In phenomenological models,diffusivity is at least a function of composition and the diffusivities at infinite dilution.An additional parameter(?),which can be determined by diffusivity in midpoint,are specially broug...In phenomenological models,diffusivity is at least a function of composition and the diffusivities at infinite dilution.An additional parameter(?),which can be determined by diffusivity in midpoint,are specially brought forward as token of fractional friction related with the interactions of same molecules in this paper,to extrapolate a new correlative equation for the mutual Maxwell-Stefan diffusivities.Furthermore,the correlative equation can be extended to calculate diffusivities in multicomponent mixtures based on binary data alone.The theoretical calculations are evaluated with published experimental data.The M-S diffusivities in a three-component liquid system are regarded as binary coefficients,the predictive results also agree with the experimental data.Results indicate that the model with additional coefficients is superior to currently used Darken methods,especially for systems of polar organic-water and those containing associative component.展开更多
In the present work, the mass transfer characteristics, namely moisture diffusivity and moisture transfer coefficient of “Violet de Galmi” variety of onions were evaluated using the analytical model. Onions were dri...In the present work, the mass transfer characteristics, namely moisture diffusivity and moisture transfer coefficient of “Violet de Galmi” variety of onions were evaluated using the analytical model. Onions were dried in a single layer at different temperatures (40℃, 50℃, 60℃, and 70℃) and for a relative humidity of drying air of 20%. The results showed a reasonably good agreement between the values predicted by the correlation and the experimental observations. This model computed the Biot number, effective moisture diffusivity, and mass transfer coefficient. Effective diffusion coefficient values are obtained between 0.2578 × 10<sup>-9</sup> m<sup>2</sup>·s<sup>-1</sup> and 0.5460 × 10<sup>-9</sup> m<sup>2</sup>·s<sup>-1</sup>. Mass transfer coefficients of “Violet de Galmi” onion drying vary between 3.37 × 10<sup>-7</sup> m·s<sup>-1</sup> and 13.38 × 10<sup>-7</sup> m·s<sup>-1</sup>. Numbers of mass transfer Biot are found between 0.9797 and 2.9397. The activation energy E<sub>a</sub> is 31.73 kJ·mol<sup>-1</sup>.展开更多
Cerebral small vessel disease encompasses a group of neurological disorders characterized by injury to small blood vessels,often leading to stroke and dementia.Due to its diverse etiologies and complex pathological me...Cerebral small vessel disease encompasses a group of neurological disorders characterized by injury to small blood vessels,often leading to stroke and dementia.Due to its diverse etiologies and complex pathological mechanisms,preventing and treating cerebral small vessel vasculopathy is challenging.Recent studies have shown that the glymphatic system plays a crucial role in interstitial solute clearance and the maintenance of brain homeostasis.Increasing evidence also suggests that dysfunction in glymphatic clearance is a key factor in the progression of cerebral small vessel disease.This review begins with a comprehensive introduction to the structure,function,and driving factors of the glymphatic system,highlighting its essential role in brain waste clearance.Afterwards,cerebral small vessel disease was reviewed from the perspective of the glymphatic system,after which the mechanisms underlying their correlation were summarized.Glymphatic dysfunction may lead to the accumulation of metabolic waste in the brain,thereby exacerbating the pathological processes associated with cerebral small vessel disease.The review also discussed the direct evidence of glymphatic dysfunction in patients and animal models exhibiting two subtypes of cerebral small vessel disease:arteriolosclerosis-related cerebral small vessel disease and amyloid-related cerebral small vessel disease.Diffusion tensor image analysis along the perivascular space is an important non-invasive tool for assessing the clearance function of the glymphatic system.However,the effectiveness of its parameters needs to be enhanced.Among various nervous system diseases,including cerebral small vessel disease,glymphatic failure may be a common final pathway toward dementia.Overall,this review summarizes prevention and treatment strategies that target glymphatic drainage and will offer valuable insight for developing novel treatments for cerebral small vessel disease.展开更多
The fast solution of linear equations has always been one of the hot spots in scientific computing.A kind of the diagonal matrix splitting iteration methods are provided,which is different from the classical matrix sp...The fast solution of linear equations has always been one of the hot spots in scientific computing.A kind of the diagonal matrix splitting iteration methods are provided,which is different from the classical matrix splitting methods.Taking the decomposition of the diagonal elements for coefficient matrix as the key point,some new preconditioners are constructed.Taking the tri-diagonal coefficient matrix as an example,the convergence domains and optimal relaxation factor of the new method are analyzed theoretically.The presented new iteration methods are applied to solve linear algebraic equations,even 2D and 3D diffusion problems with the fully implicit discretization.The results of numerical experiments are matched with the theoretical analysis,and show that the iteration numbers are reduced greatly.The superiorities of presented iteration methods exceed some classical iteration methods dramatically.展开更多
