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Pharmacophore-guided design,synthesis and evaluation of quinazoline-arylpiperazines as newα_1-adrenoceptor antagonists 认领 引用 被引量：4
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作者 Hao Fang Min Yong Li Lin Xia 《Chinese Chemical Letters》 SCIE CAS 2007年第1期41-44,共4页
A series of arylpiperazinesquinazoline-2,4-diamine compounds were designed and synthesized based on pharmacophore for m-selective α1-adrenoceptor antagonists and 3D chemical database searching. The in vitro functiona... A series of arylpiperazinesquinazoline-2,4-diamine compounds were designed and synthesized based on pharmacophore for m-selective α1-adrenoceptor antagonists and 3D chemical database searching. The in vitro functional analysis showed that compounds 9 and 14 showed better and similar α1-AR antagonistic activity compared with prazosin. 展开更多
关键词 α1-Adrcnoceptor Antagonists Pharmacophore-guided design
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Inverse design framework of hybrid honeycomb structure with high impact resistance based on active learning 认领 引用 被引量：2
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作者 Xingyu Shen Ke Yan +5 位作者 Difeng Zhu Hao Wu Shijun Luo Shaobo Qi Mengqi Yuan Xinming Qian 《Defence Technology（防务技术）》 SCIE EI CAS CSCD 2026年第1期407-421,共15页
In this study,an inverse design framework was established to find lightweight honeycomb structures(HCSs)with high impact resistance.The hybrid HCS,composed of re-entrant(RE)and elliptical annular re-entrant(EARE)honey... In this study,an inverse design framework was established to find lightweight honeycomb structures(HCSs)with high impact resistance.The hybrid HCS,composed of re-entrant(RE)and elliptical annular re-entrant(EARE)honeycomb cells,was created by constructing arrangement matrices to achieve structural lightweight.The machine learning(ML)framework consisted of a neural network(NN)forward regression model for predicting impact resistance and a multi-objective optimization algorithm for generating high-performance designs.The surrogate of the local design space was initially realized by establishing the NN in the small sample dataset,and the active learning strategy was used to continuously extended the local optimal design until the model converged in the global space.The results indicated that the active learning strategy significantly improved the inference capability of the NN model in unknown design domains.By guiding the iteration direction of the optimization algorithm,lightweight designs with high impact resistance were identified.The energy absorption capacity of the optimal design reached 94.98%of the EARE honeycomb,while the initial peak stress and mass decreased by 28.85%and 19.91%,respectively.Furthermore,Shapley Additive Explanations(SHAP)for global explanation of the NN indicated a strong correlation between the arrangement mode of HCS and its impact resistance.By reducing the stiffness of the cells at the top boundary of the structure,the initial impact damage sustained by the structure can be significantly improved.Overall,this study proposed a general lightweight design method for array structures under impact loads,which is beneficial for the widespread application of honeycomb-based protective structures. 展开更多
关键词 Re-entrant honeycomb Hybrid structures Inverse design Impact resistance Lightweight
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Memristor devices for next-generation computing:from performance optimization to application-specific co-design 认领 引用 被引量：1
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作者 Zhaorui Liu Caifang Gao +5 位作者 Jingbo Yang Zuxin Chen Enlong Li Jun Li Mengjiao Li Jianhua Zhang 《International Journal of Extreme Manufacturing》 SCIE EI CAS CSCD 2026年第1期119-146,共28页
Memristors have emerged as a transformative technology in the realm of electronic devices,offering unique advantages such as fast switching speeds,low power consumption,and the ability to sensor-memory-compute.The app... Memristors have emerged as a transformative technology in the realm of electronic devices,offering unique advantages such as fast switching speeds,low power consumption,and the ability to sensor-memory-compute.The applications span across non-volatile memory,neuromorphic computing,hardware security,and beyond,prompting memristors to become a versatile solution for next-generation computing and data storage systems.Despite enormous potential of memristors,the transition from laboratory prototypes to large-scale applications is challenging in terms of material stability,device reproducibility,and array scalability.This review systematically explores recent advancements in high-performance memristor technologies,focusing on performance enhancement strategies through material engineering,structural design,pulse protocol optimization,and algorithm control.We provide an in-depth analysis of key performance metrics tailored to specific applications,including non-volatile memory,neuromorphic computing,and hardware security.Furthermore,we propose a co-design framework that integrates device-level optimizations with operational-level improvements,aiming to bridge the gap between theoretical models and practical implementations. 展开更多
