Valve-regulated-lead-acid (VRLA) battery charging performed in high-temperature environments is extremely risky under overcharge conditions, and may lead to a subsequent thermal runaway. A new pressure-controlled char...Valve-regulated-lead-acid (VRLA) battery charging performed in high-temperature environments is extremely risky under overcharge conditions, and may lead to a subsequent thermal runaway. A new pressure-controlled charging method was adopted and the charging characteristics of the pressure-controlled VRLA battery in high-temperature environments were ex-perimentally studied. The concept was tested in a large temperature gradient to obtain more details about the effects of users' accustomed charging and discharging modes on battery capacity. The premature capacity loss (PCL) phenomenon under high temperature exposure was analyzed. The results showed that the capacity loss could be recovered by charging using a large current.展开更多
In the fields of optoelectronics and semiconductors, reliable fixation and handling of brittle materials (glass, wafer, etc.) in high-temperature, vacuum, and vibration environments face particular technical challenge...In the fields of optoelectronics and semiconductors, reliable fixation and handling of brittle materials (glass, wafer, etc.) in high-temperature, vacuum, and vibration environments face particular technical challenges. These challenges include the inability of suction cups in a vacuum, the residue of chemical adhesives, and the easy damage of mechanical clamping. In this paper, fluorine-based bionic adhesive pads (FBAPs) obtained using molding technology to imitate gecko micropillar arrays are presented. FBAPs inhibit the substantial decay of adhesive properties at high temperatures and provide stable and reliable performance in vacuum and vibration environments. The results demonstrated that the decayed force values of the normal and tangential strength of the FBAP were only 9.01% and 5.82% of the planar samples when warmed up to 300℃ from 25℃, respectively. In a vacuum, all FBAPs exhibit less than 20% adhesion attenuation, and in a vibrational environment, they can withstand accelerations of at least 4.27 g. The design of the microstructure arrays enables the realization of efficient and non-destructive separation through mechanical rotation or blowing. It provides a bionic material basis for the fixation of brittle materials on smooth surfaces under complex environments and for transportation automation.展开更多
In this study,the design,analysis,manufacturing,and testing of a 3D-printed conformal microstrip array antenna for high-temperature environments is presented.3D printing technology is used to fabricate a curved cerami...In this study,the design,analysis,manufacturing,and testing of a 3D-printed conformal microstrip array antenna for high-temperature environments is presented.3D printing technology is used to fabricate a curved ceramic substrate,and laser sintering and microdroplet spraying processes are used to add the conductive metal on the curved substrate.The problems of gain loss,bandwidth reduction,and frequency shift caused by high temperatures are addressed by using a proper antenna design,with parasitic patches,slots,and metal resonant cavities.The antenna prototype is characterized by the curved substrates and the conductive metals for the power dividers,the patch,and the ground plane;its performance is examined up to a temperature of 600℃in a muffle furnace and compared with the results from the numerical analysis.The results show that the antenna can effectively function at 600℃and even higher temperatures.展开更多
To mitigate the impact of interdiffusion reactions between the silicide slurry and Ta12W alloy substrate during vacuum sintering process on the oxidation resistance of the silicide coating,a micro-arc oxidation pretre...To mitigate the impact of interdiffusion reactions between the silicide slurry and Ta12W alloy substrate during vacuum sintering process on the oxidation resistance of the silicide coating,a micro-arc oxidation pretreatment was employed to construct a Ta_(2)O_(5)ceramic layer on the Ta12W alloy surface.Subsequently,a slurry spraying-vacuum sintering method was used to prepare a Si-Cr-Ti-Zr coating on the pretreated substrate.Comparative studies were conducted on the microstructure,phase composition,and isothermal oxidation resistance(at 1600℃)of the as-prepared coatings with and without the micro-arc oxidation ceramic layer.The results show that the Ta_(2)O_(5)layer prepared at 400 V is more continuous and has smaller pores than that prepared at 350 V.After microarc oxidation pretreatment,the Si-Cr-Ti-Zr coating on Ta12W alloy consists of three distinct layers:an upper layer dominated by Ti_(5)Si_(3),Ta_(5)Si_(3),and ZrSi;a middle layer dominated by TaSi_(2);a coating/substrate interfacial reaction layer dominated by Ta_(5)Si_(3).Both the Si-Cr-Ti-Zr coatings with and without the Ta_(2)O_(5)ceramic layer do not fail after isothermal oxidation at 1600℃for 5 h.Notably,the addition of the Ta2O5 ceramic layer reduces the high-temperature oxidation rate of the coating.展开更多
A calcium zirconate crucible material with excellent performance was prepared by fixing the particle size proportion and exploring the addition of Y_(2)O_(3).The results show that Y^(3+)solid-dissolves into c-ZrO_(2)t...A calcium zirconate crucible material with excellent performance was prepared by fixing the particle size proportion and exploring the addition of Y_(2)O_(3).The results show that Y^(3+)solid-dissolves into c-ZrO_(2)to occupy the Zr^(4+)positions,leading to structural defects and promoting the sintering of calcium zirconate.Adding 0.5 wt.%Y_(2)O_(3)into calcium zirconate can enhance the modulus of rupture,reduce the thermal expansion coefficient,and improve the thermal shock resistance.Through high-temperature test,it is found that adding 0.5 wt.%Y_(2)O_(3)significantly improves the corrosion resistance of the sample.展开更多
The limited high-temperature oxidation resistance of Mg alloys is a key factor restricting their development and application.The addition of some rare earth elements(REs),owing to their unique physical and chemical pr...The limited high-temperature oxidation resistance of Mg alloys is a key factor restricting their development and application.The addition of some rare earth elements(REs),owing to their unique physical and chemical properties,can significantly enhance the oxidation resistance of Mg alloys.Based on our previous study,we conclude that REs such as Gd,Y,and Ce enhance the oxidation resistance of Mg-RE alloys.This article comprehensively reviews recent research progress on high-temperature oxidation behavior and the potential mechanism in Mg-RE alloys.Based on the thermodynamic and kinetic analyses,the evolution of the complex oxide system formed during the high-temperature oxidation of Mg-RE alloys is first summarized.The diffusion behavior and concentration control mechanisms of REs during the oxidation process and how these mechanisms affect the sustained growth of the oxide film and antioxidant properties were elucidated.Moreover,the different structures of the oxide films were classified,and their properties were discussed.Finally,this paper introduces the applications of commonly used REs in Mg alloys and frontier research on their oxidation mechanisms.Based on the above review,we propose that future research perspectives can be explored in terms of expanding the experimental temperature range for oxidation tests,optimizing the chemical composition by adding trace REs to study their synergistic mechanism,revealing the underlying oxidation mechanism through advanced in situ microscopic characterization methods,and investigating the mechanical properties of oxide films using diverse approaches.展开更多
