The integration of artificial intelligence (AI) with high-throughput experimentation (HTE) techniques is revolutionizing catalyst design, addressing challenges in efficiency, cost, and scalability. This review explore...The integration of artificial intelligence (AI) with high-throughput experimentation (HTE) techniques is revolutionizing catalyst design, addressing challenges in efficiency, cost, and scalability. This review explores the synergistic application of AI and HTE, highlighting their role in accelerating catalyst discovery, optimizing reaction parameters, and understanding structure-performance relationships. HTE facilitates the rapid preparation, characterization, and evaluation of diverse catalyst formulations, generating large datasets essential for AI model training. Machine learning algorithms, including regression models, neural networks, and active learning frameworks, analyze these datasets to uncover the underlying relationships between the data, predict performance, and optimize experimental workflows in real-time. Case studies across heterogeneous, homogeneous, and electrocatalysis demonstrate significant advancements, including improved reaction selectivity, enhanced material stability, and shorten discovery cycles. The integration of AI with HTE has significantly accelerated discovery cycles, enabling the optimization of catalyst formulations and reaction conditions. Despite these achievements, challenges remain, including reliance on researcher expertise, real-time adaptability, and the complexity of large-scale data analysis. Addressing these limitations through refined experimental protocols, standardized datasets, and interpretable AI models will unlock the full potential of AI-HTE integration.展开更多
Sm–Co-based films play an irreplaceable role in special applications due to their high curie temperature and magnetocrystalline anisotropic energy,especially in heat-assisted magnetic recording(HAMR),but the complex ...Sm–Co-based films play an irreplaceable role in special applications due to their high curie temperature and magnetocrystalline anisotropic energy,especially in heat-assisted magnetic recording(HAMR),but the complex composition of Sm–Co phase and unclear synergistic coupling mechanisms of multi-elemental doping become the challenges to enhance the properties.In this work,a novel strategy combining magnetron sputtering and a high-throughput experiment method is applied to solve the above-mentioned problems.Fe/Cu co-doping highly increases the remanence while maintaining a coercivity larger than 26 kOe,leading to an enhancement of the magnetic energy product to 18.1 MGOe.X-ray diffraction(XRD)and high-resolution transmission electron microscope(HRTEM)reveals that SmCo_(5) phase occupies the major fraction,with Co atoms partially substituted by Fe and Cu atoms.In situ Lorentz transmission electron microscopy(LTEM)observations show that the Sm(Co,Cu)5 phase effectively prohibits domain wall motions,leading to an increase of coercivity(H_(c)).Fe doping increases the low saturation magnetization(M_(s))and low remanence(Mr)due to the Fe atom having a higher saturation magnetic moment.The magnetization reversal behaviors are further verified by micromagnetic simulations.Our results suggest that Sm–Co-based films prepared via Fe/Cu co-doping could be a promising candidate for high-performed HAMR in the future.展开更多
For the advancement of fast-charging sodium-ion batteries(SIBs),the synthesis of cutting-edge cathode materials with superior structural stability and enhanced Na+diffusion kinetics is imperative.Multiphase layered tr...For the advancement of fast-charging sodium-ion batteries(SIBs),the synthesis of cutting-edge cathode materials with superior structural stability and enhanced Na+diffusion kinetics is imperative.Multiphase layered transition metal oxides(LTMOs),which leverage the synergistic properties of two distinct monophasic LTMOs,have garnered significant attention;however,their efficacy under fast-charging conditions remains underexplored.In this study,we developed a high-throughput computational screening framework to identify optimal dopants that maximize the electrochemical performance of LTMOs.Specifically,we evaluated the efficacy of 32 dopants based on P2/O3-type Mn/Fe-based Na_(x)Mn_(0.5)Fe_(0.5)O_(2)(NMFO)cathode material.Multiphase LTMOs satisfying criteria for thermodynamic and structural stability,minimized phase transitions,and enhanced Na^(+)diffusion were systematically screened for their suitability in fast-charging applications.The analysis identified two dopants,Ti and Zr,which met all predefined screening criteria.Furthermore,we ranked and scored dopants based on their alignment with these criteria,establishing a comprehensive dopant performance database.These findings provide a robust foundation for experimental exploration and offer detailed guidelines for tailoring dopants to optimize fast-charging SIBs.展开更多
Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a nove...Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system emergence.To address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating laws.Finally,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”.展开更多
It is difficult to rescue people from outside, and emergency evacuation is still a main measure to decrease casualties in high-rise building fires. To improve evacuation efficiency, a valid and easily manipulated grou...It is difficult to rescue people from outside, and emergency evacuation is still a main measure to decrease casualties in high-rise building fires. To improve evacuation efficiency, a valid and easily manipulated grouping evacuation strategy is proposed. Occupants escape in groups according to the shortest evacuation route is determined by graph theory. In order to evaluate and find the optimal grouping, computational experiments are performed to design and simulate the evacuation processes. A case study shown the application in detail and quantitative research conclusions is obtained. The thoughts and approaches of this study can be used to guide actual high-rise building evacuation processes in future.展开更多
Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is...Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors.展开更多
