期刊：
Journal of Tribology,2026年148(1):011701 ISSN：0742-4787
通讯作者：
Hua-Xi Zhou
作者机构：
[Jing-Lun Xie; Chang-Guang Zhou] Department of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China;[Xiao-Yi Wang; Hua-Xi Zhou; Yi Zhang] Department of Mechanical Engineering, Wuhan Polytechnic University, Wuhan 430048, China
通讯机构：
[Hua-Xi Zhou] D;Department of Mechanical Engineering, Wuhan Polytechnic University, Wuhan 430048, China
摘要：
The vat photopolymerization (VPP) technology offers exceptional flexibility in design and manufaction of high-performance piezoceramic structures. However, due to the high refractive index and strong UV absorption characteristics of Pb-based ceramics, ceramic slurries are required to have a low solid content in for efficient deep-curing. This limitation often results in sintering distortion, cracking, low density, and deteriorated piezoelectric properties. To address these challenges, a heat treatment process was initially employed to spheroidize the PZT powder, which effectively decreased light scattering and absorption. Subsequently, high-refractive-index and highly reactive photosensitive resins were introduced to enhance the penetration of UV light and reduce the critical exposure energy of the slurry. Additionally, a hindered amine light stabilizer is added to capture the peroxy radicals to overcome the oxygen inhibition effect and further increase the curing depth. As a result, a PZT slurry with a high solid content of 45 vol.%, was successfully formulated, facilitating the manufacturing of PZT ceramics with complex structures. The sintered samples achieved a high relative density of 96.5% and a d 33 value of 573 pC/N. These optimized strategies provide a solid foundation for the development of high-performance PZT devices with intricate geometries.
通讯机构：
[Chen, Y ] W;Wuhan Polytech Univ, Coll Mech Engn, Wuhan 430048, Hubei, Peoples R China.
关键词：
3D point cloud;Genetic algorithm-based wavelet neural network;Mean absolute percentage error;Poultry viscera;Root mean square error
摘要：
In order to avoid damaging viscera during poultry evisceration and enhance the economic value of poultry products, this paper proposes a predictive method for poultry carcass visceral dimensions based on 3D point cloud and a Genetic Algorithm-based Wavelet Neural Network (GA-WNN). In this study, a data set of poultry carcasses was obtained through the use of 3D point cloud scanning equipment combined with reverse engineering software. The inputs and predicted targets of the model were determined through correlation analysis of various carcass dimensions. Then, a prediction model of poultry visceral size (GA-WNN) was built by K-fold cross validation method, Genetic Algorithm and Wavelet Neural Network (WNN). By comparing the prediction results and analyzing Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) of the six models, it was determined that the GA-WNN model had the best prediction results. Finally, in order to verify the generalizability of the method, generalizability experiments were conducted on different breeds of poultry, which proved that the method of this study had superior generalizability ability. In the comparative analysis of the six models, the MAPE and RMSE of the GA-WNN model for the prediction of the three visceral dimensions were the lowest except for the RMSE for the prediction of visceral length. Compared with the largest of the two kinds of errors, the MAPE and RMSE for the prediction of the position of the upper end of the left liver by the method of this study were lower by 5.56% and 0.915 cm, respectively, and the prediction effect had a significant advantage. The experimental results showed that the model built in this paper based on 3D point cloud and GA-WNN network can accurately predict the size of the viscera of poultry carcasses, thus providing theoretical references for the automated evisceration technology without damaging the viscera.
In order to avoid damaging viscera during poultry evisceration and enhance the economic value of poultry products, this paper proposes a predictive method for poultry carcass visceral dimensions based on 3D point cloud and a Genetic Algorithm-based Wavelet Neural Network (GA-WNN). In this study, a data set of poultry carcasses was obtained through the use of 3D point cloud scanning equipment combined with reverse engineering software. The inputs and predicted targets of the model were determined through correlation analysis of various carcass dimensions. Then, a prediction model of poultry visceral size (GA-WNN) was built by K-fold cross validation method, Genetic Algorithm and Wavelet Neural Network (WNN). By comparing the prediction results and analyzing Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) of the six models, it was determined that the GA-WNN model had the best prediction results. Finally, in order to verify the generalizability of the method, generalizability experiments were conducted on different breeds of poultry, which proved that the method of this study had superior generalizability ability. In the comparative analysis of the six models, the MAPE and RMSE of the GA-WNN model for the prediction of the three visceral dimensions were the lowest except for the RMSE for the prediction of visceral length. Compared with the largest of the two kinds of errors, the MAPE and RMSE for the prediction of the position of the upper end of the left liver by the method of this study were lower by 5.56% and 0.915 cm, respectively, and the prediction effect had a significant advantage. The experimental results showed that the model built in this paper based on 3D point cloud and GA-WNN network can accurately predict the size of the viscera of poultry carcasses, thus providing theoretical references for the automated evisceration technology without damaging the viscera.
