To enhance the computational efficiency of spatio-temporally discretized phase-field models,we present a high-speed solver specifically designed for the Poisson equations,a component frequently used in the numerical c...To enhance the computational efficiency of spatio-temporally discretized phase-field models,we present a high-speed solver specifically designed for the Poisson equations,a component frequently used in the numerical computation of such models.This efficient solver employs algorithms based on discrete cosine transformations(DCT)or discrete sine transformations(DST)and is not restricted by any spatio-temporal schemes.Our proposed methodology is appropriate for a variety of phase-field models and is especially efficient when combined with flow field systems.Meanwhile,this study has conducted an extensive numerical comparison and found that employing DCT and DST techniques not only yields results comparable to those obtained via the Multigrid(MG)method,a conventional approach used in the resolution of the Poisson equations,but also enhances computational efficiency by over 90%.展开更多
Accurately simulating mesoscale convective systems(MCSs)is essential for predicting global precipitation patterns and extreme weather events.Despite the ability of advanced models to reproduce MCS climate statistics,c...Accurately simulating mesoscale convective systems(MCSs)is essential for predicting global precipitation patterns and extreme weather events.Despite the ability of advanced models to reproduce MCS climate statistics,capturing extreme storm cases over complex terrain remains challenging.This study utilizes the Global–Regional Integrated Forecast System(GRIST)with variable resolution to simulate an eastward-propagating MCS event.The impact of three microphysics schemes,including two single-moment schemes(WSM6,Lin)and one double-moment scheme(Morrison),on the model sensitivity of MCS precipitation simulations is investigated.The results demonstrate that while all the schemes capture the spatial distribution and temporal variation of MCS precipitation,the Morrison scheme alleviates overestimated precipitation compared to the Lin and WSM6 schemes.The ascending motion gradually becomes weaker in the Morrison scheme during the MCS movement process.Compared to the runs with convection parameterization,the explicit-convection setup at 3.5-km resolution reduces disparities in atmospheric dynamics due to microphysics sensitivity in terms of vertical motions and horizontal kinetic energy at the high-wavenumber regimes.The explicit-convection setup more accurately captures the propagation of both main and secondary precipitation centers during the MCS development,diminishing the differences in both precipitation intensity and propagation features between the Morrison and two single-moment schemes.These findings underscore the importance of microphysics schemes for global nonhydrostatic modeling at the kilometer scale.The role of explicit convection for reducing model uncertainty is also outlined.展开更多
This paper presents an explicit formula based on reparameterization technique for progressively computing a simple root of a smooth function,which may have wide applications in robotics,geomagnetic navigation,geometri...This paper presents an explicit formula based on reparameterization technique for progressively computing a simple root of a smooth function,which may have wide applications in robotics,geomagnetic navigation,geometric processing and computer graphics.Comparing with Newton-like method,it can achieve convergence rate 2 by adding one more functional evaluation,improve the computational stability and ensure the convergence,and also obtain higher convergence rate and higher efficiency index.Compared with clipping methods for polynomials,it doesn't need to bound the polynomials,directly bound the roots and can also work well for non-polynomial functions with much higher computational efficiency.Comparing with previous progressive methods,it achieves a much higher computational efficiency and is extended to solve bivariate equation system.Numerical examples show its much better performance on approximation error,computational efficiency and computational stability.展开更多
In recent years,there has been a growing demand for more efficient and robust control strategies in cooperative multi-robot systems.This paper introduces the cascade explicit tube model predictive controller(CET-MPC),...In recent years,there has been a growing demand for more efficient and robust control strategies in cooperative multi-robot systems.This paper introduces the cascade explicit tube model predictive controller(CET-MPC),a control architecture designed specifically for distributed aerial robot systems.By integrating an explicit model predictive controller(MPC)with a tube MPC,our approach significantly reduces online computational demands while enhancing robustness against disturbances such as wind and measurement noise,as well as uncertainties in inertia parameters.Further,we incorporate a cascade controller to minimize steady-state errors and improve system performance dynamically.The results of this assessment provide valuable insights into the effectiveness and reliability of the CET-MPC approach under realistic operating conditions.The simulation results of flight scenarios for multi-agent quadrotors demonstrate the controller’s stability and accurate tracking of the desired path.By addressing the complexities of quadrotors’six degrees of freedom,this controller serves as a versatile solution applicable to a wide range of multi-robot systems with varying degrees of freedom,demonstrating its adaptability and scalability beyond the quadrotor domain.展开更多
