By investigating the evolution of shale gas generation,storage,adjustment and accumulation under different structural settings in superimposed basins,this study elucidates the differential accumulation mechanisms of s...By investigating the evolution of shale gas generation,storage,adjustment and accumulation under different structural settings in superimposed basins,this study elucidates the differential accumulation mechanisms of shale gas.An improved evaluation method of shale gas content evolution in superimposed basins is proposed.This method incorporates the coupling effect of key geological factors such as temperature,pressure,organic matter abundance,maturity,and pore characteristics on the content and occurrence state of shale gas,as well as the configuration relationship between shale gas generation and storage throughout geological history.Using this approach,the gas evolution histories of the Longmaxi Formation shales in wells N201 and PY1 are reconstructed under varying geological conditions.The Longmaxi Formation shales in these wells are dominated by typeⅠkerogen,with original total organic carbon(TOC_(o))contents of 6.20 wt% and 4.92 wt%,respectively,indicating differences in the initial material basis for gas generation.At the maximum burial depth of approximately 5000 m,the Longmaxi Formation shale in well N201 exhibits a formation pressure coefficient of 2.05,an organic matter maturity of 2.2%,and organic pores accounting for 68%of the total porosity.The gas generation quantity(Q_(g))reaches 19.24 m^(3)/t,while the gas storage capacity(Q_(s))is 4.30 m^(3)/t.The actual total gas content(Q_(a)),constrained by Q_(s),is 4.30 m^(3)/t,with free gas comprising 94%.Following relatively moderate tectonic uplift,the Q_(a) in well N201 decreases to 4.03 m^(3)/t,with free gas accounting for 63%.In contrast,the Longmaxi Formation shale in well PY1 reached a maximum burial depth of 6300 m,associated with a formation pressure coefficient of 1.62,organic matter maturity of 2.5%,and organic pore proportion of 67%.Here,Q_(g) is 16.87 m^(3)/t,and both Q_(s) and Q_(a) are 3.65 m^(3)/t,with free gas accounting for 98%.After intense tectonic uplift,Q_(a) declines to 2.72 m^(3)/t,and the proportion of free gas drops to51%.Finally,a four-stage differential accumulation model of shale gas is established:Slow gas generation and only adsorbed gas occur in stageⅠ,which is primarily controlled by TOC content;both adsorbed gas and free gas present in stageⅡ,with free gas becoming dominant;rapid gas generation and free gas predominance are controlled by temperature and porosity in stageⅢ;and gas adjustment and accumulation are primarily controlled by temperature and pressure in stageⅣ.展开更多
Gas sensors are valuable tools for human applications,and extensive research has been conducted in this field.However,practical implementation has yet to be fully realized.In response,efforts have been made to explore...Gas sensors are valuable tools for human applications,and extensive research has been conducted in this field.However,practical implementation has yet to be fully realized.In response,efforts have been made to explore metal-organic frameworks(MOFs),a novel class of porous materials,as potential solutions.MOFs exhibit exceptional porosity and highly tunable chemical compositions and structures,giving rise to a wide range of unique physical and chemical properties.Significant progress has been achieved in developing MOF-based gas sensors,improving sensing performance for various gases.This review aims to provide a comprehensive understanding of MOF-based gas sensors,even for readers unfamiliar with MOFs and gas sensors.It covers the working principles of these sensors,fundamental concepts of MOFs,strategies for tuning MOF properties,fabrication techniques for MOF films,and recent studies on MOF and MOF-derivative gas sensors.Finally,current challenges,overlooked aspects,and future directions for fully exploiting the potential of MOFs in gas sensor development are discussed.展开更多
This paper examines how natural gas disperses vertically when high-pressure pipelines with large openings fail in unconfined environments,providing insight into hazardous gas cloud development and behavior.A comprehen...This paper examines how natural gas disperses vertically when high-pressure pipelines with large openings fail in unconfined environments,providing insight into hazardous gas cloud development and behavior.A comprehensive study was conducted using a full-scale field experiment(1,219 mm diameter,12 MPa pressure,100 mm aperture)combined with a validated computational fluid dynamics(CFD)numerical simulation model to systematically analyze the coupling effects of pipeline pressure and ambient wind speed.The results indicate that:(1)Pipeline pressure determines the vertical jet scale,where jet height is positively correlated with pressure;at 12 MPa,the maximum jet height reaches 69.4 m(approximately 2.65 times that at 4 MPa),and the lower explosive limit(LEL)cloud area follows a quadratic polynomial trend.(2)Ambient wind speed significantly alters the diffusion trajectory;at a wind speed of 10 m/s,the LEL gas cloud area expands by 1.69 times compared to calm conditions,while the jet height is suppressed to 29.9%of the calm wind value.(3)Our developed dynamic prediction model for the hazardous gas-cloud region achieves a determination coefficient of 0.975 and maintaining prediction errors maintained within approximately 12%.The proposed empirical correlations and dynamic prediction model provide essential quantitative data support for safety-distance design and emergency-response decision-making for high-pressure natural gas pipelines.展开更多