作者机构：
[Tahir, Muhammad; Tahir, M; Ahmad, Waheed; Dai, Jun; Dai, J] Beijing Inst Technol, Sch Mechatron Engn, Beijing 100081, Peoples R China.;[Bibi, Batoul] Ghazi Univ, Dept Chem, DG Khan 32200, Pakistan.;[Peng, Zhen; He, L; Xiong, Yibo; Khan, Arif Ullah; He, Liang; Ul Nisa, Fazal; Ma, Zeyu; Naseem, Mizna] Sichuan Univ, Sch Mech Engn, State Key Lab Intelligent Construct & Hlth Operat, Chengdu 610065, Peoples R China.;[Gong, Fengming] Sichuan Univ, West China Hosp 2, Dept Gynecol & Obstet, Dev & Related Dis Women & Children Key Lab Sichuan, Chengdu 610041, Peoples R China.;[Tang, Hui] Univ Elect Sci & Technol China, Sch Mat & Energy, Chengdu 611731, Peoples R China.
通讯机构：
[He, L ] S;[Tahir, M; Dai, J ] B;Beijing Inst Technol, Sch Mechatron Engn, Beijing 100081, Peoples R China.;Sichuan Univ, Sch Mech Engn, State Key Lab Intelligent Construct & Hlth Operat, Chengdu 610065, Peoples R China.
关键词：
Zeolitic imidazolate frameworks;Metal-organic frameworks;Electrochemical gas sensors
摘要：
Zeolitic imidazolate framework-8 (ZIF-8), a subgroup of metal-organic frameworks, has garnered significant focus due to its remarkable structural tunability, chemical stability, and high surface area. These attributes make ZIF-8 and its derivatives desirable materials for drug delivery, catalysis, absorption of different gases, and gas sensing applications. This review comprehensively explains the current advances in the synthesis of ZIF-8 and its derivatives, emphasizing the various approaches, including solvothermal, mechanochemical, sonochemical, and seed-assisted methods, etc. The influence of critical parameters like linkers, solvents, pH, temperature, reaction flow rate, viscosity, interfacial tension, and reaction conditions on the morphology and performance of ZIF-8 is systematically analyzed. Furthermore, it explores the roles of ZIF-8-based materials in electrochemical sensing, highlighting their performance in sensing gases such as CO 2 , NH 3 , H 2 S, volatile organic compounds, NO 2 , and H 2 . The mechanisms behind the sensing capabilities of pure, composite, and hybrid ZIF-8 are explained, emphasizing the structure-property relationship and the development of composites. Challenges such as reproducibility, scalability, and environmental stability are also addressed, alongside prospects for integrating ZIF-8 into next-generation gas sensors. This review provides insight into the synthesis-application nexus, aiming to guide future research towards the rational design of ZIF-8-based gas sensors with improved performance and practical utility.
Zeolitic imidazolate framework-8 (ZIF-8), a subgroup of metal-organic frameworks, has garnered significant focus due to its remarkable structural tunability, chemical stability, and high surface area. These attributes make ZIF-8 and its derivatives desirable materials for drug delivery, catalysis, absorption of different gases, and gas sensing applications. This review comprehensively explains the current advances in the synthesis of ZIF-8 and its derivatives, emphasizing the various approaches, including solvothermal, mechanochemical, sonochemical, and seed-assisted methods, etc. The influence of critical parameters like linkers, solvents, pH, temperature, reaction flow rate, viscosity, interfacial tension, and reaction conditions on the morphology and performance of ZIF-8 is systematically analyzed. Furthermore, it explores the roles of ZIF-8-based materials in electrochemical sensing, highlighting their performance in sensing gases such as CO 2 , NH 3 , H 2 S, volatile organic compounds, NO 2 , and H 2 . The mechanisms behind the sensing capabilities of pure, composite, and hybrid ZIF-8 are explained, emphasizing the structure-property relationship and the development of composites. Challenges such as reproducibility, scalability, and environmental stability are also addressed, alongside prospects for integrating ZIF-8 into next-generation gas sensors. This review provides insight into the synthesis-application nexus, aiming to guide future research towards the rational design of ZIF-8-based gas sensors with improved performance and practical utility.