结合武汉市江岸区新直街社区规划实践,探索人工智能生成内容技术的文本生成和图像生成等模型在社区规划前、中期工作环节中的具体运用方法,并考察其对于效率创意和公平正义的促进情况。在“语言交流”环节,采用“Qwen+Ollama Web UI+本...结合武汉市江岸区新直街社区规划实践,探索人工智能生成内容技术的文本生成和图像生成等模型在社区规划前、中期工作环节中的具体运用方法,并考察其对于效率创意和公平正义的促进情况。在“语言交流”环节,采用“Qwen+Ollama Web UI+本地专属知识库”的文本生成模型及运行框架,辅助规划设计师回复居民对话、提炼议题观点和实时分析语言情感倾向,促进规划共识达成。在“语言—方案转译”环节,基于“Stable Diffusion—Comfy UI”的图像生成模型及运行界面构建“激发设计灵感”和“优化底图照片”两个工作流,前者将规划共识转化为AI模型理解的提示词语言和相应的空间化参考方案,为设计者提供灵感创意,实现文本生成与图像生成两类模型之间的耦合;后者清理现状照片中前景遮挡要素以形成设计底图。在“方案设计”环节,根据不同居民的设计习惯,搭建“涂抹蒙版改绘”和“涂鸦线条改绘”两类基于现状照片的局部改绘工作流,快速生成具象草图方案。人工智能生成内容技术为社区规划的公众参与工作提供了全新思路和方案,同时该技术的运用需要突破传统的工具主义观念,不断致力于“技术赋权”而非“技术减权”。展开更多
Hard carbon(HC)in sodium-ion batteries is searched by numerous investigations,which can offer the excellent performance of reversible Na^(+)insertion and extraction.The covalent heteroatom doping in HC is recently wor...Hard carbon(HC)in sodium-ion batteries is searched by numerous investigations,which can offer the excellent performance of reversible Na^(+)insertion and extraction.The covalent heteroatom doping in HC is recently worth concentrating,which can dilate the interlayer spacing of graphite to adjust the electrochemical storage performance in carbon anodes.However,the reported doping strategies of the modified HC have only resulted in limited improvement,especially unobvious effects on tuning porous structure.In this study,tannin extract and K_(2)SO_(4) are respectively utilized as carbon source and sulfur source for the fabrication of HC,in which K_(2)SO_(4) can contribute to the heteroatom doping,and the pore forming as well.The tannin-derived sulfur-doped carbon anode shows the excellent cycle stability,achieving a high reversible capacity of 520.5 mAh/g at a current density of 100 mA/g.Even after 500 cycles at a current density of 3 A/g,a high specific capacity of 236.7 mAh/g and a capacity retention rate of 92.6%can be reserved.Compared with the initial carbon,the adsorption energy of Na^(+)is multifold times higher,whereas Na^(+)diffusion energy barriers manyfold decrease.Moreover,the full battery assembled with Na_(3)V_(2)(PO_(4))_(3)/tannin-based HC demonstrates a stable cycling performance.This work can manifest the potentiality of the tannin-based electrode as anode for a high-performance sodium-ion batteries(SIBs),which could especially offer an explanation of Na^(+)storage and solid-electrolyte interface(SEI)stability to the electrochemical performance.展开更多
Fine-grained nuclear graphite is a key material in high-temperature gas-cooled reactors(HTGRs).During air ingress accidents,core graphite components undergo severe oxidation,threatening structural integrity.Therefore,...Fine-grained nuclear graphite is a key material in high-temperature gas-cooled reactors(HTGRs).During air ingress accidents,core graphite components undergo severe oxidation,threatening structural integrity.Therefore,understanding the oxidation behavior of nuclear graphite is essential for reactor safety.The influence of oxidation involves multiple factors,including temperature,sample size,oxidant,impurities,filler type and size,etc.The size of the filler particles plays a crucial role in this study.Five ultrafine-and superfine-grained nuclear graphite samples(5.9-34.4μm)are manufactured using identical raw materials and manufacturing processes.Isothermal oxidation tests conducted at 650℃-750℃ are used to study the oxidation behavior.Additionally,comprehensive characterization is performed to analyze the crystal structure,surface morphology,and nanoscale to microscale pore structure of the samples.Results indicate that oxidation behavior cannot be predicted solely based on filler grain size.Reactive site concentration,characterized by active surface area,dominates the chemical reaction kinetics,whereas pore tortuosity,quantified by the structural parameterΨ,plays a key role in regulating oxidant diffusion.These findings clarify the dual role of microstructure in oxidation mechanisms and establish a theoretical and experimental basis for the design of high-performance nuclear graphite capable of long-term service in high-temperature gas-cooled reactors.展开更多
With the rapid development of generative artificial intelligence(GenAI),the task of story visualization,which transforms natural language narratives into coherent and consistent image sequences,has attracted growing r...With the rapid development of generative artificial intelligence(GenAI),the task of story visualization,which transforms natural language narratives into coherent and consistent image sequences,has attracted growing research attention.However,existing methods still face limitations in balancing multi-frame character consistency and generation efficiency,which restricts their feasibility for large-scale practical applications.To address this issue,this study proposes a modular cloud-based distributed system built on Stable Diffusion.By separating the character generation and story generation processes,and integratingmulti-feature control techniques,a cachingmechanism,and an asynchronous task queue architecture,the system enhances generation efficiency and scalability.The experimental design includes both automated and human evaluations of character consistency,performance testing,and multinode simulation.The results show that the proposed system outperforms the baseline model StoryGen in both CLIP-I and human evaluation metrics.In terms of performance,under the experimental environment of this study,dual-node deployment reduces average waiting time by approximately 19%,while the four-node simulation further reduces it by up to 65%.Overall,this study demonstrates the advantages of cloud-distributed GenAI in maintaining character consistency and reducing generation latency,highlighting its potential value inmulti-user collaborative story visualization applications.展开更多
