The proliferation of wearable biodevices has boosted the development of soft,innovative,and multifunctional materials for human health monitoring.The integration of wearable sensors with intelligent systems is an over...The proliferation of wearable biodevices has boosted the development of soft,innovative,and multifunctional materials for human health monitoring.The integration of wearable sensors with intelligent systems is an overwhelming tendency,providing powerful tools for remote health monitoring and personal health management.Among many candidates,two-dimensional(2D)materials stand out due to several exotic mechanical,electrical,optical,and chemical properties that can be efficiently integrated into atomic-thin films.While previous reviews on 2D materials for biodevices primarily focus on conventional configurations and materials like graphene,the rapid development of new 2D materials with exotic properties has opened up novel applications,particularly in smart interaction and integrated functionalities.This review aims to consolidate recent progress,highlight the unique advantages of 2D materials,and guide future research by discussing existing challenges and opportunities in applying 2D materials for smart wearable biodevices.We begin with an in-depth analysis of the advantages,sensing mechanisms,and potential applications of 2D materials in wearable biodevice fabrication.Following this,we systematically discuss state-of-the-art biodevices based on 2D materials for monitoring various physiological signals within the human body.Special attention is given to showcasing the integration of multi-functionality in 2D smart devices,mainly including self-power supply,integrated diagnosis/treatment,and human–machine interaction.Finally,the review concludes with a concise summary of existing challenges and prospective solutions concerning the utilization of2D materials for advanced biodevices.展开更多
A functional interlayer based on two-dimensional(2D)porous modified vermiculite nanosheets(PVS)was obtained by acid-etching vermiculite nanosheets.The as-obtained 2D porous nanosheets exhibited a high specific surface...A functional interlayer based on two-dimensional(2D)porous modified vermiculite nanosheets(PVS)was obtained by acid-etching vermiculite nanosheets.The as-obtained 2D porous nanosheets exhibited a high specific surface area of 427 m^(2)·g^(-1)and rich surface active sites,which help restrain polysulfides(LiPSs)through good physi-cal and chemical adsorption,while simultaneously accelerating the nucleation and dissolution kinetics of Li_(2)S,effec-tively suppressing the shuttle effect.The assembled lithium-sulfur batteries(LSBs)employing the PVS-based inter-layer delivered a high initial discharge capacity of 1386 mAh·g^(-1)at 0.1C(167.5 mAh·g^(-1)),long-term cycling stabil-ity,and good rate property.展开更多
Lithium-sulfur(Li-S)batteries with high energy density and capacity have garnered significant research attention among various energy storage devices.However,the shuttle effect of polysulfides(LiPSs)remains a major ch...Lithium-sulfur(Li-S)batteries with high energy density and capacity have garnered significant research attention among various energy storage devices.However,the shuttle effect of polysulfides(LiPSs)remains a major challenge for their practical application.The design of battery separators has become a key aspect in addressing the challenge.MXenes,a promising two-dimensional(2D)material,offer exceptional conductivity,large surface area,high mechanical strength,and active sites for surface reactions.When assembled into layered films,MXenes form highly tunable two-dimensional channels ranging from a few angstroms to over 1 nm.These nanoconfined channels are instrumental in facilitating lithium-ion transport while effectively impeding the shuttle effect of LiPSs,which are essential for improving the specific capacity and cyclic stability of Li-S batteries.Substantial progress has been made in developing MXenes-based separators for Li-S batteries,yet there remains a research gap in summarizing advancements from the perspective of interlayer engineering.This entails maintaining the 2D nanochannels of layered MXenes-based separators while modulating the physicochemical environment within the MXenes interlayers through targeted modifications.This review highlights advancements in in situ modification of MXenes and their integration with 0D,1D,and 2D materials to construct laminated nanocomposite separators for Li-S batteries.The future development directions of MXenes-based materials in Li-S energy storage devices are also outlined,to drive further advancements in MXenes for Li-S battery separators.展开更多
The published article titled“Comparison of Structural Probabilistic and Non-Probabilistic Reliability Computational Methods under Big Data Condition”[1]has been retracted from Structural Durability&Health Monito...The published article titled“Comparison of Structural Probabilistic and Non-Probabilistic Reliability Computational Methods under Big Data Condition”[1]has been retracted from Structural Durability&Health Monitoring(SDHM),Vol.16,No.2,2022,pp.129–143.展开更多
Titanium dioxide(TiO_(2))has been an important protective ingredient in mineral-based sunscreens since the 1990s.However,traditional TiO_(2)nanoparticle formulations have seen little improvement over the past decades ...Titanium dioxide(TiO_(2))has been an important protective ingredient in mineral-based sunscreens since the 1990s.However,traditional TiO_(2)nanoparticle formulations have seen little improvement over the past decades and continue to face persistent challenges related to light transmission,biosafety,and visual appearance.Here,we report the discovery of two-dimensional(2D)TiO_(2),characterized by a micro-sized lateral dimension(~1.6μm)and atomic-scale thickness,which fundamentally resolves these long-standing issues.The 2D structure enables exceptional light management,achieving 80%visible light transparency—rendering it nearly invisible on the skin—while maintaining UV-blocking performance comparable to unmodified rutile TiO_(2)nanoparticles.Its larger lateral size results in a two-orders-of-magnitude reduction in skin penetration(0.96 w/w%),significantly enhancing biosafety.Moreover,the unique layered architecture inherently suppresses the generation of reactive oxygen species(ROS)under sunlight exposure,reducing the ROS generation rate by 50-fold compared to traditional TiO_(2)nanoparticles.Through precise metal element modulation,we further developed the first customizable sunscreen material capable of tuning UV protection ranges and automatically matching diverse skin tones.The 2D TiO_(2)offers a potentially transformative approach to modern sunscreen formulation,combining superior UV protection,enhanced safety and a natural appearance.展开更多