通讯机构：
[Yang, L ] W;Wuhan Polytech Univ, Coll Mech Engn, Wuhan 430048, Hubei, Peoples R China.
关键词：
Vertical rice mill;Interaction mechanism;Rice;Discrete element method
摘要：
The external milling vertical rice mill (EMVRM) is one of the new rice milling process equipment. The grains moving and interaction mechanism are basic points for milling, rice blade-sand bar spacing H, sieve structure are important structural parameters need considering. The EMVRM 3D model and DEM contact working model are established. The rice blade spacing H and sieve structure effect on grains motion and interaction in is analyzed. Grains motion velocity and density in milling chamber gradually reduced along axial flow direction. The milling chamber grains average motion velocity difference decreases with spacing H increasing. The grain normal and tangential force show down parabolic relation with axial distance from inlet. The sieve direction has little effect on grain motion velocity and force. Normal and tangential force in milling chamber reduced downward along the axial. The research provides practical guidance for EMVRM mill design.
The external milling vertical rice mill (EMVRM) is one of the new rice milling process equipment. The grains moving and interaction mechanism are basic points for milling, rice blade-sand bar spacing H, sieve structure are important structural parameters need considering. The EMVRM 3D model and DEM contact working model are established. The rice blade spacing H and sieve structure effect on grains motion and interaction in is analyzed. Grains motion velocity and density in milling chamber gradually reduced along axial flow direction. The milling chamber grains average motion velocity difference decreases with spacing H increasing. The grain normal and tangential force show down parabolic relation with axial distance from inlet. The sieve direction has little effect on grain motion velocity and force. Normal and tangential force in milling chamber reduced downward along the axial. The research provides practical guidance for EMVRM mill design.
摘要：
Investigations using hot compression tests on a new high-strength weathering steel revealed specific deformation behaviors across different conditions. These tests were performed at temperatures ranging from 850 to 1050°C and at strain rates from 0.01 to 5s(-1). Results indicated that a decrease in the deformation temperature combined with an increase in strain rate notably enhanced both the maximum stress and strain achieved. Notably, above 900°C and with strain rates below 0.1s(-1), the flow stress of the material reached a steady state at certain strain levels. At a strain rate of 1s(-1), irrespective of the temperature, the steel shows a continuous strain hardening behavior, achieving no stable flow stress state. Notably, when the true strain exceeds 0.8, an unusual increase in flow stress occurs, predominantly due to secondary work hardening effects. The microstructural changes in the deformed samples were examined using electron backscatter diffraction (EBSD), which helped elucidate the softening mechanisms inherent in this high-strength steel. Further, processing maps developed from true strains of 0.1-0.9, derived from the experimental flow stress data, suggest controlling the strain within 0.2-0.4 to minimize instability during hot working.
期刊：
Aerospace Science and Technology,2025年:111005 ISSN：1270-9638
通讯作者：
Rao Jun
作者机构：
[Yang Xueli] School of Mechanical Engineering, Wuhan Polytechnic University, Wuhan 430040, Hubei, China;[Song Han; Liu Mingyao; Rao Jun] School of Mechanical and Electrical Engineering, Wuhan University of Technology, Wuhan 430070, Hubei, China
通讯机构：
[Rao Jun] S;School of Mechanical and Electrical Engineering, Wuhan University of Technology, Wuhan 430070, Hubei, China
摘要：
As a core component of aircraft thermal management systems, the plate-fin heat exchanger (PFHE) plays a decisive role in determining the system’s thermal safety limits. Local temperature non-uniformity within PFHEs is a key factor that degrades heat transfer efficiency. To overcome limitations of traditional performance evaluation models and localized thermal monitoring techniques, this study develops a comprehensive evaluation model incorporating non-uniformity parameters and implements a localized temperature monitoring system using fiber Bragg grating (FBG) sensing arrays. Twenty-four compact, vibration-resistant FBG sensors with fast response characteristics were embedded inside the flow channels, facilitating real-time temperature field mapping. Experiments conducted on a customized aviation thermal simulation platform detected significant temperature non-uniformity on both fluid sides, yielding coefficients of variation of 0.130 (cold side) and 0.041 (hot side). The comprehensive model quantitatively demonstrates the degradation mechanism: temperature gradients cause substantial thermal efficiency reductions of 45% and 43% on the cold and hot sides, respectively. This integrated evaluation framework and monitoring methodology offer crucial insights for guiding PFHE geometric optimization and advancing aerospace thermal management strategies.