Traditional Chinese medicine(TCM)is a precious treasure of the Chinese nation and has unique advantages in the prevention and treatment of diseases.The holistic view of TCM coincides with the new generation of medical...Traditional Chinese medicine(TCM)is a precious treasure of the Chinese nation and has unique advantages in the prevention and treatment of diseases.The holistic view of TCM coincides with the new generation of medical research paradigm characterized by network and system.TCM gave birth to a new method featuring holistic and systematic"network target",a core theory and method of network pharmacology.TCM is also an important research object of network pharmacology.TCM network pharmacology,which aims to understand the network-based biological basis of complex diseases,TCM syndromes and herb treatments,plays a critical role in the origin and development process of network pharmacology.This review introduces new progresses of TCM network pharmacology in recent years,including predicting herb targets,understanding biological foundation of diseases and syndromes,network regulation mechanisms of herbal formulae,and identifying disease and syndrome biomarkers based on biological network.These studies show a trend of combining computational,experimental and clinical approaches,which is a promising direction of TCM network pharmacology research in the future.Considering that TCM network pharmacology is still a young research field,it is necessary to further standardize the research process and evaluation indicators to promote its healthy development.展开更多
The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carb...The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carbon dioxide(CO_2) and store methane(CH4), where the latter is a kind of clean energy source with abundant reserves and lower CO_2 emission. Hundreds of thousands of porous materials can be enrolled on the candidate list, but how to quickly identify the really promising ones, or even evolve materials(namely, rational design high-performing candidates) based on the large database of present porous materials? In this context, high-throughput computational techniques, which have emerged in the past few years as powerful tools, make the targets of fast evaluation of adsorbents and evolving materials for CO_2 capture and CH_4 storage feasible. This review provides an overview of the recent computational efforts on such related topics and discusses the further development in this field.展开更多
Aqueous zinc ion batteries(AZIBs)have attracted much attention in recent years due to their high safety,low cost,and decent electrochemical performance.However,the traditional electrodes development process requires t...Aqueous zinc ion batteries(AZIBs)have attracted much attention in recent years due to their high safety,low cost,and decent electrochemical performance.However,the traditional electrodes development process requires tedious synthesis and testing procedures,which reduces the efficiency of developing highperformance battery devices.Here,we proposed a high-throughput screening strategy based on firstprinciples calculations to aid the experimental development of high-performance spinel cathode materials for AZIBs.We obtained 14 spinel materials from 12,047 Mn/Zn-O based materials by examining their structures and whether they satisfy the basic properties of electrodes.Then their band structures and density of states,open circuit voltage and volume expansion rate,ionic diffusion coefficient and energy barrier were further evaluated by first-principles calculations,resulting in five potential candidates.One of the promising candidates identified,Mg_(2)MnO_(4),was experimentally synthesized,characterized and integrated into an AZIB based cell to verify its performance as a cathode.The Mg_(2)MnO_(4)cathode exhibits excellent cycling stability,which is consistent with the theoretically predicted low volume expansion.Moreover,at high current density,the Mg_(2)MnO_(4)cathode still exhibits high reversible capacity and excellent rate performance,indicating that it is an excellent cathode material for AZIBs.Our work provides a new approach to accelerate the development of high-performance cathodes for AZIBs and other ion batteries.展开更多
To provide physically based wind modelling for wind erosion research at regional scale, a 3D computational fluid dynamics (CFD) wind model was developed. The model was programmed in C language based on the Navier-Stok...To provide physically based wind modelling for wind erosion research at regional scale, a 3D computational fluid dynamics (CFD) wind model was developed. The model was programmed in C language based on the Navier-Stokes equations, and it is freely available as open source. Integrated with the spatial analysis and modelling tool (SAMT), the wind model has convenient input preparation and powerful output visualization. To validate the wind model, a series of experiments was con- ducted in a wind tunnel. A blocking inflow experiment was designed to test the performance of the model on simulation of basic fluid processes. A round obstacle experiment was designed to check if the model could simulate the influences of the obstacle on wind field. Results show that measured and simulated wind fields have high correlations, and the wind model can simulate both the basic processes of the wind and the influences of the obstacle on the wind field. These results show the high reliability of the wind model. A digital elevation model (DEM) of an area (3800 m long and 1700 m wide) in the Xilingele grassland in Inner Mongolia (autonomous region, China) was applied to the model, and a 3D wind field has been successfully generated. The clear imple- mentation of the model and the adequate validation by wind tunnel experiments laid a solid foundation for the prediction and assessment of wind erosion at regional scale.展开更多
COMPUTATIONAL experiments method is an essential tool for analyzing,designing,managing,and integrating complex systems.However,a significant challenge arises in constructing agents with human-like characteristics to f...COMPUTATIONAL experiments method is an essential tool for analyzing,designing,managing,and integrating complex systems.However,a significant challenge arises in constructing agents with human-like characteristics to form an AI society.Agent modeling typically encompasses four levels:1)The autonomy features of agents,e.g.,perception,behavior,and decision-making;2)The evolutionary features of agents,e.g.,bounded rationality,heterogeneity,and learning evolution;3)The social features of agents,e.g.,interaction,cooperation,and competition;4)The emergent features of agents,e.g.,gaming with environments or regulatory strategies.Traditional modeling techniques primarily derive from ABMs(Agent-based Models)and incorporate various emerging technologies(e.g.,machine learning,big data,and social networks),which can enhance modeling capabilities,while amplifying the complexity[1].展开更多