Weather forecasts from numerical weather prediction models play a central role in solar energy forecasting,where a cascade of physics-based models is used in a model chain approach to convert forecasts of solar irradi...Weather forecasts from numerical weather prediction models play a central role in solar energy forecasting,where a cascade of physics-based models is used in a model chain approach to convert forecasts of solar irradiance to solar power production.Ensemble simulations from such weather models aim to quantify uncertainty in the future development of the weather,and can be used to propagate this uncertainty through the model chain to generate probabilistic solar energy predictions.However,ensemble prediction systems are known to exhibit systematic errors,and thus require post-processing to obtain accurate and reliable probabilistic forecasts.The overarching aim of our study is to systematically evaluate different strategies to apply post-processing in model chain approaches with a specific focus on solar energy:not applying any post-processing at all;post-processing only the irradiance predictions before the conversion;post-processing only the solar power predictions obtained from the model chain;or applying post-processing in both steps.In a case study based on a benchmark dataset for the Jacumba solar plant in the U.S.,we develop statistical and machine learning methods for postprocessing ensemble predictions of global horizontal irradiance(GHI)and solar power generation.Further,we propose a neural-network-based model for direct solar power forecasting that bypasses the model chain.Our results indicate that postprocessing substantially improves the solar power generation forecasts,in particular when post-processing is applied to the power predictions.The machine learning methods for post-processing slightly outperform the statistical methods,and the direct forecasting approach performs comparably to the post-processing strategies.展开更多
As the proportion of newenergy increases,the traditional cumulant method(CM)produces significant errorswhen performing probabilistic load flow(PLF)calculations with large-scale wind power integrated.Considering the wi...As the proportion of newenergy increases,the traditional cumulant method(CM)produces significant errorswhen performing probabilistic load flow(PLF)calculations with large-scale wind power integrated.Considering the wind speed correlation,a multi-scenario PLF calculation method that combines random sampling and segmented discrete wind farm power was proposed.Firstly,based on constructing discrete scenes of wind farms,the Nataf transform is used to handle the correlation between wind speeds.Then,the random sampling method determines the output probability of discrete wind power scenarios when wind speed exhibits correlation.Finally,the PLF calculation results of each scenario areweighted and superimposed following the total probability formula to obtain the final power flow calculation result.Verified in the IEEE standard node system,the absolute percent error(APE)for the mean and standard deviation(SD)of the node voltages and branch active power are all within 1%,and the average root mean square(AMSR)values of the probability curves are all less than 1%.展开更多
Owing to their rolling friction,two-dimensional piston pumps are highly suitable as power components for electro-hydrostatic actuators(EHAs).These pumps are particularly advantageous for applications requiring high ef...Owing to their rolling friction,two-dimensional piston pumps are highly suitable as power components for electro-hydrostatic actuators(EHAs).These pumps are particularly advantageous for applications requiring high efficiency and reliability.However,the ambiguity surrounding the output flow characteristics of individual two-dimensional pumps poses a significant challenge in achieving precise closed-loop control of the EHA positions.To address this issue,this study established a comprehensive numerical model that included gap leakage to analyze the impact of leakage on the output flow characteristics of a two-dimensional piston pump.The validity of the numerical analysis was indirectly confirmed through meticulous measurements of the leakage and volumetric efficiency,ensuring robust results.The research findings indicated that,at lower pump speeds,leakage significantly affected the output flow rate,leading to potential inefficiencies in the system.Conversely,at higher rotational speeds,the impact of leakage was less pronounced,implying that the influence of leakage on the pump outlet flow must be carefully considered and managed for EHAs to perform position servo control.Additionally,the research demonstrates that two-dimensional motion does not have a unique or additional effect on pump leakage,thus simplifying the design considerations.Finally,the study concluded that maintaining an oil-filled leakage environment is beneficial because it helps reduce the impact of leakage and enhances the overall volumetric efficiency of the pump system.展开更多
Environmental catalysis has been considered one of the important research topics.Some technologies(e.g.,photocatalysis and electrocatalysis)have been intensively developed with the advance of synthetic technologies of...Environmental catalysis has been considered one of the important research topics.Some technologies(e.g.,photocatalysis and electrocatalysis)have been intensively developed with the advance of synthetic technologies of catalytical materials.In 2019,we discussed the development trend of this field,and wrote a roadmap on this topic in Chinese Chemical Letters(30(2019)2065-2088).Nowadays,we discuss it again from a new viewpoint along this road.In this paper,several subtopics are discussed,e.g.,photocatalysis based on titanium dioxide,violet phosphorus,graphitic carbon and covalent organic frameworks,electrocatalysts based on carbon,metal-and covalent-organic framework.Finally,we hope that this roadmap can enrich the development of two-dimensional materials in environmental catalysis with novel understanding,and give useful inspiration to explore new catalysts for practical applications.展开更多
Sandy cobble soil exhibits pronounced heterogeneity.The assessment of the uncertainty surrounding its properties is crucial for the analysis of settlement characteristics resulting from volume loss during shield tunne...Sandy cobble soil exhibits pronounced heterogeneity.The assessment of the uncertainty surrounding its properties is crucial for the analysis of settlement characteristics resulting from volume loss during shield tunnelling.In this study,a series of probabilistic analyses of surface and subsurface settlements was conducted considering the spatial variability of the friction angle and reference stiffness modulus,under different volumetric block proportions(Pv)and tunnel volume loss rates(ηt).The non-intrusive random finite difference method was used to investigate the probabilistic characteristics of maximum surface settlement,width of subsurface settlement trough,maximum subsurface settlement,and subsurface soil volume loss rate through Monte Carlo simulations.Additionally,a comparison between stochastic and deterministic analysis results is presented to underscore the significance of probabilistic analysis.Parametric analyses were subsequently conducted to investigate the impacts of the key input parameters in random fields on the settlement characteristics.The results indicate that scenarios with higher Pv or greaterηt result in a higher dispersion of stochastic analysis results.Neglecting the spatial variability of soil properties and relying solely on the mean values of material parameters for deterministic analysis may result in an underestimation of surface and subsurface settlements.From a probabilistic perspective,deterministic analysis alone may prove inadequate in accurately capturing the volumetric deformation mode of the soil above the tunnel crown,potentially affecting the prediction of subsurface settlement.展开更多