Current gas well decline analysis under boundary-dominated flow(BDF)is largely based on the Arps'empirical hyperbolic decline model and the analytical type curve tools associated with pseudo-functions.Due to the n...Current gas well decline analysis under boundary-dominated flow(BDF)is largely based on the Arps'empirical hyperbolic decline model and the analytical type curve tools associated with pseudo-functions.Due to the nonlinear flow behavior of natural gas,these analysis methods generally require iterative calculations.In this study,the dimensionless gas rate(qg/qgi)is introduced,and an explicit method to determine the average reservoir pressure and the original gas in place(OGIP)for a volumetric gas reservoir is proposed.We show that the dimensionless gas rate in the BDF is only the function of the gas PVT parameters and reservoir pressure.Step-by-step analysis procedures are presented that enable explicit and straightforward estimation of average reservoir pressure and OGIP by straight-line analysis.Compared with current techniques,this methodology avoids the iterative calculation of pseudo-time and pseudo-pressure functions,lowers the multiplicity of type curve analysis,and is applicable in different production situations(constant/variable gas flow rate,constant/variable bottom-hole pressure)with a broad range of applications and ease of use.Reservoir numerical simulation and field examples are thoroughly discussed to highlight the capabilities of the proposed approach.展开更多
Electronic control suspension(ECS)systems are of significance to ride comfort and handling stability of ground vehicles.However,ECS systems may pose unreasonable safety risks due to performance inadequacies or imprope...Electronic control suspension(ECS)systems are of significance to ride comfort and handling stability of ground vehicles.However,ECS systems may pose unreasonable safety risks due to performance inadequacies or improper use by drivers,which are referred to as safety of the intended functionality(SOTIF)issues.Aiming to address the inadequate performance of the ECS system,this study proposes a model predictive control(MPC)method,with a particular focus on ensuring SOTIF.First,Systems theoretic process analysis(STPA)is utilized to assess the SOTIF of the ECS system and the ECS system control architecture is built.Then,Models including the input model,lateral and vertical coupled dynamics model,and nonlinear actuator model are established.In addition,an MPC strategy with explicit dynamic constraints is designed,incorporating the dynamic mechanical performance boundaries of ECS actuators into the constraints of the controller.Subsequently,a hardware-in-the-loop testing platform is constructed for the ECS system to conduct simulation experiments under various operating conditions.Results demonstrate that the designed control strategy effectively mitigates performance inadequacies of the suspension system,significantly enhancing its overall functionality and safety.展开更多
Inferring phylogenetic trees from molecular sequences is a cornerstone of evolutionary biology.Many standard phylogenetic methods(such as maximum-likelihood[ML])rely on explicit models of sequence evolution and thus o...Inferring phylogenetic trees from molecular sequences is a cornerstone of evolutionary biology.Many standard phylogenetic methods(such as maximum-likelihood[ML])rely on explicit models of sequence evolution and thus often suffer from model misspecification or inadequacy.The on-rising deep learning(DL)techniques offer a powerful alternative.Deep learning employs multi-layered artificial neural networks to progressively transform input data into more abstract and complex representations.DL methods can autonomously uncover meaningful patterns from data,thereby bypassing potential biases introduced by predefined features(Franklin,2005;Murphy,2012).Recent efforts have aimed to apply deep neural networks(DNNs)to phylogenetics,with a growing number of applications in tree reconstruction(Suvorov et al.,2020;Zou et al.,2020;Nesterenko et al.,2022;Smith and Hahn,2023;Wang et al.,2023),substitution model selection(Abadi et al.,2020;Burgstaller-Muehlbacher et al.,2023),and diversification rate inference(Voznica et al.,2022;Lajaaiti et al.,2023;Lambert et al.,2023).In phylogenetic tree reconstruction,PhyDL(Zou et al.,2020)and Tree_learning(Suvorov et al.,2020)are two notable DNN-based programs designed to infer unrooted quartet trees directly from alignments of four amino acid(AA)and DNA sequences,respectively.展开更多