Supersaturated design is essentially a fractional factorial design in which the number of potential effects is greater than the number of runs. In this article, the supersaturated design is applied to a computer exper...Supersaturated design is essentially a fractional factorial design in which the number of potential effects is greater than the number of runs. In this article, the supersaturated design is applied to a computer experiment through an example of steady current circuit model problem. A uniform mixed-level supersaturated design and the centered quadratic regression model are used. This example shows that supersaturated design and quadratic regression modeling method are very effective for screening effects and building the predictor. They are not only useful in computer experiments but also in industrial and other scientific experiments.展开更多
Disordered ferromagnets with a domain structure that exhibit a hysteresis loop when driven by the external magnetic field are essential materials for modern technological applications.Therefore,the understanding and p...Disordered ferromagnets with a domain structure that exhibit a hysteresis loop when driven by the external magnetic field are essential materials for modern technological applications.Therefore,the understanding and potential for controlling the hysteresis phenomenon in thesematerials,especially concerning the disorder-induced critical behavior on the hysteresis loop,have attracted significant experimental,theoretical,and numerical research efforts.We review the challenges of the numerical modeling of physical phenomena behind the hysteresis loop critical behavior in disordered ferromagnetic systems related to the non-equilibriumstochastic dynamics of domain walls driven by external fields.Specifically,using the extended Random Field Ising Model,we present different simulation approaches and advanced numerical techniques that adequately describe the hysteresis loop shapes and the collective nature of the magnetization fluctuations associated with the criticality of the hysteresis loop for different sample shapes and varied parameters of disorder and rate of change of the external field,as well as the influence of thermal fluctuations and demagnetizing fields.The studied examples demonstrate how these numerical approaches reveal newphysical insights,providing quantitativemeasures of pertinent variables extracted from the systems’simulated or experimentally measured Barkhausen noise signals.The described computational techniques using inherent scale-invariance can be applied to the analysis of various complex systems,both quantum and classical,exhibiting non-equilibrium dynamical critical point or self-organized criticality.展开更多
Due to the complex chemical composition of nickel ores, the requests for the decrease of production costs, and the increase of nickel extraction in the existing depletion of high-grade sulfide ores around the world, c...Due to the complex chemical composition of nickel ores, the requests for the decrease of production costs, and the increase of nickel extraction in the existing depletion of high-grade sulfide ores around the world, computer modeling of nickel ore leaching process be- came a need and a challenge. In this paper, the design of experiments （DOE） theory was used to determine the optimal experimental design plan matrix based on the D optimality criterion. In the high-pressure sulfuric acid leaching （HPSAL） process for nickel laterite in ＂Rudjinci＂ ore in Serbia, the temperature, the sulfuric acid to ore ratio, the stirring speed, and the leaching time as the predictor variables, and the degree of nickel extraction as the response have been considered. To model the process, the multiple linear regression （MLR） and response surface method （RSM）, together with the two-level and four-factor full factorial central composite design （CCD） plan, were used. The proposed re- gression models have not been proven adequate. Therefore, the artificial neural network （ANN） approach with the same experimental plan was used in order to reduce operational costs, give a better modeling accuracy, and provide a more successful process optimization. The model is based on the multi-layer neural networks with the back-propagation （BP） learning algorithm and the bipolar sigmoid activation function.展开更多
In china,many students are unable to do experiments in computer architecture courses,which is very important in helping them to understand many key points.The reason is that the cost of the hardware required is too mu...In china,many students are unable to do experiments in computer architecture courses,which is very important in helping them to understand many key points.The reason is that the cost of the hardware required is too much.Besides,it is very difficult to do research study in hardware experiments.In our course,we adopted an alternative way to deal with the problem: to use software simulators,and designed a set of virtual experiments based on these simulators,which are described in detail in this paper.展开更多
Equipment systems-of-systems （SOS） effectiveness evaluation can provide important reference for construction and optimization of the equipment SoS. After discussing the basic theory and methods of parallel experimen...Equipment systems-of-systems （SOS） effectiveness evaluation can provide important reference for construction and optimization of the equipment SoS. After discussing the basic theory and methods of parallel experiments, we depict an SoS effectiveness analysis and evaluation method using parallel expe- riments theory in detail. A case study is carried out which takes the missile defense system as an example. An artificial system of the missile defense system is constructed with the multi-agent modeling method. Then, single factor, multiple factors and defense position deployment computational experiments are carried out and evaluated with the statistical analysis method. Experiment re- sults show that the altitude of the secondary interception missile is not the key factor which affects SoS effectiveness and putting the defense position ahead will increase defense effectiveness. The case study demonstrates the feasibility of the proposed method.展开更多