It is a key challenge to prepare two-dimensional diamond(2D-diamond).Herein,we develop a method for synthesizing 2D-diamond by depositing monodisperse tantalum(Ta)atoms onto graphene substrates using a hot-filament ch...It is a key challenge to prepare two-dimensional diamond(2D-diamond).Herein,we develop a method for synthesizing 2D-diamond by depositing monodisperse tantalum(Ta)atoms onto graphene substrates using a hot-filament chemical vapor deposition setup,followed by annealing treatment under different temperatures at ambient pressure.The results indicate that when the annealing temperature increases from 700℃ to 1000℃,the size of the 2D-diamond found in the samples gradually increases from close to 20 nm to around 30 nm.Meanwhile,the size and number of amorphous carbon spheres and Ta-containing compounds between the graphene layers gradually increase.As the annealing temperature continues to rise to 1100℃,a significant aggregation of Ta-containing compounds is observed in the samples,with no diamond structure detected.This further confirms that monodisperse Ta atoms play a key role in graphene phase transition into 2D-diamond.This study provides a novel method for the ambient-pressure phase transition of graphene into 2D-diamond.展开更多
Electron-hole interactions play a crucial role in determining the optoelectronic properties of materials,and in lowdimensional systems this is especially true due to the decrease of screening.In this review,we focus o...Electron-hole interactions play a crucial role in determining the optoelectronic properties of materials,and in lowdimensional systems this is especially true due to the decrease of screening.In this review,we focus on one unique quantum phase induced by the electron-hole interaction in two-dimensional systems,known as“exciton insulators”(EIs).Although this phase of matter has been studied for more than half a century,suitable platforms for its stable realization remain scarce.We provide an overview of the strategies to realize EIs in accessible materials and structures,along with a discussion on some unique properties of EIs stemming from the band structures of these materials.Additionally,signatures in experiments to distinguish EIs are discussed.展开更多
The development of modern engineering components and equipment features large size,intricate shape and long service life,which places greater demands on valid methods for fatigue performance analysis.Achieving a smoot...The development of modern engineering components and equipment features large size,intricate shape and long service life,which places greater demands on valid methods for fatigue performance analysis.Achieving a smooth transformation between small-scale laboratory specimens’fatigue properties and full-scale engineering components’fatigue strength has been a long-term challenge.In this work,two dominant factors impeding the smooth transformation—notch and size effect were experimentally studied,in which fatigue tests on Al 7075-T6511(a very high-strength aviation alloy)notched specimens of different scales were carried out.Fractography analyses identified the evidence of the size effect on notch fatigue damage evolution.Accordingly,the Energy Field Intensity(EFI)initially developed for multiaxial notch fatigue analysis was improved by utilizing the volume ratio of the Effective Damage Zones(EDZs)for size effect correction.In particular,it was extended to a probabilistic model considering the inherent variability of the fatigue phenomenon.The experimental data of Al 7075-T6511 notched specimens and the model-predicted results were compared,indicating the high potential of the proposed approach in fatigue evaluation under combined notch and size effects.展开更多
The pursuit of sustainable hydrogen production has positioned water electrolysis as a cornerstone technology for global carbon neutrality.However,sluggish kinetics,catalyst scarcity,and system integration challenges h...The pursuit of sustainable hydrogen production has positioned water electrolysis as a cornerstone technology for global carbon neutrality.However,sluggish kinetics,catalyst scarcity,and system integration challenges hinder its widespread deployment.Ultrathin two-dimensional(2D)materials,with their atomically exposed surfaces,tunable electronic structures,and defect-engineering capabilities,present unique opportunities for next-generation electrocatalysts.This review provides an integrated overview of ultrathin 2D electrocatalysts,discussing their structural diversity,synthetic routes,structure-activity relationships,and mechanistic understanding in water electrolysis processes.Special focus is placed on the translation of 2D materials from laboratory research to practical device implementation,emphasizing challenges such as scalable fabrication,interfacial engineering,and operational durability in realistic electrolyzer environments.The role of advanced characterization techniques in capturing dynamic structural changes and active site evolution is discussed.Finally,we outline future research directions,emphasizing the synergy of machine learning-driven materials discovery,advanced operando characterization,and scalable system integration to accelerate the industrial translation of 2D electrocatalysts for green hydrogen production.展开更多
Protocol Reverse Engineering(PRE)is of great practical importance in Internet security-related fields such as intrusion detection,vulnerability mining,and protocol fuzzing.For unknown binary protocols having fixed-len...Protocol Reverse Engineering(PRE)is of great practical importance in Internet security-related fields such as intrusion detection,vulnerability mining,and protocol fuzzing.For unknown binary protocols having fixed-length fields,and the accurate identification of field boundaries has a great impact on the subsequent analysis and final performance.Hence,this paper proposes a new protocol segmentation method based on Information-theoretic statistical analysis for binary protocols by formulating the field segmentation of unsupervised binary protocols as a probabilistic inference problem and modeling its uncertainty.Specifically,we design four related constructions between entropy changes and protocol field segmentation,introduce random variables,and construct joint probability distributions with traffic sample observations.Probabilistic inference is then performed to identify the possible protocol segmentation points.Extensive trials on nine common public and industrial control protocols show that the proposed method yields higher-quality protocol segmentation results.展开更多
Vehicle electrification,an important method for reducing carbon emissions from road transport,has been promoted globally.In this study,we analyze how individuals adapt to this transition in transportation and its subs...Vehicle electrification,an important method for reducing carbon emissions from road transport,has been promoted globally.In this study,we analyze how individuals adapt to this transition in transportation and its subsequent impact on urban structure.Considering the varying travel costs associated with electric and fuel vehicles,we analyze the dynamic choices of households concerning house locations and vehicle types in a two-dimensional monocentric city.A spatial equilibrium is developed to model the interactions between urban density,vehicle age and vehicle type.An agent-based microeconomic residential choice model dynamically coupled with a house rent market is developed to analyze household choices of home locations and vehicle energy types,considering vehicle ages and competition for public charging piles.Key findings from our proposed models show that the proportion of electric vehicles(EVs)peaks at over 50%by the end of the first scrappage period,accompanied by more than a 40%increase in commuting distance and time compared to the scenario with only fuel vehicles.Simulation experiments on a theoretical grid indicate that heterogeneity-induced residential segregation can lead to urban sprawl and congestion.Furthermore,households with EVs tend to be located farther from the city center,and an increase in EV ownership contributes to urban expansion.Our study provides insights into how individuals adapt to EV transitions and the resulting impacts on home locations and land use changes.It offers a novel perspective on the dynamic interactions between EV adoption and urban development.展开更多