As a core component of aircraft thermal management systems, the plate-fin heat exchanger (PFHE) plays a decisive role in determining the system’s thermal safety limits. Local temperature non-uniformity within PFHEs is a key factor that degrades heat transfer efficiency. To overcome limitations of traditional performance evaluation models and localized thermal monitoring techniques, this study develops a comprehensive evaluation model incorporating non-uniformity parameters and implements a localized temperature monitoring system using fiber Bragg grating (FBG) sensing arrays. Twenty-four compact, vibration-resistant FBG sensors with fast response characteristics were embedded inside the flow channels, facilitating real-time temperature field mapping. Experiments conducted on a customized aviation thermal simulation platform detected significant temperature non-uniformity on both fluid sides, yielding coefficients of variation of 0.130 (cold side) and 0.041 (hot side). The comprehensive model quantitatively demonstrates the degradation mechanism: temperature gradients cause substantial thermal efficiency reductions of 45% and 43% on the cold and hot sides, respectively. This integrated evaluation framework and monitoring methodology offer crucial insights for guiding PFHE geometric optimization and advancing aerospace thermal management strategies.
摘要：
This study comprehensively investigates the corrosion mechanism of laser-cladded FeCoNiCrCu high-entropy alloy (HEA) coatings fabricated with varying initial powder particle sizes in a 3.5 % NaCl solution. Subsequent to orthogonal experimental optimization, optimal laser cladding parameters were obtained to generate fine coatings with exceptional quality. It's noteworthy that finer initial powder particles possess higher specific surface energy, promoting the formation of coatings with fewer defects. Aside from that, steady increases in corrosion current density and decreases in corrosion potential were observed with coarser initial powder particles, accompanied by lower charge transfer resistance. Corrosion preferentially initiates at surface defects, with more severe defects directly degrading corrosion resistance. The Cu accumulation at these defects generates a less extensively protective passivation film, which hinders the formation of Cr oxides. As evidently demonstrated by XPS analysis, smaller powder particles form protective films with more Cr oxides and fewer Cu oxides in comparison with those formed by larger particles. To sum up, coatings prepared from finer initial powder particle sizes display superior corrosion resistance.
This study comprehensively investigates the corrosion mechanism of laser-cladded FeCoNiCrCu high-entropy alloy (HEA) coatings fabricated with varying initial powder particle sizes in a 3.5 % NaCl solution. Subsequent to orthogonal experimental optimization, optimal laser cladding parameters were obtained to generate fine coatings with exceptional quality. It's noteworthy that finer initial powder particles possess higher specific surface energy, promoting the formation of coatings with fewer defects. Aside from that, steady increases in corrosion current density and decreases in corrosion potential were observed with coarser initial powder particles, accompanied by lower charge transfer resistance. Corrosion preferentially initiates at surface defects, with more severe defects directly degrading corrosion resistance. The Cu accumulation at these defects generates a less extensively protective passivation film, which hinders the formation of Cr oxides. As evidently demonstrated by XPS analysis, smaller powder particles form protective films with more Cr oxides and fewer Cu oxides in comparison with those formed by larger particles. To sum up, coatings prepared from finer initial powder particle sizes display superior corrosion resistance.