关键词 memristor performance optimization device design neuromorphic computing
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AI-and Biotechnology-Driven Digital Design of Biohydrogen-Producing Microbiota 认领 引用 被引量：1
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作者 Qian Liu Shuang Gao +5 位作者 Yanan Hou Jianfeng Liu Qianqian Yuan Ai-Jie Wang Nanqi Ren Cong Huang 《Engineering》 SCIE EI CSCD 2026年第7期296-302,共7页
Biohydrogen, produced via microbial fermentation of biomass waste, is poised to play a pivotal role in China's green energy transition. Nonetheless, significant obstacles such as high costs, unstable production dy... Biohydrogen, produced via microbial fermentation of biomass waste, is poised to play a pivotal role in China's green energy transition. Nonetheless, significant obstacles such as high costs, unstable production dynamics, regulatory and metabolic inefficiencies, and limited actual hydrogen yields hinder large-scale application. Addressing these challenges necessitates the integration of machine learning and synthetic biology, forming a robust pathway to enhanced process efficacy and output consistency. The convergence of artificial intelligence (AI) and biotechnology (BT) is revolutionizing biohydrogen production by shifting from traditional empirical methodologies to predictive, engineering-based frameworks. AI equips researchers to interpret and optimize complex metabolic and genetic networks through machine learning and genome-scale modeling. Concurrently, BT is evolving to manipulate microbial communities holistically via synthetic ecology and dynamic modeling. Here, we propose a “digital microbial community” paradigm, intergating multi-scale metabolic modeling and emergent property prediction, AI-powered ecological niche decomposition and closed-loop BT enhanced evolutionary framework for continuous optimization of digital twins through experimental feedback. This fusion facilitates the rational design and real-time optimization of programmable microbial ecosystems, greatly enhancing biohydrogen producing control and efficiency. The transition to digital and data-driven design, utilizing multi-omics and ecosystem-level analytics, further bolsters precision and scalability. While moving from single cells to complex microbial consortia introduces challenges, such as non-linear dynamics and ecosystem stability, the synergy of AI and BT underpins the intelligent, resilient, and sustainable production of biohydrogen, thereby reinforcing its potential as a foundational component of China's renewable energy landscape. 展开更多
关键词 Artificial intelligence Biotechnology Biohydrogen Rational design Digital cell Digital microbiota Digital system
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Advanced Design for High-Performance and AI Chips 认领 引用 被引量：1
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作者 Ying Cao Yuejiao Chen +2 位作者 Xi Fan Hong Fu Bingang Xu 《Nano-Micro Letters》 SCIE EI CAS CSCD 2026年第1期306-336,共31页
Recent years have witnessed transformative changes brought about by artificial intelligence(AI)techniques with billions of parameters for the realization of high accuracy,proposing high demand for the advanced and AI ... Recent years have witnessed transformative changes brought about by artificial intelligence(AI)techniques with billions of parameters for the realization of high accuracy,proposing high demand for the advanced and AI chip to solve these AI tasks efficiently and powerfully.Rapid progress has been made in the field of advanced chips recently,such as the development of photonic computing,the advancement of the quantum processors,the boost of the biomimetic chips,and so on.Designs tactics of the advanced chips can be conducted with elaborated consideration of materials,algorithms,models,architectures,and so on.Though a few reviews present the development of the chips from their unique aspects,reviews in the view of the latest design for advanced and AI chips are few.Here,the newest development is systematically reviewed in the field of advanced chips.First,background and mechanisms are summarized,and subsequently most important considerations for co-design of the software and hardware are illustrated.Next,strategies are summed up to obtain advanced and AI chips with high excellent performance by taking the important information processing steps into consideration,after which the design thought for the advanced chips in the future is proposed.Finally,some perspectives are put forward. 展开更多
关键词 Artificial intelligence Advanced chips AI chips Design tactics Review and perspective
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AI-assisted design of 3 D-printed prosthesis for integrated replacement of the hip,femur,and knee caused by osseous hydatidosis 认领 引用 被引量：1
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作者 Yanlong Han Haoyuan Lei +7 位作者 Ruozhen Jia Wei Zhao Habaxi Kaken Deli Wang Yongsheng Liu Zhen Tan Li Wang Changchun Zhou 《Bio-Design and Manufacturing》 SCIE EI CAS CSCD 2026年第1期94-99,I0017,共6页