Scalable simulation leveraging real-world data plays an essential role in advancing autonomous driving,owing to its efficiency and applicability in both training and evaluating algorithms.Consequently,there has been i...Scalable simulation leveraging real-world data plays an essential role in advancing autonomous driving,owing to its efficiency and applicability in both training and evaluating algorithms.Consequently,there has been increasing attention on generating highly realistic and consistent driving videos,particularly those involving viewpoint changes guided by the control commands or trajectories of ego vehicles.However,current reconstruction approaches,such as Neural Radiance Fields and 3D Gaussian Splatting,frequently suffer from limited generalization and depend on substantial input data.Meanwhile,2D generative models,though capable of producing unknown scenes,still have room for improvement in terms of coherence and visual realism.To overcome these challenges,we introduce GenScene,a world model that synthesizes front-view driving videos conditioned on trajectories.A new temporal module is presented to improve video consistency by extracting the global context of each frame,calculating relationships of frames using these global representations,and fusing frame contexts accordingly.Moreover,we propose an innovative attention mechanism that computes relations of pixels within each frame and pixels in the corresponding window range of the initial frame.Extensive experiments show that our approach surpasses various state-of-the-art models in driving video generation,and the introduced modules contribute significantly to model performance.This work establishes a new paradigm for goal-oriented video synthesis in autonomous driving,which facilitates on-demand simulation to expedite algorithm development.展开更多
High-voltage Li-rich Mn-based oxide(LRMO)cathodes are promising for breaking through the energy density limits of lithium-ion batteries,yet their practical application remains limited by electrochemical performance de...High-voltage Li-rich Mn-based oxide(LRMO)cathodes are promising for breaking through the energy density limits of lithium-ion batteries,yet their practical application remains limited by electrochemical performance degradation caused by unstable cathode-electrolyte interphase(CEI)evolution during longterm cycling.To address this issue,we propose a novel surface modification strategy using La_(0.7)Sr_(0.3)MnO_(3-σ)(LSMO)nanodots,which exhibit high electronic co nductivity and excellent corrosion resistance.These nanodots act as stable anchoring sites,facilitating the formation of a robust CEI on LRMO,The LSMOmodified cathode demonstrates significantly improved anionic redox reversibility,effectively mitigating transition metal migration and lattice oxygen loss.Furthermore,the optimized interfacial electrochemical kinetics ensure sustained rapid Li+diffusion throughout cycling,while the formation of a stable trilayer CEI structure suppresses electrolyte decomposition.Benefiting from these synergistic effects,the LSMO nanodot-engineered LRMO cathode delivers outstanding cycling stability,retaining 97.4%capacity after 300 cycles at 1 C.This work not only highlights the critical role of nanodot heterostructures in stabilizing CEI but also provides a new approach to designing high-voltage cathodes with superior interfacial compatibility and long-term durability.展开更多
Reaction-diffusion systems are widely used to describe pattern formation,and various control strategies have been applied to reaction-diffusion systems to achieve control objectives such as boundary control,output fee...Reaction-diffusion systems are widely used to describe pattern formation,and various control strategies have been applied to reaction-diffusion systems to achieve control objectives such as boundary control,output feedback stabilization,and synchronization.However,controlling pattern dynamics in reaction-diffusion systems with fractional-order diffusion remains an unresolved problem.This paper presents a proportional-derivative(PD)control strategy for the Schnakenberg system with fractional-order diffusion and cross-diffusion.Theoretical analysis explores the amplitude equation near the Turing bifurcation threshold,determining the selection and stability of pattern formations.Numerical simulations demonstrate that the PD controller accomplishes the modification of pattern structures and suppression of Turing instability by adjusting only two control parameters.Additionally,it is found that for smaller fractional diffusion order,the region can accommodate more hexagonal and stripe patterns in space.This work contributes to the control of complex pattern dynamics and offers a new approach to enhancing stability in fractional reaction-diffusion systems.展开更多
In this paper,we are concerned with the stability of traveling wavefronts of a Belousov-Zhabotinsky model with mixed nonlocal and degenerate diffusions.Such a system can be used to study the competition among nonlocal...In this paper,we are concerned with the stability of traveling wavefronts of a Belousov-Zhabotinsky model with mixed nonlocal and degenerate diffusions.Such a system can be used to study the competition among nonlocally diffusive species and degenerately diffusive species.We prove that the traveling wavefronts are exponentially stable,when the initial perturbation around the traveling waves decays exponentially as x→-∞,but in other locations,the initial data can be arbitrarily large.The adopted methods are the weighted energy with the comparison principle and squeezing technique.展开更多