The diffusion trajectory of a Brownian particle passing over the saddle point of a two-dimensional quadratic potential energy surface is tracked in detail according to the deep learning strategies.Generative adversari...The diffusion trajectory of a Brownian particle passing over the saddle point of a two-dimensional quadratic potential energy surface is tracked in detail according to the deep learning strategies.Generative adversarial networks(GANs)emanating in the category of machine learning(ML)frameworks are used to generate and assess the rationality of the data.While their optimization is based on the long short-term memory(LSTM)strategies.In addition to drawing a heat map,the optimal path of two-dimensional(2D)diffusion is simultaneously demonstrated in a stereoscopic space.The results of our simulation are completely consistent with the previous theoretical predictions.展开更多
Aiming at the problems of increasing uncertainty of low-carbon generation energy in active distribution network(ADN)and the difficulty of security assessment of distribution network,this paper proposes a two-phase sch...Aiming at the problems of increasing uncertainty of low-carbon generation energy in active distribution network(ADN)and the difficulty of security assessment of distribution network,this paper proposes a two-phase scheduling model for flexible resources in ADN based on probabilistic risk perception.First,a full-cycle probabilistic trend sequence is constructed based on the source-load historical data,and in the day-ahead scheduling phase,the response interval of the flexibility resources on the load and storage side is optimized based on the probabilistic trend,with the probability of the security boundary as the security constraint,and with the economy as the objective.Then in the intraday phase,the core security and economic operation boundary of theADNis screened in real time.Fromthere,it quantitatively senses the degree of threat to the core security and economic operation boundary under the current source-load prediction information,and identifies the strictly secure and low/high-risk time periods.Flexibility resources within the response interval are dynamically adjusted in real-time by focusing on high-risk periods to cope with future core risks of the distribution grid.Finally,the improved IEEE 33-node distribution system is simulated to obtain the flexibility resource scheduling scheme on the load and storage side.Thescheduling results are evaluated from the perspectives of risk probability and flexible resource utilization efficiency,and the analysis shows that the scheduling model in this paper can promote the consumption of low-carbon energy from wind and photovoltaic sourceswhile reducing the operational risk of the distribution network.展开更多
Moiré superlattices have revolutionized the study of two-dimensional materials, enabling unprecedented control over their electronic, magnetic, optical, and mechanical properties. This review provides a comprehen...Moiré superlattices have revolutionized the study of two-dimensional materials, enabling unprecedented control over their electronic, magnetic, optical, and mechanical properties. This review provides a comprehensive analysis of the latest advancements in moiré physics, focusing on the formation of moiré superlattices due to rotational misalignment or lattice mismatch in two-dimensional materials. These superlattices induce flat band structures and strong correlation effects,leading to the emergence of exotic quantum phases, such as unconventional superconductivity, correlated insulating states,and fractional quantum anomalous Hall effects. The review also explores the underlying mechanisms of these phenomena and discusses the potential technological applications of moiré physics, offering insights into future research directions in this rapidly evolving field.展开更多
The study presents the results of over 30,000 numerical analyses on the stability of lava tubes under lunar conditions.The research considered random irregularities in cave geometry and their impact on stability,with ...The study presents the results of over 30,000 numerical analyses on the stability of lava tubes under lunar conditions.The research considered random irregularities in cave geometry and their impact on stability,with a particular focus on the geometric characteristics of identified collapses.We propose a procedure for extracting the collapse areas and integrating it into the stability analysis results.The results were examined to assess the possibility of describing the geometry characteristics of collapses using commonly applied probability density distributions,such as normal or lognormal distribution.Our aim is to facilitate future risk assessment of lunar caves.Such an assessment will be essential prior to robotically exploring caves beneath the lunar surface and can be extended to be used for planetary caves beyond the Moon.Our findings indicate that several collapse characteristics can be represented by unimodal probability density distributions,which could significantly simplify the candidate selection process.Based on our results,we also highlight several key directions for future research and suggested implications related to their future exploration.展开更多
基金the support from the National Natural Science Foundation of China(22272004,62272041)the Fundamental Research Funds for the Central Universities(YWF-22-L-1256)+1 种基金the National Key R&D Program of China(2023YFC3402600)the Beijing Institute of Technology Research Fund Program for Young Scholars(No.1870011182126)。
文摘The proliferation of wearable biodevices has boosted the development of soft,innovative,and multifunctional materials for human health monitoring.The integration of wearable sensors with intelligent systems is an overwhelming tendency,providing powerful tools for remote health monitoring and personal health management.Among many candidates,two-dimensional(2D)materials stand out due to several exotic mechanical,electrical,optical,and chemical properties that can be efficiently integrated into atomic-thin films.While previous reviews on 2D materials for biodevices primarily focus on conventional configurations and materials like graphene,the rapid development of new 2D materials with exotic properties has opened up novel applications,particularly in smart interaction and integrated functionalities.This review aims to consolidate recent progress,highlight the unique advantages of 2D materials,and guide future research by discussing existing challenges and opportunities in applying 2D materials for smart wearable biodevices.We begin with an in-depth analysis of the advantages,sensing mechanisms,and potential applications of 2D materials in wearable biodevice fabrication.Following this,we systematically discuss state-of-the-art biodevices based on 2D materials for monitoring various physiological signals within the human body.Special attention is given to showcasing the integration of multi-functionality in 2D smart devices,mainly including self-power supply,integrated diagnosis/treatment,and human–machine interaction.Finally,the review concludes with a concise summary of existing challenges and prospective solutions concerning the utilization of2D materials for advanced biodevices.