TiB_(2)coatings can significantly enhance the high-temperature oxidation resistance of molybdenum,which would broaden the application range of molybdenum and alloys thereof.However,traditional methods for preparing Ti...TiB_(2)coatings can significantly enhance the high-temperature oxidation resistance of molybdenum,which would broaden the application range of molybdenum and alloys thereof.However,traditional methods for preparing TiB_(2)coatings have disadvantages such as high equipment costs,complicated processes,and highly toxic gas emissions.This paper proposes an environmentally friendly method,which requires inexpensive equipment and simple processing,for preparing TiB_(2)coating on molybdenum via electrophoretic deposition within Na3AlF6-based molten salts.The produced TiB_(2)layer had an approximate thickness of 60μm and exhibited high density,outstanding hardness(38.2 GPa)and robust adhesion strength(51 N).Additionally,high-temperature oxidation experiments revealed that,at900℃,the TiB_(2)coating provided effective protection to the molybdenum substrate against oxidation for 3 h.This result indicates that the TiB_(2)coating prepared on molybdenum using molten salt electrophoretic deposition possesses good high-temperature oxidation resistance.展开更多
The development of infrared engineering technologies for extreme environments remains a formidable challenge due to the inherent trade-offs among optical performance,thermal stability,and mechanical integrity in therm...The development of infrared engineering technologies for extreme environments remains a formidable challenge due to the inherent trade-offs among optical performance,thermal stability,and mechanical integrity in thermal photonic metamaterials(TPMs).This work introduces a novel multi-obj ective design framework and demonstrates the design,fabrication,and validation of a TPM operating under extreme temperatures up to 1873 K.We have established a holistic design framework integrating temperaturedependent neural network and Pareto multi-obj ective optimization to co-optimize spectral response,component light-weighting,and structural efficiency.The framework achieves 100 times faster computation than genetic algorithms.The performance of the designed TPM was evaluated under various atmospheric models and detection distances.The TPM achieved a peak radiance suppression efficiency of 82%and a maximum attenuation of-7.4 dB at 1200-1500 K.Experimentally,we fabricated an all-dielectric TPM using a refractory TiO_(2)/BeO multilayer stack with only 5 layers and 2um total thickness.The optimized structure shows high reflectivity(0.62 at 3-5 um;0.48 at 8-14μm)for radiative suppression and high emissivity(0.87 at 5-8μm)for radiative cooling.The TPM withstands 1873 K for 12 h in air with less than 3%spectral drift,retaining excellent mechanical properties.On high-temperature components,it achieves 40-50%radiative suppression and 40-60 K(~10.1 kW m^(-2))radiative cooling at 1100 K,endures over 20 times thermal shock cycles(>150 K s^(-1),700-1500 K),and maintains stable performance over 5 cycles,with 78%visible and 98%microwave transmittance.This work establishes a new paradigm in the design and application of photonic materials for extreme environments.展开更多
Driven by rapid advances in deep learning,object detection has been widely adopted across diverse application scenarios.However,in low-light conditions,critical visual cues of target objects are severely degraded,posi...Driven by rapid advances in deep learning,object detection has been widely adopted across diverse application scenarios.However,in low-light conditions,critical visual cues of target objects are severely degraded,posing a significant challenge for accurate low-light object detection.Existing methods struggle to preserve discriminative features while maintaining semantic consistency between low-light and normal-light images.For this purpose,this study proposes a DL-YOLO model specially tailored for low-light detection.To mitigate target feature attenuation introduced by repeated downsampling,we design aMulti-Scale FeatureConvolution(MSF-Conv)module that captures rich,multi-level details via multi-scale feature learning,thereby reducing model complexity and computational cost.For feature fusion,we integrated the C3k2-DWRmodule by embedding the Dilation-wise Residual(DWR)mechanism into the 2-core optimized Cross Stage Partial(C3)framework,achieving efficient feature integration.In addition,we replace conventional localization losses with WIoU(Weighted Intersection over Union),which dynamically adjusts gradient gain according to sample quality,thereby improving localization robustness and precision.Experiments on the ExDark dataset demonstrate that DL-YOLO delivers strong low-light detection performance.The relevant code is published at https://github.com/cym0997/DL-YOLO.展开更多
In fire rescue scenarios,traditional manual operations are highly dangerous,as dense smoke,low visibility,extreme heat,and toxic gases not only hinder rescue efficiency but also endanger firefighters’safety.Although ...In fire rescue scenarios,traditional manual operations are highly dangerous,as dense smoke,low visibility,extreme heat,and toxic gases not only hinder rescue efficiency but also endanger firefighters’safety.Although intelligent rescue robots can enter hazardous environments in place of humans,smoke poses major challenges for human detection algorithms.These challenges include the attenuation of visible and infrared signals,complex thermal fields,and interference frombackground objects,all ofwhichmake it difficult to accurately identify trapped individuals.To address this problem,we propose VIF-YOLO,a visible–infrared fusion model for real-time human detection in dense smoke environments.The framework introduces a lightweight multimodal fusion(LMF)module based on learnable low-rank representation blocks to end-to-end integrate visible and infrared images,preserving fine details while enhancing salient features.In addition,an efficient multiscale attention(EMA)mechanism is incorporated into the YOLOv10n backbone to improve feature representation under low-light conditions.Extensive experiments on our newly constructedmultimodal smoke human detection(MSHD)dataset demonstrate thatVIF-YOLOachievesmAP50 of 99.5%,precision of 99.2%,and recall of 99.3%,outperforming YOLOv10n by a clear margin.Furthermore,when deployed on the NVIDIA Jetson Xavier NX,VIF-YOLO attains 40.6 FPS with an average inference latency of 24.6 ms,validating its real-time capability on edge-computing platforms.These results confirm that VIF-YOLO provides accurate,robust,and fast detection across complex backgrounds and diverse smoke conditions,ensuring reliable and rapid localization of individuals in need of rescue.展开更多
In modern industrial production,foreign object detection in complex environments is crucial to ensure product quality and production safety.Detection systems based on deep-learning image processing algorithms often fa...In modern industrial production,foreign object detection in complex environments is crucial to ensure product quality and production safety.Detection systems based on deep-learning image processing algorithms often face challenges with handling high-resolution images and achieving accurate detection against complex backgrounds.To address these issues,this study employs the PatchCore unsupervised anomaly detection algorithm combined with data augmentation techniques to enhance the system’s generalization capability across varying lighting conditions,viewing angles,and object scales.The proposed method is evaluated in a complex industrial detection scenario involving the bogie of an electric multiple unit(EMU).A dataset consisting of complex backgrounds,diverse lighting conditions,and multiple viewing angles is constructed to validate the performance of the detection system in real industrial environments.Experimental results show that the proposed model achieves an average area under the receiver operating characteristic curve(AUROC)of 0.92 and an average F1 score of 0.85.Combined with data augmentation,the proposed model exhibits improvements in AUROC by 0.06 and F1 score by 0.03,demonstrating enhanced accuracy and robustness for foreign object detection in complex industrial settings.In addition,the effects of key factors on detection performance are systematically analyzed,providing practical guidance for parameter selection in real industrial applications.展开更多