Microseismic(MS)monitoring is an effective technique to detect mining-induced rock fractures.However,recognizing grouting-induced signals is challenging due to complex geological conditions in deep rock plates.Therefo...Microseismic(MS)monitoring is an effective technique to detect mining-induced rock fractures.However,recognizing grouting-induced signals is challenging due to complex geological conditions in deep rock plates.Therefore,a hybrid model(WM-ResNet50)integrating data enhancement,a deep convolutional neural network(CNN),and convolutional block attention modules(CBAM)was proposed.Firstly,an MS system was established at the Xieqiao coal mine in Anhui Province,China.MS waveforms and injection parameters were acquired during grouting.Secondly,signals were categorized based on time-frequency characteristics to build a dataset,which was divided into training,validation,and test sets at a ratio of 4:1:1.Subsequently,the performance of WM-ResNet50 was evaluated based on indices such as individual precision,total accuracy,recall,and loss function.The results indicated that WMResNet50 achieved an average recognition accuracy of 94.38%,surpassing that of a simple CNN(90.04%),ResNet18(91.72%),and ResNet50(92.48%).Finally,WM-ResNet50 was applied to monitor the whole process at laboratory tests and field cases.Both results affirmed the feasibility and effectiveness of MS inversion in predicting actual slurry diffusion ranges within deep rock layers.By comparison,it was revealed that the MS sources classified by WM-ResNet50 matched grouting records well.A solution to address insufficient diffusion under long-borehole grouting has been proposed.WM-ResNet50′s accuracy was validated through in-situ coring and XRD analysis for cement-based hydration products.This study provides a beneficial reference for similar rock signal processing and in-field grouting practices.展开更多
Injecting impure CO_(2)for enhanced gas recovery(CO_(2)-EGR)offers a dual benefit by improving natural gas extraction while enabling CO_(2)sequestration.However,the interactions between CO_(2),N_(2),and CH_(4)under re...Injecting impure CO_(2)for enhanced gas recovery(CO_(2)-EGR)offers a dual benefit by improving natural gas extraction while enabling CO_(2)sequestration.However,the interactions between CO_(2),N_(2),and CH_(4)under reservoir conditions require further investigation.This study employs Grand Canonical Monte Carlo(GCMC)and Molecular Dynamics(MD)simulations to quantify the adsorption and diffusion behaviors of CO_(2),N_(2),and CH_(4)in quartz nanopores over a pressure range of 1-24 MPa under varying water saturations and gas compositions.The results indicate that:(1)CO_(2)exhibits the broadest energy distribution and the strongest adsorption stability,occupying about 20%-30%more adsorption sites than CH_(4)or N_(2)and showing the least sensitivity to water saturation,with only a 30%reduction at 50%saturation,compared to 60%for CH_(4),giving CO_(2)a clear competitive advantage.(2)The adsorption and desorption behaviors are strongly pressure dependent,as increasing pressure reduces the adsorption layer area and shifts gas distribution from adsorption dominated to free phase.Competitive adsorption analysis reveals that while CO_(2)dominates displacement at low pressures,mixtures that contain N_(2)achieve higher CH_(4)desorption efficiency above 13 MPa by mitigating diffusion resistance.(3)A higher N_(2)fraction improves CH_(4)diffusion coefficients,thereby facilitating gas mobility and ensuring superior recovery performance under high-pressure conditions.This study advances the fundamental knowledge of microscale gas behavior in tight sandstones and supports the feasibility of impure CO_(2)injection as a practical strategy for sustainable gas production.展开更多
This research explores the influence of crystallinity on gas chromatographic(GC) separation using covalent organic frameworks(COFs) as stationary phases.Three COF materials(CTF-DCBs) with varying crystallinity were sy...This research explores the influence of crystallinity on gas chromatographic(GC) separation using covalent organic frameworks(COFs) as stationary phases.Three COF materials(CTF-DCBs) with varying crystallinity were synthesized and characterized.CTF-DCB-1,with superior crystallinity,demonstrated highselectivity GC separation of benzene isomers as well as styrene/phenylacetylene mixtures,while CTFDCB-2 and CTF-DCB-3 exhibited lower crystallinity and worse separation performance.Thermodynamic and kinetic tests showed that CTF-DCB-1 had the worst thermodynamic adsorption but low diffusion mass transfer resistance,which resulted in the best separation.Therefore,optimizing the crystallinity of COFs is necessary for balancing the kinetic diffusion and thermodynamic interactions towards the analytes,achieving high-performance GC stationary phases.展开更多
文摘In phenomenological models,diffusivity is at least a function of composition and the diffusivities at infinite dilution.An additional parameter(?),which can be determined by diffusivity in midpoint,are specially brought forward as token of fractional friction related with the interactions of same molecules in this paper,to extrapolate a new correlative equation for the mutual Maxwell-Stefan diffusivities.Furthermore,the correlative equation can be extended to calculate diffusivities in multicomponent mixtures based on binary data alone.The theoretical calculations are evaluated with published experimental data.The M-S diffusivities in a three-component liquid system are regarded as binary coefficients,the predictive results also agree with the experimental data.Results indicate that the model with additional coefficients is superior to currently used Darken methods,especially for systems of polar organic-water and those containing associative component.