文摘A functional interlayer based on two-dimensional(2D)porous modified vermiculite nanosheets(PVS)was obtained by acid-etching vermiculite nanosheets.The as-obtained 2D porous nanosheets exhibited a high specific surface area of 427 m^(2)·g^(-1)and rich surface active sites,which help restrain polysulfides(LiPSs)through good physi-cal and chemical adsorption,while simultaneously accelerating the nucleation and dissolution kinetics of Li_(2)S,effec-tively suppressing the shuttle effect.The assembled lithium-sulfur batteries(LSBs)employing the PVS-based inter-layer delivered a high initial discharge capacity of 1386 mAh·g^(-1)at 0.1C(167.5 mAh·g^(-1)),long-term cycling stabil-ity,and good rate property.
基金supported by Beijing Natural Science Foundation(Nos.2232037 and 2242035)the National Natural Science Foundation of China(Nos.22005012,22105012 and 51803183)+1 种基金Chunhui Plan Cooperative Project of Ministry of Education(No.202201298)the China Postdoctoral Science Foundation Funded Project(No.2023M733520).
文摘Lithium-sulfur(Li-S)batteries with high energy density and capacity have garnered significant research attention among various energy storage devices.However,the shuttle effect of polysulfides(LiPSs)remains a major challenge for their practical application.The design of battery separators has become a key aspect in addressing the challenge.MXenes,a promising two-dimensional(2D)material,offer exceptional conductivity,large surface area,high mechanical strength,and active sites for surface reactions.When assembled into layered films,MXenes form highly tunable two-dimensional channels ranging from a few angstroms to over 1 nm.These nanoconfined channels are instrumental in facilitating lithium-ion transport while effectively impeding the shuttle effect of LiPSs,which are essential for improving the specific capacity and cyclic stability of Li-S batteries.Substantial progress has been made in developing MXenes-based separators for Li-S batteries,yet there remains a research gap in summarizing advancements from the perspective of interlayer engineering.This entails maintaining the 2D nanochannels of layered MXenes-based separators while modulating the physicochemical environment within the MXenes interlayers through targeted modifications.This review highlights advancements in in situ modification of MXenes and their integration with 0D,1D,and 2D materials to construct laminated nanocomposite separators for Li-S batteries.The future development directions of MXenes-based materials in Li-S energy storage devices are also outlined,to drive further advancements in MXenes for Li-S battery separators.
文摘The published article titled“Comparison of Structural Probabilistic and Non-Probabilistic Reliability Computational Methods under Big Data Condition”[1]has been retracted from Structural Durability&Health Monitoring(SDHM),Vol.16,No.2,2022,pp.129–143.
基金supported by the National Key Research and Development Project(No.2019YFA0705403)the National Natural Science Foundation of China(No.T2293693,52273311)+2 种基金the Guangdong Basic and Applied Basic Research Foundation(No.2020B0301030002)and the Shenzhen Basic Research Project(Nos.WDZC20200824091903001,JSGG20220831105402004,JCYJ20220818100806014)Shenzhen Major Science and Technology Projects(Nos.KCXFZ20240903094013018,KCXFZ20240903094203005)。
文摘Titanium dioxide(TiO_(2))has been an important protective ingredient in mineral-based sunscreens since the 1990s.However,traditional TiO_(2)nanoparticle formulations have seen little improvement over the past decades and continue to face persistent challenges related to light transmission,biosafety,and visual appearance.Here,we report the discovery of two-dimensional(2D)TiO_(2),characterized by a micro-sized lateral dimension(~1.6μm)and atomic-scale thickness,which fundamentally resolves these long-standing issues.The 2D structure enables exceptional light management,achieving 80%visible light transparency—rendering it nearly invisible on the skin—while maintaining UV-blocking performance comparable to unmodified rutile TiO_(2)nanoparticles.Its larger lateral size results in a two-orders-of-magnitude reduction in skin penetration(0.96 w/w%),significantly enhancing biosafety.Moreover,the unique layered architecture inherently suppresses the generation of reactive oxygen species(ROS)under sunlight exposure,reducing the ROS generation rate by 50-fold compared to traditional TiO_(2)nanoparticles.Through precise metal element modulation,we further developed the first customizable sunscreen material capable of tuning UV protection ranges and automatically matching diverse skin tones.The 2D TiO_(2)offers a potentially transformative approach to modern sunscreen formulation,combining superior UV protection,enhanced safety and a natural appearance.