With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comp...With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comprise heterogeneous networks where outdated systems coexist with the latest devices,spanning a range of devices from non-encrypted ones to fully encrypted ones.Given the limited visibility into payloads in this context,this study investigates AI-based attack detection methods that leverage encrypted traffic metadata,eliminating the need for decryption and minimizing system performance degradation—especially in light of these heterogeneous devices.Using the UNSW-NB15 and CICIoT-2023 dataset,encrypted and unencrypted traffic were categorized according to security protocol,and AI-based intrusion detection experiments were conducted for each traffic type based on metadata.To mitigate the problem of class imbalance,eight different data sampling techniques were applied.The effectiveness of these sampling techniques was then comparatively analyzed using two ensemble models and three Deep Learning(DL)models from various perspectives.The experimental results confirmed that metadata-based attack detection is feasible using only encrypted traffic.In the UNSW-NB15 dataset,the f1-score of encrypted traffic was approximately 0.98,which is 4.3%higher than that of unencrypted traffic(approximately 0.94).In addition,analysis of the encrypted traffic in the CICIoT-2023 dataset using the same method showed a significantly lower f1-score of roughly 0.43,indicating that the quality of the dataset and the preprocessing approach have a substantial impact on detection performance.Furthermore,when data sampling techniques were applied to encrypted traffic,the recall in the UNSWNB15(Encrypted)dataset improved by up to 23.0%,and in the CICIoT-2023(Encrypted)dataset by 20.26%,showing a similar level of improvement.Notably,in CICIoT-2023,f1-score and Receiver Operation Characteristic-Area Under the Curve(ROC-AUC)increased by 59.0%and 55.94%,respectively.These results suggest that data sampling can have a positive effect even in encrypted environments.However,the extent of the improvement may vary depending on data quality,model architecture,and sampling strategy.展开更多
Antibiotic resistance genes(ARGs) are recognized as a primary threat to the sustainability of environment and human health in the 21^(st) century.Nanomaterials(NMs) have attracted substantial attention due to their un...Antibiotic resistance genes(ARGs) are recognized as a primary threat to the sustainability of environment and human health in the 21^(st) century.Nanomaterials(NMs) have attracted substantial attention due to their unique dimensions and structures.Unfortunately,emerging evidence suggests that NMs may facilitate the transmission of ARGs.It is crucial to elucidate how NMs affect the evolution and dissemination of ARGs.The current review comprehensively examines the role of NMs in the widespread transmission of ARGs in aquatic environments and the underlying mechanisms involved in the process.It aims to clarify the effects and mechanisms of NMs on the horizontal gene transfer processes that are associated with ARGs,including the enhancement of cell membrane permeability,the formation of nanopores on membranes,promotion of mutagenesis,and the generation of reactive oxygen species(ROSs).Furthermore,the trade-off between the removal of ARGs and horizontal transfer has been elucidated.The review aspires to guide future research directions,advance knowledge on the implications of NMs in the field of ARGs' transmission,and provide a theoretical foundation for the development of safer and more effective applications of NMs.展开更多
With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,exist...With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,existing methods often suffer from rigid reward functions and limited adaptability to evolving adversarial strategies.Moreover,most research assumes open airspace,overlooking the influence of potential obstacles.In this paper,we address one-on-one within-visual-range ACMD in obstructed environments,and propose an improved Soft Actor-Critic(SAC)algorithm trained under a curriculum self-play framework.A maneuver strategy mirroring inference module is integrated to estimate each other's likely positions when visual obstruction occurs.By leveraging curriculum learning to guide progressive experience accumulation and self-play for adversarial evolution,our method enhances both training efficiency and tactical diversity.We further integrate an attention mechanism that dynamically adjusts the weights of sub-rewards,enabling the learned policy to adapt to rapidly changing air combat situations.Numerical simulations demonstrate that our enhanced SAC converges more quickly and achieves higher win rates than other baseline methods.An animation is available at bilibili.com/video/BV1BHVszHE98 for better illustration.展开更多
The atmospheric corrosion behavior of 510L low alloy steel subjected to acid-cleaned surface(ACS)and eco-pickled surface(EPS)treatments is systematically examined.After 1 year of atmospheric exposure,both ACS-and EPS-...The atmospheric corrosion behavior of 510L low alloy steel subjected to acid-cleaned surface(ACS)and eco-pickled surface(EPS)treatments is systematically examined.After 1 year of atmospheric exposure,both ACS-and EPS-treated samples demonstrate protective ability index values exceeding 2,indicating robust protective properties of the developed rust layers.The corrosion rates of ACS-and EPS-treated samples are similar.During the initial corrosion stage,γ-FeOOH emerges as the dominant corrosion product.With the prolonged atmospheric exposure,γ-FeOOH content progressively decreases through phase transformation into thermodynamically stableα-FeOOH and densely structured Fe_(3)O_(4),which markedly suppresses the corrosion of the steel.Notably,the corrosion rate of the coated EPS sample is obviously lower than that of the coated ACS counterpart,which is ascribed to the distinctive micro-roughness of EPS-treated surfaces that promote mechanical interlocking with protective coatings.展开更多
As large,room-scale environments become increasingly common,their spatial complexity increases due to variable,unstructured elements.Consequently,demand for room-scale service robots is surging,yet most technologies r...As large,room-scale environments become increasingly common,their spatial complexity increases due to variable,unstructured elements.Consequently,demand for room-scale service robots is surging,yet most technologies remain corridor-centric,and autonomous navigation in expansive rooms becomes unstable even around static obstacles.Existing approaches face several structural limitations.These include the labor-intensive requirement for large-scale object annotation and continual retraining,as well as the vulnerability of vanishing point or linebased methods when geometric cues are insufficient.In addition,the high cost of LiDAR and 3D perception errors caused by limited wall cues and dense interior clutter further limit their effectiveness.To address these challenges,we propose a zero-shot vision-based algorithm for robust 3D map reconstruction in geometry-deficient room-scale environments.The algorithm operates in three layers:Layer 1 performs dimension-wise boundary detection;Layer 2 estimates vanishing points,refines the precise perspective space,and extracts a floor mask;and Layer 3 conducts 3D spatial mapping and obstacle recognition.The proposed method was experimentally validated across various geometric-deficient room-scale environments,including lobbies,seminar rooms,conference rooms,cafeterias,and museums—demonstrating its ability to reliably reconstruct 3D maps and accurately recognize obstacles.Experimental results show that the proposed algorithm achieved an F1 score of 0.959 in precision perspective space detection and 0.965 in floor mask extraction.For obstacle recognition and classification,it obtained F1 scores of 0.980 in obstacle absent areas,0.913 in solid obstacle environments,and 0.939 in skeleton-type sparse obstacle environments,confirming its high precision and reliability in geometric-deficient room-scale environments.展开更多