Cases of widespread bone hydatid infection are relatively rare in clinical practice.In this study,we reported for the first time a validated integrated repair therapy for multiple bone tissues,including the hip,femur,... Cases of widespread bone hydatid infection are relatively rare in clinical practice.In this study,we reported for the first time a validated integrated repair therapy for multiple bone tissues,including the hip,femur,and knee,caused by echinococ cosis.Artificial intelligence(AI)was used to develop a targeted surgical plan and to design a personalized prosthesis.Finite element analysis(FEA)was used to optimize the mechanical effectiveness of a customized integrated replacement prosthesis and to model stress distribution in the surrounding bone.Three-dimensional(3 D)printing was used to fabricate a customized prosthesis.With the assistance of AI,FEA,and 3 D printing technology,a personalized surgical plan and customized prosthesis were successfully constructed based on the patient’s disease.This approach achieved a successful therapeutic effect,demonstrating that AI-assisted personalized medicine holds great promise for the future. 展开更多
关键词 develop targeted surgical plan optimize mechanical effectiveness AI assisted design D printed prosthesis design personalized prosthesisfinite element analysis fea bone tissuesincluding bone hydatid infection integrated repair therapy
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Aerodynamics-informed parametric method for rapid waverider design based on the second-order curved shock theory 认领 引用 被引量：1
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作者 Yiqi TANG Xiaogang ZHENG +2 位作者 Chongguang SHI Chengxiang ZHU Yancheng YOU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第3期1-23,共23页
Waverider design based on osculating theory presents two critical issues:robust specification of design curves and accurate solution of the basic flowfield.Although the existing parametric approaches have advanced rap... Waverider design based on osculating theory presents two critical issues:robust specification of design curves and accurate solution of the basic flowfield.Although the existing parametric approaches have advanced rapid configuration generation through geometric parameterization frameworks,they critically neglect the inherent coupling between aerodynamic constraints and geometric design parameters.To overcome this limitation,an Aerodynamics-Informed Parametric(AIP)method is developed by analytically deriving three waverider design curves and integrating them with the second-order curved shock theory.This method enables rapid waverider surface design while accounting for inflow conditions and shock wave geometry.Three typical waveriders,each featuring distinct combinations of design curves as inputs,are constructed and evaluated through inviscid and viscous numerical simulations to validate the applicability and accuracy of the AIP method.The results indicate that waveriders derived using the AIP method successfully reproduce the preassigned shock waves and original flowfields.Compared to traditional waverider design techniques based on the method of characteristics,the AIP method reduces computation time by approximately 94%,while maintaining errors in the inviscid lift-to-drag ratio,viscous lift-to-drag ratio,and volumetric efficiency below 0.1%,4.0%,and 0.1%,respectively.Additionally,a specially designed model is fabricated for the wind-tunnel tests to analyze the hypersonic aerodynamic performance of the waverider.Both numerical and experimental results confirm the feasibility of the AIP method,making it a promising candidate for waverider design and optimization. 展开更多
关键词 Analytical expressions Curved shock theory Hypersonic vehicles Rapid waverider design
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Data-driven insights into nonradical activation mechanisms for biochar inverse design:A synergistic approach using DFT and machine learning with meta-analysis 认领 引用 被引量：1
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作者 Honglin Chen Rupeng Wang +1 位作者 Zixiang He Shih-Hsin Ho 《Chinese Chemical Letters》 SCIE CAS CSCD 2026年第2期708-712,共5页
Machine learning(ML)is recognized as a potent tool for the inverse design of environmental functional material,particularly for complex entities like biochar-based catalysts(BCs).Thus,the tailored BCs can have a disti... Machine learning(ML)is recognized as a potent tool for the inverse design of environmental functional material,particularly for complex entities like biochar-based catalysts(BCs).Thus,the tailored BCs can have a distinct ability to trigger the nonradical pathway in advance oxidation processes(AOPs),promising a stable,rapid and selective degradation of persistent contaminants.However,due to the inherent“black box”nature and limitations of input features,results and conclusions derived from ML may not always be intuitively understood or comprehensively validated.To