Some patients with systemic lupus erythematosus experience neuropsychiatric symptoms.Although magnetic resonance imaging can detect abnormal signals in the white matter of the brain,conventional methods often struggle...Some patients with systemic lupus erythematosus experience neuropsychiatric symptoms.Although magnetic resonance imaging can detect abnormal signals in the white matter of the brain,conventional methods often struggle to accurately capture microstructural changes.Various diffusion models have been used to study white matter in systemic lupus erythematosus;however,comparative analyses of their sensitivity and specificity for detecting microstructural changes remain insufficient.To address this,our team designed a diagnostic trial that used multimodal diffusion imaging techniques to observe white matter microstructural changes in patients with systemic lupus erythematosus who had neuropsychiatric symptoms,with an aim to identify key diagnostic biomarkers for these patients.Patients with active lupus who received treatment at the Department of Rheumatology and Immunology,The First Affiliated Hospital of China Medical University,from September 2023 to March 2024 were recruited.According to the standards of the American College of Rheumatology,patients with systemic lupus erythematosus who had neuropsychiatric symptoms were assigned to the systemic lupus erythematosus group,whereas those without neuropsychiatric symptoms were assigned to the non-systemic lupus erythematosus group.Additionally,healthy volunteers matched by region,sex,and age were recruited as controls.All three groups underwent the same diffusion magnetic resonance imaging examination protocol to compare differences in diffusion parameters.Advanced diffusion imaging models were able to sensitively detect microstructural changes in the white matter fibers of patients with systemic lupus erythematosus who had neuropsychiatric symptoms,with specific diffusion parameters showing significant abnormalities in key brain regions.In the left superior longitudinal fasciculus subregion and the right thalamic radiations of patients with systemic lupus erythematosus who had neuropsychiatric symptoms,we also identified abnormal diffusion characteristics that were clearly correlated with disease activity,suggesting that microstructural changes in these areas may reflect the dynamic process of neuroinflammatory damage.The present study addresses critical challenges in the diagnosis of systemic lupus erythematosus by identifying specific white matter imaging biomarkers and elucidating the association between microstructural damage and clinical manifestations.The main contributions of our study include:1)establishing axial regression probability parameters from mean apparent propagator magnetic resonance imaging as sensitive biomarkers for systemic lupus erythematosus,particularly in the third subregion of the left superior longitudinal fasciculus;2)demonstrating that multimodal diffusion imaging may be superior to conventional diffusion tensor imaging for detecting white matter microstructural abnormalities in patients with systemic lupus erythematosus;and 3)integrating tract-based spatial statistics with clinically relevant analyses to link imaging findings to pathological mechanisms.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
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
Prussian blue analogs(PBAs)have emerged as environmentally friendly and structurally tunable cathode materials for aqueous ammonium-ion batteries(AIBs).However,the fundamental role of crystalline H_(2)O in regulating ...Prussian blue analogs(PBAs)have emerged as environmentally friendly and structurally tunable cathode materials for aqueous ammonium-ion batteries(AIBs).However,the fundamental role of crystalline H_(2)O in regulating ammonium-ion storage and transport remains poorly understood.In this study,we present a comprehensive comparison between hydrated NH_(4)NiHCF-H_(2)O and its anhydrous counterpart NH_(4)NiHCF,revealing the critical contribution of interstitial water to electrochemical performance.Structural and spectroscopic analyses confirm that interstitial water forms robust hydrogen bonds with NH_(4)+ions,stabilizing the PBA framework and mitigating structural degradation during cycling.Electrochemical measurements show that NH_(4)NiHCF-H_(2)O delivers a significantly higher specific capacity of 61 mA h g^(−1)at 0.2 C and markedly improved rate performance compared to NH_(4)NiHCF(48 mA h g^(−1)at 0.2 C).Kinetic analysis reveals that interstitial water enhances NH_(4)+diffusion,as evidenced by higher diffusion coefficients.Furthermore,density functional theory(DFT)calculations demonstrate that crystal water acts as a hydrogen bond acceptor,preferentially interacting with NH_(4)+and reducing the migration energy barrier,thereby facilitating fast ion transport.This work provides fundamental insights into the role of crystal water in PBAs and offers a rational design strategy for improving the kinetics,structural stability of PBAs cathodes for AIBs.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
Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frame...Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.展开更多
Physics-informed neural networks(PINNs),as a novel artificial intelligence method for solving partial differential equations,are applicable to solve both forward and inverse problems.This study evaluates the performan...Physics-informed neural networks(PINNs),as a novel artificial intelligence method for solving partial differential equations,are applicable to solve both forward and inverse problems.This study evaluates the performance of PINNs in solving the temperature diffusion equation of the seawater across six scenarios,including forward and inverse problems under three different boundary conditions.Results demonstrate that PINNs achieved consistently higher accuracy with the Dirichlet and Neumann boundary conditions compared to the Robin boundary condition for both forward and inverse problems.Inaccurate weighting of terms in the loss function can reduce model accuracy.Additionally,the sensitivity of model performance to the positioning of sampling points varied between different boundary conditions.In particular,the model under the Dirichlet boundary condition exhibited superior robustness to variations in point positions during the solutions of inverse problems.In contrast,for the Neumann and Robin boundary conditions,accuracy declines when points were sampled from identical positions or at the same time.Subsequently,the Argo observations were used to reconstruct the vertical diffusion of seawater temperature in the north-central Pacific for the applicability of PINNs in the real ocean.The PINNs successfully captured the vertical diffusion characteristics of seawater temperature,reflected the seasonal changes of vertical temperature under different topographic conditions,and revealed the influence of topography on the temperature diffusion coefficient.The PINNs were proved effective in solving the temperature diffusion equation of seawater with limited data,providing a promising technique for simulating or predicting ocean phenomena using sparse observations.展开更多
