Brazing filler metals are widely applied,which serve as an industrial adhesive in the joining of dissimilar structures.With the continuous emergence of new structures and materials,the demand for novel brazing filler ...Brazing filler metals are widely applied,which serve as an industrial adhesive in the joining of dissimilar structures.With the continuous emergence of new structures and materials,the demand for novel brazing filler metals is ever-increasing.It is of great significance to investigate the optimized composition design methods and to establish systematic design guidelines for brazing filler metals.This study elucidated the fundamental rules for the composition design of brazing filler metals from a three-dimensional perspective encompassing the basic properties of applied brazing filler metals,formability and processability,and overall cost.The basic properties of brazing filler metals refer to their mechanical properties,physicochemical properties,electromagnetic properties,corrosion resistance,and the wettability and fluidity during brazing.The formability and processability of brazing filler metals include the processes of smelting and casting,extrusion,rolling,drawing and ring-making,as well as the processes of granulation,powder production,and the molding of amorphous and microcrystalline structures.The cost of brazing filler metals corresponds to the sum of materials value and manufacturing cost.Improving the comprehensive properties of brazing filler metals requires a comprehensive and systematic consideration of design indicators.Highlighting the unique characteristics of brazing filler metals should focus on relevant technical indicators.Binary or ternary eutectic structures can effectively enhance the flow spreading ability of brazing filler metals,and solid solution structures contribute to the formability.By employing the proposed design guidelines,typical Ag based,Cu based,Zn based brazing filler metals,and Sn based solders were designed and successfully applied in major scientific and engineering projects.展开更多
The big-tapered profiled ring disk is a key component of engines for rockets and missiles.A new forming technology,as called spinning-rolling process,has been proposed previously for the high performance,high efficien...The big-tapered profiled ring disk is a key component of engines for rockets and missiles.A new forming technology,as called spinning-rolling process,has been proposed previously for the high performance,high efficiency and low-cost manufacturing of the component.Blank design is the key part of plastic forming process design.For spinning-rolling process,the shape and size of the blank play a crucial role in process stability,deformation behavior and dimensional accuracy.So this work proposes a blank design method to determine the geometry structure and sizes of the blank.The mathematical model for calculating the blank size has been deduced based on volume conservation and neutral layer length invariance principle.The FE simulation and corresponding trial production of an actual big-tapered profiled ring disk show that the proposed blank design method is applicative.In order to obtain a preferred blank,the influence rules of blank size determined by different deformation degrees(rolling ratio k)on the spinning-rolling process are revealed by comprehensive FE simulations.Overall considering the process stability,circularity of the deformed ring disk and forming forces,a reasonable range of deformation degree(rolling ratio k)is recommended for the blank design of the new spinning-rolling process.展开更多
[Objectives]To optimize the optimal extraction process of Qingdu Jianpi Mixture.[Methods]Taking water addition ratio,extraction time and extraction times as process investigation factors,psoralen content,astilbin cont...[Objectives]To optimize the optimal extraction process of Qingdu Jianpi Mixture.[Methods]Taking water addition ratio,extraction time and extraction times as process investigation factors,psoralen content,astilbin content and dry extract yield as evaluation indicators,the main influencing factors and level range of the extraction process of Qingdu Jianpi Mixture were determined on the basis of single factor test method,and the optimal weight coefficient was screened by AHP-entropy method mixed with weighting method.Combined with L_(9)(3^(4))orthogonal experiment,the best extraction process was obtained.At the same time,thin-layer chromatographic identification was used to identify Ficus simplicissima Lour.and Smilax glabra Roxb.in the medicinal liquid.[Results]The best extraction process:add 1:12 water to the prescription decoction pieces,extract under reflux for 2 times,1.5 h per time,and combine the filtrate to 250 mL.Thin layer chromatography analysis showed that the spots of Ficus simplicissima Lour.and Smilax glabra Roxb.in the medicinal solution were the same as those of reference substances at the corresponding positions,and the negative control had no interference.[Conclusions]The experimental method is reasonable and feasible,and the process is reliable,which can provide experimental reference for the subsequent application of in-hospital preparations and research and development of Qingdu Jianpi Mixture.展开更多
Conceptual process design (CPD) research focuses on finding design alternatives that address various design problems. It has a long history of well-established methodologies to answer these complex questions, such as ...Conceptual process design (CPD) research focuses on finding design alternatives that address various design problems. It has a long history of well-established methodologies to answer these complex questions, such as heuristics, mathematical programming, and pinch analysis. Nonetheless, progress continues from different formulations of design problems using bottom-up approaches, to the utilization of new tools such as artificial intelligence (AI). It was not until recently that AI methods were involved again in assisting the decision-making steps for chemical engineers. This has led to a gap in understanding AI's capabilities and limitations within the field of CPD research. Thus, this article aims to provide an overview of conventional methods for process synthesis, integration, and intensification approaches and survey emerging AI-assisted process design applications to bridge the gap. A review of all AI-assisted methods is highlighted, where AI is used as a key component within a design framework, to explain the utility of AI with comparative examples. The studies were categorized into supervised and reinforcement learning based on the machine learning training principles they used to enhance the understanding of requirements, benefits, and challenges that come with it. Furthermore, we provide challenges and prospects that can facilitate or hinder the progress of AI-assisted approaches in the future.展开更多