tackle this challenge,we linked the front-point interpretable analysis approaches with back-point density functional theory(DFT)calculations to form a chained learning strategy for deeper sight into the intrinsic activation mechanism of BCs in AOPs.At the front point,we conducted an easy-to-interpret meta-analysis to validate two strategies for enhancing nonradical pathways by increasing oxygen content and specific surface area(SSA),and prepared oxidized biochar(OBC500)and SSA-increased biochar(SBC900)by controlling pyrolysis conditions and modification methods.Subsequently,experimental results showed that OBC500 and SBC900 had distinct dominant degradation pathways for 1O2 generation and electron transfer,respectively.Finally,at the end point,DFT calculations revealed their active sites and degradation mechanisms.This chained learning strategy elucidates fundamental principles for BC inverse design and showcases the exceptional capacity to integrate computational techniques to accelerate catalyst inverse design. 展开更多
关键词 Machine learning DFT Biochar-based catalysts Nonradical activation Peroxymonosulfate Inverse design Meta-analysis
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Automatic gating and riser system design and defect control for K4169 superalloy guide blade casting based on parametric 3D modeling-simulation integrated system 认领 引用 被引量：1
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作者 Le-chuan Li Ya-jun Yin +4 位作者 Bing-zheng Fan Guo-yan Shui Xiao-yuan Ji Jian-xin Zhou Lei Jin 《China Foundry》 SCIE EI CAS CSCD 2026年第1期20-30,共11页
Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical si... Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements,but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions,making real-time adjustments to gating and riser designs challenging.In this study,an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed,which enhances the flexibility and usability of evaluating the casting process by simulation.Firstly,geometric feature extraction technology is employed to obtain the geometric information of the target casting.Based on this information,an automated design framework for gating and riser systems is established,incorporating multiple structural parameters for real-time process control.Subsequently,the simulation results for various structural parameters are analyzed,and the influence of these parameters on casting formation is thoroughly investigated.Finally,the optimal design scheme is generated and validated through experimental verification.Simulation analysis and experimental results show that using a larger gate neck(24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state,effectively eliminating shrinkage cavities and enhancing process yield by 15%. 展开更多
关键词 numerical simulation automatic design investment casting parametric 3D modeling gating and riser system
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Structure design of oxide path mechanism-based electrocatalysts for enhanced oxygen evolution reaction performance 认领 引用 被引量：2
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作者 Jin Yang Shengbo Sang Meiling Wang 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2026年第2期464-483,I0011,共20页
The oxygen evolution reaction(OER)suffers from sluggish kinetics,necessitating efficient electrocatalysts to reduce overpotentials in water splitting.Currently recognized OER mechanisms primarily include the adsorbate... The oxygen evolution reaction(OER)suffers from sluggish kinetics,necessitating efficient electrocatalysts to reduce overpotentials in water splitting.Currently recognized OER mechanisms primarily include the adsorbate evolution mechanism(AEM),lattice oxygen mechanism(LOM),and oxide path mechanism(OPM).Compared to AEM,limited by scaling relationships,and LOM,constrained by stability issues,the OPM offers a promising alternative by enabling direct O-O bond formation via dual active sites,thus bypassing*OOH intermediates and lattice O involvement and achieving a balance between activity and durability.However,activating the OPM process requires precise control over the spatial and electronic structure of active sites,making the design of OPM-based catalysts challenging.While previous reviews have focused on homo/heteronuclear diatomic perspectives of OPM-based catalysts,it is urgent to systematically summarize design strategies to provide a rational reference for their development.Herein,a review of design strategies for OPM-based OER catalysts across three scales is comprehensively presented,including in-situ engineering,doping-enabled sites reconstruction,and introducing new sites for nanoparticles,direct synthesis or post-treatments for molecular catalysts,and doping or template strategies for atom pairs or arrays.The unique advantage of atom arrays is also highlighted,and their future research directions and possible strategies are discussed.This review provides a systematic summary and forward-looking perspectives for rationally designing high-performance OPM-based OER catalysts. 展开更多