摘要：
The granularity effect is a key factor in many experiments, significantly influencing the properties and performance of materials. This study prepared oleogels and hydrogels using beeswax and gelatin as gelators, respectively. The study examined the effects of hydrogel particle size on the performance of the bigels and the influence of storage conditions on hydrogel particle size. The results indicate that the Fourier Transform Infrared Spectroscopy (FTIR) spectral characteristics of the bigels are predominantly governed by the oleogel component. Differential scanning calorimetry (DSC) analysis further revealed that the bigels began to melt at approximately 37 °C, reached a peak endothermic response at 55 °C, and completed melting at 60 °C, exhibiting more complex and broader thermal behavior than the individual components. As the hydrogel particle size within the bigels decreased, hardness increased by 2.20 times, elastic modulus by 2.23 times, and both storage and loss moduli also rose, indicating enhanced elasticity and energy dissipation. Smaller hydrogel particle sizes improved oil retention capacity, with BG5 exhibiting a 15.73 % higher oil retention rate than BG1 under non-freeze-thaw conditions. Freeze-thaw cycles significantly affected hydrogel particle size, with the particle size of BG1 increasing by 38.33 μm and BG5 increasing by only 12.61 μm.
The granularity effect is a key factor in many experiments, significantly influencing the properties and performance of materials. This study prepared oleogels and hydrogels using beeswax and gelatin as gelators, respectively. The study examined the effects of hydrogel particle size on the performance of the bigels and the influence of storage conditions on hydrogel particle size. The results indicate that the Fourier Transform Infrared Spectroscopy (FTIR) spectral characteristics of the bigels are predominantly governed by the oleogel component. Differential scanning calorimetry (DSC) analysis further revealed that the bigels began to melt at approximately 37 °C, reached a peak endothermic response at 55 °C, and completed melting at 60 °C, exhibiting more complex and broader thermal behavior than the individual components. As the hydrogel particle size within the bigels decreased, hardness increased by 2.20 times, elastic modulus by 2.23 times, and both storage and loss moduli also rose, indicating enhanced elasticity and energy dissipation. Smaller hydrogel particle sizes improved oil retention capacity, with BG5 exhibiting a 15.73 % higher oil retention rate than BG1 under non-freeze-thaw conditions. Freeze-thaw cycles significantly affected hydrogel particle size, with the particle size of BG1 increasing by 38.33 μm and BG5 increasing by only 12.61 μm.
摘要：
Beef tallow refining typically employs mild methods to preserve its distinctive flavor. While phospholipase-based enzymatic degumming is well-established in vegetable oils processing for its low-temperature operation, efficiency, and energy economy, its application to animal fats remains scarcely studied. This work systematically investigates phospholipase A1 (PLA1) in beef tallow degumming, employing single-factor and orthogonal experimental designs to optimize process parameters. Degumming efficiency and sensory quality served as dual evaluation metrics. The results indicated that the optimal parameter combination for PLA1 degumming of crude beef tallow was determined to be: 3.0 g/100g water addition, 80 mg/kg enzyme dosage, 50 °C reaction temperature, 210 min processing time, and pH 5.0. Strikingly, PLA1 enzymatic degumming dramatically reduced the oxidation induction time of beef tallow from 5.96 h to merely 0.91 h. A marginal decrease (from 2.61 mg/kg to 1.97 mg/kg) in total tocopherol content was observed. Although the overall fatty acid composition was minimally impacted, the trans fatty acid content was significantly decreased (from 8.44 % to 4.53 %). These findings provide both theoretical and practical guidance for industrial-scale enzymatic degumming of beef tallow, balancing efficiency with quality preservation.
Beef tallow refining typically employs mild methods to preserve its distinctive flavor. While phospholipase-based enzymatic degumming is well-established in vegetable oils processing for its low-temperature operation, efficiency, and energy economy, its application to animal fats remains scarcely studied. This work systematically investigates phospholipase A1 (PLA1) in beef tallow degumming, employing single-factor and orthogonal experimental designs to optimize process parameters. Degumming efficiency and sensory quality served as dual evaluation metrics. The results indicated that the optimal parameter combination for PLA1 degumming of crude beef tallow was determined to be: 3.0 g/100g water addition, 80 mg/kg enzyme dosage, 50 °C reaction temperature, 210 min processing time, and pH 5.0. Strikingly, PLA1 enzymatic degumming dramatically reduced the oxidation induction time of beef tallow from 5.96 h to merely 0.91 h. A marginal decrease (from 2.61 mg/kg to 1.97 mg/kg) in total tocopherol content was observed. Although the overall fatty acid composition was minimally impacted, the trans fatty acid content was significantly decreased (from 8.44 % to 4.53 %). These findings provide both theoretical and practical guidance for industrial-scale enzymatic degumming of beef tallow, balancing efficiency with quality preservation.