Aqueous hydrogen(H_(2))gas batteries with unmatched lifespan are ideal for grid-scale energy storage,yet their deployment remains limited by the lack of low-cost,efficient,and durable hydrogen electrodes.Here,we repor...Aqueous hydrogen(H_(2))gas batteries with unmatched lifespan are ideal for grid-scale energy storage,yet their deployment remains limited by the lack of low-cost,efficient,and durable hydrogen electrodes.Here,we report a high-throughput and durable gas diffusion electrode(GDE)based on a simply preparable carbon-coated nickel(Ni@C)catalyst and the design of H_(2) diffusion channels.By optimizing the carbon layer structure,a balance between the intrinsic activity and stability of the catalyst can be achieved.This Ni@C catalyst exhibits a hydrogen oxidation reaction(HOR)activity of 44 A g^(-1) as well as remarkable hydrogen evolution reaction(HER)performance.Experimental results and theoretical calculations confirm the electronic interaction between the carbon shell and Ni.In combination with a hydrophobic design,a robust and durable Ni@C-GDE has been fabricated.This electrode achieves a low HOR polarization of only 91 mV at 30 mA cm^(-2),outperforming Pt/C-GDE(154 mV),and operates stably over 4500cycles(3200 h)for HOR/HER reversing.Enabled by this electrode,a 10 Ah Ni-H_(2) battery with an energy density of 156.3 Wh kg^(-1) and cost of 62.2$kWh^(-1) is demonstrated.This work offers a viable strategy for practical and scalable hydrogen gas batteries.展开更多
The Ordovician Majiagou Formation(O1m)in the Ordos Basin is a crucial exploration field for natural gas,and exploration of the Ordovician middle assemblage(O_(1)m_(5)^(5-7))has recently yielded great breakthrough.The ...The Ordovician Majiagou Formation(O1m)in the Ordos Basin is a crucial exploration field for natural gas,and exploration of the Ordovician middle assemblage(O_(1)m_(5)^(5-7))has recently yielded great breakthrough.The Daniudi gas field provides a good case study to determine the gas source for the strata.The O_(1)m_(5)^(5-7)gas displays C1/C1-5 ratios of 0.932-0.985 and CO_(2)contents of 1.56%-11.75%,and the detectable H2S content ranges from 0.0002%to 1.8617%.Theδ^(13)C1,δ^(13)C2,δ^(13)CCO_(2),andδD_(1)values are−39.7‰to−35.6‰,−30.4‰to−23.7‰,−12.4‰to−4.6‰,and−204‰to−185‰,respectively.Identification of the gas origin and source indicates that the gaseous alkanes are commonly coal-derived gas.The gas was generated from the coal measures in the Taiyuan Formation(C_(3t))and subsequently migrated.A small amount of oil-associated gas,mainly from O1m carbonate source rocks,has been incorporated into the gas reservoir.The natural gas has experienced insignificant alteration by thermochemical sulfate reduction,and the relatively high levels of CO_(2)are probably associated with corrosion alteration of carbonate reservoirs by injected fluid during acid fracturing.展开更多
It is crucial to develop arsenic removal adsorbents with strong sulfur resistance under middle-low-temperature flue gas conditions(<400℃).In this work,five Fe-Ce-La oxides were prepared by co-precipitation method,...It is crucial to develop arsenic removal adsorbents with strong sulfur resistance under middle-low-temperature flue gas conditions(<400℃).In this work,five Fe-Ce-La oxides were prepared by co-precipitation method,and FeCeLaO/SiO_(2)-Al_(2)O_(3) composite adsorbents were prepared by coupling fly ash-based Si-Al carriers.The active components Fe-Ce-La oxides and Si-Al carriers were characterized by TPD,TG,XRF,BET and XPS,respectively.The effects of temperature,Si/Al ratio and FeCeLaO loading rate on the sulfur resistance were investigated.Results show that the SO_(2) promotes the arsenic removal of Fe_(2)O_(3),CeLaO and FeCeLaO.At 400℃,the arsenic removal efficiencies of the three oxides increase from 45.3%,72.5% and 81.3% without SO_(2) to 62.6%,80.5%and 91.0%,respectively.The SO_(2) inhibits the arsenic removal of La_(2)O_(2)CO_(3) and FeLaO,and the inhibition effect is pronounced at high temperatures.The sulfur poisoning resistance of Si-Al carriers increases with the increase of Si/Al ratio.When the Si/Al ratio is increased to 9.74,the arsenic removal efficiency in the SO_(2) environment is 13.9% higher than that in the absence of SO_(2).Introducing FeCeLaO active components is beneficial for enhancing the SO_(2) poisoning resistance of Si-Al carriers.The strong sulfur resistance of the FeCeLaO/SiO_(2)-Al_(2)O_(3) composite adsorbent results from multiple factors:protective effects of Ce on Fe,La and Al;sulfation-induced generation of Ce^(3+)and surface-adsorbed oxygen;and strong surface acidity of SiO_(2).展开更多
The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recogni...The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.展开更多
Gas wells often encounter blockages in gas recovery channels owing to fluid accumulation during the later stages of extraction,which adversely affects subsequent recovery efforts.These undesirable conditions(e.g.,high...Gas wells often encounter blockages in gas recovery channels owing to fluid accumulation during the later stages of extraction,which adversely affects subsequent recovery efforts.These undesirable conditions(e.g.,high condensate content,high temperature,and high salinity)often affect foaming agent performance.In this study,surfactants were screened using an airflow method that closely resembles field treatment method.Notably,alcohol ether sulfates(AE_(n)S)with various polyoxyethylene(EO)units demonstrated exceptional performance in terms of liquid unloading efficiency and foam stability.At 80℃,the unloading efficiency of AE_(n)S with two EO units(AE_(2)S)in a high NaCl mass concentration(up to 200 g/L)and high condensate volume fraction(up to 20%)reached 84%.The dynamic surface tension and interfacial tension measured at the same temperature were used to analyze the influence of the diffusion rate and interfacial characteristics on the AE_(n)S foam,while the viscosity and liquid film thickness measurements reflected the mechanical strength and liquid-carrying capacity.In addition,transmission electron microscopy(TEM)revealed that AE_(2)S formed“dendritic”micellar aggregates at a high NaCl mass concentration,which significantly enhanced the viscosity and stability of the foam.The interactions among AE_(n)S,NaCl,and H2O were analyzed using molecular dynamics,and it was confirmed from a molecular mechanics perspective that a stable structure can form among the three,contributing to the foam stability.These findings demonstrate the significant potential of the AE_(2)S foam for gas well deliquification.展开更多