关键词 Oxygen evolution reaction Oxide path mechanism Dual sites Nanoparticle catalysts Molecular catalysts Atom arrays Design strategies
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OptimizationDesign and Numerical Simulation of Variable Tube Diameter Heat Exchanger for Split Air Conditioning Indoor Unit 认领 引用 被引量：1
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作者 Zheming Cheng Xinping Ou Yang +2 位作者 Leren Tao Zihao Wang Ke Sun 《Frontiers in Heat and Mass Transfer》 EI CAS 2026年第1期288-313,共26页
Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers of... Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers offer advantages such as reduced material usage,lower refrigerant charge,and compact structure.However,they also face challenges,including increased refrigerant pressure drop and smaller heat transfer area inside the tubes.This paper combines the advantages and disadvantages of both small and large-diameter tubes and proposes a combined-diameter heat exchanger,consisting of large and small diameters,for use in the indoor units of split-type air conditioners.There are relatively few studies in this area.In this paper,A theoretical and numerical computation method is employed to establish a theoretical-numerical calculation model,and its reliability is verified through experiments.Using this model,the optimal combined diameters and flow path design for a combined-diameter heat exchanger using R32 as the working fluid are derived.The results show that the heat transfer performance of all combined diameter configurations improves by 2.79%to 8.26%compared to the baseline design,with the coefficient of performance(COP)increasing from 4.15 to 4.27~4.5.These designs can save copper material,but at the cost of an increase in pressure drop by 66.86%to 131.84%.The scheme IIIH,using R32,is the optimal combined-diameter and flow path configuration that balances both heat transfer performance and economic cost. 展开更多
关键词 Split air condition variable tube diameter enhanced heat transfer numerical simulation structural design optimization
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Reimagining synergy between architects and computational systems:Insights from web-based generative design applications 认领 引用
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作者 Baizhou Zhang Yichen Mo Biao Li 《Frontiers of Architectural Research》 EI CSCD 2026年第3期795-805,共11页
This study reconsiders the evolving relationship between architects and computa-tional systems in the context of increasingly embedded digital and intelligent technologies.Rather than focusing only on what tools can d... This study reconsiders the evolving relationship between architects and computa-tional systems in the context of increasingly embedded digital and intelligent technologies.Rather than focusing only on what tools can do,it looks at how tool-making itself helps reshape how architects think and work.Through four web-based generative design applications―SIM-Forms,ANYSite,NEXUSpace,and FLEXUrban―this paper investigates how architects engage with computation not only as tool users,but also as developers of generative algorithms,and organizers of workflows.Based on these cases,the paper proposes a framework of three interrelated mechanisms of human-computer collaboration:reconstructing intuitive media,adopting algorithmic design thinking,and organizing programmable design systems.The framework aims to provide a conceptual foundation for reimagining how architects can stay actively involved in shaping the tools and processes that define digital design today. 展开更多
关键词 Generative design Human-computer collaboration Computational design Architectural agency Design tools
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pH-dependent electrochemical oxidation of 5-hydroxymethylfurfural:Reaction mechanism,catalyst design,and reactor design across alkaline to acidic media 认领 引用
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作者 Peiyun Zhou Xikang Zhao +2 位作者 Yang Song Ruixiang Ge Haohong Duan 《Smart Molecules》 CSCD 2026年第1期45-67,共23页
The electrochemical oxidation of biomass-derived platform molecule 5-hydroxymethylfurfural(HMF)represents a crucial pathway for green transformation into high-value chemicals,yet its reaction pathway selectivity,effic... The electrochemical oxidation of biomass-derived platform molecule 5-hydroxymethylfurfural(HMF)represents a crucial pathway for green transformation into high-value chemicals,yet its reaction pathway selectivity,efficiency,and catalyst stability are strongly dependent on the electrolyte pH environment.Under alkaline conditions,high OH−concentration facilitates preferential aldehyde group oxidation and efficient deprotonation,enabling highly efficient synthesis of 2,5-furandicarboxylic acid,but simultaneously induces HMF self-degradation and complicates product separation.As pH decreases,the reaction mechanism shifts toward enhanced hydroxymethyl oxidation,leading to intermediate accumulation(such as 5-hydroxymethyl-2-furancarboxylic acid,2,5-diformylfuran,and 5-formyl-2-furancarboxylic acid)with challenging selectivity