-level inspection. Experiments on a real-world industrial oil-monitoring record show that the proposed framework achieves an average F1-score of 0.985 with no observed false positives in the predefined pre-alarm reference interval of the finite test set. In addition to accurate anomaly detection, ResAD-Net captures early residual distributional shifts before clear macroscopic deviations emerge and provides diagnostic association cues for interpreting oil-monitoring changes around the system-level alarm. Full article

Soybean is a critical economic, oil and industrial raw material crop, yet its production is often hindered by pathogen infection and pesticide residues. This study explored the synergistic effects of Rhizophagus intraradices and mycorrhizal helper bacteria (MHB) on AMF colonization, AMF spore density, total number of bacterial colonies, soybean growth, root rot disease index, and carbendazim residues. Hydroponic and pot experiments were conducted using a completely randomized design (CRD) with five biological replicates per treatment; after 30 days of growth, three replicates were randomly selected for all measurements. Results showed that inoculation with microbial agents, particularly co-inoculation, increased soybean biomass, reduced disease index, and decreased carbendazim residues. In the hydroponic experiment, co-inoculation increased plant height, aboveground fresh weight, and underground dry weight by 64.28%, 78.13%, and 109.09%, respectively, and decreased carbendazim residues by 71.84% relative to the carbendazim-alone group. In the pot experiment, co-inoculation reduced carbendazim residues by 81.25% and root rot disease index by 45.56% compared with the carbendazim-alone group. Correlation analysis showed a strong positive correlation (p < 0.001) between carbendazim degradation in hydroponic and pot systems, indicating stable degradation function across environments. Co-inoculation of R. intraradices and MHB synergistically promotes soybean growth, suppresses root rot, and reduces carbendazim residues, providing a theoretical basis for developing functional microbial inoculants for safe and green soybean production. Full article

Coffee oil, an increasingly recognized yet underutilized byproduct of spent coffee grounds, has attracted attention due to its diverse lipid composition and minor components. This study systematically investigated the lipid characteristics of coffee oils extracted from both Arabica and Robusta spent coffee grounds subjected to varying roasting degrees. Comprehensive analyses were conducted, mainly regarding oil yield, acid and peroxide values, fatty acid profiles, sn-2 positional fatty acid distribution, triacylglycerol composition, tocopherol content and total Folin-reactive compounds, as well as squalene and sterol profiles. The selected Arabica samples generally showed higher oil yields than Robusta samples, with oil contents ranging from 12.13% to 15.14% and 10.10% to 13.01%, respectively. Arabica coffee oils showed relatively high total tocopherol levels, ranging from 930.35 to 1495.37 mg/kg, whereas Robusta coffee oils ranged from 637.69 to 867.21 mg/kg. Total Folin-reactive compounds varied among samples and should be interpreted as composition-related indicators rather than direct evidence of antioxidant function. In contrast, Robusta coffee oils contained much higher levels of squalene and total sterols, ranging from 97.00 to 170.37 mg/100 g and 787.29 to 1007.92 mg/100 g, respectively. Chemometric analyses showed distinct grouping patterns among the selected coffee oil samples. In the present sample set, the overall lipid profiles were more closely associated with the Arabica and Robusta sample groups than with the assigned roasting levels. These results provide compositional information for the potential use of Arabica coffee oil as a tocopherol- and Folin-reactive compound-rich lipid ingredient. Robusta coffee oil may be further evaluated for applications requiring higher levels of squalene, phytosterols, and relatively saturated lipid structures. This study provides novel insights into the compositional complexity of coffee oil and supports its targeted valorization across various industries. Full article