There are various types of natural gas resources in coal measures,making them major targets for natural gas exploration and development in China.In view of the particularity of the whole petroleum system of coal measu...There are various types of natural gas resources in coal measures,making them major targets for natural gas exploration and development in China.In view of the particularity of the whole petroleum system of coal measures and the reservoir-forming evolution of natural gas in coal,this study reveals the formation,enrichment characteristics and distribution laws of coal-rock gas by systematically reviewing the main types and geological characteristics of natural gas in the whole petroleum system of coal measures.First,natural gas in the whole petroleum system of coal measures is divided into two types,conventional gas and unconventional gas,according to its occurrence characteristics and accumulation mechanism,and into six types,distal detrital rock gas,special rock gas,distal/proximal tight sandstone gas,inner-source tight sandstone gas,shale gas,and coal-rock gas,according to its source and reservoir lithology.The natural gas present in coal-rock reservoirs is collectively referred to as coal-rock gas.Existing data indicate significant differences in the geological characteristics of coal-rock gas exploration and development between shallow and deep layers in the same area,with the transition depth boundary generally 1500-2000 m.Based on the current understanding of coal-rock gas and respecting the historical usage conventions of coalbed methane terminology,coal-rock gas can be divided into deep coal-rock gas and shallow coalbed methane according to burial depth.Second,according to the research concept of“full-process reservoir formation”in the theory of the whole petroleum system of coal measures,based on the formation and evolution of typical coal-rock gas reservoirs,coal-rock gas is further divided into four types:primary coal-rock gas,regenerated coal-rock gas,residual coal-rock gas,and bio coal-rock gas.The first two belong to deep coal-rock gas,while the latter two belong to shallow coal-rock gas.Third,research on the coal-rock gas reservoir formation and evolution shows that shallow coal-rock gas is mainly residual coal-rock gas or bio coal-rock gas formed after geological transformation of primary coal-rock gas,with the reservoir characteristics such as low reservoir pressure,low gas saturation,adsorbed gas in dominance,and gas production by drainage and depressurization,while deep coal-rock gas is mainly primary coal-rock gas and regenerated coal-rock gas,with the reservoir characteristics such as high reservoir pressure,high gas saturation,abundant free gas,and no or little water.In particular,the primary coal-rock gas is wide in distribution,large in resource quantity,and good in reservoir quality,making it the most favorable type of coal-rock gas for exploration and development.展开更多
Natural Gas Industry B创刊于2014年,是天然气工业杂志社与KeAi公司合作出版的国际OA期刊,在爱思唯尔旗下的Science Direct平台上双月出版。论文聚焦天然气、氢气、氦气、地热等地质能源,涵盖地质勘探、气藏开发、工程技术、储运利用...Natural Gas Industry B创刊于2014年,是天然气工业杂志社与KeAi公司合作出版的国际OA期刊,在爱思唯尔旗下的Science Direct平台上双月出版。论文聚焦天然气、氢气、氦气、地热等地质能源,涵盖地质勘探、气藏开发、工程技术、储运利用、净化化工、产业趋势等专业方向。期刊服务全球天然气产业,并积极推动能源行业碳减排和低碳转型的发展。展开更多
Natural Gas Industry B创刊于2014年,是天然气工业杂志社与KeAi公司合作出版的国际OA期刊,在爱思唯尔旗下的ScienceDirect平台上双月出版。论文聚焦天然气、氢气、氦气、地热等地质能源,涵盖地质勘探、气藏开发、工程技术、储运利用、...Natural Gas Industry B创刊于2014年,是天然气工业杂志社与KeAi公司合作出版的国际OA期刊,在爱思唯尔旗下的ScienceDirect平台上双月出版。论文聚焦天然气、氢气、氦气、地热等地质能源,涵盖地质勘探、气藏开发、工程技术、储运利用、净化化工、产业趋势等专业方向。期刊服务全球天然气产业,并积极推动能源行业碳减排和低碳转型的发展。展开更多
Thermal power plants are the main contributors to greenhouse gas emissions.The prediction of the emission supports the decision makers and environmental sustainability.The objective of this study is to enhance the acc...Thermal power plants are the main contributors to greenhouse gas emissions.The prediction of the emission supports the decision makers and environmental sustainability.The objective of this study is to enhance the accuracy of emission prediction models,supporting more effective real-time monitoring and enabling informed operational decisions that align with environmental compliance efforts.This paper presents a data-driven approach for the accurate prediction of gas emissions,specifically nitrogen oxides(NOx)and carbon monoxide(CO),in natural gas power plants using an optimized hybrid machine learning framework.The proposed model integrates a Feedforward Neural Network(FFNN)trained using Particle Swarm Optimization to capture the nonlinear emission dynamics under varying gas turbine operating conditions.To further enhance predictive performance,the K-Nearest Neighbor(K-NN)algorithm serves as a post-processing method to enhance IPSO-FFNN predictions through adjustment and refinement,improving overall prediction accuracy,while Neighbor Component Analysis is used to identify and rank the most influential operational variables.The study makes a significant contribution through the combination of NCA feature selection with PSO global optimization,FFNN nonlinear modelling,and K-NN error correction into one unified system,which delivers precise emission predictions.The model was developed and tested using a real-world dataset collected from gas-fired turbine operations,with validated results demonstrating robust accuracy,achieving Root Mean Square Error values of 0.355 for CO and 0.368 for NOx.When benchmarked against conventional models such as standard FFNN,Support Vector Regression,and Long Short-Term Memory networks,the hybrid model achieved substantial improvements,up to 97.8%in Mean Squared Error,95%in Mean Absolute Error(MAE),and 85.19%in RMSE for CO;and 97.16%in MSE,93.4%in MAE,and 83.15%in RMSE for NOx.These results underscore the model’s potential for improving emission prediction,thereby supporting enhanced operational efficiency and adherence to environmental standards.展开更多