The dynamics of phase separation in H–He binary systems within gas giants such as Jupiter and Saturn exhibit remarkable complexity, yet lack systematic investigation. Through large-scale machine-learning-accelerated ...The dynamics of phase separation in H–He binary systems within gas giants such as Jupiter and Saturn exhibit remarkable complexity, yet lack systematic investigation. Through large-scale machine-learning-accelerated molecular dynamics simulations spanning broad temperature-pressure-composition(2000–10000 K, 1–7 Mbar,pure H to pure He) regimes, we systematically determine self and mutual diffusion coefficients in H–He systems and establish a six-dimensional framework correlating temperature, pressure, helium abundance, phase separation degree, diffusion coefficients, and anisotropy. Key findings reveal that hydrogen exhibits active directional migration with pronounced diffusion anisotropy, whereas helium passively aggregates in response. While the conventional mixing rule underestimates mutual diffusion coefficients by neglecting velocity cross-correlations,the assumption of an ideal thermodynamic factor(Q = 1) overestimates them due to unaccounted non-ideal thermodynamic effects—both particularly pronounced in strongly phase-separated regimes. Notably, hydrogen's dual role, anisotropic diffusion and bond stabilization via helium doping, modulates demixing kinetics. Large-scale simulations(216,000 atoms) propose novel phase-separation paradigms, such as “hydrogen bubble/wisp” formation, challenging the classical “helium rain” scenario, striving to bridge atomic-scale dynamics to planetary-scale phase evolution.展开更多
Missing values in radionuclide diffusion datasets can undermine the predictive accuracy and robustness of the machine learning(ML)models.In this study,regression-based missing data imputation method using a light grad...Missing values in radionuclide diffusion datasets can undermine the predictive accuracy and robustness of the machine learning(ML)models.In this study,regression-based missing data imputation method using a light gradient boosting machine(LGBM)algorithm was employed to impute more than 60%of the missing data,establishing a radionuclide diffusion dataset containing 16 input features and 813 instances.The effective diffusion coefficient(D_(e))was predicted using ten ML models.The predictive accuracy of the ensemble meta-models,namely LGBM-extreme gradient boosting(XGB)and LGBM-categorical boosting(CatB),surpassed that of the other ML models,with R^(2)values of 0.94.The models were applied to predict the D_(e)values of EuEDTA^(−)and HCrO_(4)^(−)in saturated compacted bentonites at compactions ranging from 1200 to 1800 kg/m^(3),which were measured using a through-diffusion method.The generalization ability of the LGBM-XGB model surpassed that of LGB-CatB in predicting the D_(e)of HCrO_(4)^(−).Shapley additive explanations identified total porosity as the most significant influencing factor.Additionally,the partial dependence plot analysis technique yielded clearer results in the univariate correlation analysis.This study provides a regression imputation technique to refine radionuclide diffusion datasets,offering deeper insights into analyzing the diffusion mechanism of radionuclides and supporting the safety assessment of the geological disposal of high-level radioactive waste.展开更多
Accurately identifying building distribution from remote sensing images with complex background information is challenging.The emergence of diffusion models has prompted the innovative idea of employing the reverse de...Accurately identifying building distribution from remote sensing images with complex background information is challenging.The emergence of diffusion models has prompted the innovative idea of employing the reverse denoising process to distill building distribution from these complex backgrounds.Building on this concept,we propose a novel framework,building extraction diffusion model(BEDiff),which meticulously refines the extraction of building footprints from remote sensing images in a stepwise fashion.Our approach begins with the design of booster guidance,a mechanism that extracts structural and semantic features from remote sensing images to serve as priors,thereby providing targeted guidance for the diffusion process.Additionally,we introduce a cross-feature fusion module(CFM)that bridges the semantic gap between different types of features,facilitating the integration of the attributes extracted by booster guidance into the diffusion process more effectively.Our proposed BEDiff marks the first application of diffusion models to the task of building extraction.Empirical evidence from extensive experiments on the Beijing building dataset demonstrates the superior performance of BEDiff,affirming its effectiveness and potential for enhancing the accuracy of building extraction in complex urban landscapes.展开更多
A medical image encryption is proposed based on the Fisher-Yates scrambling,filter diffusion and S-box substitution.First,chaotic sequence associated with the plaintext is generated by logistic-sine-cosine system,whic...A medical image encryption is proposed based on the Fisher-Yates scrambling,filter diffusion and S-box substitution.First,chaotic sequence associated with the plaintext is generated by logistic-sine-cosine system,which is used for the scrambling,substitution and diffusion processes.The three-dimensional Fisher-Yates scrambling,S-box substitution and diffusion are employed for the first round of encryption.The chaotic sequence is adopted for secondary encryption to scramble the ciphertext obtained in the first round.Then,three-dimensional filter is applied to diffusion for further useful information hiding.The key to the algorithm is generated by the combination of hash value of plaintext image and the input parameters.It improves resisting ability of plaintext attacks.The security analysis shows that the algorithm is effective and efficient.It can resist common attacks.In addition,the good diffusion effect shows that the scheme can solve the differential attacks encountered in the transmission of medical images and has positive implications for future research.展开更多