The existing research on the path following of the autonomous electric vehicle(AEV)mainly focuses on the path planning and the kinematic control.However,the dynamic control with the state observation and the communica...The existing research on the path following of the autonomous electric vehicle(AEV)mainly focuses on the path planning and the kinematic control.However,the dynamic control with the state observation and the communication delay is usually ignored,so the path following performance of the AEV cannot be ensured.This article studies the observer-based path following control strategy for the AEV with the communication delay via a robust explicit model predictive control approach.Firstly,a projected interval unscented Kalman filter is proposed to observe the vehicle sideslip angle and yaw rate.The observer considers the state constraints during the observation process,and the robustness of the observer is also considered.Secondly,an explicit model predictive control is designed to reduce the computational complexity.Thirdly,considering the efficiency of the information transmission,the influence of the communication delay is considered when designing the observer-based path following control strategy.Finally,the numerical simulation and the hardware-in-the-loop test are conducted to examine the effectiveness and practicability of the proposed strategy.展开更多
Dual atomic catalysts(DAC),particularly copper(Cu_(2))-based nitrogen(N)doped graphene,show great potential to effectively convert CO_(2)and nitrate(NO_(3)-)into important industrial chemicals such as ethylene,glycol,...Dual atomic catalysts(DAC),particularly copper(Cu_(2))-based nitrogen(N)doped graphene,show great potential to effectively convert CO_(2)and nitrate(NO_(3)-)into important industrial chemicals such as ethylene,glycol,acetamide,and urea through an efficient catalytical process that involves C–C and C–N coupling.However,the origin of the coupling activity remained unclear,which substantially hinders the rational design of Cu-based catalysts for the N-integrated CO_(2)reduction reaction(CO_(2)RR).To address this challenge,this work performed advanced density functional theory calculations incorporating explicit solvation based on a Cu_(2)-based N-doped carbon(Cu_(2)N_(6)C_(10))catalyst for CO_(2)RR.These calculations are aimed to gain insight into the reaction mechanisms for the synthesis of ethylene,acetamide,and urea via coupling in the interfacial reaction micro-environment.Due to the sluggishness of CO_(2),the formation of a solvation electric layer by anions(F^(-),Cl^(-),Br^(-),and I^(-))and cations(Na+,Mg^(2+),K+,and Ca^(2+))leads to electron transfer towards the Cu surface.This process significantly accelerates the reduction of CO_(2).These results reveal that*CO intermediates play a pivotal role in N-integrated CO_(2)RR.Remarkably,the Cu_(2)-based N-doped carbon catalyst examined in this study has demonstrated the most potential for C–N coupling to date.Our findings reveal that through the process of a condensation reaction between*CO and NH_(2)OH for urea synthesis,*NO_(3)-is reduced to*NH_(3),and*CO_(2)to*CCO at dual Cu atom sites.This dual-site reduction facilitates the synthesis of acetamide through a nucleophilic reaction between NH_(3)and the ketene intermediate.Furthermore,we found that the I-and Mg^(2+)ions,influenced by pH,were highly effective for acetamide and ammonia synthesis,except when F-and Ca^(2+)were present.Furthermore,the mechanisms of C–N bond formation were investigated via ab-initio molecular dynamics simulations,and we found that adjusting the micro-environment can change the dominant side reaction,shifting from hydrogen production in acidic conditions to water reduction in alkaline ones.This study introduces a novel approach using ion-H_(2)O cages to significantly enhance the efficiency of C–N coupling reactions.展开更多
In recent years,machine learning(ML)techniques have been shown to be effective in accelerating the development process of optoelectronic devices.However,as"black box"models,they have limited theoretical inte...In recent years,machine learning(ML)techniques have been shown to be effective in accelerating the development process of optoelectronic devices.However,as"black box"models,they have limited theoretical interpretability.In this work,we leverage symbolic regression(SR)technique for discovering the explicit symbolic relationship between the structure of the optoelectronic Fabry-Perot(FP)laser and its optical field distribution,which greatly improves model transparency compared to ML.We demonstrated that the expressions explored through SR exhibit lower errors on the test set compared to ML models,which suggests that the expressions have better fitting and generalization capabilities.展开更多
The chief objective of the article is to learn the spatial characteristics of stress distribution around a shallow buried cylinder Karst cave in limestone strata.Firstly,taking into account the geometry of limestone f...The chief objective of the article is to learn the spatial characteristics of stress distribution around a shallow buried cylinder Karst cave in limestone strata.Firstly,taking into account the geometry of limestone formations,and the characteristics of Karst geomorphology in China,a spatial axialsymmetrical hollow model was established.Concurrently,combining available work and the concept of elasticity,the boundary conditions are determined.Subsequently,Love displacement method was introduced,the expressions of stress components were gained.The diagram characteristics of each stress component are summarized,which are affected by various influencing factors.Finally,in order to prove the rationality of the general solution,numerical simulation was carried out on the basis of practical engineering,and the maximum error is less than 5%.Thus,the analytical solution could represent the spatial characteristics of stress distribution around a shallow buried cylinder Karst cave in limestone strata.展开更多