control and significantly slowed reaction kinetics.This review comprehensively examines the systematic differences in HMF oxidation pathways and surface catalytic mechanisms across the full pH range from alkaline to acidic conditions.Addressing the distinct reaction characteristics and core challenges in alkaline,near-neutral,and acidic media,we systematically evaluate design strategies for high-efficiency electrocatalysts and explore reactor design aspects.Future research should focus on process integration(with tailored reactor design)for energy consumption reduction in alkaline systems,targeted synthesis of diverse oxidation products in near-neutral systems,and innovative catalyst development for acidic systems,thereby advancing the efficiency,selectivity,and practical application of HMF electrooxidation technologies across the entire pH spectrum through synergistic optimization of catalyst,reactor,and process. 展开更多
关键词 biomass valorization electrocatalyst design full pH HMF electrooxidation reaction mechanism reactor design
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World’s first AI-powered magnesium materials design platform“MagNova”has been launched 认领 引用
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作者 Yuan Yuan Jun Tan +1 位作者 Aitao Tang Xianhua Chen 《Journal of Magnesium and Alloys》 SCIE EI CAS CSCD 2026年第4期11-12,共2页
The world’s first big data and intelligent design platform for magnesium materials,“MagNova”,jointly developed by Mingyue Lake Laboratory,Chongqing University,and the National Engineering Research Center for Magnes... The world’s first big data and intelligent design platform for magnesium materials,“MagNova”,jointly developed by Mingyue Lake Laboratory,Chongqing University,and the National Engineering Research Center for Magnesium Alloys,was officially launched. 展开更多
关键词 AI powered Chongqing University intelligent design platform intelligent design big data design platform magnesium materials Mingyue Lake Laboratory
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Inverse design of 3D integrated high-efficiency grating couplers using deep learning 认领 引用
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作者 Yu Wang Yue Wang +4 位作者 Guohui Yang Kuang Zhang Xing Yang Chunhui Wang Yu Zhang 《Chinese Physics B》 SCIE EI CAS CSCD 2026年第2期363-373,共11页
In recent years,the use of deep learning to replace traditional numerical methods for electromagnetic propagation has shown tremendous potential in the rapid design of photonic devices.However,most research on deep le... In recent years,the use of deep learning to replace traditional numerical methods for electromagnetic propagation has shown tremendous potential in the rapid design of photonic devices.However,most research on deep learning has focused on single-layer grating couplers,and the accuracy of multi-layer grating couplers has not yet reached a high level.This paper proposes and demonstrates a novel deep learning network-assisted strategy for inverse design.The network model is based on a multi-layer perceptron(MLP)and incorporates convolutional neural networks(CNNs)and transformers.Through the stacking of multiple layers,it achieves a high-precision design for both multi-layer and single-layer raster couplers with various functionalities.The deep learning network exhibits exceptionally high predictive accuracy,with an average absolute error across the full wavelength range of 1300–1700 nm being only 0.17%,and an even lower predictive absolute error below 0.09%at the specific wavelength of 1550 nm.By combining the deep learning network with the genetic algorithm,we can efficiently design grating couplers that perform different functions.Simulation results indicate that the designed single-wavelength grating couplers achieve coupling efficiencies exceeding 80%at central wavelengths of 1550 nm and 1310 nm.The performance of designed dual-wavelength and broadband grating couplers also reaches high industry standards.Furthermore,the network structure and inverse design method are highly scalable and can be applied not only to multi-layer grating couplers but also directly to the prediction and design of single-layer grating couplers,providing a new perspective for the innovative development of photonic devices. 展开更多
关键词 deep learning inverse design grating couplers photonic devices
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A Topology-Guided Design Strategy for Polymerized Naphthoquinone Cathodes in Rechargeable Aluminium-Ion Batteries 认领 引用
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作者 Jia Qiao Yanfang Wang +6 位作者 Jiming Peng Guokang Wei Xinqi Xu Borui Wang Zhenhua Luo Aichun Dou Sijiang Hu 《Rare Metals》 SCIE EI CAS CSCD 2026年第5期391-400,共10页