Federated Learning(FL)provides an effective framework for efficient processing in vehicular edge computing.However,the dynamic and uncertain communication environment,along with the performance variations of vehicular...Federated Learning(FL)provides an effective framework for efficient processing in vehicular edge computing.However,the dynamic and uncertain communication environment,along with the performance variations of vehicular devices,affect the distribution and uploading processes of model parameters.In FL-assisted Internet of Vehicles(IoV)scenarios,challenges such as data heterogeneity,limited device resources,and unstable communication environments become increasingly prominent.These issues necessitate intelligent vehicle selection schemes to enhance training efficiency.Given this context,we propose a new scenario involving FL-assisted IoV systems under dynamic and uncertain communication conditions,and develop a dynamic interval multi-objective optimization algorithm to jointly optimize various factors including training experiments,system energy consumption,and bandwidth utilization to meet multi-criteria resource optimization requirements.For the problem at hand,we design a dynamic interval multi-objective optimization algorithm based on interval overlap detection.Simulation results demonstrate that our method outperforms other solutions in terms of accuracy,training cost,and server utilization.It effectively enhances training efficiency under wireless channel environments while rationally utilizing bandwidth resources,thus possessing significant scientific value and application potential in the field of IoV.展开更多
To assess the effectiveness of vaccination in contaminated environments,this study introduces a modeling framework that encompasses two transmission routes,namely direct human-to-human contact and indirect human-to-en...To assess the effectiveness of vaccination in contaminated environments,this study introduces a modeling framework that encompasses two transmission routes,namely direct human-to-human contact and indirect human-to-environment contact,as well as the implementation of new M72/AS01_(E)vaccine.Motivated by this,a coupled age-structured tuberculosis(TB)model is proposed.Its well-posedness requirement is verified using the integrated semigroup theory.Furthermore,this study presents a comprehensive analysis of threshold dynamics associated with the proposed model.Specifically,the global stability of the disease-free and positive steady states is demonstrated by employing Lyapunov functionals.Lastly,the effects of the vaccination with M72/AS01_(E)and contaminated environments on TB control are numerically simulated.Experimental results indicate that high concentrations of Mycobacterium tuberculosis in contaminated environments may somewhat impede TB control efforts,but that large-scale deployment of new vaccine could significantly reduce the prevalence of TB.展开更多
There is a lack of systematic understanding of coal-forming environment classification and its influences on coal petrological characteristics,a coal-forming mire classification scheme applicable to the petroleum indu...There is a lack of systematic understanding of coal-forming environment classification and its influences on coal petrological characteristics,a coal-forming mire classification scheme applicable to the petroleum industry is proposed based on modern ecological peatland frameworks.The formation,evolutionary processes,and diagnostic criteria of coal-forming environments are systematically clarified.The results show that:(1)modern peatlands can be classified according to hydrological conditions,vegetation types,and geomorphic settings,and coal-forming mires can be divided into low moor,transitional,and high moor peat mires based on geomorphology;(2)the development of coal-forming environments includes three modes:subaqueous peat infilling,autochthonous peat accumulation in wetlands,and mire development in arid regions;(3)peat accumulation is jointly controlled by plant production and decomposition,hydrological disturbances,and sediment input,and the peat-to-coal thickness ratio varies with coalification;(4)diagnostic criteria for low moor,transitional,and high moor peat mires are established based on ash yield,gamma-ray log responses,and vitrinite-to-inertinite ratios;and(5)transgression-regression processes exert a key control on peat mire evolution,directly influencing peat thickness and continuity,while the evolution of low moor,transitional,and high moor mires governs coal maceral assemblages and thereby affects hydrocarbon generation potential and reservoir properties of coals.The coal-forming environment classification and identification system developed in this study effectively reveals the vertical heterogeneity of coals in the Ordos Basin,providing theoretical and practical guidance for efficient exploration and development of coal-rock gas.展开更多
During the production processes of energy,metallurgy,chemical engineering,and other process industries,substantial high-temperature dustladen flue gas is generated.Asymmetric silicon carbide(SiC)membranes exhibit sign...During the production processes of energy,metallurgy,chemical engineering,and other process industries,substantial high-temperature dustladen flue gas is generated.Asymmetric silicon carbide(SiC)membranes exhibit significant potential in flue gas filtration since they enable direct filtration of high-temperature gas and facilitate thermal energy recovery.However,membrane particle penetration is a prevalent issue when constructing membrane layer directly on macroporous support,which contributes to a considerable mass transfer resistance.Herein,a novel hydrophobic modification strategy was developed to avoid the slurry penetration,thereby fabricating the asymmetric SiC membrane without the necessity of any intermediate or sacrificial layer.Firstly,the modifier concentration was adjusted to guarantee that the support was hydrophobic enough to prevent the slurry from penetrating.Subsequently,the slurry surface tension was fine-tuned by introducing ethanol to enhance the integrity of the SiC membrane.Furthermore,the effect of solid content was systematically investigated.It was demonstrated that the optimized SiC membranes obtained excellent gas permeance from 100.8 to 199.8 m^(3)·m^(-2)·h^(-1)·kPa^(-1)with the pore size ranging from 1.93 to 3.89μm.Also,the SiC membrane exhibited excellent stability for 24 h and achieved an excellent dust removal efficiency(99.99%)when filtering ultrafine dust particles(~300 nm)under high temperatures.This method effectively bridges the membrane particle penetration issue caused by the particle size disparity among different layers of the asymmetric membrane,establishing an efficient strategy to fabricate highpermeance SiC membranes applied in high-temperature dust-laden gas filtration.展开更多
文摘Valve-regulated-lead-acid (VRLA) battery charging performed in high-temperature environments is extremely risky under overcharge conditions, and may lead to a subsequent thermal runaway. A new pressure-controlled charging method was adopted and the charging characteristics of the pressure-controlled VRLA battery in high-temperature environments were ex-perimentally studied. The concept was tested in a large temperature gradient to obtain more details about the effects of users' accustomed charging and discharging modes on battery capacity. The premature capacity loss (PCL) phenomenon under high temperature exposure was analyzed. The results showed that the capacity loss could be recovered by charging using a large current.