This study aims to examine the explicit solution for calculating the Average Run Length(ARL)on the triple exponentially weighted moving average(TEWMA)control chart applied to autoregressive model(AR(p)),where AR(p)is ...This study aims to examine the explicit solution for calculating the Average Run Length(ARL)on the triple exponentially weighted moving average(TEWMA)control chart applied to autoregressive model(AR(p)),where AR(p)is an autoregressive model of order p,representing a time series with dependencies on its p previous values.Additionally,the study evaluates the accuracy of both explicit and numerical integral equation(NIE)solutions for AR(p)using the TEWMA control chart,focusing on the absolute percentage relative error.The results indicate that the explicit and approximate solutions are in close agreement.Furthermore,the study investigates the performance of exponentially weighted moving average(EWMA)and TEWMA control charts in detecting changes in the process,using the relative mean index(RMI)as a measure.The findings demonstrate that the TEWMA control chart outperforms the EWMA control chart in detecting process changes,especially when the value ofλis sufficiently large.In addition,an analysis using historical data from the SET index between January 2024 and May 2024 and historical data of global annual plastic production,the results of both data sets also emphasize the superior performance of the TEWMA control chart.展开更多
基金Supported by Shanxi Province Natural Science Research(202203021212249)Special/Youth Foundation of Taiyuan University of Technology(2022QN101)+3 种基金National Natural Science Foundation of China(12301556)Research Project Supported by Shanxi Scholarship Council of China(2021-029)International Cooperation Base and Platform Project of Shanxi Province(202104041101019)Basic Research Plan of Shanxi Province(202203021211129)。
文摘To enhance the computational efficiency of spatio-temporally discretized phase-field models,we present a high-speed solver specifically designed for the Poisson equations,a component frequently used in the numerical computation of such models.This efficient solver employs algorithms based on discrete cosine transformations(DCT)or discrete sine transformations(DST)and is not restricted by any spatio-temporal schemes.Our proposed methodology is appropriate for a variety of phase-field models and is especially efficient when combined with flow field systems.Meanwhile,this study has conducted an extensive numerical comparison and found that employing DCT and DST techniques not only yields results comparable to those obtained via the Multigrid(MG)method,a conventional approach used in the resolution of the Poisson equations,but also enhances computational efficiency by over 90%.
基金supported by the National Natural Science Foundation of China(Grant No.42305169)the Basic Research Fund of CAMS(Grant No.2023Y001)the National Key Scientific and Technological Infrastructure project“Earth System Numerical Simulation Facility”(Earth Lab)。
文摘Accurately simulating mesoscale convective systems(MCSs)is essential for predicting global precipitation patterns and extreme weather events.Despite the ability of advanced models to reproduce MCS climate statistics,capturing extreme storm cases over complex terrain remains challenging.This study utilizes the Global–Regional Integrated Forecast System(GRIST)with variable resolution to simulate an eastward-propagating MCS event.The impact of three microphysics schemes,including two single-moment schemes(WSM6,Lin)and one double-moment scheme(Morrison),on the model sensitivity of MCS precipitation simulations is investigated.The results demonstrate that while all the schemes capture the spatial distribution and temporal variation of MCS precipitation,the Morrison scheme alleviates overestimated precipitation compared to the Lin and WSM6 schemes.The ascending motion gradually becomes weaker in the Morrison scheme during the MCS movement process.Compared to the runs with convection parameterization,the explicit-convection setup at 3.5-km resolution reduces disparities in atmospheric dynamics due to microphysics sensitivity in terms of vertical motions and horizontal kinetic energy at the high-wavenumber regimes.The explicit-convection setup more accurately captures the propagation of both main and secondary precipitation centers during the MCS development,diminishing the differences in both precipitation intensity and propagation features between the Morrison and two single-moment schemes.These findings underscore the importance of microphysics schemes for global nonhydrostatic modeling at the kilometer scale.The role of explicit convection for reducing model uncertainty is also outlined.