Flow behavior of gas and particles in conical spouted beds is experimentally studied and simulated using the twofluid gas-solid model with the kinetic theory of granular flow.The bed pressure drop and fountain height ...Flow behavior of gas and particles in conical spouted beds is experimentally studied and simulated using the twofluid gas-solid model with the kinetic theory of granular flow.The bed pressure drop and fountain height are measured in a conical spouted bed of 100 mm I.D.at different gas velocities.The simulation results are compared with measurements of bed pressure drop and fountain height.The comparison shows that the drag coefficient model used in cylindrical beds under-predicted bed pressure drop and fountain height in conical spouted beds due to the partial weight of particles supported by the inclined side walls.It is found that the numerical results using the drag coefficient model proposed based on the conical spouted bed in this study are in good agreement with experimental data.The present study provides a useful basis for further works on the CFD simulation of conical spouted bed.展开更多
A combinatorial high-throughput experiment(HTE)was used to optimize composition and process of nickel-saving cryogenic steel.A gradient temperature heat treatment method with a high linear distribution of heat treatme...A combinatorial high-throughput experiment(HTE)was used to optimize composition and process of nickel-saving cryogenic steel.A gradient temperature heat treatment method with a high linear distribution of heat treatment temperature using customized graphite sleeve direct current heating was used in the combinatorial HTE,which enhanced the richness of the sample library for the single preparation of the 10^(2) level component process variables.Cryogenic steel with excellent mechanical properties was optimized using this combinatorial HTE,and the Ni content was reduced from the traditional 9 to 5.6 wt.%by using Mn instead of Ni.The heterogeneous structure architecture strategy and strengthening and toughening mechanism of the harmonic structure induced by intrinsic heat treatment of additive manufacturing were revealed.Taking the composition process optimization of Ni-saving cryogenic steel as an example,the boosting ability of combinatorial HTE in the research and development of new metal materials was proposed.展开更多
Objective:This study examined the relationship between structural empowerment and nurses’experience and attitudes toward computer use.Methods:This study was conducted using a cross-sectional quantitative design.A tot...Objective:This study examined the relationship between structural empowerment and nurses’experience and attitudes toward computer use.Methods:This study was conducted using a cross-sectional quantitative design.A total of 184 registered nurses from four hospitals in Jordan participated in the current study.Data were collected using a demographics questionnaire,the Conditions for Work Effectiveness Questionnaire-II(CWEQ-II),and the Pretest for Attitudes toward Computers in Healthcare(PATCH).Results:The median of experience in years among nurses was 5.0,ranging from one to 26 years.The mean score for the attitudes toward computer use was 61.90±11.38.Almost half of the participants,45.11%,were in the category of“feel comfortable using user-friendly computers.”The participants’mean average of the total structural empowerment was 12.40±2.43,and the values for its four subscales were:opportunity 3.57±0.87,resources 2.83±0.85,information 3.06±0.79,and support 2.95±0.86.The frequencies analysis revealed that most participants had a moderate level of empowerment(n¼127,69.02%).The bivariate correlation between nurses’experience and attitudes toward computer use was significant(r¼0.17,P<0.05).The relationship between the total structural empowerment score and attitudes toward computer use was positive but weak(r¼0.20,P<0.01).Conclusion:The results indicated that more experienced nurses are more reluctant toward computer use.However,creating an empowering work environment can facilitate nurses’attitudes toward computer use.展开更多
In the last years, architectural practice has been confronted with a paradigm shift towards the application of digital methods in design activities. In this regard, it is a pedagogic challenge to provide a suitable co...In the last years, architectural practice has been confronted with a paradigm shift towards the application of digital methods in design activities. In this regard, it is a pedagogic challenge to provide a suitable computational background for architectural students, to improve their ability to apply algorithmic-parametric logic, as well as fabrication and prototyping resources to design problem solving. This challenge is even stronger when considering less favored social and technological contexts, such as in Brazil, for example. In this scenario, this article presents and discusses the procedures and the results from a didactic experience carried out in a design computing-oriented discipline, inserted in the curriculum of a Brazilian architecture course. Hence, this paper shares some design computing teaching experiences and presents some results on computational methods and creative approaches, with a view to contribute to a better understanding about the relations between logical thinking, mathematics and architectural design processes.展开更多
基金supported by the Special Project of National Natural Science Foundation(42341204)the the National Natural Science Foundation of China(W2411009).
文摘The integration of artificial intelligence (AI) with high-throughput experimentation (HTE) techniques is revolutionizing catalyst design, addressing challenges in efficiency, cost, and scalability. This review explores the synergistic application of AI and HTE, highlighting their role in accelerating catalyst discovery, optimizing reaction parameters, and understanding structure-performance relationships. HTE facilitates the rapid preparation, characterization, and evaluation of diverse catalyst formulations, generating large datasets essential for AI model training. Machine learning algorithms, including regression models, neural networks, and active learning frameworks, analyze these datasets to uncover the underlying relationships between the data, predict performance, and optimize experimental workflows in real-time. Case studies across heterogeneous, homogeneous, and electrocatalysis demonstrate significant advancements, including improved reaction selectivity, enhanced material stability, and shorten discovery cycles. The integration of AI with HTE has significantly accelerated discovery cycles, enabling the optimization of catalyst formulations and reaction conditions. Despite these achievements, challenges remain, including reliance on researcher expertise, real-time adaptability, and the complexity of large-scale data analysis. Addressing these limitations through refined experimental protocols, standardized datasets, and interpretable AI models will unlock the full potential of AI-HTE integration.