基金supported by the National Natural Science Foundation of China(No.52075249)the Tianyuan Laboratory Fund(No.24-JSKY-ZZKT-14).
文摘In the fields of optoelectronics and semiconductors, reliable fixation and handling of brittle materials (glass, wafer, etc.) in high-temperature, vacuum, and vibration environments face particular technical challenges. These challenges include the inability of suction cups in a vacuum, the residue of chemical adhesives, and the easy damage of mechanical clamping. In this paper, fluorine-based bionic adhesive pads (FBAPs) obtained using molding technology to imitate gecko micropillar arrays are presented. FBAPs inhibit the substantial decay of adhesive properties at high temperatures and provide stable and reliable performance in vacuum and vibration environments. The results demonstrated that the decayed force values of the normal and tangential strength of the FBAP were only 9.01% and 5.82% of the planar samples when warmed up to 300℃ from 25℃, respectively. In a vacuum, all FBAPs exhibit less than 20% adhesion attenuation, and in a vibrational environment, they can withstand accelerations of at least 4.27 g. The design of the microstructure arrays enables the realization of efficient and non-destructive separation through mechanical rotation or blowing. It provides a bionic material basis for the fixation of brittle materials on smooth surfaces under complex environments and for transportation automation.
基金National Natural Science Foundation of China(No.U2241205)the Natural Science Basic Research Program of Shaanxi(Nos.2022JC-33,2023-GHZD-35,and 2024JC-ZDXM-25)+1 种基金the Fundamental Research Funds for the Central Universitiesthe National 111 Project to provide fund for conducting experiments。
文摘In this study,the design,analysis,manufacturing,and testing of a 3D-printed conformal microstrip array antenna for high-temperature environments is presented.3D printing technology is used to fabricate a curved ceramic substrate,and laser sintering and microdroplet spraying processes are used to add the conductive metal on the curved substrate.The problems of gain loss,bandwidth reduction,and frequency shift caused by high temperatures are addressed by using a proper antenna design,with parasitic patches,slots,and metal resonant cavities.The antenna prototype is characterized by the curved substrates and the conductive metals for the power dividers,the patch,and the ground plane;its performance is examined up to a temperature of 600℃in a muffle furnace and compared with the results from the numerical analysis.The results show that the antenna can effectively function at 600℃and even higher temperatures.
基金National Natural Science Foundation of China(52071274)Key Research and Development Projects of Shaanxi Province(2023-YBGY-442)Science and Technology Nova Project-Innovative Talent Promotion Program of Shaanxi Province(2020KJXX-062)。
文摘To mitigate the impact of interdiffusion reactions between the silicide slurry and Ta12W alloy substrate during vacuum sintering process on the oxidation resistance of the silicide coating,a micro-arc oxidation pretreatment was employed to construct a Ta_(2)O_(5)ceramic layer on the Ta12W alloy surface.Subsequently,a slurry spraying-vacuum sintering method was used to prepare a Si-Cr-Ti-Zr coating on the pretreated substrate.Comparative studies were conducted on the microstructure,phase composition,and isothermal oxidation resistance(at 1600℃)of the as-prepared coatings with and without the micro-arc oxidation ceramic layer.The results show that the Ta_(2)O_(5)layer prepared at 400 V is more continuous and has smaller pores than that prepared at 350 V.After microarc oxidation pretreatment,the Si-Cr-Ti-Zr coating on Ta12W alloy consists of three distinct layers:an upper layer dominated by Ti_(5)Si_(3),Ta_(5)Si_(3),and ZrSi;a middle layer dominated by TaSi_(2);a coating/substrate interfacial reaction layer dominated by Ta_(5)Si_(3).Both the Si-Cr-Ti-Zr coatings with and without the Ta_(2)O_(5)ceramic layer do not fail after isothermal oxidation at 1600℃for 5 h.Notably,the addition of the Ta2O5 ceramic layer reduces the high-temperature oxidation rate of the coating.
基金provided by the National Natural Science Foundation of China(NSFC)through the Joint Fund Project(No.U24A202815)the Youth Science Fund Project(No.52302031).
文摘A calcium zirconate crucible material with excellent performance was prepared by fixing the particle size proportion and exploring the addition of Y_(2)O_(3).The results show that Y^(3+)solid-dissolves into c-ZrO_(2)to occupy the Zr^(4+)positions,leading to structural defects and promoting the sintering of calcium zirconate.Adding 0.5 wt.%Y_(2)O_(3)into calcium zirconate can enhance the modulus of rupture,reduce the thermal expansion coefficient,and improve the thermal shock resistance.Through high-temperature test,it is found that adding 0.5 wt.%Y_(2)O_(3)significantly improves the corrosion resistance of the sample.
基金supported by the Key R&D Program of Shandong Province,China(No.2025CXGC 010412)the National Key Research and Development Program of China(No.2022YFB3709300)the National Natural Science Foundation of China(No.U21A2048).
文摘The limited high-temperature oxidation resistance of Mg alloys is a key factor restricting their development and application.The addition of some rare earth elements(REs),owing to their unique physical and chemical properties,can significantly enhance the oxidation resistance of Mg alloys.Based on our previous study,we conclude that REs such as Gd,Y,and Ce enhance the oxidation resistance of Mg-RE alloys.This article comprehensively reviews recent research progress on high-temperature oxidation behavior and the potential mechanism in Mg-RE alloys.Based on the thermodynamic and kinetic analyses,the evolution of the complex oxide system formed during the high-temperature oxidation of Mg-RE alloys is first summarized.The diffusion behavior and concentration control mechanisms of REs during the oxidation process and how these mechanisms affect the sustained growth of the oxide film and antioxidant properties were elucidated.Moreover,the different structures of the oxide films were classified,and their properties were discussed.Finally,this paper introduces the applications of commonly used REs in Mg alloys and frontier research on their oxidation mechanisms.Based on the above review,we propose that future research perspectives can be explored in terms of expanding the experimental temperature range for oxidation tests,optimizing the chemical composition by adding trace REs to study their synergistic mechanism,revealing the underlying oxidation mechanism through advanced in situ microscopic characterization methods,and investigating the mechanical properties of oxide films using diverse approaches.