基金Supported by the National Natural Science Foundation of China (61972120)。
文摘This paper presents an explicit formula based on reparameterization technique for progressively computing a simple root of a smooth function,which may have wide applications in robotics,geomagnetic navigation,geometric processing and computer graphics.Comparing with Newton-like method,it can achieve convergence rate 2 by adding one more functional evaluation,improve the computational stability and ensure the convergence,and also obtain higher convergence rate and higher efficiency index.Compared with clipping methods for polynomials,it doesn't need to bound the polynomials,directly bound the roots and can also work well for non-polynomial functions with much higher computational efficiency.Comparing with previous progressive methods,it achieves a much higher computational efficiency and is extended to solve bivariate equation system.Numerical examples show its much better performance on approximation error,computational efficiency and computational stability.
文摘In recent years,there has been a growing demand for more efficient and robust control strategies in cooperative multi-robot systems.This paper introduces the cascade explicit tube model predictive controller(CET-MPC),a control architecture designed specifically for distributed aerial robot systems.By integrating an explicit model predictive controller(MPC)with a tube MPC,our approach significantly reduces online computational demands while enhancing robustness against disturbances such as wind and measurement noise,as well as uncertainties in inertia parameters.Further,we incorporate a cascade controller to minimize steady-state errors and improve system performance dynamically.The results of this assessment provide valuable insights into the effectiveness and reliability of the CET-MPC approach under realistic operating conditions.The simulation results of flight scenarios for multi-agent quadrotors demonstrate the controller’s stability and accurate tracking of the desired path.By addressing the complexities of quadrotors’six degrees of freedom,this controller serves as a versatile solution applicable to a wide range of multi-robot systems with varying degrees of freedom,demonstrating its adaptability and scalability beyond the quadrotor domain.
基金supported by the Young Elite Scientist Sponsorship Program by Beijing Association for Science and Technology,China(No.BYESS2023262)the Science Foundation of China University of Petroleum(Beijing),China(No.2462022BJRC004).
文摘Current gas well decline analysis under boundary-dominated flow(BDF)is largely based on the Arps'empirical hyperbolic decline model and the analytical type curve tools associated with pseudo-functions.Due to the nonlinear flow behavior of natural gas,these analysis methods generally require iterative calculations.In this study,the dimensionless gas rate(qg/qgi)is introduced,and an explicit method to determine the average reservoir pressure and the original gas in place(OGIP)for a volumetric gas reservoir is proposed.We show that the dimensionless gas rate in the BDF is only the function of the gas PVT parameters and reservoir pressure.Step-by-step analysis procedures are presented that enable explicit and straightforward estimation of average reservoir pressure and OGIP by straight-line analysis.Compared with current techniques,this methodology avoids the iterative calculation of pseudo-time and pseudo-pressure functions,lowers the multiplicity of type curve analysis,and is applicable in different production situations(constant/variable gas flow rate,constant/variable bottom-hole pressure)with a broad range of applications and ease of use.Reservoir numerical simulation and field examples are thoroughly discussed to highlight the capabilities of the proposed approach.
基金Supported by Anhui Provincial Key Research and Development Projects(Grant No.202304a05020087)the National Natural Science Foundation of China(Grant No.52272392)the Fundamental Research Funds for the Central Universities(Grant No.JZ2023YQTD0073).
文摘Electronic control suspension(ECS)systems are of significance to ride comfort and handling stability of ground vehicles.However,ECS systems may pose unreasonable safety risks due to performance inadequacies or improper use by drivers,which are referred to as safety of the intended functionality(SOTIF)issues.Aiming to address the inadequate performance of the ECS system,this study proposes a model predictive control(MPC)method,with a particular focus on ensuring SOTIF.First,Systems theoretic process analysis(STPA)is utilized to assess the SOTIF of the ECS system and the ECS system control architecture is built.Then,Models including the input model,lateral and vertical coupled dynamics model,and nonlinear actuator model are established.In addition,an MPC strategy with explicit dynamic constraints is designed,incorporating the dynamic mechanical performance boundaries of ECS actuators into the constraints of the controller.Subsequently,a hardware-in-the-loop testing platform is constructed for the ECS system to conduct simulation experiments under various operating conditions.Results demonstrate that the designed control strategy effectively mitigates performance inadequacies of the suspension system,significantly enhancing its overall functionality and safety.