The interdiffusion coefficients in Al_(0.2)CoCrFeNi,CoCrCu_(0.2)FeNi,and CoCrFeMn_(0.2)Ni high-entropy alloys were efficiently determined by combining diffusion couple experiments and high-throughput determination of ...The interdiffusion coefficients in Al_(0.2)CoCrFeNi,CoCrCu_(0.2)FeNi,and CoCrFeMn_(0.2)Ni high-entropy alloys were efficiently determined by combining diffusion couple experiments and high-throughput determination of interdiffusion coefficients(HitDIC)software at 1273−1373 K.The results show that the addition of Al,Cu,and Mn to CoCrFeNi high-entropy alloys promotes the diffusion of Co,Cr,and Fe atoms.The comparison of tracer diffusion coefficients indicates that there is no sluggish diffusion in tracer diffusion on the thermodynamic temperature scale for the present Al_(0.2)CoCrFeNi,CoCrCu_(0.2)FeNi,and CoCrFeMn_(0.2)Ni high-entropy alloys.The linear relationship between diffusion entropy and activation energy reveals that the diffusion process of atoms is unaffected by an increase in the number of components as long as the crystal structure remains unchanged.展开更多
The application of generative artificial intelligence(AI)is bringing about notable changes in anime creation.This paper surveys recent advancements and applications of diffusion and language models in anime generation...The application of generative artificial intelligence(AI)is bringing about notable changes in anime creation.This paper surveys recent advancements and applications of diffusion and language models in anime generation,focusing on their demonstrated potential to enhance production efficiency through automation and personalization.Despite these benefits,it is crucial to acknowledge the substantial initial computational investments required for training and deploying these models.We conduct an in-depth survey of cutting-edge generative AI technologies,encompassing models such as Stable Diffusion and GPT,and appraise pivotal large-scale datasets alongside quantifiable evaluation metrics.Review of the surveyed literature indicates the achievement of considerable maturity in the capacity of AI models to synthesize high-quality,aesthetically compelling anime visual images from textual prompts,alongside discernible progress in the generation of coherent narratives.However,achieving perfect long-form consistency,mitigating artifacts like flickering in video sequences,and enabling fine-grained artistic control remain critical ongoing challenges.Building upon these advancements,research efforts have increasingly pivoted towards the synthesis of higher-dimensional content,such as video and three-dimensional assets,with recent studies demonstrating significant progress in this burgeoning field.Nevertheless,formidable challenges endure amidst these advancements.Foremost among these are the substantial computational exigencies requisite for training and deploying these sophisticated models,particularly pronounced in the realm of high-dimensional generation such as video synthesis.Additional persistent hurdles include maintaining spatial-temporal consistency across complex scenes and mitigating ethical considerations surrounding bias and the preservation of human creative autonomy.This research underscores the transformative potential and inherent complexities of AI-driven synergy within the creative industries.We posit that future research should be dedicated to the synergistic fusion of diffusion and autoregressive models,the integration of multimodal inputs,and the balanced consideration of ethical implications,particularly regarding bias and the preservation of human creative autonomy,thereby establishing a robust foundation for the advancement of anime creation and the broader landscape of AI-driven content generation.展开更多
In this study,DyF_(3)powder was sprayed onto the polar and side surfaces of the magnets to determine the anisotropic diffusion mechanism of Dy in the sintered Nd-Fe-B magnet.The coercivity and squareness of the magnet...In this study,DyF_(3)powder was sprayed onto the polar and side surfaces of the magnets to determine the anisotropic diffusion mechanism of Dy in the sintered Nd-Fe-B magnet.The coercivity and squareness of the magnet in which the diffusion of Dy is perpendicular to the c-axis(a-magnet)are lower than those of the magnet with the diffusion of Dy parallel to the c-axis(c-magnet).Compared with the c-magnet,the a-magnet has a longer Dy-enrichment region from the diffusion surface,where Dy is enriched in the 2:14:1 grain.By contrast,the Dy concentration in the grain boundaries beyond the Dy enrichment region is lower in the a-magnet.Moreover,the Dy shells beyond the Dy enrichment region in the a-magnet are distributed on the side surfaces of the 2:14:1 grains but not on the polar surfaces.Based on the micromagnetic simulation,the Dy shells on the polar surfaces of the grains are more effective in enhancing coercivity.According to first-principle calculations,Dy migrating through 001 into the Nd vacancy in the Nd_(2)Fe_(14)B crystal has a higher diffusion barrier,thus indicating that the lattice diffusion of Dy parallel to the c-axis is more difficult.展开更多
Diffusion of solutes significantly affects the coarsening rate of γ'precipitates in precipitation-hardened high entropy alloys(PH-HEAs).In this work,we systematically study the refractory solutes M(Hf,Nb,Ta,Mo,W,...Diffusion of solutes significantly affects the coarsening rate of γ'precipitates in precipitation-hardened high entropy alloys(PH-HEAs).In this work,we systematically study the refractory solutes M(Hf,Nb,Ta,Mo,W,Re,Ru)diffusion in face-centered-cubic(FCC)NiCoFeCr lattice through a combination of first-principles calculations,diffusion couples,and coarsening of γ'precipitates experiments.Our calculations reveal that there exists a stronger negative correlation between solute diffusivity and Young’s modulus than between solute diffusivity and atomic size;i.e.,the higher the Young’s modulus,the more difficult solute diffusion is.Based on the electronic structure analysis,the underlying origins for such a relation-ship could be ascribed to the fact that solutes with high Young’s modulus have stronger bonds with neighboring host atoms,less compressibility,and thus poor diffusivity.Afterwards,the main interdiffu-sion coefficients of three refractory elements with similar atomic sizes and increasing Young’s modulus,Mo,W,and Re,at 1150℃in(NiCoFeCr)_(92)Al_(3)Ti_(3)M_(2)are,in order of magnitude,D_(MoMo)^(Ni)>D_(WW)^(Ni)>D_(ReRe)^(Ni),as determined by the diffusion-couple experiments.Further investigations on the coarsening kinetics of precipitates confirmed the additions of refractory elements improve the coarsening resistance of γ'pre-cipitates in the order of Re>W>Mo.The trends in the diffusivity determined by experiment and simulation are in excellent agreement.More importantly,the Young’s modulus effect for the diffusion of refractory solutes in HEAs is also carefully analyzed and discussed.Our present findings will give new insights into future design of γ'-strengthened HEAs for high-temperature structural applications.展开更多