Novel antibacterial strategies such as antibacterial photodynamic therapy(aPDT)and photothermal therapy(PTT)have gained significant attention,however,relying on a single-treatment approach still faces challenges of in...Novel antibacterial strategies such as antibacterial photodynamic therapy(aPDT)and photothermal therapy(PTT)have gained significant attention,however,relying on a single-treatment approach still faces challenges of insufficient therapeutic efficiency and the potential for drug resistance.In this study,a multimodal synergistic antibacterial nanoplatform by coupling a carbon monoxide(CO)donor(4-(3-hydroxy-4-oxo-4H-chromen-2-yl)benzoic acid(4-BA))with carbon dots(CDs)is developed,referred to as CDs-CO,which integrates multiple antibacterial modes of aPDT,PTT,and gas therapy.This nanoplatform is designed for highly efficient antibacterial action with a low risk of inducing drug resistance.CDs are engineered to possess tailored functions,including deep-red light-triggered heat and singlet oxygen(^(1)O_(2))production.After modification with 4-BA and exposure to 660 nm laser irradiation,CDs-CO exhibits favorable photothermal conversion efficiency(η=52.7%),robust ^(1)O_(2) generation,and ^(1)O_(2)-activated CO release.Antibacterial experiments demonstrated the excellent sterilization effects of CDs-CO against both Escherichia coli(E.coli)and Staphylococcus aureus(S.aureus),underscoring the enhanced antibacterial efficiency of this multimodal nanoplatform.This study offers a rational approach for designing multimodal synergistic antibacterial platforms,highlighting their potential for effectively treating bacterial infections.展开更多
Single-crystal GaN epilayers were irradiated with heavy inert gas ions(2.3-MeV Ne^(8+),5.3-MeV Kr^(19+))to fluences ranging from 1.0×1.0^(11) to 1.0×1.0^(15)ions∕cm^(2).The strain-related damage accumulatio...Single-crystal GaN epilayers were irradiated with heavy inert gas ions(2.3-MeV Ne^(8+),5.3-MeV Kr^(19+))to fluences ranging from 1.0×1.0^(11) to 1.0×1.0^(15)ions∕cm^(2).The strain-related damage accumulation versus ion fluences was studied using highresolution X-ray diffraction(HRXRD)and ultraviolet–visible(UV–Vis)spectroscopy.The results showed that the damage accumulation was mainly dominated by nuclear energy loss.When the ion fluence was less than∼0.055 displacement per atom(dpa),the lattice expansions and lattice strains markedly increased linearly with increasing ion fluences,accompanied by a slow enhancement in the dislocation densities,distortion parameters,and Urbach energy for both ion irradiations.Above this fluence(∼0.055 dpa),the lattice strains presented a slight increase,whereas a remarkable increase was observed in the dislocation densities,distortion parameters,and Urbach energy with the ion fluences after both ion irradiations.∼0.055 dpa is the threshold ion fluence for defect evolution and lattice damage related to strain.The mechanisms underlying the damage accumulation are discussed in detail.展开更多
The Dongsha area,a key target for gas hydrate exploration,is influenced by multiple factors,including sedimentary processes and the paleoenvironment,which play critical roles in gas hydrate formation.To elucidate the ...The Dongsha area,a key target for gas hydrate exploration,is influenced by multiple factors,including sedimentary processes and the paleoenvironment,which play critical roles in gas hydrate formation.To elucidate the coupling among sedimentary processes,paleoenvironment,and gas hydrate accumulation,this study investigates the Site DS-W16 using particle size analysis,biological component content,and geochemistry data.Oxygen isotope data from foraminifera and biostratigraphic evidence indicate that sedimentation at the bottom of core interval from Site DS-W16 began during MIS 11(Marine isotope stage).The sedimentation dynamics of the studied layers are complex,involving gravity flows,traction currents,and suspended deposition.Organic matter shows a significant correlation with transgressive-regressive cycle.The site DS-W16 contains two distinct gas hydrate reservoirs:a shallow reservoir(10-24 mbsf)and a deep reservoir(below 182 mbsf).The paleomarine environment influences gas hydrate accumulation by altering sedimentary processes and sediment characteristics,especially the distribution of biological components.Both shallow and deep gas hydrate reservoirs formed under dynamic conditions dominated by traction currents and are characterized by a higher abundance of foraminifera.Sedimentary layers rich in foraminifera and modified by traction currents represent key intervals for preferential gas hydrate accumulation.展开更多
The critical components of gas turbines suffer from prolonged exposure to factors such as thermal oxidation,mechanical wear,and airflow disturbances during prolonged operation.These conditions can lead to a series of ...The critical components of gas turbines suffer from prolonged exposure to factors such as thermal oxidation,mechanical wear,and airflow disturbances during prolonged operation.These conditions can lead to a series of issues,including mechanical faults,air path malfunctions,and combustion irregularities.Traditional modelbased approaches face inherent limitations due to their inability to handle nonlinear problems,natural factors,measurement uncertainties,fault coupling,and implementation challenges.The development of artificial intelligence algorithms has provided an effective solution to these issues,sparking extensive research into data-driven fault diagnosis methodologies.The review mechanism involved searching IEEE Xplore,ScienceDirect,and Web of Science for peerreviewed articles published between 2019 and 2025,focusing on multi-fault diagnosis techniques.A total of 220 papers were identified,with 123 meeting the inclusion criteria.This paper provides a comprehensive review of diagnostic methodologies,detailing their operational principles and distinctive features.It analyzes current research hotspots and challenges while forecasting future trends.The study systematically evaluates the strengths and limitations of various fault diagnosis techniques,revealing their practical applicability and constraints through comparative analysis.Furthermore,this paper looks forward to the future development direction of this field and provides a valuable reference for the optimization and development of gas turbine fault diagnosis technology in the future.展开更多
Selectivity remains a significant challenge for gas sensors. In contrast to conventional gas sensors that depend solely on conductivity to detect gases, we exploited a single NiO-doped SnO_(2) sensor to simultaneously...Selectivity remains a significant challenge for gas sensors. In contrast to conventional gas sensors that depend solely on conductivity to detect gases, we exploited a single NiO-doped SnO_(2) sensor to simultaneously monitor transient changes in both sensor conductivity and temperature. The distinct response profiles of H_(2) and NH_(3) gases were attributed to differences in their redox rates and enthalpy changes during chemical reactions, which provided an opportunity for gas identification using machine learning(ML) algorithms. The test results indicate that preprocessing the extracted calorimetric and chemi-resistive parameters using the principal component analysis(PCA), followed by the application of ML classifiers for identification,enables a 100% accuracy for both target analytes. This work presents a facile gas identification method that enhances chiplevel sensor applications while minimizing the need for complex sensor arrays.展开更多