Rechargeable aluminium-ion batteries(RAIBs)are promising candidates for sustainable energy storage owing to their low cost,safety,and resource abundance.However,the lack of durable cathode materials restricts their de... Rechargeable aluminium-ion batteries(RAIBs)are promising candidates for sustainable energy storage owing to their low cost,safety,and resource abundance.However,the lack of durable cathode materials restricts their development.Here,we propose a topology-guided design strategy by synthesizing three thioether-bridged naphthoquinone polymers from 1,4-naphthoquinone.Structural characterization combined with density functional theory calculations confirms that polymerization reduces crystallinity,enhances thermal stability,and extendsπ-conjugation,with the para-topology providing the most favorable configuration and strongest AlCl2+coordination.The nearly planar para-naphthoquinone polymer(p-PNQ)exhibits an extended conjugated backbone,reduced bandgap,and uniform electrostatic potential distribution.Electrochemical tests reveal that p-PNQ delivers 146 mAh g-1 initially at 0.1 A g-1 and a 97.2%retention after 500 cycles,surpassing pristine 1,4-NQ and o-/m-isomers.Ex situ analyses confirm that redox activity originates from reversible coordination between carbonyl groups and AlCl2+species.This study establishes molecular topology as a key parameter for designing organic cathodes,and demonstrates that topology-controlled strategies enable durable,high-performance cathodes for energy storage in RAIBs. 展开更多
关键词 naphthoquinone organic cathode rechargeable aluminium-ion batteries topology-guided design
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Numerical investigation of slurry shield cutterhead design for clogging mitigation using a coupled computational fluid dynamics–discrete element method approach 认领 引用
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作者 Yi YANG Jingwen QU +3 位作者 Xinggao LI Xuyang WANG Shuai ZHENG Changjin MA 《ENGINEERING Structure and Civil Engineering》 SCIE EI CAS CSCD 2026年第1期202-220,共19页
Cutterhead clogging remains a significant challenge in slurry shield tunneling,particularly in clay-rich strata,leading to reduced efficiency and increased operational costs.This paper presents a comparative numerical... Cutterhead clogging remains a significant challenge in slurry shield tunneling,particularly in clay-rich strata,leading to reduced efficiency and increased operational costs.This paper presents a comparative numerical study of three common slurry shield cutterhead designs,atmospheric soft-soil cutterhead,atmospheric mix-ground cutterhead,and conventional cutterhead,using a coupled computational fluid dynamics–discrete element method(CFD–DEM)approach.The integrated CFD–DEM model allows for a detailed examination of slurry flow dynamics and granular material behavior within the cutterhead chamber.The analysis focuses on muck discharge efficiency,quantifying the volume of excavated material effectively removed,as well as particle accumulation patterns within the slurry chamber,identifying areas prone to clogging.Furthermore,the study examines cutterhead torque and thrust requirements for each design,providing a comprehensive performance assessment.Results demonstrate variations in performance across the three types,with the conventional cutterhead exhibiting the highest muck discharge rate under the tested conditions,while atmospheric-pressure designs show a higher risk of clogging due to increased particle accumulation in specific zones.This work contributes to a more informed selection and design methodology for slurry shield cutterheads,enabling engineers to optimize designs for specific soil conditions and minimize the risk of clogging in challenging geological conditions. 展开更多
关键词 slurry shield cutterhead design cutterhead clogging CFD-DEM modeling
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Design and characterization of a novel vehicle-mounted dual-reactor smog chamber for controlled and real-world atmospheric process simulations 认领 引用
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作者 Chenghao Liao Chao Peng +6 位作者 Weiqiang Yang Chenshuo Ye Wei Song Junling Li Hong Li Yongbo Zhang Xinming Wang 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2026年第7期19-28,共10页
Smog chambers provide controlled environments for studying atmospheric processes.This study presents the design and characterization of a novel vehicle-mounted dual-reactor smog chamber,capable of simulating atmospher... Smog chambers provide controlled environments for studying atmospheric processes.This study presents the design and characterization of a novel vehicle-mounted dual-reactor smog chamber,capable of simulating atmospheric oxidation processes in both indoor and outdoor settings.Developed at the Guangdong Provincial Academy of Environmental Science,this innovative system consists of two 8 m³ cylindrical fluorinated ethylene propylene Teflon reactors housed in a van semi-trailer.The reactors can independently operate under black lamp irradiation or solar radiation,allowing seamless transitions between controlled laboratory conditions and real-world outdoor scenarios.Comprehensive characterization demonstrates excellent performance in temperature control(within±0.5℃ between 25 and 35℃ for indoor experiments),rapid mixing(2-3 min),high light transmission(>88%at 300-950 nm)and low wall loss rates for gases(10⁻⁵-10⁻⁴min⁻¹)and particles(0.12-0.17 h⁻¹).Parallel experiments in two reactors yield consistent results,confirming the reliability of the system for comparative studies.Validation experiments,including toluene-NOₓ photochemical oxidation and α-pinene ozonolysis,showed strong agreement with box model simulations,demonstrating the chamber’s utility for investigating atmospheric chemical mechanisms and secondary organic aerosol formation.The dual-reactor design,combining mobility and adaptability,enables versatile and high-fidelity simulations of oxidation processes. 展开更多