基金supported by the National Key R&D Program of China(No.2022YFB3505700)the National Natural Science Foundation of China(No.51901079)+4 种基金Guangdong Science and Technology Program(No.2023A0505050145)the Natural Science Foundation of Guangdong Province(Nos.2024A1515030178,2020A1515010736 and 2021A1515010451)Guangzhou Municipal Science and Technology Program(No.202007020008)the Fundamental Research Funds for the Central Universities,the Opening Project of National Engineering Research Center for Powder Metallurgy of Titanium&Rare Metals,the Fundamental Research Funds for the Central Universities and Zhongshan Municipal Science and Technology Program(No.191007102629094)Zhongshan Collaborative Innovation Fund(No.2018C1001).
文摘Sm–Co-based films play an irreplaceable role in special applications due to their high curie temperature and magnetocrystalline anisotropic energy,especially in heat-assisted magnetic recording(HAMR),but the complex composition of Sm–Co phase and unclear synergistic coupling mechanisms of multi-elemental doping become the challenges to enhance the properties.In this work,a novel strategy combining magnetron sputtering and a high-throughput experiment method is applied to solve the above-mentioned problems.Fe/Cu co-doping highly increases the remanence while maintaining a coercivity larger than 26 kOe,leading to an enhancement of the magnetic energy product to 18.1 MGOe.X-ray diffraction(XRD)and high-resolution transmission electron microscope(HRTEM)reveals that SmCo_(5) phase occupies the major fraction,with Co atoms partially substituted by Fe and Cu atoms.In situ Lorentz transmission electron microscopy(LTEM)observations show that the Sm(Co,Cu)5 phase effectively prohibits domain wall motions,leading to an increase of coercivity(H_(c)).Fe doping increases the low saturation magnetization(M_(s))and low remanence(Mr)due to the Fe atom having a higher saturation magnetic moment.The magnetization reversal behaviors are further verified by micromagnetic simulations.Our results suggest that Sm–Co-based films prepared via Fe/Cu co-doping could be a promising candidate for high-performed HAMR in the future.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(No.2022R1F1A1074339)。
文摘For the advancement of fast-charging sodium-ion batteries(SIBs),the synthesis of cutting-edge cathode materials with superior structural stability and enhanced Na+diffusion kinetics is imperative.Multiphase layered transition metal oxides(LTMOs),which leverage the synergistic properties of two distinct monophasic LTMOs,have garnered significant attention;however,their efficacy under fast-charging conditions remains underexplored.In this study,we developed a high-throughput computational screening framework to identify optimal dopants that maximize the electrochemical performance of LTMOs.Specifically,we evaluated the efficacy of 32 dopants based on P2/O3-type Mn/Fe-based Na_(x)Mn_(0.5)Fe_(0.5)O_(2)(NMFO)cathode material.Multiphase LTMOs satisfying criteria for thermodynamic and structural stability,minimized phase transitions,and enhanced Na^(+)diffusion were systematically screened for their suitability in fast-charging applications.The analysis identified two dopants,Ti and Zr,which met all predefined screening criteria.Furthermore,we ranked and scored dopants based on their alignment with these criteria,establishing a comprehensive dopant performance database.These findings provide a robust foundation for experimental exploration and offer detailed guidelines for tailoring dopants to optimize fast-charging SIBs.
基金the National Key Research and Development Program of China(2021YFF0900800)the National Natural Science Foundation of China(61972276,62206116,62032016)+2 种基金the New Liberal Arts Reform and Practice Project of National Ministry of Education(2021170002)the Open Research Fund of the State Key Laboratory for Management and Control of Complex Systems(20210101)Tianjin University Talent Innovation Reward Program for Literature and Science Graduate Student(C1-2022-010)。
文摘Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system emergence.To address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating laws.Finally,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”.
基金supported by Beijing University of Civil Engineering and Architecture Nature Science(ZF16078,X18067)
文摘It is difficult to rescue people from outside, and emergency evacuation is still a main measure to decrease casualties in high-rise building fires. To improve evacuation efficiency, a valid and easily manipulated grouping evacuation strategy is proposed. Occupants escape in groups according to the shortest evacuation route is determined by graph theory. In order to evaluate and find the optimal grouping, computational experiments are performed to design and simulate the evacuation processes. A case study shown the application in detail and quantitative research conclusions is obtained. The thoughts and approaches of this study can be used to guide actual high-rise building evacuation processes in future.