Rechargeable aqueous zinc-metal batteries (AZMBs) are promising candidates for large-scale energy storage systems due to their low cost and high safety.However,their performance and sustainability are significantly hi...Rechargeable aqueous zinc-metal batteries (AZMBs) are promising candidates for large-scale energy storage systems due to their low cost and high safety.However,their performance and sustainability are significantly hindered by the sluggish desolvation kinetics at the electrode/electrolyte interface and the corresponding hydrogen evolution reaction where active water molecules tightly participate in the Zn(H_(2)O)_(6)^(2+)solvation shell.Herein,learnt from self-generated solid electrolyte interphase (SEI) in anodes,the dielectric but ion-conductive zinc niobate nanoparticles artificial layer is constructed on metallic Zn surface (ZNB@Zn),acting as a rapid desolvation promotor.The zincophilic and dielectric-conductive properties of ZNB layer accelerate interfacial desolvation/diffusion and suppress surface corrosion or dendrite formation,achieving uniform Zn plating/stripping behavior,as confirmed by electronic/optical microscopies and interface spectroscopical measurements together with theoretical calculations.Consequently,the as-prepared ZNB@Zn electrode exhibits excellent cycling stability of over 2000 h and robust reversibility (99.54%) even under high current density and depth of discharge conditions.Meanwhile,the assembled ZNB@Zn-based full cell displays high capacity-retention rate of 80.21%after 3000 cycles at 5 A g^(-1)and outstanding rate performance up to 10 A g^(-1).The large-areal pouch cell is stabilized for hundreds of cycles,highlighting the bright prospects of the dielectric but ion-conductive layer in further application of AZMBs.展开更多
Absorption and desorption processes of hydrogen in metals are facilitated by alloying elements;however,the formation of secondary phases often reduces storage capacity.The alloying effect on the hydrogen kinetics has ...Absorption and desorption processes of hydrogen in metals are facilitated by alloying elements;however,the formation of secondary phases often reduces storage capacity.The alloying effect on the hydrogen kinetics has been examined by time-lag permeation measurement,which lacks spatial resolution and yields the averaged diffusion coefficient from multiple phases.Here,we report an advanced scanning Kelvin probe force microscopy,combined with in-situ hydrogen loading system for submicron-scale measurement of diffusion kinetics in metals.Successive probing of the surface during hydrogen loading detects the temporal and spatial variations in the surface potential,enabling the estimation of diffusion coefficient.Not only for a single-phase magnesium but also for multiphase titaniumiron based alloys,we can obtain the diffusion coefficients of hydrogen in each phase.The estimated diffusion coefficients for TiFe alloys are higher than that for the pristine TiFe intermetallic compound,due to alloying elements that reduce the diffusion barrier and modify bond character.Our approach paves the way to the microscopic understanding of hydrogen diffusion in metals.展开更多
In this paper,we study the eigenvalue problem of the Markov diffusion operator L^(2),and give generalized inequalities for eigenvalues of the operator L^(2)on a Markov diffusion triple.By applying these inequalities,w...In this paper,we study the eigenvalue problem of the Markov diffusion operator L^(2),and give generalized inequalities for eigenvalues of the operator L^(2)on a Markov diffusion triple.By applying these inequalities,we then get some new universal bounds for eigenvalues of a special Markov diffusion operator L^(2)on bounded domains in an Euclidean space.Moreover,our results can reveal the relationship between the(k+1)-th eigenvalue and the first k eigenvalues in a relatively straightforward manner.展开更多
To reveal the complex crude oil-CO_(2) interaction mechanism and oil mobilization behavior during CO_(2) huff-n-puff in shale-type shale oil reservoirs,CO_(2) huff-n-puff experiments with on-line nuclear magnetic reso...To reveal the complex crude oil-CO_(2) interaction mechanism and oil mobilization behavior during CO_(2) huff-n-puff in shale-type shale oil reservoirs,CO_(2) huff-n-puff experiments with on-line nuclear magnetic resonance monitoring were conducted on Gulong shale cores,combined with the prediction model of CO_(2) dynamic diffusion coefficient,the flow mechanism and factors influencing oil mobilization during CO_(2) huff and puff in Gulong shale oil reservoirs are studied,and the diffusion and mass transfer behavior of CO_(2) in shale is investigated.The results show that at the injection stage,CO_(2) invades into macropores near the injection end,and drives part of the crude oil to micropores in the deep part of the core.At the shut-in stage,the crude oil gradually reflows to macropores near the injection end and is redistributed in the core.At the production stage,the oil mobilization zone is gradually expanded from the production end(injection end)to the deep part of the core.The contribution ratio of produced oil from macropores and micropores is about 8︰3 after production.The diffusion coefficient of CO_(2) in shale porous media gradually decreases with the advance of diffusion front at shut-in stage.The better the porosity and permeability of core samples,the higher the CO_(2) concentration at diffusion front,the greater the CO_(2) diffusion coefficient,and the slower the diffusion decline rate is.Increasing the huff and puff cycles could effectively enhance oil displacement efficiency,though its impact on the crude oil mobilization zone remains insignificant.The crude oil in small pores of the small layer with undeveloped laminae is difficult to be produced during CO_(2) huff and puff,and the oil recovery is only 12.72%.The crude oil in macropores and micropores of the small layer with developed laminae can be effectively mobilized during CO_(2) huff and puff,and the oil recovery can reach 39.11%.展开更多
基金supported by the National Natural Science Foundation Joint Fund,No.U22A20309(to PY)the Natural Science Foundation of LiaoningProvince,No.2023-MS-07(to HuL)the Unveiling Key Scientific and Technological Projects of Liaoning Province,No.2021JH1/10400051(to HuL).