摘要：
Fractionation allows the separation of components in beef tallow. This study compared the physicochemical characteristics and cholesterol content of beef tallow and its liquid fraction, evaluating their frying performance as potential deep-fat frying oils against plant oils. Results showed effective separation of unsaturated components from beef tallow through fractionation. Beef tallow exhibited superior physicochemical properties during frying, with lower deterioration levels than plant oils. Benzo[ a ]pyrene content increased in plant oils but remained low in beef tallow and its liquid fraction. The liquid fraction had a significantly shorter oxidative induction time of 0.38 h compared to 5.85 h and 5.24 h for plant oils. This study revealed that alterations were observed in beef tallow and its liquid fraction when used as frying oils, with beef tallow demonstrating stronger antioxidative properties compared to the liquid fraction, which exhibited lower levels of cholesterol and saturated fatty acids.
Fractionation allows the separation of components in beef tallow. This study compared the physicochemical characteristics and cholesterol content of beef tallow and its liquid fraction, evaluating their frying performance as potential deep-fat frying oils against plant oils. Results showed effective separation of unsaturated components from beef tallow through fractionation. Beef tallow exhibited superior physicochemical properties during frying, with lower deterioration levels than plant oils. Benzo[ a ]pyrene content increased in plant oils but remained low in beef tallow and its liquid fraction. The liquid fraction had a significantly shorter oxidative induction time of 0.38 h compared to 5.85 h and 5.24 h for plant oils. This study revealed that alterations were observed in beef tallow and its liquid fraction when used as frying oils, with beef tallow demonstrating stronger antioxidative properties compared to the liquid fraction, which exhibited lower levels of cholesterol and saturated fatty acids.
摘要：
Degumming, a critical process in the edible oil industry, is essential for removing phospholipids. Traditional methods such as water-degumming and acid-degumming have limitations in this regard. This study aimed to assess the efficacy of different degumming techniques, including acid, single and multi-enzyme methods, on rice bran oil (RBO). The investigation also focused on the impact of these techniques on the physicochemical characteristics and preservation of micronutrients in RBO during the degumming process. The primary phospholipids identified were phosphatidylethanolamine (29.51 %), phosphatidylcholine (37.00 %), and phosphatidylinositol (24.49 %). Acid degumming removed 84.23 % of phospholipids, while a significantly higher removal rate of 98.7 % was achieved with the combination of phospholipase A1 & phospholipase C. The degumming process effectively inhibited oxidation in RBO, leading to a substantial increase in the oxidation induction time from 5.7 to 10.0 hours. Furthermore, multi-enzyme degumming showed slightly greater radical-scavenging activity compared to single enzyme degumming in RBO. However, the levels of micronutrients such as phenols, sterols, tocopherols, squalene, and oryzanol were reduced by 6.27–22.17 %. This study provides a comprehensive analysis of the effects of different degumming processes on the physicochemical properties, fatty acid profiles, antioxidant capacities, and preservation of micronutrients in RBO.
Degumming, a critical process in the edible oil industry, is essential for removing phospholipids. Traditional methods such as water-degumming and acid-degumming have limitations in this regard. This study aimed to assess the efficacy of different degumming techniques, including acid, single and multi-enzyme methods, on rice bran oil (RBO). The investigation also focused on the impact of these techniques on the physicochemical characteristics and preservation of micronutrients in RBO during the degumming process. The primary phospholipids identified were phosphatidylethanolamine (29.51 %), phosphatidylcholine (37.00 %), and phosphatidylinositol (24.49 %). Acid degumming removed 84.23 % of phospholipids, while a significantly higher removal rate of 98.7 % was achieved with the combination of phospholipase A1 & phospholipase C. The degumming process effectively inhibited oxidation in RBO, leading to a substantial increase in the oxidation induction time from 5.7 to 10.0 hours. Furthermore, multi-enzyme degumming showed slightly greater radical-scavenging activity compared to single enzyme degumming in RBO. However, the levels of micronutrients such as phenols, sterols, tocopherols, squalene, and oryzanol were reduced by 6.27–22.17 %. This study provides a comprehensive analysis of the effects of different degumming processes on the physicochemical properties, fatty acid profiles, antioxidant capacities, and preservation of micronutrients in RBO.