文摘In the present work, the mass transfer characteristics, namely moisture diffusivity and moisture transfer coefficient of “Violet de Galmi” variety of onions were evaluated using the analytical model. Onions were dried in a single layer at different temperatures (40℃, 50℃, 60℃, and 70℃) and for a relative humidity of drying air of 20%. The results showed a reasonably good agreement between the values predicted by the correlation and the experimental observations. This model computed the Biot number, effective moisture diffusivity, and mass transfer coefficient. Effective diffusion coefficient values are obtained between 0.2578 × 10<sup>-9</sup> m<sup>2</sup>·s<sup>-1</sup> and 0.5460 × 10<sup>-9</sup> m<sup>2</sup>·s<sup>-1</sup>. Mass transfer coefficients of “Violet de Galmi” onion drying vary between 3.37 × 10<sup>-7</sup> m·s<sup>-1</sup> and 13.38 × 10<sup>-7</sup> m·s<sup>-1</sup>. Numbers of mass transfer Biot are found between 0.9797 and 2.9397. The activation energy E<sub>a</sub> is 31.73 kJ·mol<sup>-1</sup>.
基金supported by the National Natural Science Foundation of China,No.82274304(to YH)the Major Clinical Study Projects of Shanghai Shenkang Hospital Development Center,No.SHDC2020CR2046B(to YH)Shanghai Municipal Health Commission Talent Plan,No.2022LJ010(to YH).
文摘Cerebral small vessel disease encompasses a group of neurological disorders characterized by injury to small blood vessels,often leading to stroke and dementia.Due to its diverse etiologies and complex pathological mechanisms,preventing and treating cerebral small vessel vasculopathy is challenging.Recent studies have shown that the glymphatic system plays a crucial role in interstitial solute clearance and the maintenance of brain homeostasis.Increasing evidence also suggests that dysfunction in glymphatic clearance is a key factor in the progression of cerebral small vessel disease.This review begins with a comprehensive introduction to the structure,function,and driving factors of the glymphatic system,highlighting its essential role in brain waste clearance.Afterwards,cerebral small vessel disease was reviewed from the perspective of the glymphatic system,after which the mechanisms underlying their correlation were summarized.Glymphatic dysfunction may lead to the accumulation of metabolic waste in the brain,thereby exacerbating the pathological processes associated with cerebral small vessel disease.The review also discussed the direct evidence of glymphatic dysfunction in patients and animal models exhibiting two subtypes of cerebral small vessel disease:arteriolosclerosis-related cerebral small vessel disease and amyloid-related cerebral small vessel disease.Diffusion tensor image analysis along the perivascular space is an important non-invasive tool for assessing the clearance function of the glymphatic system.However,the effectiveness of its parameters needs to be enhanced.Among various nervous system diseases,including cerebral small vessel disease,glymphatic failure may be a common final pathway toward dementia.Overall,this review summarizes prevention and treatment strategies that target glymphatic drainage and will offer valuable insight for developing novel treatments for cerebral small vessel disease.
基金The National Natural Science Foundations of China (12202219)the Natural Science Foundations of Ningxia (2024AAC02009, 2023AAC05001)the Ningxia Youth Top Talents Training Project。
文摘The fast solution of linear equations has always been one of the hot spots in scientific computing.A kind of the diagonal matrix splitting iteration methods are provided,which is different from the classical matrix splitting methods.Taking the decomposition of the diagonal elements for coefficient matrix as the key point,some new preconditioners are constructed.Taking the tri-diagonal coefficient matrix as an example,the convergence domains and optimal relaxation factor of the new method are analyzed theoretically.The presented new iteration methods are applied to solve linear algebraic equations,even 2D and 3D diffusion problems with the fully implicit discretization.The results of numerical experiments are matched with the theoretical analysis,and show that the iteration numbers are reduced greatly.The superiorities of presented iteration methods exceed some classical iteration methods dramatically.