基金supported by the Original Exploratory Program of the National Natural Science Foundation of China(No.52450012)。
文摘TiB_(2)coatings can significantly enhance the high-temperature oxidation resistance of molybdenum,which would broaden the application range of molybdenum and alloys thereof.However,traditional methods for preparing TiB_(2)coatings have disadvantages such as high equipment costs,complicated processes,and highly toxic gas emissions.This paper proposes an environmentally friendly method,which requires inexpensive equipment and simple processing,for preparing TiB_(2)coating on molybdenum via electrophoretic deposition within Na3AlF6-based molten salts.The produced TiB_(2)layer had an approximate thickness of 60μm and exhibited high density,outstanding hardness(38.2 GPa)and robust adhesion strength(51 N).Additionally,high-temperature oxidation experiments revealed that,at900℃,the TiB_(2)coating provided effective protection to the molybdenum substrate against oxidation for 3 h.This result indicates that the TiB_(2)coating prepared on molybdenum using molten salt electrophoretic deposition possesses good high-temperature oxidation resistance.
基金supported by National Key Research and Development Program of China(2024YFA1210500,2023YFB4606105)Fundamental Research Center Projects(52488301)of National Natural Science Foundation of China(NSFC)+1 种基金Key Research Program of Frontier Sciences(ZDBS-LYJSC030)of Chinese Academy of SciencesWestern Light Program(xbzg-zdsys-202402)of Chinese Academy of Sciences。
文摘The development of infrared engineering technologies for extreme environments remains a formidable challenge due to the inherent trade-offs among optical performance,thermal stability,and mechanical integrity in thermal photonic metamaterials(TPMs).This work introduces a novel multi-obj ective design framework and demonstrates the design,fabrication,and validation of a TPM operating under extreme temperatures up to 1873 K.We have established a holistic design framework integrating temperaturedependent neural network and Pareto multi-obj ective optimization to co-optimize spectral response,component light-weighting,and structural efficiency.The framework achieves 100 times faster computation than genetic algorithms.The performance of the designed TPM was evaluated under various atmospheric models and detection distances.The TPM achieved a peak radiance suppression efficiency of 82%and a maximum attenuation of-7.4 dB at 1200-1500 K.Experimentally,we fabricated an all-dielectric TPM using a refractory TiO_(2)/BeO multilayer stack with only 5 layers and 2um total thickness.The optimized structure shows high reflectivity(0.62 at 3-5 um;0.48 at 8-14μm)for radiative suppression and high emissivity(0.87 at 5-8μm)for radiative cooling.The TPM withstands 1873 K for 12 h in air with less than 3%spectral drift,retaining excellent mechanical properties.On high-temperature components,it achieves 40-50%radiative suppression and 40-60 K(~10.1 kW m^(-2))radiative cooling at 1100 K,endures over 20 times thermal shock cycles(>150 K s^(-1),700-1500 K),and maintains stable performance over 5 cycles,with 78%visible and 98%microwave transmittance.This work establishes a new paradigm in the design and application of photonic materials for extreme environments.
文摘Driven by rapid advances in deep learning,object detection has been widely adopted across diverse application scenarios.However,in low-light conditions,critical visual cues of target objects are severely degraded,posing a significant challenge for accurate low-light object detection.Existing methods struggle to preserve discriminative features while maintaining semantic consistency between low-light and normal-light images.For this purpose,this study proposes a DL-YOLO model specially tailored for low-light detection.To mitigate target feature attenuation introduced by repeated downsampling,we design aMulti-Scale FeatureConvolution(MSF-Conv)module that captures rich,multi-level details via multi-scale feature learning,thereby reducing model complexity and computational cost.For feature fusion,we integrated the C3k2-DWRmodule by embedding the Dilation-wise Residual(DWR)mechanism into the 2-core optimized Cross Stage Partial(C3)framework,achieving efficient feature integration.In addition,we replace conventional localization losses with WIoU(Weighted Intersection over Union),which dynamically adjusts gradient gain according to sample quality,thereby improving localization robustness and precision.Experiments on the ExDark dataset demonstrate that DL-YOLO delivers strong low-light detection performance.The relevant code is published at https://github.com/cym0997/DL-YOLO.
基金funded by the National Natural Science Foundation of China under Grant 62306128the Leading Innovation Project of Changzhou Science and Technology Bureau underGrant CQ20230072+2 种基金the Basic Science Research Project of Jiangsu Provincial Department of Education under Grant 23KJD520003the Science and Technology Development Plan Project of Jilin Provinceunder Grant 20240101382JCthe National KeyR esearch and Development Program of China under Grant 2023YFF1105102.
文摘In fire rescue scenarios,traditional manual operations are highly dangerous,as dense smoke,low visibility,extreme heat,and toxic gases not only hinder rescue efficiency but also endanger firefighters’safety.Although intelligent rescue robots can enter hazardous environments in place of humans,smoke poses major challenges for human detection algorithms.These challenges include the attenuation of visible and infrared signals,complex thermal fields,and interference frombackground objects,all ofwhichmake it difficult to accurately identify trapped individuals.To address this problem,we propose VIF-YOLO,a visible–infrared fusion model for real-time human detection in dense smoke environments.The framework introduces a lightweight multimodal fusion(LMF)module based on learnable low-rank representation blocks to end-to-end integrate visible and infrared images,preserving fine details while enhancing salient features.In addition,an efficient multiscale attention(EMA)mechanism is incorporated into the YOLOv10n backbone to improve feature representation under low-light conditions.Extensive experiments on our newly constructedmultimodal smoke human detection(MSHD)dataset demonstrate thatVIF-YOLOachievesmAP50 of 99.5%,precision of 99.2%,and recall of 99.3%,outperforming YOLOv10n by a clear margin.Furthermore,when deployed on the NVIDIA Jetson Xavier NX,VIF-YOLO attains 40.6 FPS with an average inference latency of 24.6 ms,validating its real-time capability on edge-computing platforms.These results confirm that VIF-YOLO provides accurate,robust,and fast detection across complex backgrounds and diverse smoke conditions,ensuring reliable and rapid localization of individuals in need of rescue.
文摘In modern industrial production,foreign object detection in complex environments is crucial to ensure product quality and production safety.Detection systems based on deep-learning image processing algorithms often face challenges with handling high-resolution images and achieving accurate detection against complex backgrounds.To address these issues,this study employs the PatchCore unsupervised anomaly detection algorithm combined with data augmentation techniques to enhance the system’s generalization capability across varying lighting conditions,viewing angles,and object scales.The proposed method is evaluated in a complex industrial detection scenario involving the bogie of an electric multiple unit(EMU).A dataset consisting of complex backgrounds,diverse lighting conditions,and multiple viewing angles is constructed to validate the performance of the detection system in real industrial environments.Experimental results show that the proposed model achieves an average area under the receiver operating characteristic curve(AUROC)of 0.92 and an average F1 score of 0.85.Combined with data augmentation,the proposed model exhibits improvements in AUROC by 0.06 and F1 score by 0.03,demonstrating enhanced accuracy and robustness for foreign object detection in complex industrial settings.In addition,the effects of key factors on detection performance are systematically analyzed,providing practical guidance for parameter selection in real industrial applications.