基金funded by the Sinopec Science and Technology Project(No.P23132)the AAPG Foundation Grants-inAid Program(No.18644937)。
文摘By investigating the evolution of shale gas generation,storage,adjustment and accumulation under different structural settings in superimposed basins,this study elucidates the differential accumulation mechanisms of shale gas.An improved evaluation method of shale gas content evolution in superimposed basins is proposed.This method incorporates the coupling effect of key geological factors such as temperature,pressure,organic matter abundance,maturity,and pore characteristics on the content and occurrence state of shale gas,as well as the configuration relationship between shale gas generation and storage throughout geological history.Using this approach,the gas evolution histories of the Longmaxi Formation shales in wells N201 and PY1 are reconstructed under varying geological conditions.The Longmaxi Formation shales in these wells are dominated by typeⅠkerogen,with original total organic carbon(TOC_(o))contents of 6.20 wt% and 4.92 wt%,respectively,indicating differences in the initial material basis for gas generation.At the maximum burial depth of approximately 5000 m,the Longmaxi Formation shale in well N201 exhibits a formation pressure coefficient of 2.05,an organic matter maturity of 2.2%,and organic pores accounting for 68%of the total porosity.The gas generation quantity(Q_(g))reaches 19.24 m^(3)/t,while the gas storage capacity(Q_(s))is 4.30 m^(3)/t.The actual total gas content(Q_(a)),constrained by Q_(s),is 4.30 m^(3)/t,with free gas comprising 94%.Following relatively moderate tectonic uplift,the Q_(a) in well N201 decreases to 4.03 m^(3)/t,with free gas accounting for 63%.In contrast,the Longmaxi Formation shale in well PY1 reached a maximum burial depth of 6300 m,associated with a formation pressure coefficient of 1.62,organic matter maturity of 2.5%,and organic pore proportion of 67%.Here,Q_(g) is 16.87 m^(3)/t,and both Q_(s) and Q_(a) are 3.65 m^(3)/t,with free gas accounting for 98%.After intense tectonic uplift,Q_(a) declines to 2.72 m^(3)/t,and the proportion of free gas drops to51%.Finally,a four-stage differential accumulation model of shale gas is established:Slow gas generation and only adsorbed gas occur in stageⅠ,which is primarily controlled by TOC content;both adsorbed gas and free gas present in stageⅡ,with free gas becoming dominant;rapid gas generation and free gas predominance are controlled by temperature and porosity in stageⅢ;and gas adjustment and accumulation are primarily controlled by temperature and pressure in stageⅣ.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(RS-2024-00333650)supported by basic science research program through the National Research Foundation of Korea funded by the Ministry of Education(NRF-2019R1A6A1A11055660)+1 种基金supported by the Technology Innovation Program(“20013621”,Center for Super Critical Material Industrial Technology)funded By the Ministry of Trade,Industry&Energy(MOTIE,Korea)supported by Strategic Networking&Development Program funded by the Ministry of Science and ICT through the National Research Foundation of Korea(RS-2023-00268523)。
文摘Gas sensors are valuable tools for human applications,and extensive research has been conducted in this field.However,practical implementation has yet to be fully realized.In response,efforts have been made to explore metal-organic frameworks(MOFs),a novel class of porous materials,as potential solutions.MOFs exhibit exceptional porosity and highly tunable chemical compositions and structures,giving rise to a wide range of unique physical and chemical properties.Significant progress has been achieved in developing MOF-based gas sensors,improving sensing performance for various gases.This review aims to provide a comprehensive understanding of MOF-based gas sensors,even for readers unfamiliar with MOFs and gas sensors.It covers the working principles of these sensors,fundamental concepts of MOFs,strategies for tuning MOF properties,fabrication techniques for MOF films,and recent studies on MOF and MOF-derivative gas sensors.Finally,current challenges,overlooked aspects,and future directions for fully exploiting the potential of MOFs in gas sensor development are discussed.
基金supported by the National Natural Science Foundation of China(Grant No.52574278)the Xinjiang Uygur Autonomous Region Key R&D Program Project(Grant No.2024B01003).
文摘This paper examines how natural gas disperses vertically when high-pressure pipelines with large openings fail in unconfined environments,providing insight into hazardous gas cloud development and behavior.A comprehensive study was conducted using a full-scale field experiment(1,219 mm diameter,12 MPa pressure,100 mm aperture)combined with a validated computational fluid dynamics(CFD)numerical simulation model to systematically analyze the coupling effects of pipeline pressure and ambient wind speed.The results indicate that:(1)Pipeline pressure determines the vertical jet scale,where jet height is positively correlated with pressure;at 12 MPa,the maximum jet height reaches 69.4 m(approximately 2.65 times that at 4 MPa),and the lower explosive limit(LEL)cloud area follows a quadratic polynomial trend.(2)Ambient wind speed significantly alters the diffusion trajectory;at a wind speed of 10 m/s,the LEL gas cloud area expands by 1.69 times compared to calm conditions,while the jet height is suppressed to 29.9%of the calm wind value.(3)Our developed dynamic prediction model for the hazardous gas-cloud region achieves a determination coefficient of 0.975 and maintaining prediction errors maintained within approximately 12%.The proposed empirical correlations and dynamic prediction model provide essential quantitative data support for safety-distance design and emergency-response decision-making for high-pressure natural gas pipelines.