基金The authors are grateful for financial support from the National Key Projects for Fundamental Research and Development of China(2021YFA1500803)the National Natural Science Foundation of China(51825205,52120105002,22102202,22088102,U22A20391)+1 种基金the DNL Cooperation Fund,CAS(DNL202016)the CAS Project for Young Scientists in Basic Research(YSBR-004).
文摘Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors.
基金supported by the National Natural Science Foundation of China(Nos.6201101081,81630103 and 81225025)Tsinghua University Spring Breeze Fund(No.2020-Z99CFY040)Beijing National Research Center for Information Science and Technology(Nos.BNR2019TD01020 and BNR2019-RC01012)。
文摘Traditional Chinese medicine(TCM)is a precious treasure of the Chinese nation and has unique advantages in the prevention and treatment of diseases.The holistic view of TCM coincides with the new generation of medical research paradigm characterized by network and system.TCM gave birth to a new method featuring holistic and systematic"network target",a core theory and method of network pharmacology.TCM is also an important research object of network pharmacology.TCM network pharmacology,which aims to understand the network-based biological basis of complex diseases,TCM syndromes and herb treatments,plays a critical role in the origin and development process of network pharmacology.This review introduces new progresses of TCM network pharmacology in recent years,including predicting herb targets,understanding biological foundation of diseases and syndromes,network regulation mechanisms of herbal formulae,and identifying disease and syndrome biomarkers based on biological network.These studies show a trend of combining computational,experimental and clinical approaches,which is a promising direction of TCM network pharmacology research in the future.Considering that TCM network pharmacology is still a young research field,it is necessary to further standardize the research process and evaluation indicators to promote its healthy development.
基金supported by the Natural Science Foundation of China (Nos.21706106,21536001 and 21322603)the National Key Basic Research Program of China ("973") (No.2013CB733503)+1 种基金the Natural Science Foundation of Jiangsu Normal University(16XLR011)Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carbon dioxide(CO_2) and store methane(CH4), where the latter is a kind of clean energy source with abundant reserves and lower CO_2 emission. Hundreds of thousands of porous materials can be enrolled on the candidate list, but how to quickly identify the really promising ones, or even evolve materials(namely, rational design high-performing candidates) based on the large database of present porous materials? In this context, high-throughput computational techniques, which have emerged in the past few years as powerful tools, make the targets of fast evaluation of adsorbents and evolving materials for CO_2 capture and CH_4 storage feasible. This review provides an overview of the recent computational efforts on such related topics and discusses the further development in this field.
基金This work was financially supported by research grants from the Natural Science Foundation of China(Nos.12004057,62074022,52173235)Support plan for Overseas Students to Return to China for Entrepreneurship and Innovation(No.cx2020075)+3 种基金Open Fund of Key Laboratory of Low-grade Energy Utilization Technologies and Systems(No.LLEUTS-2020008)Chongqing Funds for Distinguished Young Scientists(No.cstc2021jcyj-jqX0015)Chongqing Talent Plan(No.CQYC2021059206)Fundamental Research Funds for the Central Universities(No.2020CDJQY-A055).
文摘Aqueous zinc ion batteries(AZIBs)have attracted much attention in recent years due to their high safety,low cost,and decent electrochemical performance.However,the traditional electrodes development process requires tedious synthesis and testing procedures,which reduces the efficiency of developing highperformance battery devices.Here,we proposed a high-throughput screening strategy based on firstprinciples calculations to aid the experimental development of high-performance spinel cathode materials for AZIBs.We obtained 14 spinel materials from 12,047 Mn/Zn-O based materials by examining their structures and whether they satisfy the basic properties of electrodes.Then their band structures and density of states,open circuit voltage and volume expansion rate,ionic diffusion coefficient and energy barrier were further evaluated by first-principles calculations,resulting in five potential candidates.One of the promising candidates identified,Mg_(2)MnO_(4),was experimentally synthesized,characterized and integrated into an AZIB based cell to verify its performance as a cathode.The Mg_(2)MnO_(4)cathode exhibits excellent cycling stability,which is consistent with the theoretically predicted low volume expansion.Moreover,at high current density,the Mg_(2)MnO_(4)cathode still exhibits high reversible capacity and excellent rate performance,indicating that it is an excellent cathode material for AZIBs.Our work provides a new approach to accelerate the development of high-performance cathodes for AZIBs and other ion batteries.
基金the Sino-German research project MAGIM (Matter fluxes in Grasslands of Inner Mongolia as influenced by stocking rate) funded by DFG (German Research Foundation, Research Unit 536)
文摘To provide physically based wind modelling for wind erosion research at regional scale, a 3D computational fluid dynamics (CFD) wind model was developed. The model was programmed in C language based on the Navier-Stokes equations, and it is freely available as open source. Integrated with the spatial analysis and modelling tool (SAMT), the wind model has convenient input preparation and powerful output visualization. To validate the wind model, a series of experiments was con- ducted in a wind tunnel. A blocking inflow experiment was designed to test the performance of the model on simulation of basic fluid processes. A round obstacle experiment was designed to check if the model could simulate the influences of the obstacle on wind field. Results show that measured and simulated wind fields have high correlations, and the wind model can simulate both the basic processes of the wind and the influences of the obstacle on the wind field. These results show the high reliability of the wind model. A digital elevation model (DEM) of an area (3800 m long and 1700 m wide) in the Xilingele grassland in Inner Mongolia (autonomous region, China) was applied to the model, and a 3D wind field has been successfully generated. The clear imple- mentation of the model and the adequate validation by wind tunnel experiments laid a solid foundation for the prediction and assessment of wind erosion at regional scale.