文摘Some patients with systemic lupus erythematosus experience neuropsychiatric symptoms.Although magnetic resonance imaging can detect abnormal signals in the white matter of the brain,conventional methods often struggle to accurately capture microstructural changes.Various diffusion models have been used to study white matter in systemic lupus erythematosus;however,comparative analyses of their sensitivity and specificity for detecting microstructural changes remain insufficient.To address this,our team designed a diagnostic trial that used multimodal diffusion imaging techniques to observe white matter microstructural changes in patients with systemic lupus erythematosus who had neuropsychiatric symptoms,with an aim to identify key diagnostic biomarkers for these patients.Patients with active lupus who received treatment at the Department of Rheumatology and Immunology,The First Affiliated Hospital of China Medical University,from September 2023 to March 2024 were recruited.According to the standards of the American College of Rheumatology,patients with systemic lupus erythematosus who had neuropsychiatric symptoms were assigned to the systemic lupus erythematosus group,whereas those without neuropsychiatric symptoms were assigned to the non-systemic lupus erythematosus group.Additionally,healthy volunteers matched by region,sex,and age were recruited as controls.All three groups underwent the same diffusion magnetic resonance imaging examination protocol to compare differences in diffusion parameters.Advanced diffusion imaging models were able to sensitively detect microstructural changes in the white matter fibers of patients with systemic lupus erythematosus who had neuropsychiatric symptoms,with specific diffusion parameters showing significant abnormalities in key brain regions.In the left superior longitudinal fasciculus subregion and the right thalamic radiations of patients with systemic lupus erythematosus who had neuropsychiatric symptoms,we also identified abnormal diffusion characteristics that were clearly correlated with disease activity,suggesting that microstructural changes in these areas may reflect the dynamic process of neuroinflammatory damage.The present study addresses critical challenges in the diagnosis of systemic lupus erythematosus by identifying specific white matter imaging biomarkers and elucidating the association between microstructural damage and clinical manifestations.The main contributions of our study include:1)establishing axial regression probability parameters from mean apparent propagator magnetic resonance imaging as sensitive biomarkers for systemic lupus erythematosus,particularly in the third subregion of the left superior longitudinal fasciculus;2)demonstrating that multimodal diffusion imaging may be superior to conventional diffusion tensor imaging for detecting white matter microstructural abnormalities in patients with systemic lupus erythematosus;and 3)integrating tract-based spatial statistics with clinically relevant analyses to link imaging findings to pathological mechanisms.
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(52172227)the Natural Science Foundation of Hubei Province(2023AFA114)+2 种基金the Guizhou Provincial Key Technology R&D Program(ZD[2025]019)Additional funding was provided by the Startup Fund(20QD80 and 22QD28)The authors also acknowledge support from the Science&Technology Top Talents Program of Guizhou Province([2024]349).We gratefully acknowledge Beijing SciStar Technology Co.,Ltd.for in-situ measurements and analysis.
文摘Prussian blue analogs(PBAs)have emerged as environmentally friendly and structurally tunable cathode materials for aqueous ammonium-ion batteries(AIBs).However,the fundamental role of crystalline H_(2)O in regulating ammonium-ion storage and transport remains poorly understood.In this study,we present a comprehensive comparison between hydrated NH_(4)NiHCF-H_(2)O and its anhydrous counterpart NH_(4)NiHCF,revealing the critical contribution of interstitial water to electrochemical performance.Structural and spectroscopic analyses confirm that interstitial water forms robust hydrogen bonds with NH_(4)+ions,stabilizing the PBA framework and mitigating structural degradation during cycling.Electrochemical measurements show that NH_(4)NiHCF-H_(2)O delivers a significantly higher specific capacity of 61 mA h g^(−1)at 0.2 C and markedly improved rate performance compared to NH_(4)NiHCF(48 mA h g^(−1)at 0.2 C).Kinetic analysis reveals that interstitial water enhances NH_(4)+diffusion,as evidenced by higher diffusion coefficients.Furthermore,density functional theory(DFT)calculations demonstrate that crystal water acts as a hydrogen bond acceptor,preferentially interacting with NH_(4)+and reducing the migration energy barrier,thereby facilitating fast ion transport.This work provides fundamental insights into the role of crystal water in PBAs and offers a rational design strategy for improving the kinetics,structural stability of PBAs cathodes for AIBs.
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supported by the National Natural Science Foundation of China(Grant No.72161034).
文摘Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.
基金Supported by the National Key Research and Development Program of China(No.2023YFC3008200)the Independent Research Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(No.SML2022SP505)。
文摘Physics-informed neural networks(PINNs),as a novel artificial intelligence method for solving partial differential equations,are applicable to solve both forward and inverse problems.This study evaluates the performance of PINNs in solving the temperature diffusion equation of the seawater across six scenarios,including forward and inverse problems under three different boundary conditions.Results demonstrate that PINNs achieved consistently higher accuracy with the Dirichlet and Neumann boundary conditions compared to the Robin boundary condition for both forward and inverse problems.Inaccurate weighting of terms in the loss function can reduce model accuracy.Additionally,the sensitivity of model performance to the positioning of sampling points varied between different boundary conditions.In particular,the model under the Dirichlet boundary condition exhibited superior robustness to variations in point positions during the solutions of inverse problems.In contrast,for the Neumann and Robin boundary conditions,accuracy declines when points were sampled from identical positions or at the same time.Subsequently,the Argo observations were used to reconstruct the vertical diffusion of seawater temperature in the north-central Pacific for the applicability of PINNs in the real ocean.The PINNs successfully captured the vertical diffusion characteristics of seawater temperature,reflected the seasonal changes of vertical temperature under different topographic conditions,and revealed the influence of topography on the temperature diffusion coefficient.The PINNs were proved effective in solving the temperature diffusion equation of seawater with limited data,providing a promising technique for simulating or predicting ocean phenomena using sparse observations.