基金supported by the National Key R&D Program of China(2022YFD1401600)the National Science Foundation for Distinguished Young Scholars of Zhejang Province,China(LR23C140001)supported by the Key Area Research and Development Program of Guangdong Province,China(2018B020205003 and 2020B0202090001).
文摘Inferring phylogenetic trees from molecular sequences is a cornerstone of evolutionary biology.Many standard phylogenetic methods(such as maximum-likelihood[ML])rely on explicit models of sequence evolution and thus often suffer from model misspecification or inadequacy.The on-rising deep learning(DL)techniques offer a powerful alternative.Deep learning employs multi-layered artificial neural networks to progressively transform input data into more abstract and complex representations.DL methods can autonomously uncover meaningful patterns from data,thereby bypassing potential biases introduced by predefined features(Franklin,2005;Murphy,2012).Recent efforts have aimed to apply deep neural networks(DNNs)to phylogenetics,with a growing number of applications in tree reconstruction(Suvorov et al.,2020;Zou et al.,2020;Nesterenko et al.,2022;Smith and Hahn,2023;Wang et al.,2023),substitution model selection(Abadi et al.,2020;Burgstaller-Muehlbacher et al.,2023),and diversification rate inference(Voznica et al.,2022;Lajaaiti et al.,2023;Lambert et al.,2023).In phylogenetic tree reconstruction,PhyDL(Zou et al.,2020)and Tree_learning(Suvorov et al.,2020)are two notable DNN-based programs designed to infer unrooted quartet trees directly from alignments of four amino acid(AA)and DNA sequences,respectively.
基金Supported by the National Key Research and Development Program of China(Grant No.2023YFE0204700)the National Natural Science Foundation of China(Grant Nos.52472402 and 52302469)+7 种基金the Guangdong Basic and Applied Basic Research Foundation(Grant Nos.2023A1515012327 and 2024A1515010449)the research grant of the University of Macao(Grant No.MYRG GRG2023-00235-FST-UMDF)Shandong Provincial Natural Science Foundation(Grant No.ZR2023ME133)the Fundamental Research Funds for the Central Universities(Grant No.N2403012)the Science and Technology Development Fund of Macao SAR(Grant No.0091/2023/AMJ)the China Postdoctoral Science Foundation(Grant Nos.2023M740538 and AM2024003)the Zhuhai Science and Technology Innovation Bureau(Grant No.2220004003107)the Yunfu Science and Technology Project(Grant No.2024090202).
文摘The existing research on the path following of the autonomous electric vehicle(AEV)mainly focuses on the path planning and the kinematic control.However,the dynamic control with the state observation and the communication delay is usually ignored,so the path following performance of the AEV cannot be ensured.This article studies the observer-based path following control strategy for the AEV with the communication delay via a robust explicit model predictive control approach.Firstly,a projected interval unscented Kalman filter is proposed to observe the vehicle sideslip angle and yaw rate.The observer considers the state constraints during the observation process,and the robustness of the observer is also considered.Secondly,an explicit model predictive control is designed to reduce the computational complexity.Thirdly,considering the efficiency of the information transmission,the influence of the communication delay is considered when designing the observer-based path following control strategy.Finally,the numerical simulation and the hardware-in-the-loop test are conducted to examine the effectiveness and practicability of the proposed strategy.