基金supported in part by National Key Research and Development Program of China(2021YFF0900800)National Natural Science Foundation of China(62472306,62441221,62206116)+2 种基金Tianjin University’s 2024 Special Project on Disciplinary Development(XKJS-2024-5-9)Tianjin University Talent Innovation Reward Program for Literature&Science Graduate Student(C1-2022-010)Shanxi Province Social Science Foundation(2020F002).
文摘COMPUTATIONAL experiments method is an essential tool for analyzing,designing,managing,and integrating complex systems.However,a significant challenge arises in constructing agents with human-like characteristics to form an AI society.Agent modeling typically encompasses four levels:1)The autonomy features of agents,e.g.,perception,behavior,and decision-making;2)The evolutionary features of agents,e.g.,bounded rationality,heterogeneity,and learning evolution;3)The social features of agents,e.g.,interaction,cooperation,and competition;4)The emergent features of agents,e.g.,gaming with environments or regulatory strategies.Traditional modeling techniques primarily derive from ABMs(Agent-based Models)and incorporate various emerging technologies(e.g.,machine learning,big data,and social networks),which can enhance modeling capabilities,while amplifying the complexity[1].
基金Research supported by the National Natural Science Foundation of China (10301015)the Science and Technology Innovation Fund of Nankai University, the Visiting Scholar Program at Chern Institute of Mathematicsa Hong Kong Research Grants Council Grant (RGC/HKBU 200804)
文摘Supersaturated design is essentially a fractional factorial design in which the number of potential effects is greater than the number of runs. In this article, the supersaturated design is applied to a computer experiment through an example of steady current circuit model problem. A uniform mixed-level supersaturated design and the centered quadratic regression model are used. This example shows that supersaturated design and quadratic regression modeling method are very effective for screening effects and building the predictor. They are not only useful in computer experiments but also in industrial and other scientific experiments.
基金Djordje Spasojevic and Svetislav Mijatovic acknowledge the support from the Ministry of Science,TechnologicalDevelopment and Innovation of the Republic of Serbia(Agreement No.451-03-65/2024-03/200162)S.J.ibid.(Agreement No.451-03-65/2024-03/200122)Bosiljka Tadic from the Slovenian Research Agency(program P1-0044).
文摘Disordered ferromagnets with a domain structure that exhibit a hysteresis loop when driven by the external magnetic field are essential materials for modern technological applications.Therefore,the understanding and potential for controlling the hysteresis phenomenon in thesematerials,especially concerning the disorder-induced critical behavior on the hysteresis loop,have attracted significant experimental,theoretical,and numerical research efforts.We review the challenges of the numerical modeling of physical phenomena behind the hysteresis loop critical behavior in disordered ferromagnetic systems related to the non-equilibriumstochastic dynamics of domain walls driven by external fields.Specifically,using the extended Random Field Ising Model,we present different simulation approaches and advanced numerical techniques that adequately describe the hysteresis loop shapes and the collective nature of the magnetization fluctuations associated with the criticality of the hysteresis loop for different sample shapes and varied parameters of disorder and rate of change of the external field,as well as the influence of thermal fluctuations and demagnetizing fields.The studied examples demonstrate how these numerical approaches reveal newphysical insights,providing quantitativemeasures of pertinent variables extracted from the systems’simulated or experimentally measured Barkhausen noise signals.The described computational techniques using inherent scale-invariance can be applied to the analysis of various complex systems,both quantum and classical,exhibiting non-equilibrium dynamical critical point or self-organized criticality.
文摘Due to the complex chemical composition of nickel ores, the requests for the decrease of production costs, and the increase of nickel extraction in the existing depletion of high-grade sulfide ores around the world, computer modeling of nickel ore leaching process be- came a need and a challenge. In this paper, the design of experiments （DOE） theory was used to determine the optimal experimental design plan matrix based on the D optimality criterion. In the high-pressure sulfuric acid leaching （HPSAL） process for nickel laterite in ＂Rudjinci＂ ore in Serbia, the temperature, the sulfuric acid to ore ratio, the stirring speed, and the leaching time as the predictor variables, and the degree of nickel extraction as the response have been considered. To model the process, the multiple linear regression （MLR） and response surface method （RSM）, together with the two-level and four-factor full factorial central composite design （CCD） plan, were used. The proposed re- gression models have not been proven adequate. Therefore, the artificial neural network （ANN） approach with the same experimental plan was used in order to reduce operational costs, give a better modeling accuracy, and provide a more successful process optimization. The model is based on the multi-layer neural networks with the back-propagation （BP） learning algorithm and the bipolar sigmoid activation function.