基金supported by the National University of Defense Technology Research Fund Projectthe National Natural Science Foundation of China under Grant Nos. 12047561 and 12104507+1 种基金the NSAF under Grant No. U1830206the Science and Technology Innovation Program of Hunan Province under Grant No. 2021RC4026。
文摘The dynamics of phase separation in H–He binary systems within gas giants such as Jupiter and Saturn exhibit remarkable complexity, yet lack systematic investigation. Through large-scale machine-learning-accelerated molecular dynamics simulations spanning broad temperature-pressure-composition(2000–10000 K, 1–7 Mbar,pure H to pure He) regimes, we systematically determine self and mutual diffusion coefficients in H–He systems and establish a six-dimensional framework correlating temperature, pressure, helium abundance, phase separation degree, diffusion coefficients, and anisotropy. Key findings reveal that hydrogen exhibits active directional migration with pronounced diffusion anisotropy, whereas helium passively aggregates in response. While the conventional mixing rule underestimates mutual diffusion coefficients by neglecting velocity cross-correlations,the assumption of an ideal thermodynamic factor(Q = 1) overestimates them due to unaccounted non-ideal thermodynamic effects—both particularly pronounced in strongly phase-separated regimes. Notably, hydrogen's dual role, anisotropic diffusion and bond stabilization via helium doping, modulates demixing kinetics. Large-scale simulations(216,000 atoms) propose novel phase-separation paradigms, such as “hydrogen bubble/wisp” formation, challenging the classical “helium rain” scenario, striving to bridge atomic-scale dynamics to planetary-scale phase evolution.
基金supported by the National Natural Science Foundation of China(No.12475340 and 12375350)Special Branch project of South Taihu Lakethe Scientific Research Fund of Zhejiang Provincial Education Department(No.Y202456326).
文摘Missing values in radionuclide diffusion datasets can undermine the predictive accuracy and robustness of the machine learning(ML)models.In this study,regression-based missing data imputation method using a light gradient boosting machine(LGBM)algorithm was employed to impute more than 60%of the missing data,establishing a radionuclide diffusion dataset containing 16 input features and 813 instances.The effective diffusion coefficient(D_(e))was predicted using ten ML models.The predictive accuracy of the ensemble meta-models,namely LGBM-extreme gradient boosting(XGB)and LGBM-categorical boosting(CatB),surpassed that of the other ML models,with R^(2)values of 0.94.The models were applied to predict the D_(e)values of EuEDTA^(−)and HCrO_(4)^(−)in saturated compacted bentonites at compactions ranging from 1200 to 1800 kg/m^(3),which were measured using a through-diffusion method.The generalization ability of the LGBM-XGB model surpassed that of LGB-CatB in predicting the D_(e)of HCrO_(4)^(−).Shapley additive explanations identified total porosity as the most significant influencing factor.Additionally,the partial dependence plot analysis technique yielded clearer results in the univariate correlation analysis.This study provides a regression imputation technique to refine radionuclide diffusion datasets,offering deeper insights into analyzing the diffusion mechanism of radionuclides and supporting the safety assessment of the geological disposal of high-level radioactive waste.
基金supported by the National Natural Science Foundation of China(Nos.61906168,62202429 and 62272267)the Zhejiang Provincial Natural Science Foundation of China(No.LY23F020023)the Construction of Hubei Provincial Key Laboratory for Intelligent Visual Monitoring of Hydropower Projects(No.2022SDSJ01)。
文摘Accurately identifying building distribution from remote sensing images with complex background information is challenging.The emergence of diffusion models has prompted the innovative idea of employing the reverse denoising process to distill building distribution from these complex backgrounds.Building on this concept,we propose a novel framework,building extraction diffusion model(BEDiff),which meticulously refines the extraction of building footprints from remote sensing images in a stepwise fashion.Our approach begins with the design of booster guidance,a mechanism that extracts structural and semantic features from remote sensing images to serve as priors,thereby providing targeted guidance for the diffusion process.Additionally,we introduce a cross-feature fusion module(CFM)that bridges the semantic gap between different types of features,facilitating the integration of the attributes extracted by booster guidance into the diffusion process more effectively.Our proposed BEDiff marks the first application of diffusion models to the task of building extraction.Empirical evidence from extensive experiments on the Beijing building dataset demonstrates the superior performance of BEDiff,affirming its effectiveness and potential for enhancing the accuracy of building extraction in complex urban landscapes.
文摘A medical image encryption is proposed based on the Fisher-Yates scrambling,filter diffusion and S-box substitution.First,chaotic sequence associated with the plaintext is generated by logistic-sine-cosine system,which is used for the scrambling,substitution and diffusion processes.The three-dimensional Fisher-Yates scrambling,S-box substitution and diffusion are employed for the first round of encryption.The chaotic sequence is adopted for secondary encryption to scramble the ciphertext obtained in the first round.Then,three-dimensional filter is applied to diffusion for further useful information hiding.The key to the algorithm is generated by the combination of hash value of plaintext image and the input parameters.It improves resisting ability of plaintext attacks.The security analysis shows that the algorithm is effective and efficient.It can resist common attacks.In addition,the good diffusion effect shows that the scheme can solve the differential attacks encountered in the transmission of medical images and has positive implications for future research.
基金supported by the National Natural Science Foundation of China(No.52374372)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(No.23KJB430042)+3 种基金the Jiangsu Province Large Scientific Instruments Open Sharing Autonomous Research Filing Project,China(No.TC2023A037)the Yangzhou City−Yangzhou University Cooperation Foundation,China(No.YZ2022183)High-end Talent Support Program of Yangzhou University,China,Qinglan Project of Yangzhou University,ChinaLvyangjinfeng Talent program of Yangzhou,China.