基金supported by the Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.RS-2023-00235509Development of security monitoring technology based network behavior against encrypted cyber threats in ICT convergence environment).
文摘With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comprise heterogeneous networks where outdated systems coexist with the latest devices,spanning a range of devices from non-encrypted ones to fully encrypted ones.Given the limited visibility into payloads in this context,this study investigates AI-based attack detection methods that leverage encrypted traffic metadata,eliminating the need for decryption and minimizing system performance degradation—especially in light of these heterogeneous devices.Using the UNSW-NB15 and CICIoT-2023 dataset,encrypted and unencrypted traffic were categorized according to security protocol,and AI-based intrusion detection experiments were conducted for each traffic type based on metadata.To mitigate the problem of class imbalance,eight different data sampling techniques were applied.The effectiveness of these sampling techniques was then comparatively analyzed using two ensemble models and three Deep Learning(DL)models from various perspectives.The experimental results confirmed that metadata-based attack detection is feasible using only encrypted traffic.In the UNSW-NB15 dataset,the f1-score of encrypted traffic was approximately 0.98,which is 4.3%higher than that of unencrypted traffic(approximately 0.94).In addition,analysis of the encrypted traffic in the CICIoT-2023 dataset using the same method showed a significantly lower f1-score of roughly 0.43,indicating that the quality of the dataset and the preprocessing approach have a substantial impact on detection performance.Furthermore,when data sampling techniques were applied to encrypted traffic,the recall in the UNSWNB15(Encrypted)dataset improved by up to 23.0%,and in the CICIoT-2023(Encrypted)dataset by 20.26%,showing a similar level of improvement.Notably,in CICIoT-2023,f1-score and Receiver Operation Characteristic-Area Under the Curve(ROC-AUC)increased by 59.0%and 55.94%,respectively.These results suggest that data sampling can have a positive effect even in encrypted environments.However,the extent of the improvement may vary depending on data quality,model architecture,and sampling strategy.
基金supported by the State Key Laboratory of Urban Water Resource and Environment (Harbin Institute of Technology) (No.2022TS13)the key projects of National Natural Science Foundation of China (No.2019YFC0408503)the Key Research Program of Wuhan (No.2022022202015015)。
文摘Antibiotic resistance genes(ARGs) are recognized as a primary threat to the sustainability of environment and human health in the 21^(st) century.Nanomaterials(NMs) have attracted substantial attention due to their unique dimensions and structures.Unfortunately,emerging evidence suggests that NMs may facilitate the transmission of ARGs.It is crucial to elucidate how NMs affect the evolution and dissemination of ARGs.The current review comprehensively examines the role of NMs in the widespread transmission of ARGs in aquatic environments and the underlying mechanisms involved in the process.It aims to clarify the effects and mechanisms of NMs on the horizontal gene transfer processes that are associated with ARGs,including the enhancement of cell membrane permeability,the formation of nanopores on membranes,promotion of mutagenesis,and the generation of reactive oxygen species(ROSs).Furthermore,the trade-off between the removal of ARGs and horizontal transfer has been elucidated.The review aspires to guide future research directions,advance knowledge on the implications of NMs in the field of ARGs' transmission,and provide a theoretical foundation for the development of safer and more effective applications of NMs.
基金support of the National Key Research and Development Plan(No.2021YFB3302501)the financial support of the National Science Foundation of China(No.12161076)the financial support of the Fundamental Research Funds for the Central Universities(No.DUT25GF207).
文摘With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,existing methods often suffer from rigid reward functions and limited adaptability to evolving adversarial strategies.Moreover,most research assumes open airspace,overlooking the influence of potential obstacles.In this paper,we address one-on-one within-visual-range ACMD in obstructed environments,and propose an improved Soft Actor-Critic(SAC)algorithm trained under a curriculum self-play framework.A maneuver strategy mirroring inference module is integrated to estimate each other's likely positions when visual obstruction occurs.By leveraging curriculum learning to guide progressive experience accumulation and self-play for adversarial evolution,our method enhances both training efficiency and tactical diversity.We further integrate an attention mechanism that dynamically adjusts the weights of sub-rewards,enabling the learned policy to adapt to rapidly changing air combat situations.Numerical simulations demonstrate that our enhanced SAC converges more quickly and achieves higher win rates than other baseline methods.An animation is available at bilibili.com/video/BV1BHVszHE98 for better illustration.
基金support by National Natural Science Foundation of China(Grant No.52401103)Key Scientific Research Project in Shanxi Province(Grant No.202302050201015)+3 种基金Central Guiding Science and Technology Development of Local Fund(Grant No.YDZJSK20231A046)the Special Fund for Science and Technology Innovation Teams of Shanxi Province(202204051001004)Science and Technology Cooperation and Exchange Special Project of Shanxi Province(202404041101038)Postgraduate Education Innovation Project of Shanxi Province(Grant No.2024SJ304).
文摘The atmospheric corrosion behavior of 510L low alloy steel subjected to acid-cleaned surface(ACS)and eco-pickled surface(EPS)treatments is systematically examined.After 1 year of atmospheric exposure,both ACS-and EPS-treated samples demonstrate protective ability index values exceeding 2,indicating robust protective properties of the developed rust layers.The corrosion rates of ACS-and EPS-treated samples are similar.During the initial corrosion stage,γ-FeOOH emerges as the dominant corrosion product.With the prolonged atmospheric exposure,γ-FeOOH content progressively decreases through phase transformation into thermodynamically stableα-FeOOH and densely structured Fe_(3)O_(4),which markedly suppresses the corrosion of the steel.Notably,the corrosion rate of the coated EPS sample is obviously lower than that of the coated ACS counterpart,which is ascribed to the distinctive micro-roughness of EPS-treated surfaces that promote mechanical interlocking with protective coatings.
基金supported by Kyonggi University Research Grant 2025.