文摘In china,many students are unable to do experiments in computer architecture courses,which is very important in helping them to understand many key points.The reason is that the cost of the hardware required is too much.Besides,it is very difficult to do research study in hardware experiments.In our course,we adopted an alternative way to deal with the problem: to use software simulators,and designed a set of virtual experiments based on these simulators,which are described in detail in this paper.
文摘Equipment systems-of-systems （SOS） effectiveness evaluation can provide important reference for construction and optimization of the equipment SoS. After discussing the basic theory and methods of parallel experiments, we depict an SoS effectiveness analysis and evaluation method using parallel expe- riments theory in detail. A case study is carried out which takes the missile defense system as an example. An artificial system of the missile defense system is constructed with the multi-agent modeling method. Then, single factor, multiple factors and defense position deployment computational experiments are carried out and evaluated with the statistical analysis method. Experiment re- sults show that the altitude of the secondary interception missile is not the key factor which affects SoS effectiveness and putting the defense position ahead will increase defense effectiveness. The case study demonstrates the feasibility of the proposed method.
基金Supported by the National Natural Science Foundation of China(51206020)the Program for New Century Excellent Talents in University(NCET-12-0703)the Northeast Petroleum University Foundation
文摘Flow behavior of gas and particles in conical spouted beds is experimentally studied and simulated using the twofluid gas-solid model with the kinetic theory of granular flow.The bed pressure drop and fountain height are measured in a conical spouted bed of 100 mm I.D.at different gas velocities.The simulation results are compared with measurements of bed pressure drop and fountain height.The comparison shows that the drag coefficient model used in cylindrical beds under-predicted bed pressure drop and fountain height in conical spouted beds due to the partial weight of particles supported by the inclined side walls.It is found that the numerical results using the drag coefficient model proposed based on the conical spouted bed in this study are in good agreement with experimental data.The present study provides a useful basis for further works on the CFD simulation of conical spouted bed.
基金the financial support of the National KeyR&DProgram of China(No.2021YFB3702401)Major Program of the National Natural Science Foundation of China(No.52293394)the National Natural Science Foundation of China(No.51831002).
文摘A combinatorial high-throughput experiment(HTE)was used to optimize composition and process of nickel-saving cryogenic steel.A gradient temperature heat treatment method with a high linear distribution of heat treatment temperature using customized graphite sleeve direct current heating was used in the combinatorial HTE,which enhanced the richness of the sample library for the single preparation of the 10^(2) level component process variables.Cryogenic steel with excellent mechanical properties was optimized using this combinatorial HTE,and the Ni content was reduced from the traditional 9 to 5.6 wt.%by using Mn instead of Ni.The heterogeneous structure architecture strategy and strengthening and toughening mechanism of the harmonic structure induced by intrinsic heat treatment of additive manufacturing were revealed.Taking the composition process optimization of Ni-saving cryogenic steel as an example,the boosting ability of combinatorial HTE in the research and development of new metal materials was proposed.
文摘Objective:This study examined the relationship between structural empowerment and nurses’experience and attitudes toward computer use.Methods:This study was conducted using a cross-sectional quantitative design.A total of 184 registered nurses from four hospitals in Jordan participated in the current study.Data were collected using a demographics questionnaire,the Conditions for Work Effectiveness Questionnaire-II(CWEQ-II),and the Pretest for Attitudes toward Computers in Healthcare(PATCH).Results:The median of experience in years among nurses was 5.0,ranging from one to 26 years.The mean score for the attitudes toward computer use was 61.90±11.38.Almost half of the participants,45.11%,were in the category of“feel comfortable using user-friendly computers.”The participants’mean average of the total structural empowerment was 12.40±2.43,and the values for its four subscales were:opportunity 3.57±0.87,resources 2.83±0.85,information 3.06±0.79,and support 2.95±0.86.The frequencies analysis revealed that most participants had a moderate level of empowerment(n¼127,69.02%).The bivariate correlation between nurses’experience and attitudes toward computer use was significant(r¼0.17,P<0.05).The relationship between the total structural empowerment score and attitudes toward computer use was positive but weak(r¼0.20,P<0.01).Conclusion:The results indicated that more experienced nurses are more reluctant toward computer use.However,creating an empowering work environment can facilitate nurses’attitudes toward computer use.
文摘In the last years, architectural practice has been confronted with a paradigm shift towards the application of digital methods in design activities. In this regard, it is a pedagogic challenge to provide a suitable computational background for architectural students, to improve their ability to apply algorithmic-parametric logic, as well as fabrication and prototyping resources to design problem solving. This challenge is even stronger when considering less favored social and technological contexts, such as in Brazil, for example. In this scenario, this article presents and discusses the procedures and the results from a didactic experience carried out in a design computing-oriented discipline, inserted in the curriculum of a Brazilian architecture course. Hence, this paper shares some design computing teaching experiences and presents some results on computational methods and creative approaches, with a view to contribute to a better understanding about the relations between logical thinking, mathematics and architectural design processes.