基金National Natural Science Foundation of China(U22B20149,22308376)Outstanding Young Scholars Foundation of China University of Petroleum(Beijing)(2462023BJRC015)Foundation of United Institute for Carbon Neutrality(CNIF20230209)。
文摘Dual atomic catalysts(DAC),particularly copper(Cu_(2))-based nitrogen(N)doped graphene,show great potential to effectively convert CO_(2)and nitrate(NO_(3)-)into important industrial chemicals such as ethylene,glycol,acetamide,and urea through an efficient catalytical process that involves C–C and C–N coupling.However,the origin of the coupling activity remained unclear,which substantially hinders the rational design of Cu-based catalysts for the N-integrated CO_(2)reduction reaction(CO_(2)RR).To address this challenge,this work performed advanced density functional theory calculations incorporating explicit solvation based on a Cu_(2)-based N-doped carbon(Cu_(2)N_(6)C_(10))catalyst for CO_(2)RR.These calculations are aimed to gain insight into the reaction mechanisms for the synthesis of ethylene,acetamide,and urea via coupling in the interfacial reaction micro-environment.Due to the sluggishness of CO_(2),the formation of a solvation electric layer by anions(F^(-),Cl^(-),Br^(-),and I^(-))and cations(Na+,Mg^(2+),K+,and Ca^(2+))leads to electron transfer towards the Cu surface.This process significantly accelerates the reduction of CO_(2).These results reveal that*CO intermediates play a pivotal role in N-integrated CO_(2)RR.Remarkably,the Cu_(2)-based N-doped carbon catalyst examined in this study has demonstrated the most potential for C–N coupling to date.Our findings reveal that through the process of a condensation reaction between*CO and NH_(2)OH for urea synthesis,*NO_(3)-is reduced to*NH_(3),and*CO_(2)to*CCO at dual Cu atom sites.This dual-site reduction facilitates the synthesis of acetamide through a nucleophilic reaction between NH_(3)and the ketene intermediate.Furthermore,we found that the I-and Mg^(2+)ions,influenced by pH,were highly effective for acetamide and ammonia synthesis,except when F-and Ca^(2+)were present.Furthermore,the mechanisms of C–N bond formation were investigated via ab-initio molecular dynamics simulations,and we found that adjusting the micro-environment can change the dominant side reaction,shifting from hydrogen production in acidic conditions to water reduction in alkaline ones.This study introduces a novel approach using ion-H_(2)O cages to significantly enhance the efficiency of C–N coupling reactions.
基金supported by the National Natural Science Foundation of China(No.92370117)the CAS Project for Young Scientists in Basic Research(No.YSBR-090)。
文摘In recent years,machine learning(ML)techniques have been shown to be effective in accelerating the development process of optoelectronic devices.However,as"black box"models,they have limited theoretical interpretability.In this work,we leverage symbolic regression(SR)technique for discovering the explicit symbolic relationship between the structure of the optoelectronic Fabry-Perot(FP)laser and its optical field distribution,which greatly improves model transparency compared to ML.We demonstrated that the expressions explored through SR exhibit lower errors on the test set compared to ML models,which suggests that the expressions have better fitting and generalization capabilities.
基金supported by National Natural Science Foundation of China(42002293,52068019)Hainan Provincial Natural Science Foundation of China(520QN229,422RC599)+2 种基金Independent Innovation Fund Project of Tianjin University and Hainan University(KF2022⁃03)Scientific Research Startup Foundation of Hainan university(KYQD(2R)1969)Systematic Project of Key Laboratory of Geological Hazards on Three Gorges Reservoir Area(Three Gorges University),Ministry of Education(2020KDZ04).
文摘The chief objective of the article is to learn the spatial characteristics of stress distribution around a shallow buried cylinder Karst cave in limestone strata.Firstly,taking into account the geometry of limestone formations,and the characteristics of Karst geomorphology in China,a spatial axialsymmetrical hollow model was established.Concurrently,combining available work and the concept of elasticity,the boundary conditions are determined.Subsequently,Love displacement method was introduced,the expressions of stress components were gained.The diagram characteristics of each stress component are summarized,which are affected by various influencing factors.Finally,in order to prove the rationality of the general solution,numerical simulation was carried out on the basis of practical engineering,and the maximum error is less than 5%.Thus,the analytical solution could represent the spatial characteristics of stress distribution around a shallow buried cylinder Karst cave in limestone strata.
基金the National Science,Research and Innovation Fund(NSRF)King Mongkuts University of Technology North Bangkok under contract no.KMUTNB-FF-68-B-08.
文摘This study aims to examine the explicit solution for calculating the Average Run Length(ARL)on the triple exponentially weighted moving average(TEWMA)control chart applied to autoregressive model(AR(p)),where AR(p)is an autoregressive model of order p,representing a time series with dependencies on its p previous values.Additionally,the study evaluates the accuracy of both explicit and numerical integral equation(NIE)solutions for AR(p)using the TEWMA control chart,focusing on the absolute percentage relative error.The results indicate that the explicit and approximate solutions are in close agreement.Furthermore,the study investigates the performance of exponentially weighted moving average(EWMA)and TEWMA control charts in detecting changes in the process,using the relative mean index(RMI)as a measure.The findings demonstrate that the TEWMA control chart outperforms the EWMA control chart in detecting process changes,especially when the value ofλis sufficiently large.In addition,an analysis using historical data from the SET index between January 2024 and May 2024 and historical data of global annual plastic production,the results of both data sets also emphasize the superior performance of the TEWMA control chart.