文摘The interdiffusion coefficients in Al_(0.2)CoCrFeNi,CoCrCu_(0.2)FeNi,and CoCrFeMn_(0.2)Ni high-entropy alloys were efficiently determined by combining diffusion couple experiments and high-throughput determination of interdiffusion coefficients(HitDIC)software at 1273−1373 K.The results show that the addition of Al,Cu,and Mn to CoCrFeNi high-entropy alloys promotes the diffusion of Co,Cr,and Fe atoms.The comparison of tracer diffusion coefficients indicates that there is no sluggish diffusion in tracer diffusion on the thermodynamic temperature scale for the present Al_(0.2)CoCrFeNi,CoCrCu_(0.2)FeNi,and CoCrFeMn_(0.2)Ni high-entropy alloys.The linear relationship between diffusion entropy and activation energy reveals that the diffusion process of atoms is unaffected by an increase in the number of components as long as the crystal structure remains unchanged.
基金supported by the National Natural Science Foundation of China(Grant No.62202210).
文摘The application of generative artificial intelligence(AI)is bringing about notable changes in anime creation.This paper surveys recent advancements and applications of diffusion and language models in anime generation,focusing on their demonstrated potential to enhance production efficiency through automation and personalization.Despite these benefits,it is crucial to acknowledge the substantial initial computational investments required for training and deploying these models.We conduct an in-depth survey of cutting-edge generative AI technologies,encompassing models such as Stable Diffusion and GPT,and appraise pivotal large-scale datasets alongside quantifiable evaluation metrics.Review of the surveyed literature indicates the achievement of considerable maturity in the capacity of AI models to synthesize high-quality,aesthetically compelling anime visual images from textual prompts,alongside discernible progress in the generation of coherent narratives.However,achieving perfect long-form consistency,mitigating artifacts like flickering in video sequences,and enabling fine-grained artistic control remain critical ongoing challenges.Building upon these advancements,research efforts have increasingly pivoted towards the synthesis of higher-dimensional content,such as video and three-dimensional assets,with recent studies demonstrating significant progress in this burgeoning field.Nevertheless,formidable challenges endure amidst these advancements.Foremost among these are the substantial computational exigencies requisite for training and deploying these sophisticated models,particularly pronounced in the realm of high-dimensional generation such as video synthesis.Additional persistent hurdles include maintaining spatial-temporal consistency across complex scenes and mitigating ethical considerations surrounding bias and the preservation of human creative autonomy.This research underscores the transformative potential and inherent complexities of AI-driven synergy within the creative industries.We posit that future research should be dedicated to the synergistic fusion of diffusion and autoregressive models,the integration of multimodal inputs,and the balanced consideration of ethical implications,particularly regarding bias and the preservation of human creative autonomy,thereby establishing a robust foundation for the advancement of anime creation and the broader landscape of AI-driven content generation.
基金supported by the National Natural Science Foundation of China(52361033)National Key Research and Development Program(2022YFB3505400)+1 种基金the Main Discipline and Technology Leaders Training Plan of Jiangxi Province(2022BCJ23007)the Jiangxi Province Postgraduate Innovation Project(YC2022-S693)。
文摘In this study,DyF_(3)powder was sprayed onto the polar and side surfaces of the magnets to determine the anisotropic diffusion mechanism of Dy in the sintered Nd-Fe-B magnet.The coercivity and squareness of the magnet in which the diffusion of Dy is perpendicular to the c-axis(a-magnet)are lower than those of the magnet with the diffusion of Dy parallel to the c-axis(c-magnet).Compared with the c-magnet,the a-magnet has a longer Dy-enrichment region from the diffusion surface,where Dy is enriched in the 2:14:1 grain.By contrast,the Dy concentration in the grain boundaries beyond the Dy enrichment region is lower in the a-magnet.Moreover,the Dy shells beyond the Dy enrichment region in the a-magnet are distributed on the side surfaces of the 2:14:1 grains but not on the polar surfaces.Based on the micromagnetic simulation,the Dy shells on the polar surfaces of the grains are more effective in enhancing coercivity.According to first-principle calculations,Dy migrating through 001 into the Nd vacancy in the Nd_(2)Fe_(14)B crystal has a higher diffusion barrier,thus indicating that the lattice diffusion of Dy parallel to the c-axis is more difficult.
基金financially supported by the National Natural Science Foundation of China(No.51701061)the Natural Sci-ence Foundation of Hebei Province(No.E2019202059).
文摘Diffusion of solutes significantly affects the coarsening rate of γ'precipitates in precipitation-hardened high entropy alloys(PH-HEAs).In this work,we systematically study the refractory solutes M(Hf,Nb,Ta,Mo,W,Re,Ru)diffusion in face-centered-cubic(FCC)NiCoFeCr lattice through a combination of first-principles calculations,diffusion couples,and coarsening of γ'precipitates experiments.Our calculations reveal that there exists a stronger negative correlation between solute diffusivity and Young’s modulus than between solute diffusivity and atomic size;i.e.,the higher the Young’s modulus,the more difficult solute diffusion is.Based on the electronic structure analysis,the underlying origins for such a relation-ship could be ascribed to the fact that solutes with high Young’s modulus have stronger bonds with neighboring host atoms,less compressibility,and thus poor diffusivity.Afterwards,the main interdiffu-sion coefficients of three refractory elements with similar atomic sizes and increasing Young’s modulus,Mo,W,and Re,at 1150℃in(NiCoFeCr)_(92)Al_(3)Ti_(3)M_(2)are,in order of magnitude,D_(MoMo)^(Ni)>D_(WW)^(Ni)>D_(ReRe)^(Ni),as determined by the diffusion-couple experiments.Further investigations on the coarsening kinetics of precipitates confirmed the additions of refractory elements improve the coarsening resistance of γ'pre-cipitates in the order of Re>W>Mo.The trends in the diffusivity determined by experiment and simulation are in excellent agreement.More importantly,the Young’s modulus effect for the diffusion of refractory solutes in HEAs is also carefully analyzed and discussed.Our present findings will give new insights into future design of γ'-strengthened HEAs for high-temperature structural applications.