基金financially supported by the“National Natural Science Foundation of China”(No.22279082)the“Natural Science Foundation of Sichuan”(2025YFHZ0056)。
文摘Aqueous hydrogen(H_(2))gas batteries with unmatched lifespan are ideal for grid-scale energy storage,yet their deployment remains limited by the lack of low-cost,efficient,and durable hydrogen electrodes.Here,we report a high-throughput and durable gas diffusion electrode(GDE)based on a simply preparable carbon-coated nickel(Ni@C)catalyst and the design of H_(2) diffusion channels.By optimizing the carbon layer structure,a balance between the intrinsic activity and stability of the catalyst can be achieved.This Ni@C catalyst exhibits a hydrogen oxidation reaction(HOR)activity of 44 A g^(-1) as well as remarkable hydrogen evolution reaction(HER)performance.Experimental results and theoretical calculations confirm the electronic interaction between the carbon shell and Ni.In combination with a hydrophobic design,a robust and durable Ni@C-GDE has been fabricated.This electrode achieves a low HOR polarization of only 91 mV at 30 mA cm^(-2),outperforming Pt/C-GDE(154 mV),and operates stably over 4500cycles(3200 h)for HOR/HER reversing.Enabled by this electrode,a 10 Ah Ni-H_(2) battery with an energy density of 156.3 Wh kg^(-1) and cost of 62.2$kWh^(-1) is demonstrated.This work offers a viable strategy for practical and scalable hydrogen gas batteries.
基金sponsored by National Natural Science Foundation of China(Grant Nos.U2244209,42172149,42488101,and 42141021).
文摘The Ordovician Majiagou Formation(O1m)in the Ordos Basin is a crucial exploration field for natural gas,and exploration of the Ordovician middle assemblage(O_(1)m_(5)^(5-7))has recently yielded great breakthrough.The Daniudi gas field provides a good case study to determine the gas source for the strata.The O_(1)m_(5)^(5-7)gas displays C1/C1-5 ratios of 0.932-0.985 and CO_(2)contents of 1.56%-11.75%,and the detectable H2S content ranges from 0.0002%to 1.8617%.Theδ^(13)C1,δ^(13)C2,δ^(13)CCO_(2),andδD_(1)values are−39.7‰to−35.6‰,−30.4‰to−23.7‰,−12.4‰to−4.6‰,and−204‰to−185‰,respectively.Identification of the gas origin and source indicates that the gaseous alkanes are commonly coal-derived gas.The gas was generated from the coal measures in the Taiyuan Formation(C_(3t))and subsequently migrated.A small amount of oil-associated gas,mainly from O1m carbonate source rocks,has been incorporated into the gas reservoir.The natural gas has experienced insignificant alteration by thermochemical sulfate reduction,and the relatively high levels of CO_(2)are probably associated with corrosion alteration of carbonate reservoirs by injected fluid during acid fracturing.
文摘It is crucial to develop arsenic removal adsorbents with strong sulfur resistance under middle-low-temperature flue gas conditions(<400℃).In this work,five Fe-Ce-La oxides were prepared by co-precipitation method,and FeCeLaO/SiO_(2)-Al_(2)O_(3) composite adsorbents were prepared by coupling fly ash-based Si-Al carriers.The active components Fe-Ce-La oxides and Si-Al carriers were characterized by TPD,TG,XRF,BET and XPS,respectively.The effects of temperature,Si/Al ratio and FeCeLaO loading rate on the sulfur resistance were investigated.Results show that the SO_(2) promotes the arsenic removal of Fe_(2)O_(3),CeLaO and FeCeLaO.At 400℃,the arsenic removal efficiencies of the three oxides increase from 45.3%,72.5% and 81.3% without SO_(2) to 62.6%,80.5%and 91.0%,respectively.The SO_(2) inhibits the arsenic removal of La_(2)O_(2)CO_(3) and FeLaO,and the inhibition effect is pronounced at high temperatures.The sulfur poisoning resistance of Si-Al carriers increases with the increase of Si/Al ratio.When the Si/Al ratio is increased to 9.74,the arsenic removal efficiency in the SO_(2) environment is 13.9% higher than that in the absence of SO_(2).Introducing FeCeLaO active components is beneficial for enhancing the SO_(2) poisoning resistance of Si-Al carriers.The strong sulfur resistance of the FeCeLaO/SiO_(2)-Al_(2)O_(3) composite adsorbent results from multiple factors:protective effects of Ce on Fe,La and Al;sulfation-induced generation of Ce^(3+)and surface-adsorbed oxygen;and strong surface acidity of SiO_(2).
文摘The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.
文摘Gas wells often encounter blockages in gas recovery channels owing to fluid accumulation during the later stages of extraction,which adversely affects subsequent recovery efforts.These undesirable conditions(e.g.,high condensate content,high temperature,and high salinity)often affect foaming agent performance.In this study,surfactants were screened using an airflow method that closely resembles field treatment method.Notably,alcohol ether sulfates(AE_(n)S)with various polyoxyethylene(EO)units demonstrated exceptional performance in terms of liquid unloading efficiency and foam stability.At 80℃,the unloading efficiency of AE_(n)S with two EO units(AE_(2)S)in a high NaCl mass concentration(up to 200 g/L)and high condensate volume fraction(up to 20%)reached 84%.The dynamic surface tension and interfacial tension measured at the same temperature were used to analyze the influence of the diffusion rate and interfacial characteristics on the AE_(n)S foam,while the viscosity and liquid film thickness measurements reflected the mechanical strength and liquid-carrying capacity.In addition,transmission electron microscopy(TEM)revealed that AE_(2)S formed“dendritic”micellar aggregates at a high NaCl mass concentration,which significantly enhanced the viscosity and stability of the foam.The interactions among AE_(n)S,NaCl,and H2O were analyzed using molecular dynamics,and it was confirmed from a molecular mechanics perspective that a stable structure can form among the three,contributing to the foam stability.These findings demonstrate the significant potential of the AE_(2)S foam for gas well deliquification.