摘要：
Localized reverse polarity (LRP) in proton exchange membrane fuel cells (PEMFCs) poses a critical degradation challenge by inducing localized redox reactions that compromise catalyst layer integrity and membrane conductivity, yet conventional voltage monitoring fails to detect its concealed electrochemical anomalies in real-time. Given the urgency of PEMFCs in sustainable energy transitions for decarbonizing transportation and stationary power systems, addressing LRP-driven degradation is vital to enhancing durability, efficiency, and safety, thereby reducing lifecycle costs and environmental impacts. While prior durability tests have quantified structural damage (e.g., 55.4 % catalyst layer thinning and 59.4 % platinum agglomeration in LRP-affected regions), no framework currently correlates these degradations with in situ impedance dynamics. This study fills this gap by introducing a non-destructive electrochemical impedance spectroscopy (EIS)-based diagnostic framework that establishes a three-dimensional quantitative model linking ohmic impedance (R ohm ) to LRP characteristics (area, duration, intensity), demonstrating a 92.0 % linear correlation with affected area. The findings enable real-time health monitoring, adaptive operational strategies to mitigate LRP, and actionable engineering insights for catalyst layer and membrane electrode assembly (MEA) optimization, thereby advancing impedance-based diagnostics as a cornerstone for sustainable, long-lived PEMFC systems and bridging the critical link between electrochemical impedance and spatially resolved degradation.
Localized reverse polarity (LRP) in proton exchange membrane fuel cells (PEMFCs) poses a critical degradation challenge by inducing localized redox reactions that compromise catalyst layer integrity and membrane conductivity, yet conventional voltage monitoring fails to detect its concealed electrochemical anomalies in real-time. Given the urgency of PEMFCs in sustainable energy transitions for decarbonizing transportation and stationary power systems, addressing LRP-driven degradation is vital to enhancing durability, efficiency, and safety, thereby reducing lifecycle costs and environmental impacts. While prior durability tests have quantified structural damage (e.g., 55.4 % catalyst layer thinning and 59.4 % platinum agglomeration in LRP-affected regions), no framework currently correlates these degradations with in situ impedance dynamics. This study fills this gap by introducing a non-destructive electrochemical impedance spectroscopy (EIS)-based diagnostic framework that establishes a three-dimensional quantitative model linking ohmic impedance (R ohm ) to LRP characteristics (area, duration, intensity), demonstrating a 92.0 % linear correlation with affected area. The findings enable real-time health monitoring, adaptive operational strategies to mitigate LRP, and actionable engineering insights for catalyst layer and membrane electrode assembly (MEA) optimization, thereby advancing impedance-based diagnostics as a cornerstone for sustainable, long-lived PEMFC systems and bridging the critical link between electrochemical impedance and spatially resolved degradation.
摘要：
Hydrogen generation from the Aluminum-water reaction is a promising technology, offering potential advantages for on-demand hydrogen supply. In this study, the activation of aluminum via high-energy ball milling with Ga, In, Bi2O2, and SnCl2 facilitates hydrogen production. The effect of composition on the hydrolysis behavior of Al-based composites was investigated using a controlled-variable approach. The results show that material composition have a significant effect on the hydrolysis property. Al-based composites exhibit a volcano-type relationship in hydrolysis property, where both hydrogen production yield and reaction rate increase to composition-dependent maxima before decreasing beyond optimal additive composition. In addition, the potential application of hydrogen, produced via the aluminum-water reaction, in PEMFCs was also discussed.
摘要：
As a key component connecting the fuel injection pump and the fuel injector, the engine high - pressure fuel pipe often suffers from problems such as scratches, pit defects, and dimension deviation of the end - head bulge during the production process. However, although traditional manual inspection is simple and convenient, it is slow and not conducive to the needs of information integration and automated production. To address the issue of difficulties in detecting the end - head defects and bulge dimensions of automotive high - pressure fuel pipes, this study developed an end - head defect detection system based on LabVIEW software, which adopts a rectangular rake instead of the traditional linear rake. The LabVIEW graphical programming language was used to construct the control program, and Vision Assistant was used for image processing and analysis. This system can accomplish the detection of scratches and pit defects on the outer surface of the fuel pipe and the measurement of the end - head bulge dimensions. Experimental results indicate that the detection rates of scratches and pits are 97% and 96% respectively. Compared with manual measurement, the dimension measurement of long end - heads and short end - heads saves 86% and 90% of the working time respectively. Compared with traditional edge - point detection, the detection speed of long end - heads and short end - heads has increased by 1.5 times. This provides support and a theoretical basis for the defect detection of automotive high - pressure fuel pipes and the research of relevant systems.