基金National Key R&D Program of China (2021YFA1201503)National Natural Science Foundation of China (21972164, 22279161, 12264038, 22309144)+4 种基金Natural Science Foundation of Jiangsu Province (BK. 20210130)China Postdoctoral Science Foundation (2023M733189)Jiangsu Double-Innovation PhD Program in 2022 (JSSCBS20221241)Senior Talents Fund of Jiangsu University (5501220014)fellowship funding provided by the Alexander von Humboldt Foundation。
文摘Rechargeable aqueous zinc-metal batteries (AZMBs) are promising candidates for large-scale energy storage systems due to their low cost and high safety.However,their performance and sustainability are significantly hindered by the sluggish desolvation kinetics at the electrode/electrolyte interface and the corresponding hydrogen evolution reaction where active water molecules tightly participate in the Zn(H_(2)O)_(6)^(2+)solvation shell.Herein,learnt from self-generated solid electrolyte interphase (SEI) in anodes,the dielectric but ion-conductive zinc niobate nanoparticles artificial layer is constructed on metallic Zn surface (ZNB@Zn),acting as a rapid desolvation promotor.The zincophilic and dielectric-conductive properties of ZNB layer accelerate interfacial desolvation/diffusion and suppress surface corrosion or dendrite formation,achieving uniform Zn plating/stripping behavior,as confirmed by electronic/optical microscopies and interface spectroscopical measurements together with theoretical calculations.Consequently,the as-prepared ZNB@Zn electrode exhibits excellent cycling stability of over 2000 h and robust reversibility (99.54%) even under high current density and depth of discharge conditions.Meanwhile,the assembled ZNB@Zn-based full cell displays high capacity-retention rate of 80.21%after 3000 cycles at 5 A g^(-1)and outstanding rate performance up to 10 A g^(-1).The large-areal pouch cell is stabilized for hundreds of cycles,highlighting the bright prospects of the dielectric but ion-conductive layer in further application of AZMBs.
基金supported by the Korea Institute of Science and Technology(No.2E30993).
文摘Absorption and desorption processes of hydrogen in metals are facilitated by alloying elements;however,the formation of secondary phases often reduces storage capacity.The alloying effect on the hydrogen kinetics has been examined by time-lag permeation measurement,which lacks spatial resolution and yields the averaged diffusion coefficient from multiple phases.Here,we report an advanced scanning Kelvin probe force microscopy,combined with in-situ hydrogen loading system for submicron-scale measurement of diffusion kinetics in metals.Successive probing of the surface during hydrogen loading detects the temporal and spatial variations in the surface potential,enabling the estimation of diffusion coefficient.Not only for a single-phase magnesium but also for multiphase titaniumiron based alloys,we can obtain the diffusion coefficients of hydrogen in each phase.The estimated diffusion coefficients for TiFe alloys are higher than that for the pristine TiFe intermetallic compound,due to alloying elements that reduce the diffusion barrier and modify bond character.Our approach paves the way to the microscopic understanding of hydrogen diffusion in metals.
基金Supported by the Open Research Fund of Key Laboratory of Nonlinear Analysis and Applications(Central China Normal University),Ministry of Education,P.R.China(Grant No.NAA2025ORG011)Science and Technology Plan Project of Jingmen(Grant No.2024YFZD076)+3 种基金Research Team Project of Jingchu University of Technology(Grant No.TD202006)Research Project of Jingchu University of Technology(Grant Nos.HX20240049HX20240200)the Teaching Reform Research Project of Hubei Province(Grant No.2024496)。
文摘In this paper,we study the eigenvalue problem of the Markov diffusion operator L^(2),and give generalized inequalities for eigenvalues of the operator L^(2)on a Markov diffusion triple.By applying these inequalities,we then get some new universal bounds for eigenvalues of a special Markov diffusion operator L^(2)on bounded domains in an Euclidean space.Moreover,our results can reveal the relationship between the(k+1)-th eigenvalue and the first k eigenvalues in a relatively straightforward manner.
基金Supported by the National Natural Science Foundation of China(520743198)Scientific and Technological Problems Tackling Project of Heilongjiang Province(DQYT-2022-JS-761).
文摘To reveal the complex crude oil-CO_(2) interaction mechanism and oil mobilization behavior during CO_(2) huff-n-puff in shale-type shale oil reservoirs,CO_(2) huff-n-puff experiments with on-line nuclear magnetic resonance monitoring were conducted on Gulong shale cores,combined with the prediction model of CO_(2) dynamic diffusion coefficient,the flow mechanism and factors influencing oil mobilization during CO_(2) huff and puff in Gulong shale oil reservoirs are studied,and the diffusion and mass transfer behavior of CO_(2) in shale is investigated.The results show that at the injection stage,CO_(2) invades into macropores near the injection end,and drives part of the crude oil to micropores in the deep part of the core.At the shut-in stage,the crude oil gradually reflows to macropores near the injection end and is redistributed in the core.At the production stage,the oil mobilization zone is gradually expanded from the production end(injection end)to the deep part of the core.The contribution ratio of produced oil from macropores and micropores is about 8︰3 after production.The diffusion coefficient of CO_(2) in shale porous media gradually decreases with the advance of diffusion front at shut-in stage.The better the porosity and permeability of core samples,the higher the CO_(2) concentration at diffusion front,the greater the CO_(2) diffusion coefficient,and the slower the diffusion decline rate is.Increasing the huff and puff cycles could effectively enhance oil displacement efficiency,though its impact on the crude oil mobilization zone remains insignificant.The crude oil in small pores of the small layer with undeveloped laminae is difficult to be produced during CO_(2) huff and puff,and the oil recovery is only 12.72%.The crude oil in macropores and micropores of the small layer with developed laminae can be effectively mobilized during CO_(2) huff and puff,and the oil recovery can reach 39.11%.