文摘结合武汉市江岸区新直街社区规划实践,探索人工智能生成内容技术的文本生成和图像生成等模型在社区规划前、中期工作环节中的具体运用方法,并考察其对于效率创意和公平正义的促进情况。在“语言交流”环节,采用“Qwen+Ollama Web UI+本地专属知识库”的文本生成模型及运行框架,辅助规划设计师回复居民对话、提炼议题观点和实时分析语言情感倾向,促进规划共识达成。在“语言—方案转译”环节,基于“Stable Diffusion—Comfy UI”的图像生成模型及运行界面构建“激发设计灵感”和“优化底图照片”两个工作流,前者将规划共识转化为AI模型理解的提示词语言和相应的空间化参考方案,为设计者提供灵感创意,实现文本生成与图像生成两类模型之间的耦合;后者清理现状照片中前景遮挡要素以形成设计底图。在“方案设计”环节,根据不同居民的设计习惯,搭建“涂抹蒙版改绘”和“涂鸦线条改绘”两类基于现状照片的局部改绘工作流,快速生成具象草图方案。人工智能生成内容技术为社区规划的公众参与工作提供了全新思路和方案,同时该技术的运用需要突破传统的工具主义观念,不断致力于“技术赋权”而非“技术减权”。
基金supported by National Natural Science Foundation of China(Nos.32271791,32171709 and 22475053)Hunan Provincial Natural Science Foundation of China(No.2024JJ7643)Natural Science Foundation of Shanghai(No.22ZR1404100).
文摘Hard carbon(HC)in sodium-ion batteries is searched by numerous investigations,which can offer the excellent performance of reversible Na^(+)insertion and extraction.The covalent heteroatom doping in HC is recently worth concentrating,which can dilate the interlayer spacing of graphite to adjust the electrochemical storage performance in carbon anodes.However,the reported doping strategies of the modified HC have only resulted in limited improvement,especially unobvious effects on tuning porous structure.In this study,tannin extract and K_(2)SO_(4) are respectively utilized as carbon source and sulfur source for the fabrication of HC,in which K_(2)SO_(4) can contribute to the heteroatom doping,and the pore forming as well.The tannin-derived sulfur-doped carbon anode shows the excellent cycle stability,achieving a high reversible capacity of 520.5 mAh/g at a current density of 100 mA/g.Even after 500 cycles at a current density of 3 A/g,a high specific capacity of 236.7 mAh/g and a capacity retention rate of 92.6%can be reserved.Compared with the initial carbon,the adsorption energy of Na^(+)is multifold times higher,whereas Na^(+)diffusion energy barriers manyfold decrease.Moreover,the full battery assembled with Na_(3)V_(2)(PO_(4))_(3)/tannin-based HC demonstrates a stable cycling performance.This work can manifest the potentiality of the tannin-based electrode as anode for a high-performance sodium-ion batteries(SIBs),which could especially offer an explanation of Na^(+)storage and solid-electrolyte interface(SEI)stability to the electrochemical performance.
基金supported by the National Key Research and Development Program of China(2024YFA1612900)the National Natural Science Foundation of China(Grant No.52103365 and No.12375270)the Guangdong Innovative and Entrepreneurial Research Team Program,China(Grant No.2021ZT09L227).
文摘Fine-grained nuclear graphite is a key material in high-temperature gas-cooled reactors(HTGRs).During air ingress accidents,core graphite components undergo severe oxidation,threatening structural integrity.Therefore,understanding the oxidation behavior of nuclear graphite is essential for reactor safety.The influence of oxidation involves multiple factors,including temperature,sample size,oxidant,impurities,filler type and size,etc.The size of the filler particles plays a crucial role in this study.Five ultrafine-and superfine-grained nuclear graphite samples(5.9-34.4μm)are manufactured using identical raw materials and manufacturing processes.Isothermal oxidation tests conducted at 650℃-750℃ are used to study the oxidation behavior.Additionally,comprehensive characterization is performed to analyze the crystal structure,surface morphology,and nanoscale to microscale pore structure of the samples.Results indicate that oxidation behavior cannot be predicted solely based on filler grain size.Reactive site concentration,characterized by active surface area,dominates the chemical reaction kinetics,whereas pore tortuosity,quantified by the structural parameterΨ,plays a key role in regulating oxidant diffusion.These findings clarify the dual role of microstructure in oxidation mechanisms and establish a theoretical and experimental basis for the design of high-performance nuclear graphite capable of long-term service in high-temperature gas-cooled reactors.
文摘With the rapid development of generative artificial intelligence(GenAI),the task of story visualization,which transforms natural language narratives into coherent and consistent image sequences,has attracted growing research attention.However,existing methods still face limitations in balancing multi-frame character consistency and generation efficiency,which restricts their feasibility for large-scale practical applications.To address this issue,this study proposes a modular cloud-based distributed system built on Stable Diffusion.By separating the character generation and story generation processes,and integratingmulti-feature control techniques,a cachingmechanism,and an asynchronous task queue architecture,the system enhances generation efficiency and scalability.The experimental design includes both automated and human evaluations of character consistency,performance testing,and multinode simulation.The results show that the proposed system outperforms the baseline model StoryGen in both CLIP-I and human evaluation metrics.In terms of performance,under the experimental environment of this study,dual-node deployment reduces average waiting time by approximately 19%,while the four-node simulation further reduces it by up to 65%.Overall,this study demonstrates the advantages of cloud-distributed GenAI in maintaining character consistency and reducing generation latency,highlighting its potential value inmulti-user collaborative story visualization applications.