基金Supported by the National Science and Technology Major Project for New Oil and Gas Exploration and Development(2025ZD1404200)Forward-looking and Fundamental Project of PetroChina Company Limited(2024DJ23)Scientific Research and Technology Development Project of PetroChina Research Institute of Petroleum Exploration&Development(2024vzz).
文摘There are various types of natural gas resources in coal measures,making them major targets for natural gas exploration and development in China.In view of the particularity of the whole petroleum system of coal measures and the reservoir-forming evolution of natural gas in coal,this study reveals the formation,enrichment characteristics and distribution laws of coal-rock gas by systematically reviewing the main types and geological characteristics of natural gas in the whole petroleum system of coal measures.First,natural gas in the whole petroleum system of coal measures is divided into two types,conventional gas and unconventional gas,according to its occurrence characteristics and accumulation mechanism,and into six types,distal detrital rock gas,special rock gas,distal/proximal tight sandstone gas,inner-source tight sandstone gas,shale gas,and coal-rock gas,according to its source and reservoir lithology.The natural gas present in coal-rock reservoirs is collectively referred to as coal-rock gas.Existing data indicate significant differences in the geological characteristics of coal-rock gas exploration and development between shallow and deep layers in the same area,with the transition depth boundary generally 1500-2000 m.Based on the current understanding of coal-rock gas and respecting the historical usage conventions of coalbed methane terminology,coal-rock gas can be divided into deep coal-rock gas and shallow coalbed methane according to burial depth.Second,according to the research concept of“full-process reservoir formation”in the theory of the whole petroleum system of coal measures,based on the formation and evolution of typical coal-rock gas reservoirs,coal-rock gas is further divided into four types:primary coal-rock gas,regenerated coal-rock gas,residual coal-rock gas,and bio coal-rock gas.The first two belong to deep coal-rock gas,while the latter two belong to shallow coal-rock gas.Third,research on the coal-rock gas reservoir formation and evolution shows that shallow coal-rock gas is mainly residual coal-rock gas or bio coal-rock gas formed after geological transformation of primary coal-rock gas,with the reservoir characteristics such as low reservoir pressure,low gas saturation,adsorbed gas in dominance,and gas production by drainage and depressurization,while deep coal-rock gas is mainly primary coal-rock gas and regenerated coal-rock gas,with the reservoir characteristics such as high reservoir pressure,high gas saturation,abundant free gas,and no or little water.In particular,the primary coal-rock gas is wide in distribution,large in resource quantity,and good in reservoir quality,making it the most favorable type of coal-rock gas for exploration and development.
文摘Natural Gas Industry B创刊于2014年,是天然气工业杂志社与KeAi公司合作出版的国际OA期刊,在爱思唯尔旗下的Science Direct平台上双月出版。论文聚焦天然气、氢气、氦气、地热等地质能源,涵盖地质勘探、气藏开发、工程技术、储运利用、净化化工、产业趋势等专业方向。期刊服务全球天然气产业,并积极推动能源行业碳减排和低碳转型的发展。
文摘Natural Gas Industry B创刊于2014年,是天然气工业杂志社与KeAi公司合作出版的国际OA期刊,在爱思唯尔旗下的ScienceDirect平台上双月出版。论文聚焦天然气、氢气、氦气、地热等地质能源,涵盖地质勘探、气藏开发、工程技术、储运利用、净化化工、产业趋势等专业方向。期刊服务全球天然气产业,并积极推动能源行业碳减排和低碳转型的发展。
文摘Thermal power plants are the main contributors to greenhouse gas emissions.The prediction of the emission supports the decision makers and environmental sustainability.The objective of this study is to enhance the accuracy of emission prediction models,supporting more effective real-time monitoring and enabling informed operational decisions that align with environmental compliance efforts.This paper presents a data-driven approach for the accurate prediction of gas emissions,specifically nitrogen oxides(NOx)and carbon monoxide(CO),in natural gas power plants using an optimized hybrid machine learning framework.The proposed model integrates a Feedforward Neural Network(FFNN)trained using Particle Swarm Optimization to capture the nonlinear emission dynamics under varying gas turbine operating conditions.To further enhance predictive performance,the K-Nearest Neighbor(K-NN)algorithm serves as a post-processing method to enhance IPSO-FFNN predictions through adjustment and refinement,improving overall prediction accuracy,while Neighbor Component Analysis is used to identify and rank the most influential operational variables.The study makes a significant contribution through the combination of NCA feature selection with PSO global optimization,FFNN nonlinear modelling,and K-NN error correction into one unified system,which delivers precise emission predictions.The model was developed and tested using a real-world dataset collected from gas-fired turbine operations,with validated results demonstrating robust accuracy,achieving Root Mean Square Error values of 0.355 for CO and 0.368 for NOx.When benchmarked against conventional models such as standard FFNN,Support Vector Regression,and Long Short-Term Memory networks,the hybrid model achieved substantial improvements,up to 97.8%in Mean Squared Error,95%in Mean Absolute Error(MAE),and 85.19%in RMSE for CO;and 97.16%in MSE,93.4%in MAE,and 83.15%in RMSE for NOx.These results underscore the model’s potential for improving emission prediction,thereby supporting enhanced operational efficiency and adherence to environmental standards.
基金supported by the National Natural Science Foundation of China(No.52173126)China Postdoctoral Science Foundation(No.2024M751152).