In the year 1971,the world’s biggest structural biology collaboration name—The Research Collaboratory for Structural Bioinformatics(RCSB),was formed to gather all the structural biologists at a single platform and t...In the year 1971,the world’s biggest structural biology collaboration name—The Research Collaboratory for Structural Bioinformatics(RCSB),was formed to gather all the structural biologists at a single platform and then extended out to be the world’s most extensive structural data repository named RCSB-Protein Data Bank(PDB)(https://www.rcsb.org/)that has provided the service for more than 50 years and continues its legacy for the discoveries and repositories for structural data.The RCSB has evolved from being a collaboratory network to a full-fledged database and tool with a huge list of protein structures,nucleic acid-containing structures,ModelArchive,and AlphaFold structures,and the best is that it is expanding day by day with computational advancement with tools and visual experiences.In this review article,we have discussed how RCSB has been a successful collaboratory network,its expansion in each decade,and how it has helped the ground-breaking research.The PDB tools that are helping the researchers,yearly data deposition,validation,processing,and suggestions that can help the developer improve for upcoming years are also discussed.This review will help future researchers understand the complete history of RCSB and its developments in each decade and how various future collaborative networks can be developed in various scientific areas and can be successful by keeping RCSB as a case study.展开更多
Proton exchange membrane water electrolyzer(PEMWE)is crucial for the storage and conversion of renewable energy.However,the harsh anode environment and the oxygen evolution reaction(OER),which involves a four-electron...Proton exchange membrane water electrolyzer(PEMWE)is crucial for the storage and conversion of renewable energy.However,the harsh anode environment and the oxygen evolution reaction(OER),which involves a four-electron transfer,result in a significant overpotential that limits the overall efficiency of hydrogen production.Identifying active sites in the OER is crucial for understanding the reaction mechanism and guiding the development of novel electrocatalysts with high activity,cost-effectiveness,and durability.Herein,we summarize the widely accepted OER mechanism in acidic media,in situ characterization and monitoring of active sites during the reaction,and provide a general understanding of the active sites on various catalysts in the OER,including Ir-based metals,Ir-based oxides,carbon/oxide-supported Ir,Ir-based perovskite oxides,and Ir-based pyrochlore oxides.For each type of electrocatalysts,reaction pathways and actual active sites are proposed based on in situ characterization techniques and theoretical calculations.Finally,the challenges and strategic research directions associated with the design of highly efficient Ir-based electrocatalysts are discussed,offering new insights for the further scientific advancement and practical application of acidic OER.展开更多
Casting technology is a fundamental and irreplaceable method in advanced manufacturing.The design and optimization of casting processes are crucial for producing high-performance,complex metal components.Transitioning...Casting technology is a fundamental and irreplaceable method in advanced manufacturing.The design and optimization of casting processes are crucial for producing high-performance,complex metal components.Transitioning from traditional process design based on"experience+experiment"to an integrated,intelligent approach is essential for achieving precise control over microstructure and properties.This paper provides a comprehensive and systematic review of intelligent casting process design and optimization for the first time.First,it explores process design methods based on casting simulation and integrated computational materials engineering(ICME).It then examines the application of machine learning(ML)in process design,highlighting its efficiency and existing challenges,along with the development of integrated intelligent design platforms.Finally,future research directions are discussed to drive further advancements and sustainable development in intelligent casting design and optimization.展开更多
The forming quality of metal bipolar plate(BPP)flow channels in proton exchange membrane fuel cells(PEMFCs)is a key factor affecting battery performance.A flow channel with straight sidewalls and a low thinning rate c...The forming quality of metal bipolar plate(BPP)flow channels in proton exchange membrane fuel cells(PEMFCs)is a key factor affecting battery performance.A flow channel with straight sidewalls and a low thinning rate can enhance battery output.Roll forming,as a new technology for BPP production,offers advantages such as a low thinning rate and high efficiency.However,existing roll curve design methods struggle to accommodate both low thinning rates and straight sidewall angles simultaneously.This study aims to develop flow channels with right-angled sidewalls,which provide benefits such as a low thinning rate,reduced residual stress,and high accuracy.A roller tooth profile was designed to achieve a flow channel with right-angled sidewalls and minimal thinning.Simulations and experiments were conducted to validate the feasibility of this novel design method for the roll forming process.The study investigated the effects of roller tooth parameters on sidewall angle,thinning rate,and residual stress.A multifactor evaluation method was developed to optimize the tip fillet radius and the tooth profile backlash of the roller.The results indicated that the tip fillet radius and the tooth profile backlash were negatively correlated with the sidewall angle.As the tip fillet radius and tooth profile backlash increased,the thinning rate and residual stress decreased.With a tip fillet radius of 0.25 mm and a tooth profile backlash of 0.19 mm,the flow channel achieved an approximately right-angled sidewall,a maximum thinning rate of 7.7%,a 29.6%reduction in maximum residual stress,and maximum and average residual stress imbalance values of 7.1%and 3.2%,respectively.This study proposes a new design method for a right-angled sidewall runner roller gear profile,facilitating the roll forming of metal BPPs with right-angled sidewalls and minimal thinning.This method provides theoretical support for the large-scale application of roll forming in the manufacture of PEMFC BPPs.展开更多