基金supported by the Cultivation Program for Major Scientific Research Projects of Harbin Institute of Technology(ZDXMPY20180109).
文摘Scalable simulation leveraging real-world data plays an essential role in advancing autonomous driving,owing to its efficiency and applicability in both training and evaluating algorithms.Consequently,there has been increasing attention on generating highly realistic and consistent driving videos,particularly those involving viewpoint changes guided by the control commands or trajectories of ego vehicles.However,current reconstruction approaches,such as Neural Radiance Fields and 3D Gaussian Splatting,frequently suffer from limited generalization and depend on substantial input data.Meanwhile,2D generative models,though capable of producing unknown scenes,still have room for improvement in terms of coherence and visual realism.To overcome these challenges,we introduce GenScene,a world model that synthesizes front-view driving videos conditioned on trajectories.A new temporal module is presented to improve video consistency by extracting the global context of each frame,calculating relationships of frames using these global representations,and fusing frame contexts accordingly.Moreover,we propose an innovative attention mechanism that computes relations of pixels within each frame and pixels in the corresponding window range of the initial frame.Extensive experiments show that our approach surpasses various state-of-the-art models in driving video generation,and the introduced modules contribute significantly to model performance.This work establishes a new paradigm for goal-oriented video synthesis in autonomous driving,which facilitates on-demand simulation to expedite algorithm development.
基金the financial support from the National Key Research and Development Program of China(2023YFB2504000)。
文摘High-voltage Li-rich Mn-based oxide(LRMO)cathodes are promising for breaking through the energy density limits of lithium-ion batteries,yet their practical application remains limited by electrochemical performance degradation caused by unstable cathode-electrolyte interphase(CEI)evolution during longterm cycling.To address this issue,we propose a novel surface modification strategy using La_(0.7)Sr_(0.3)MnO_(3-σ)(LSMO)nanodots,which exhibit high electronic co nductivity and excellent corrosion resistance.These nanodots act as stable anchoring sites,facilitating the formation of a robust CEI on LRMO,The LSMOmodified cathode demonstrates significantly improved anionic redox reversibility,effectively mitigating transition metal migration and lattice oxygen loss.Furthermore,the optimized interfacial electrochemical kinetics ensure sustained rapid Li+diffusion throughout cycling,while the formation of a stable trilayer CEI structure suppresses electrolyte decomposition.Benefiting from these synergistic effects,the LSMO nanodot-engineered LRMO cathode delivers outstanding cycling stability,retaining 97.4%capacity after 300 cycles at 1 C.This work not only highlights the critical role of nanodot heterostructures in stabilizing CEI but also provides a new approach to designing high-voltage cathodes with superior interfacial compatibility and long-term durability.
基金supported by the National Natural Science Foundation of China(62073172)the Natural Science Foundation of Jiangsu Province of China(BK20221329)。
文摘Reaction-diffusion systems are widely used to describe pattern formation,and various control strategies have been applied to reaction-diffusion systems to achieve control objectives such as boundary control,output feedback stabilization,and synchronization.However,controlling pattern dynamics in reaction-diffusion systems with fractional-order diffusion remains an unresolved problem.This paper presents a proportional-derivative(PD)control strategy for the Schnakenberg system with fractional-order diffusion and cross-diffusion.Theoretical analysis explores the amplitude equation near the Turing bifurcation threshold,determining the selection and stability of pattern formations.Numerical simulations demonstrate that the PD controller accomplishes the modification of pattern structures and suppression of Turing instability by adjusting only two control parameters.Additionally,it is found that for smaller fractional diffusion order,the region can accommodate more hexagonal and stripe patterns in space.This work contributes to the control of complex pattern dynamics and offers a new approach to enhancing stability in fractional reaction-diffusion systems.
基金Supported by the National Natural Science Foundation of China(Grant No.12261081).
文摘In this paper,we are concerned with the stability of traveling wavefronts of a Belousov-Zhabotinsky model with mixed nonlocal and degenerate diffusions.Such a system can be used to study the competition among nonlocally diffusive species and degenerately diffusive species.We prove that the traveling wavefronts are exponentially stable,when the initial perturbation around the traveling waves decays exponentially as x→-∞,but in other locations,the initial data can be arbitrarily large.The adopted methods are the weighted energy with the comparison principle and squeezing technique.
基金financial support from the National Natural Science Foundation of China(Nos.52204089,52374082)the Young Elite Scientists Sponsorship Program(No.2023QNRC001)by China Association for Science and Technology(CAST).