文摘Novel antibacterial strategies such as antibacterial photodynamic therapy(aPDT)and photothermal therapy(PTT)have gained significant attention,however,relying on a single-treatment approach still faces challenges of insufficient therapeutic efficiency and the potential for drug resistance.In this study,a multimodal synergistic antibacterial nanoplatform by coupling a carbon monoxide(CO)donor(4-(3-hydroxy-4-oxo-4H-chromen-2-yl)benzoic acid(4-BA))with carbon dots(CDs)is developed,referred to as CDs-CO,which integrates multiple antibacterial modes of aPDT,PTT,and gas therapy.This nanoplatform is designed for highly efficient antibacterial action with a low risk of inducing drug resistance.CDs are engineered to possess tailored functions,including deep-red light-triggered heat and singlet oxygen(^(1)O_(2))production.After modification with 4-BA and exposure to 660 nm laser irradiation,CDs-CO exhibits favorable photothermal conversion efficiency(η=52.7%),robust ^(1)O_(2) generation,and ^(1)O_(2)-activated CO release.Antibacterial experiments demonstrated the excellent sterilization effects of CDs-CO against both Escherichia coli(E.coli)and Staphylococcus aureus(S.aureus),underscoring the enhanced antibacterial efficiency of this multimodal nanoplatform.This study offers a rational approach for designing multimodal synergistic antibacterial platforms,highlighting their potential for effectively treating bacterial infections.
基金supported by the Program for National Natural Science Foundation of China(No.11675231)the Sichuan Science and Technology Program(Nos.2022YFG0263 and 2024NSFSC1097)the Scientific Research Starting Foundation for talents(Nos.21zx7109 and 22zx7175,24ycx1005).
文摘Single-crystal GaN epilayers were irradiated with heavy inert gas ions(2.3-MeV Ne^(8+),5.3-MeV Kr^(19+))to fluences ranging from 1.0×1.0^(11) to 1.0×1.0^(15)ions∕cm^(2).The strain-related damage accumulation versus ion fluences was studied using highresolution X-ray diffraction(HRXRD)and ultraviolet–visible(UV–Vis)spectroscopy.The results showed that the damage accumulation was mainly dominated by nuclear energy loss.When the ion fluence was less than∼0.055 displacement per atom(dpa),the lattice expansions and lattice strains markedly increased linearly with increasing ion fluences,accompanied by a slow enhancement in the dislocation densities,distortion parameters,and Urbach energy for both ion irradiations.Above this fluence(∼0.055 dpa),the lattice strains presented a slight increase,whereas a remarkable increase was observed in the dislocation densities,distortion parameters,and Urbach energy with the ion fluences after both ion irradiations.∼0.055 dpa is the threshold ion fluence for defect evolution and lattice damage related to strain.The mechanisms underlying the damage accumulation are discussed in detail.
基金supported by National Natural Science Foundation of China(No.42376217)Fundamental Research Funds for the Central Universities of China(No.3-7-10-2025-03)National Key Research and Development Program of China(No.2024YFC2814702).
文摘The Dongsha area,a key target for gas hydrate exploration,is influenced by multiple factors,including sedimentary processes and the paleoenvironment,which play critical roles in gas hydrate formation.To elucidate the coupling among sedimentary processes,paleoenvironment,and gas hydrate accumulation,this study investigates the Site DS-W16 using particle size analysis,biological component content,and geochemistry data.Oxygen isotope data from foraminifera and biostratigraphic evidence indicate that sedimentation at the bottom of core interval from Site DS-W16 began during MIS 11(Marine isotope stage).The sedimentation dynamics of the studied layers are complex,involving gravity flows,traction currents,and suspended deposition.Organic matter shows a significant correlation with transgressive-regressive cycle.The site DS-W16 contains two distinct gas hydrate reservoirs:a shallow reservoir(10-24 mbsf)and a deep reservoir(below 182 mbsf).The paleomarine environment influences gas hydrate accumulation by altering sedimentary processes and sediment characteristics,especially the distribution of biological components.Both shallow and deep gas hydrate reservoirs formed under dynamic conditions dominated by traction currents and are characterized by a higher abundance of foraminifera.Sedimentary layers rich in foraminifera and modified by traction currents represent key intervals for preferential gas hydrate accumulation.
基金funded by the Science and Technology Vice President Project in Changping District,Beijing(Project Name:Research on multi-scale optimization and intelligent control technology of integrated energy systemProject number:202302007013).
文摘The critical components of gas turbines suffer from prolonged exposure to factors such as thermal oxidation,mechanical wear,and airflow disturbances during prolonged operation.These conditions can lead to a series of issues,including mechanical faults,air path malfunctions,and combustion irregularities.Traditional modelbased approaches face inherent limitations due to their inability to handle nonlinear problems,natural factors,measurement uncertainties,fault coupling,and implementation challenges.The development of artificial intelligence algorithms has provided an effective solution to these issues,sparking extensive research into data-driven fault diagnosis methodologies.The review mechanism involved searching IEEE Xplore,ScienceDirect,and Web of Science for peerreviewed articles published between 2019 and 2025,focusing on multi-fault diagnosis techniques.A total of 220 papers were identified,with 123 meeting the inclusion criteria.This paper provides a comprehensive review of diagnostic methodologies,detailing their operational principles and distinctive features.It analyzes current research hotspots and challenges while forecasting future trends.The study systematically evaluates the strengths and limitations of various fault diagnosis techniques,revealing their practical applicability and constraints through comparative analysis.Furthermore,this paper looks forward to the future development direction of this field and provides a valuable reference for the optimization and development of gas turbine fault diagnosis technology in the future.
基金supported in part by the National Natural Science Foundation of China (62431018)in part by the Guangzhou Municipal Science and Technology Bureau (SL2023A04J00435)in part by the One Hundred Youth Project of Guangdong University of Technology (263113873)。
文摘Selectivity remains a significant challenge for gas sensors. In contrast to conventional gas sensors that depend solely on conductivity to detect gases, we exploited a single NiO-doped SnO_(2) sensor to simultaneously monitor transient changes in both sensor conductivity and temperature. The distinct response profiles of H_(2) and NH_(3) gases were attributed to differences in their redox rates and enthalpy changes during chemical reactions, which provided an opportunity for gas identification using machine learning(ML) algorithms. The test results indicate that preprocessing the extracted calorimetric and chemi-resistive parameters using the principal component analysis(PCA), followed by the application of ML classifiers for identification,enables a 100% accuracy for both target analytes. This work presents a facile gas identification method that enhances chiplevel sensor applications while minimizing the need for complex sensor arrays.