This study examined the chemical composition and quantitative source contributions of coarse (PM_10–2.5) and fine (PM_2.5) particles in ship-based PM₁₀ and PM_2.5 filter samples from 2020 to 2024 across the Yellow Sea. The observations were primarily conducted during the spring season, when the influence of continental air masses from East Asia is pronounced, and detailed analyses of water-soluble ions and elemental species were performed. In coarse particles, sea salt components (e.g., Na⁺ and Cl⁻) and soil-derived species (e.g., nss-Ca²⁺ and CO₃²⁻) were predominant, whereas fine particles were dominated by secondary inorganic species such as nss-SO₄²⁻, NO₃₋, and NH₄⁺. Source contributions were estimated using Dispersion Normalized Positive Matrix Factorization (DN-PMF), and eight common factors were identified, including sea salt, soil, secondary nitrate, secondary sulfate, oil combustion, biomass burning, marine biogenic emissions, and plant growth. Additionally, an industry factor was uniquely resolved in coarse particles, whereas a mobile source factor was identified in fine particles. In coarse particles, sea salt (30.9%) and soil (15.1%) were the major contributing sources, whereas fine particles were dominated by secondary nitrate (48.6%) and secondary sulfate (15.6%). Potential Source Contribution Function (PSCF) analysis indicated that the sea salt and oil combustion factors in coarse particles were associated with coastal regions of the Yellow Sea and the East China Sea, while the soil factor corresponded spatially with inland regions of northern China. In contrast, the secondary nitrate, secondary sulfate, and biomass burning factors in fine particles showed strong associations with inland regions of eastern China. Using size-resolved DN-PMF and five years of repeated observations over the same marine region, this study provides the first quantitative source apportionment analysis of interannual atmospheric composition variability and long-range transport affecting air quality over the Yellow Sea. Full article

In past decades, the macroeconomic stability of India has been tested repeatedly by major global disruptions, including oil price shocks, the 2008 global financial crisis and the COVID-19 pandemic. Analysing how macroeconomic variables respond to these shocks is essential for evaluating external vulnerability and policy resilience in emerging economies. Our study provides a comprehensive empirical investigation of the dynamic responses of wholesale price inflation, industrial output, oil prices and exchange rates in India by employing monthly data from January 1993 to December 2024. To examine long-run equilibrium relationships along with short-run adjustment dynamics, the present study employs co-integration analysis within a Vector Error Correction Model (VECM) framework. Further, we applied impulse response functions and forecast error variance decomposition to track volatility spillover mechanisms. Quantile regression and ARCH–GARCH models were further estimated to account for distributional heterogeneity and time-varying volatility. The findings of our study suggested stable long-run linkages among the selected variables, where oil price shocks emerged as a key external source of macroeconomic fluctuations. Short-run dynamics suggested that shocks in oil prices are transmitted primarily through inflation and exchange rate channels and then affect industrial output. Distributional estimates revealed the effects were stronger during stress periods, indicating tail risks that were not captured by the mean-based models. Lastly, volatility analysis confirmed persistent clustering, especially during phases of crisis. Overall, the findings suggest that India’s macroeconomic system remains externally sensitive, with adjustment mechanisms that operate gradually but come under strain during global disruptions. These results underscore the importance of energy risk management and crisis-responsive macroeconomic stabilisation policies. Full article

Northern Colombian Creole-Antillean avocado constitutes a promising agroindustrial resource because of its lipid-rich composition and regional availability. Despite this potential, the industrial exploitation of this biomass remains limited, particularly regarding the technical assessment of large-scale oil production systems. In this study, an avocado oil production process was evaluated through computer-aided simulation combined with the Water–Energy–Product (WEP) methodology to assess operational behavior, resource utilization, and process efficiency from an integrated technical perspective. The evaluated system achieved an overall production yield of 9.43%, mainly affected by the elevated raw material requirements associated with oil generation. Nevertheless, the extraction stage exhibited favorable technical performance, reaching an oil recovery efficiency of 81.42%. Concerning water management, the process required 26.85 m³/t of freshwater and generated wastewater equivalent to 96.05% of the total water consumed, revealing important limitations related to water integration and recirculation within the process configuration. From an energy perspective, the system presented a specific energy intensity of 19,929 MJ/t, with natural gas representing the predominant energy source throughout the operation. Overall, the obtained results demonstrate that the proposed process is technically viable for avocado oil production while also identifying critical opportunities for improving resource utilization, decreasing water demand, and enhancing the operational sustainability of the system. Full article