基金the Young Investigator Group“Artificial Intelligence for Probabilistic Weather Forecasting”funded by the Vector Stiftungfunding from the Federal Ministry of Education and Research(BMBF)and the Baden-Württemberg Ministry of Science as part of the Excellence Strategy of the German Federal and State Governments。
文摘Weather forecasts from numerical weather prediction models play a central role in solar energy forecasting,where a cascade of physics-based models is used in a model chain approach to convert forecasts of solar irradiance to solar power production.Ensemble simulations from such weather models aim to quantify uncertainty in the future development of the weather,and can be used to propagate this uncertainty through the model chain to generate probabilistic solar energy predictions.However,ensemble prediction systems are known to exhibit systematic errors,and thus require post-processing to obtain accurate and reliable probabilistic forecasts.The overarching aim of our study is to systematically evaluate different strategies to apply post-processing in model chain approaches with a specific focus on solar energy:not applying any post-processing at all;post-processing only the irradiance predictions before the conversion;post-processing only the solar power predictions obtained from the model chain;or applying post-processing in both steps.In a case study based on a benchmark dataset for the Jacumba solar plant in the U.S.,we develop statistical and machine learning methods for postprocessing ensemble predictions of global horizontal irradiance(GHI)and solar power generation.Further,we propose a neural-network-based model for direct solar power forecasting that bypasses the model chain.Our results indicate that postprocessing substantially improves the solar power generation forecasts,in particular when post-processing is applied to the power predictions.The machine learning methods for post-processing slightly outperform the statistical methods,and the direct forecasting approach performs comparably to the post-processing strategies.
基金supported by Basic Science Research Program through the National Natural Science Foundation of China(Grant No.61867003).
文摘As the proportion of newenergy increases,the traditional cumulant method(CM)produces significant errorswhen performing probabilistic load flow(PLF)calculations with large-scale wind power integrated.Considering the wind speed correlation,a multi-scenario PLF calculation method that combines random sampling and segmented discrete wind farm power was proposed.Firstly,based on constructing discrete scenes of wind farms,the Nataf transform is used to handle the correlation between wind speeds.Then,the random sampling method determines the output probability of discrete wind power scenarios when wind speed exhibits correlation.Finally,the PLF calculation results of each scenario areweighted and superimposed following the total probability formula to obtain the final power flow calculation result.Verified in the IEEE standard node system,the absolute percent error(APE)for the mean and standard deviation(SD)of the node voltages and branch active power are all within 1%,and the average root mean square(AMSR)values of the probability curves are all less than 1%.
基金Supported by National Natural Science Foundation of China(Grant No.52205072).
文摘Owing to their rolling friction,two-dimensional piston pumps are highly suitable as power components for electro-hydrostatic actuators(EHAs).These pumps are particularly advantageous for applications requiring high efficiency and reliability.However,the ambiguity surrounding the output flow characteristics of individual two-dimensional pumps poses a significant challenge in achieving precise closed-loop control of the EHA positions.To address this issue,this study established a comprehensive numerical model that included gap leakage to analyze the impact of leakage on the output flow characteristics of a two-dimensional piston pump.The validity of the numerical analysis was indirectly confirmed through meticulous measurements of the leakage and volumetric efficiency,ensuring robust results.The research findings indicated that,at lower pump speeds,leakage significantly affected the output flow rate,leading to potential inefficiencies in the system.Conversely,at higher rotational speeds,the impact of leakage was less pronounced,implying that the influence of leakage on the pump outlet flow must be carefully considered and managed for EHAs to perform position servo control.Additionally,the research demonstrates that two-dimensional motion does not have a unique or additional effect on pump leakage,thus simplifying the design considerations.Finally,the study concluded that maintaining an oil-filled leakage environment is beneficial because it helps reduce the impact of leakage and enhances the overall volumetric efficiency of the pump system.
基金supported by the National Natural Science Foundation of China(Nos.52272290,21972030,52073119,and 52373210)the Natural Science Foundation of Jilin Province(No.20230101029JC)+1 种基金the Fundamental Research Program of Shanxi Province(No.202303021212159)the Monash University Malaysia–ASEAN grant(No.ASE-000010)。
文摘Environmental catalysis has been considered one of the important research topics.Some technologies(e.g.,photocatalysis and electrocatalysis)have been intensively developed with the advance of synthetic technologies of catalytical materials.In 2019,we discussed the development trend of this field,and wrote a roadmap on this topic in Chinese Chemical Letters(30(2019)2065-2088).Nowadays,we discuss it again from a new viewpoint along this road.In this paper,several subtopics are discussed,e.g.,photocatalysis based on titanium dioxide,violet phosphorus,graphitic carbon and covalent organic frameworks,electrocatalysts based on carbon,metal-and covalent-organic framework.Finally,we hope that this roadmap can enrich the development of two-dimensional materials in environmental catalysis with novel understanding,and give useful inspiration to explore new catalysts for practical applications.
基金supported by the Natural Science Foundation of Beijing Municipality(No.8222004),Chinathe National Natural Science Foundation of China(No.51978019)+3 种基金the Natural Science Foundation of Henan Province(No.252300420445),Chinathe Doctoral Research Initiation Fund of Henan University of Science and Technology(No.4007/13480062),Chinathe Henan Postdoctoral Foundation(No.13554005),Chinathe Joint Fund of Science and Technology R&D Program of Henan Province(No.232103810082),China。
文摘Sandy cobble soil exhibits pronounced heterogeneity.The assessment of the uncertainty surrounding its properties is crucial for the analysis of settlement characteristics resulting from volume loss during shield tunnelling.In this study,a series of probabilistic analyses of surface and subsurface settlements was conducted considering the spatial variability of the friction angle and reference stiffness modulus,under different volumetric block proportions(Pv)and tunnel volume loss rates(ηt).The non-intrusive random finite difference method was used to investigate the probabilistic characteristics of maximum surface settlement,width of subsurface settlement trough,maximum subsurface settlement,and subsurface soil volume loss rate through Monte Carlo simulations.Additionally,a comparison between stochastic and deterministic analysis results is presented to underscore the significance of probabilistic analysis.Parametric analyses were subsequently conducted to investigate the impacts of the key input parameters in random fields on the settlement characteristics.The results indicate that scenarios with higher Pv or greaterηt result in a higher dispersion of stochastic analysis results.Neglecting the spatial variability of soil properties and relying solely on the mean values of material parameters for deterministic analysis may result in an underestimation of surface and subsurface settlements.From a probabilistic perspective,deterministic analysis alone may prove inadequate in accurately capturing the volumetric deformation mode of the soil above the tunnel crown,potentially affecting the prediction of subsurface settlement.