文摘Microseismic(MS)monitoring is an effective technique to detect mining-induced rock fractures.However,recognizing grouting-induced signals is challenging due to complex geological conditions in deep rock plates.Therefore,a hybrid model(WM-ResNet50)integrating data enhancement,a deep convolutional neural network(CNN),and convolutional block attention modules(CBAM)was proposed.Firstly,an MS system was established at the Xieqiao coal mine in Anhui Province,China.MS waveforms and injection parameters were acquired during grouting.Secondly,signals were categorized based on time-frequency characteristics to build a dataset,which was divided into training,validation,and test sets at a ratio of 4:1:1.Subsequently,the performance of WM-ResNet50 was evaluated based on indices such as individual precision,total accuracy,recall,and loss function.The results indicated that WMResNet50 achieved an average recognition accuracy of 94.38%,surpassing that of a simple CNN(90.04%),ResNet18(91.72%),and ResNet50(92.48%).Finally,WM-ResNet50 was applied to monitor the whole process at laboratory tests and field cases.Both results affirmed the feasibility and effectiveness of MS inversion in predicting actual slurry diffusion ranges within deep rock layers.By comparison,it was revealed that the MS sources classified by WM-ResNet50 matched grouting records well.A solution to address insufficient diffusion under long-borehole grouting has been proposed.WM-ResNet50′s accuracy was validated through in-situ coring and XRD analysis for cement-based hydration products.This study provides a beneficial reference for similar rock signal processing and in-field grouting practices.
基金supported by the National Natural Science Foundation of China(Grant No.U23A2022)the National Natural Science Foundation of China(Grant No.52474047)+2 种基金the Natural Science Foundation of Chongqing(Grant No.CSTB2024NSCQ-MSX0951)the Natural Science Foundation of Sichuan Province(Grant No.2025ZNSFSC1357)the National Science and Technology Major Project(Grant No.2025ZD1404307).
文摘Injecting impure CO_(2)for enhanced gas recovery(CO_(2)-EGR)offers a dual benefit by improving natural gas extraction while enabling CO_(2)sequestration.However,the interactions between CO_(2),N_(2),and CH_(4)under reservoir conditions require further investigation.This study employs Grand Canonical Monte Carlo(GCMC)and Molecular Dynamics(MD)simulations to quantify the adsorption and diffusion behaviors of CO_(2),N_(2),and CH_(4)in quartz nanopores over a pressure range of 1-24 MPa under varying water saturations and gas compositions.The results indicate that:(1)CO_(2)exhibits the broadest energy distribution and the strongest adsorption stability,occupying about 20%-30%more adsorption sites than CH_(4)or N_(2)and showing the least sensitivity to water saturation,with only a 30%reduction at 50%saturation,compared to 60%for CH_(4),giving CO_(2)a clear competitive advantage.(2)The adsorption and desorption behaviors are strongly pressure dependent,as increasing pressure reduces the adsorption layer area and shifts gas distribution from adsorption dominated to free phase.Competitive adsorption analysis reveals that while CO_(2)dominates displacement at low pressures,mixtures that contain N_(2)achieve higher CH_(4)desorption efficiency above 13 MPa by mitigating diffusion resistance.(3)A higher N_(2)fraction improves CH_(4)diffusion coefficients,thereby facilitating gas mobility and ensuring superior recovery performance under high-pressure conditions.This study advances the fundamental knowledge of microscale gas behavior in tight sandstones and supports the feasibility of impure CO_(2)injection as a practical strategy for sustainable gas production.
基金supported by the National Natural Science Foundation of China (Nos.22174067,22204078,and 22374077)the Natural Science Foundation of Jiangsu Province of China (No.BK20220370)+3 种基金Jiangsu Provincial Department of Education (No.22KJB150009)State Key Laboratory of Analytical Chemistry for Life Science (No.SKLACLS2218)the Priority Academic Program Development of Jiangsu Higher Education Institutions,Jiangsu Association for Science and Technology (No.TJ-2023-076)Shanghai Synchrotron Radiation Facility Beamline BL17B1 (No.2021-NFPSPT-006657)。
文摘This research explores the influence of crystallinity on gas chromatographic(GC) separation using covalent organic frameworks(COFs) as stationary phases.Three COF materials(CTF-DCBs) with varying crystallinity were synthesized and characterized.CTF-DCB-1,with superior crystallinity,demonstrated highselectivity GC separation of benzene isomers as well as styrene/phenylacetylene mixtures,while CTFDCB-2 and CTF-DCB-3 exhibited lower crystallinity and worse separation performance.Thermodynamic and kinetic tests showed that CTF-DCB-1 had the worst thermodynamic adsorption but low diffusion mass transfer resistance,which resulted in the best separation.Therefore,optimizing the crystallinity of COFs is necessary for balancing the kinetic diffusion and thermodynamic interactions towards the analytes,achieving high-performance GC stationary phases.