作者机构：
[Yu Zhai; Jianjun Yang; Xiao Rang; Zean Wang; Houchang Pei; Shaoyun Song] College of Mechanical Engineering, Wuhan Polytechnic University, Wuhan, China
会议名称：
2025 5th International Conference on Artificial Intelligence and Industrial Technology Applications (AIITA)
会议时间：
28 March 2025
会议地点：
Xi'an, China
会议论文集名称：
2025 5th International Conference on Artificial Intelligence and Industrial Technology Applications (AIITA)
关键词：
Steel material defects detection;YOLOv7;Attention mechanism;Data enhancement
摘要：
The detection of steel material defects is vital for enhancing product quality, safety, and reliability. However, conventional deep learning approaches, such as YOLOv7 and SSD, suffer from slow detection speed and suboptimal accuracy. To address these issues, we present an enhanced YOLOv7 algorithm for steel defect detection. Our approach optimizes the YOLOv7 model by integrating ResNet Channel Attention Connection modules into the backbone network to improve feature extraction capabilities. Furthermore, a self-Coordinate Attention mechanism is introduced to enhance detection accuracy. Additionally, we modify downsampling using the unfold model to improve the detection of small objects. Experimental results demonstrate the effectiveness of our proposed enhanced YOLOv7 model in accurately identifying steel defects. Compared to the original model, we achieved an 11.4% increase in mean average precision (mAP) and reduced training time by 2.795 hours.
摘要：
VO 2 has gained attention as a promising cathode material owing to its favorable ion diffusion pathways and abundant valence states. However, its performance is hindered by sluggish kinetics from zinc ions, high charge density, and vanadium dissolution induced by reactive water. Herein, Cr, ion doping is utilized to modulate the local electronic structure, enhancing zinc-ion diffusion. Additionally, a carbon-coating strategy is applied to reduce vanadium dissolution from excessive water-VO 2 contact. This dual-modification approach enables VO 2 to achieve exceptional rate capability and capacity retention, demonstrating 70% capacity retention after 1000 cycles at 3 A g −1 . Moreover, Zn 2+ diffusion in VO 2 after the Cr-doping and carbon-coating is significantly improved compared to pure VO 2 . These findings offer new insights into optimizing metal-ion battery cathode materials.
摘要：
The broken rice rate (BR) is a critical metric which influences the appearance, processing, and economic value of rice. However, current machine vision and machine learning approaches engender significant errors when calculating BR. This study introduces a novel restoring method for identifying BR by leveraging grading and morphological features. A three-class classification model using Convolutional Neural Network (CNN) was devised to distinguish broken rice types of crescent head, elliptical tail, and quadrilateral midst based on their morphological characteristics. After training, the accuracy of classfication model is over 98.7%. Taking the longest 10% of rice grains in the image to be identified as head rice references, the broken grains are filtered by calculating the length proportion to the head rice via machine vision. The filtered broken grains are classified to one of three morphological categories with the trained CNN. The broken grains are virtually ‘restored' to head rice equivalents based on the classified shape and the grading size. Finally, the BR is determined by comparing the counts of original and restored grains. The results of two testing conditions which including all and lacking some broken grains demonstrate that the proposed method can accurately and effectively identify the BR in real-time (2.5s).
The broken rice rate (BR) is a critical metric which influences the appearance, processing, and economic value of rice. However, current machine vision and machine learning approaches engender significant errors when calculating BR. This study introduces a novel restoring method for identifying BR by leveraging grading and morphological features. A three-class classification model using Convolutional Neural Network (CNN) was devised to distinguish broken rice types of crescent head, elliptical tail, and quadrilateral midst based on their morphological characteristics. After training, the accuracy of classfication model is over 98.7%. Taking the longest 10% of rice grains in the image to be identified as head rice references, the broken grains are filtered by calculating the length proportion to the head rice via machine vision. The filtered broken grains are classified to one of three morphological categories with the trained CNN. The broken grains are virtually ‘restored' to head rice equivalents based on the classified shape and the grading size. Finally, the BR is determined by comparing the counts of original and restored grains. The results of two testing conditions which including all and lacking some broken grains demonstrate that the proposed method can accurately and effectively identify the BR in real-time (2.5s).