文摘As large,room-scale environments become increasingly common,their spatial complexity increases due to variable,unstructured elements.Consequently,demand for room-scale service robots is surging,yet most technologies remain corridor-centric,and autonomous navigation in expansive rooms becomes unstable even around static obstacles.Existing approaches face several structural limitations.These include the labor-intensive requirement for large-scale object annotation and continual retraining,as well as the vulnerability of vanishing point or linebased methods when geometric cues are insufficient.In addition,the high cost of LiDAR and 3D perception errors caused by limited wall cues and dense interior clutter further limit their effectiveness.To address these challenges,we propose a zero-shot vision-based algorithm for robust 3D map reconstruction in geometry-deficient room-scale environments.The algorithm operates in three layers:Layer 1 performs dimension-wise boundary detection;Layer 2 estimates vanishing points,refines the precise perspective space,and extracts a floor mask;and Layer 3 conducts 3D spatial mapping and obstacle recognition.The proposed method was experimentally validated across various geometric-deficient room-scale environments,including lobbies,seminar rooms,conference rooms,cafeterias,and museums—demonstrating its ability to reliably reconstruct 3D maps and accurately recognize obstacles.Experimental results show that the proposed algorithm achieved an F1 score of 0.959 in precision perspective space detection and 0.965 in floor mask extraction.For obstacle recognition and classification,it obtained F1 scores of 0.980 in obstacle absent areas,0.913 in solid obstacle environments,and 0.939 in skeleton-type sparse obstacle environments,confirming its high precision and reliability in geometric-deficient room-scale environments.
基金supported in part by the Central Guidance for Local Science and Technology Development Funds under Grant No.YDZJSX2025D049Shanxi Provincial Graduate Innovation Research Program under Grant No.2024KY652.
文摘Federated Learning(FL)provides an effective framework for efficient processing in vehicular edge computing.However,the dynamic and uncertain communication environment,along with the performance variations of vehicular devices,affect the distribution and uploading processes of model parameters.In FL-assisted Internet of Vehicles(IoV)scenarios,challenges such as data heterogeneity,limited device resources,and unstable communication environments become increasingly prominent.These issues necessitate intelligent vehicle selection schemes to enhance training efficiency.Given this context,we propose a new scenario involving FL-assisted IoV systems under dynamic and uncertain communication conditions,and develop a dynamic interval multi-objective optimization algorithm to jointly optimize various factors including training experiments,system energy consumption,and bandwidth utilization to meet multi-criteria resource optimization requirements.For the problem at hand,we design a dynamic interval multi-objective optimization algorithm based on interval overlap detection.Simulation results demonstrate that our method outperforms other solutions in terms of accuracy,training cost,and server utilization.It effectively enhances training efficiency under wireless channel environments while rationally utilizing bandwidth resources,thus possessing significant scientific value and application potential in the field of IoV.
文摘To assess the effectiveness of vaccination in contaminated environments,this study introduces a modeling framework that encompasses two transmission routes,namely direct human-to-human contact and indirect human-to-environment contact,as well as the implementation of new M72/AS01_(E)vaccine.Motivated by this,a coupled age-structured tuberculosis(TB)model is proposed.Its well-posedness requirement is verified using the integrated semigroup theory.Furthermore,this study presents a comprehensive analysis of threshold dynamics associated with the proposed model.Specifically,the global stability of the disease-free and positive steady states is demonstrated by employing Lyapunov functionals.Lastly,the effects of the vaccination with M72/AS01_(E)and contaminated environments on TB control are numerically simulated.Experimental results indicate that high concentrations of Mycobacterium tuberculosis in contaminated environments may somewhat impede TB control efforts,but that large-scale deployment of new vaccine could significantly reduce the prevalence of TB.
基金Supported by the China National Science and Technology Major Project(2025ZD1405700)。
文摘There is a lack of systematic understanding of coal-forming environment classification and its influences on coal petrological characteristics,a coal-forming mire classification scheme applicable to the petroleum industry is proposed based on modern ecological peatland frameworks.The formation,evolutionary processes,and diagnostic criteria of coal-forming environments are systematically clarified.The results show that:(1)modern peatlands can be classified according to hydrological conditions,vegetation types,and geomorphic settings,and coal-forming mires can be divided into low moor,transitional,and high moor peat mires based on geomorphology;(2)the development of coal-forming environments includes three modes:subaqueous peat infilling,autochthonous peat accumulation in wetlands,and mire development in arid regions;(3)peat accumulation is jointly controlled by plant production and decomposition,hydrological disturbances,and sediment input,and the peat-to-coal thickness ratio varies with coalification;(4)diagnostic criteria for low moor,transitional,and high moor peat mires are established based on ash yield,gamma-ray log responses,and vitrinite-to-inertinite ratios;and(5)transgression-regression processes exert a key control on peat mire evolution,directly influencing peat thickness and continuity,while the evolution of low moor,transitional,and high moor mires governs coal maceral assemblages and thereby affects hydrocarbon generation potential and reservoir properties of coals.The coal-forming environment classification and identification system developed in this study effectively reveals the vertical heterogeneity of coals in the Ordos Basin,providing theoretical and practical guidance for efficient exploration and development of coal-rock gas.
基金Financial support was provided by the National Natural Science Foundation of China(22325804,22578197)National Key Research and Development Project of China(2021YFB3801302,2022YFC3900300)+1 种基金Jiangsu Future Membrane Technology Innovation Center(No.BM2021804)Natural Science Foundation of Jiangsu Higher Education Institutions of China(No.25KJA530003).
文摘During the production processes of energy,metallurgy,chemical engineering,and other process industries,substantial high-temperature dustladen flue gas is generated.Asymmetric silicon carbide(SiC)membranes exhibit significant potential in flue gas filtration since they enable direct filtration of high-temperature gas and facilitate thermal energy recovery.However,membrane particle penetration is a prevalent issue when constructing membrane layer directly on macroporous support,which contributes to a considerable mass transfer resistance.Herein,a novel hydrophobic modification strategy was developed to avoid the slurry penetration,thereby fabricating the asymmetric SiC membrane without the necessity of any intermediate or sacrificial layer.Firstly,the modifier concentration was adjusted to guarantee that the support was hydrophobic enough to prevent the slurry from penetrating.Subsequently,the slurry surface tension was fine-tuned by introducing ethanol to enhance the integrity of the SiC membrane.Furthermore,the effect of solid content was systematically investigated.It was demonstrated that the optimized SiC membranes obtained excellent gas permeance from 100.8 to 199.8 m^(3)·m^(-2)·h^(-1)·kPa^(-1)with the pore size ranging from 1.93 to 3.89μm.Also,the SiC membrane exhibited excellent stability for 24 h and achieved an excellent dust removal efficiency(99.99%)when filtering ultrafine dust particles(~300 nm)under high temperatures.This method effectively bridges the membrane particle penetration issue caused by the particle size disparity among different layers of the asymmetric membrane,establishing an efficient strategy to fabricate highpermeance SiC membranes applied in high-temperature dust-laden gas filtration.