基金supported by the Key Project of the National Natural Science Foundation of China(Grant No.U1809210)the International Science Technology Cooperation Program of China(Grant No.2014DFR51160)+3 种基金the One Belt and One Road International Cooperation Project from the Key Research and Development Program of Zhejiang Province,China(Grant No.2018C04021)the National Natural Science Foundation of China(Grant Nos.50972129,50602039,and 52102052)the Fund from Institute of Wenzhou,Zhejiang University(Grant Nos.XMGL-CX-202305 and XMGLKJZX-202307)the Project from Tanghe Scientific&Technology Company(Grant No.KYY-HX-20230024).
文摘It is a key challenge to prepare two-dimensional diamond(2D-diamond).Herein,we develop a method for synthesizing 2D-diamond by depositing monodisperse tantalum(Ta)atoms onto graphene substrates using a hot-filament chemical vapor deposition setup,followed by annealing treatment under different temperatures at ambient pressure.The results indicate that when the annealing temperature increases from 700℃ to 1000℃,the size of the 2D-diamond found in the samples gradually increases from close to 20 nm to around 30 nm.Meanwhile,the size and number of amorphous carbon spheres and Ta-containing compounds between the graphene layers gradually increase.As the annealing temperature continues to rise to 1100℃,a significant aggregation of Ta-containing compounds is observed in the samples,with no diamond structure detected.This further confirms that monodisperse Ta atoms play a key role in graphene phase transition into 2D-diamond.This study provides a novel method for the ambient-pressure phase transition of graphene into 2D-diamond.
基金supported by the National Key Research&Development Program of China(Grant Nos.2022YFA1403500 and 2021YFA1400500)the National Science Foundation of China(Grant Nos.62321004,12234001,and 12474215)+1 种基金supported by New Cornerstone Science Foundationa fellowship and a CRF award from the Research Grants Council of the Hong Kong Special Administrative Region,China(Grant Nos.HKUST SRFS2324-6S01 and C7037-22GF)。
文摘Electron-hole interactions play a crucial role in determining the optoelectronic properties of materials,and in lowdimensional systems this is especially true due to the decrease of screening.In this review,we focus on one unique quantum phase induced by the electron-hole interaction in two-dimensional systems,known as“exciton insulators”(EIs).Although this phase of matter has been studied for more than half a century,suitable platforms for its stable realization remain scarce.We provide an overview of the strategies to realize EIs in accessible materials and structures,along with a discussion on some unique properties of EIs stemming from the band structures of these materials.Additionally,signatures in experiments to distinguish EIs are discussed.
基金support from the Key Program of the National Natural Science Foundation of China(No.12232004)the Training Program of the Sichuan Province Science and the Technology Innovation Seedling Project(No.MZGC20230012)are acknowledged.
文摘The development of modern engineering components and equipment features large size,intricate shape and long service life,which places greater demands on valid methods for fatigue performance analysis.Achieving a smooth transformation between small-scale laboratory specimens’fatigue properties and full-scale engineering components’fatigue strength has been a long-term challenge.In this work,two dominant factors impeding the smooth transformation—notch and size effect were experimentally studied,in which fatigue tests on Al 7075-T6511(a very high-strength aviation alloy)notched specimens of different scales were carried out.Fractography analyses identified the evidence of the size effect on notch fatigue damage evolution.Accordingly,the Energy Field Intensity(EFI)initially developed for multiaxial notch fatigue analysis was improved by utilizing the volume ratio of the Effective Damage Zones(EDZs)for size effect correction.In particular,it was extended to a probabilistic model considering the inherent variability of the fatigue phenomenon.The experimental data of Al 7075-T6511 notched specimens and the model-predicted results were compared,indicating the high potential of the proposed approach in fatigue evaluation under combined notch and size effects.
文摘The pursuit of sustainable hydrogen production has positioned water electrolysis as a cornerstone technology for global carbon neutrality.However,sluggish kinetics,catalyst scarcity,and system integration challenges hinder its widespread deployment.Ultrathin two-dimensional(2D)materials,with their atomically exposed surfaces,tunable electronic structures,and defect-engineering capabilities,present unique opportunities for next-generation electrocatalysts.This review provides an integrated overview of ultrathin 2D electrocatalysts,discussing their structural diversity,synthetic routes,structure-activity relationships,and mechanistic understanding in water electrolysis processes.Special focus is placed on the translation of 2D materials from laboratory research to practical device implementation,emphasizing challenges such as scalable fabrication,interfacial engineering,and operational durability in realistic electrolyzer environments.The role of advanced characterization techniques in capturing dynamic structural changes and active site evolution is discussed.Finally,we outline future research directions,emphasizing the synergy of machine learning-driven materials discovery,advanced operando characterization,and scalable system integration to accelerate the industrial translation of 2D electrocatalysts for green hydrogen production.
文摘Protocol Reverse Engineering(PRE)is of great practical importance in Internet security-related fields such as intrusion detection,vulnerability mining,and protocol fuzzing.For unknown binary protocols having fixed-length fields,and the accurate identification of field boundaries has a great impact on the subsequent analysis and final performance.Hence,this paper proposes a new protocol segmentation method based on Information-theoretic statistical analysis for binary protocols by formulating the field segmentation of unsupervised binary protocols as a probabilistic inference problem and modeling its uncertainty.Specifically,we design four related constructions between entropy changes and protocol field segmentation,introduce random variables,and construct joint probability distributions with traffic sample observations.Probabilistic inference is then performed to identify the possible protocol segmentation points.Extensive trials on nine common public and industrial control protocols show that the proposed method yields higher-quality protocol segmentation results.