Pipeline valves play a crucial role in oil and gas exploration, production, transportation, and storage, and a systematic understanding of patent technologies in this field can help identify innovation trends and formulate research and development (R&D) strategies. This study collected more than 5000 pipeline-valve-related patents worldwide from 2006 to 2025, including 2292 invention patents, and adopted a progressive patent analytics approach integrating statistical analysis, network analysis, text mining, and high-value invention patent analysis. The results show that innovation activity in this field has remained active over the past two decades, especially since 2016, when the number of patent publications exceeded 300 in almost every year. China, Russia, the United States, South Korea, and Canada are the major sources of patent activity, with Chinese enterprises and universities making important contributions in terms of patent quantity. However, the analysis of high-value invention patents indicates that representative patents from the United States, Canada, and Russia also have a strong influence. Core innovation directions cover multiple pipeline valve applications in oil and gas extraction, transportation, and storage, with valve control systems and mechanical structures constituting the dominant technologies. The ten identified technological themes and their evolution show that technological innovation in this field has gradually expanded from mechanical improvements in traditional valve bodies, sealing components, and pressure relief devices to diversified directions such as wellhead control, intelligentization, and low-carbon development. The analysis of high-value invention patents further confirms this trend, indicating that pipeline valve technology is being reshaped from a relatively mature mechanical technology field into an integrated technological system that combines mechanical reliability, intelligent control, and other dimensions. Full article

Microbially induced corrosion is a common problem in the petroleum industry. In this study, weight loss and surface analysis of grade 20 carbon steel corrosion witness samples were used to evaluate biocorrosion in produced fluids from different wells (Romashkino oilfield, Republic of Tatarstan, Russia). The structure of the resulting microbial communities in the systems with high corrosion indicators was elucidated. The addition of acetate/lactate, yeast extract, and sulfate was found to promote the growth of individual microorganisms in the designed systems and to increase the corrosion rate in several samples (to an average of 0.12 mm year⁻¹). The results of 16S rRNA gene sequence analysis showed that water from different wells from the Romashkino oilfield had distinct microbial compositions. The main genera in the analyzed waters were Oleidesulfovibrio, Halanaerobium, Proteiniphilum, Acetobacterium, Fusibacter, and Methanocrinis, but their relative abundances depended on the water itself and the type of stimulation. Acetogenic bacteria of the genera Fusibacter, Proteiniphilum, Acetobacterium, and acetoclastic methanogenic archaea Methanocrinis became dominant in the microbial community structure in the acetate-enriched systems in water from one of the studied wells. Electron donors, generated by various bacteria and artificially introduced ones, facilitated active dissimilatory sulfate reduction by Oleidesulfovibrio, Desulfotignum, Desulfocurvus, and Pseudodesulfovibrio in water from another production well. The obtained results are important for identifying the causes of premature failures of oilfield equipment, particularly in areas where microbial enhanced oil recovery is used. Full article

Recently there has been notable interest in the reduction in emissions of the shipping industry via the substitution of the currently used fossil fuels with alternative green fuels. One such alternative studied presently could be the use of pure vegetable oils, which are cheaper and easier to produce than other proposed fuels. In this study, pure vegetable oils were tested in a constant volume combustion chamber to assess their ignition quality via the measurement of their Estimated Cetane Number (ECN) and to compare it with that of heavy fuel oils (HFOs). Moreover, the effect of vegetable oil composition on ignition quality was investigated. It was found that all the vegetable oils tested possessed significantly higher ignition quality than standard heavy fuel oils. Vegetable oil ignition quality was found to be most impacted by their degree of unsaturation. The results of the present study indicate that from the point of view of ignition quality, vegetable oils are a viable alternative to fossil fuels, being expected to lead to an increase in the ignition quality of standard heavy fuel oils. Full article

This study provides a comprehensive examination of the inflation-hedging potential of commodity indices and futures for U.S. investors using monthly data spanning July 1959 to December 2025 for 27 individual commodities, and January 1947 to November 2025 for 13 commodity indices. We employ multiple complementary methodologies, including optimal hedge ratios with Newey–West standard errors, asymmetric hedging analysis, long-horizon regressions, rolling window stability tests, Granger causality analysis, out-of-sample validation, and Markov-switching vector error correction models (MS-VECM). Our results reveal substantial heterogeneity in hedging effectiveness across commodity sectors. Energy commodities, particularly gasoline and crude oil, demonstrate the strongest inflation-hedging properties with higher hedge ratios and hedging effectiveness. Industrial metals, represented by copper, also provide reliable hedging with stable performance across market conditions. In contrast, precious metals, including gold and silver, show weak contemporaneous hedging ability despite their traditional safe-haven reputation, though they may offer protection during specific market regimes. Agricultural commodities and livestock exhibit minimal or negative hedging effectiveness. The MS-VECM analysis confirms that hedging relationships are time-varying, with effectiveness differing significantly between stable and turbulent market regimes. These findings have important implications for portfolio construction and risk management strategies. Full article