关键词 Smog chamber Dual-reactor Mobile design Atmospheric oxidation SOA formation Ozone
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The surface binding and energy issues in the rational design of separators for Li||S batteries 认领 引用
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作者 Hongfang Du Lijing Wang +8 位作者 Shuyu Cheng Chao Wu Sheng Yang Yang Liu Yi Zhao Dandan Cui Shaowei Zhang Shixue Dou Liangxu Lin 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2026年第1期987-1013,I0021,共27页
Lithium-sulfur batteries(LSBs)represent a next-generation energy storage technology,but widespread applications are restricted by the shuttle of lithium polysulfides(LiPSs).The rational design of separators has been d... Lithium-sulfur batteries(LSBs)represent a next-generation energy storage technology,but widespread applications are restricted by the shuttle of lithium polysulfides(LiPSs).The rational design of separators has been demonstrated to be one of the most efficient and cost-effective strategies to curb the shuttle effect,and tremendous research progress has been achieved.The efficiency of a separator depends on its interaction with LiPSs,which is governed by the surface energy and binding strength.Despite several review works that have been reported to advance the separators,most of them primarily focus on active material innovation and construction.The most crucial issues of surface binding energy have not been systematically reviewed,limiting the precise design of efficient separators.In this review,fundamentals related to surface energy and binding interactions with LiPSs are comprehensively analyzed and discussed.With surface binding and energy main lines,the advancements in separator engineering strategies are elaborately summarized and discussed.Moreover,techniques for evaluating affinity to LiPSs are thoroughly analyzed to avoid any ambiguities in measurement.Based on the research context,valuable research directions are suggested to construct efficient separators.This work provides guidelines to regulate the surface binding and energy of separators for high-performance LSBs. 展开更多
关键词 Lithium-sulfur batteries Separator Surface binding affinity Surface energy Rational design
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Machine learning accelerates the design and discovery of single-atom catalysts for electrochemical reactions 认领 引用
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作者 Shiyan Wang Chaopeng Liu +5 位作者 Weiyao Hao Xianjun Zhu Xianghong Niu Dongwei Ma Longlu Wang Qiang Zhao 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2026年第4期347-371,I0009,共25页
Single-atom catalysts(SACs)stand at the forefront of catalysis research,attributable to their distinctive electronic structure,maximized atomic utilization,and exceptional catalytic performance,making them highly prom... Single-atom catalysts(SACs)stand at the forefront of catalysis research,attributable to their distinctive electronic structure,maximized atomic utilization,and exceptional catalytic performance,making them highly promising for renewable energy and sustainable energy conversion applications.However,their complex design parameters—including metal active sites,coordination environments,and substrate interactions—pose significant challenges for traditional experimental and computational approaches.These limitations hinder the systematic understanding of structure-property relationships in SACs.Machine learning(ML)offers a powerful alternative,enabling rapid screening and rational design by uncovering hidden patterns in high-dimensional catalyst data.This review summarizes recent advances in applying ML to the design and discovery of SACs.First,we analyze and summarize the recent trends and representative works in ML applications for SACs research.Next,a systematic workflow is proposed to guide researchers through ML-assisted SACs discovery,from data engineering to model application.We then showcase ML's impact on critical catalytic reactions—CO2RR,HER,NRR,and ORR/OER—demonstrating its ability to uncover high-performance catalysts.Finally,we discuss challenges and future directions for integrating ML with SAC research,aiming to inspire innovative solutions and interdisciplinary collaboration.By bridging ML and catalysis,this review provides researchers with a practical roadmap to expedite the advancement of SACs. 展开更多
关键词 Machine learning Single-atom catalysts Catalysts design Catalysts discovery Electrochemical reactions
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