基金supported by National Natural Science Foundation of China(72288101,72361137002,and 72101018)the Dutch Research Council(NWO Grant 482.22.01).
文摘Vehicle electrification,an important method for reducing carbon emissions from road transport,has been promoted globally.In this study,we analyze how individuals adapt to this transition in transportation and its subsequent impact on urban structure.Considering the varying travel costs associated with electric and fuel vehicles,we analyze the dynamic choices of households concerning house locations and vehicle types in a two-dimensional monocentric city.A spatial equilibrium is developed to model the interactions between urban density,vehicle age and vehicle type.An agent-based microeconomic residential choice model dynamically coupled with a house rent market is developed to analyze household choices of home locations and vehicle energy types,considering vehicle ages and competition for public charging piles.Key findings from our proposed models show that the proportion of electric vehicles(EVs)peaks at over 50%by the end of the first scrappage period,accompanied by more than a 40%increase in commuting distance and time compared to the scenario with only fuel vehicles.Simulation experiments on a theoretical grid indicate that heterogeneity-induced residential segregation can lead to urban sprawl and congestion.Furthermore,households with EVs tend to be located farther from the city center,and an increase in EV ownership contributes to urban expansion.Our study provides insights into how individuals adapt to EV transitions and the resulting impacts on home locations and land use changes.It offers a novel perspective on the dynamic interactions between EV adoption and urban development.
基金supported by the Natural Science Foundation of Shandong Province(Grant No.ZR2020MA092)the Innovation Project for Graduate Students of Ludong University(Grant No.IPGS2024-048).
文摘The diffusion trajectory of a Brownian particle passing over the saddle point of a two-dimensional quadratic potential energy surface is tracked in detail according to the deep learning strategies.Generative adversarial networks(GANs)emanating in the category of machine learning(ML)frameworks are used to generate and assess the rationality of the data.While their optimization is based on the long short-term memory(LSTM)strategies.In addition to drawing a heat map,the optimal path of two-dimensional(2D)diffusion is simultaneously demonstrated in a stereoscopic space.The results of our simulation are completely consistent with the previous theoretical predictions.
基金supported by Key Technology Research and Application of Online Control Simulation and Intelligent Decision Making for Active Distribution Network(5108-202218280A-2-377-XG).
文摘Aiming at the problems of increasing uncertainty of low-carbon generation energy in active distribution network(ADN)and the difficulty of security assessment of distribution network,this paper proposes a two-phase scheduling model for flexible resources in ADN based on probabilistic risk perception.First,a full-cycle probabilistic trend sequence is constructed based on the source-load historical data,and in the day-ahead scheduling phase,the response interval of the flexibility resources on the load and storage side is optimized based on the probabilistic trend,with the probability of the security boundary as the security constraint,and with the economy as the objective.Then in the intraday phase,the core security and economic operation boundary of theADNis screened in real time.Fromthere,it quantitatively senses the degree of threat to the core security and economic operation boundary under the current source-load prediction information,and identifies the strictly secure and low/high-risk time periods.Flexibility resources within the response interval are dynamically adjusted in real-time by focusing on high-risk periods to cope with future core risks of the distribution grid.Finally,the improved IEEE 33-node distribution system is simulated to obtain the flexibility resource scheduling scheme on the load and storage side.Thescheduling results are evaluated from the perspectives of risk probability and flexible resource utilization efficiency,and the analysis shows that the scheduling model in this paper can promote the consumption of low-carbon energy from wind and photovoltaic sourceswhile reducing the operational risk of the distribution network.
基金Project supported by the National Key R&D Program of China (Grant No. 2019YFA0307800)the National Natural Science Foundation of China (Grant No. 12074377)+2 种基金Fundamental Research Funds for the Central Universities,the International Partnership Program of Chinese Academy of Sciences (Grant No. 211211KYSB20210007)the China Postdoctoral Science Foundation (Grant No. 2024M753465)the Postdoctoral Fellowship Program (Grade C) of China Postdoctoral Science Foundation (Grant No. GZC20241893)。
文摘Moiré superlattices have revolutionized the study of two-dimensional materials, enabling unprecedented control over their electronic, magnetic, optical, and mechanical properties. This review provides a comprehensive analysis of the latest advancements in moiré physics, focusing on the formation of moiré superlattices due to rotational misalignment or lattice mismatch in two-dimensional materials. These superlattices induce flat band structures and strong correlation effects,leading to the emergence of exotic quantum phases, such as unconventional superconductivity, correlated insulating states,and fractional quantum anomalous Hall effects. The review also explores the underlying mechanisms of these phenomena and discusses the potential technological applications of moiré physics, offering insights into future research directions in this rapidly evolving field.
基金The work was performed based on the research project no.2023/51/D/ST10/01956,financed by the National Science Center,Poland.
文摘The study presents the results of over 30,000 numerical analyses on the stability of lava tubes under lunar conditions.The research considered random irregularities in cave geometry and their impact on stability,with a particular focus on the geometric characteristics of identified collapses.We propose a procedure for extracting the collapse areas and integrating it into the stability analysis results.The results were examined to assess the possibility of describing the geometry characteristics of collapses using commonly applied probability density distributions,such as normal or lognormal distribution.Our aim is to facilitate future risk assessment of lunar caves.Such an assessment will be essential prior to robotically exploring caves beneath the lunar surface and can be extended to be used for planetary caves beyond the Moon.Our findings indicate that several collapse characteristics can be represented by unimodal probability density distributions,which could significantly simplify the candidate selection process.Based on our results,we also highlight several key directions for future research and suggested implications related to their future exploration.