In the foundry industries,process design has traditionally relied on manuals and complex theoretical calculations.With the advent of 3D design in casting,computer-aided design(CAD)has been applied to integrate the fea...In the foundry industries,process design has traditionally relied on manuals and complex theoretical calculations.With the advent of 3D design in casting,computer-aided design(CAD)has been applied to integrate the features of casting process,thereby expanding the scope of design options.These technologies use parametric model design techniques for rapid component creation and use databases to access standard process parameters and design specifications.However,3D models are currently still created through inputting or calling parameters,which requires numerous verifications through calculations to ensure the design rationality.This process may be significantly slowed down due to repetitive modifications and extended design time.As a result,there are increasingly urgent demands for a real-time verification mechanism to address this issue.Therefore,this study proposed a novel closed-loop model and software development method that integrated contextual design with real-time verification,dynamically verifying relevant rules for designing 3D casting components.Additionally,the study analyzed three typical closed-loop scenarios of agile design in an independent developed intelligent casting process system.It is believed that foundry industries can potentially benefit from favorably reduced design cycles to yield an enhanced competitive product market.展开更多
This review presents a comprehensive and forward-looking analysis of how Large Language Models(LLMs)are transforming knowledge discovery in the rational design of advancedmicro/nano electrocatalyst materials.Electroca...This review presents a comprehensive and forward-looking analysis of how Large Language Models(LLMs)are transforming knowledge discovery in the rational design of advancedmicro/nano electrocatalyst materials.Electrocatalysis is central to sustainable energy and environmental technologies,but traditional catalyst discovery is often hindered by high complexity,fragmented knowledge,and inefficiencies.LLMs,particularly those based on Transformer architectures,offer unprecedented capabilities in extracting,synthesizing,and generating scientific knowledge from vast unstructured textual corpora.This work provides the first structured synthesis of how LLMs have been leveraged across various electrocatalysis tasks,including automated information extraction from literature,text-based property prediction,hypothesis generation,synthesis planning,and knowledge graph construction.We comparatively analyze leading LLMs and domain-specific frameworks(e.g.,CatBERTa,CataLM,CatGPT)in terms of methodology,application scope,performance metrics,and limitations.Through curated case studies across key electrocatalytic reactions—HER,OER,ORR,and CO_(2)RR—we highlight emerging trends such as the growing use of embedding-based prediction,retrieval-augmented generation,and fine-tuned scientific LLMs.The review also identifies persistent challenges,including data heterogeneity,hallucination risks,lack of standard benchmarks,and limited multimodal integration.Importantly,we articulate future research directions,such as the development of multimodal and physics-informedMatSci-LLMs,enhanced interpretability tools,and the integration of LLMswith selfdriving laboratories for autonomous discovery.By consolidating fragmented advances and outlining a unified research roadmap,this review provides valuable guidance for both materials scientists and AI practitioners seeking to accelerate catalyst innovation through large language model technologies.展开更多
Direct electrolysis of seawater to produce green hydrogen is a more environmentally friendly process than freshwater electrolysis.The renewable energy sector exhibits tremendous interest in practical seawater electrol...Direct electrolysis of seawater to produce green hydrogen is a more environmentally friendly process than freshwater electrolysis.The renewable energy sector exhibits tremendous interest in practical seawater electrolysis techniques due to its substantial capacity to mitigate the need for freshwater consumption.With the low catalytic efficiency of the current seawater splitting process and the poor reliability of its operation,the process suffers from severe corrosion caused by chloride ions,as well as anodic competition between oxygen evolution and chlorine oxidation reactions.This review provides an overview of the latest electrocatalyst developments for promoting selectivity and stability in seawater electrolysis.Using the characterization and simulation results,as well as active machine learning,advanced electrocatalytic materials can be designed and developed,a research direction that will become increasingly important in the future.A variety of strategies are discussed in detail for designing advanced electrocatalysts in seawater electrolysis,including the surface protective layer,structural regulation by heteroatom doping and vacancies,porous structure,core-shell construction,and 3D hetero-structure construction to hinder chlorine evolution reactions.Finally,future perspectives and challenges for green hydrogen production from seawater electrolysis are also described.展开更多
Designing high-performance electrocatalysts is one of the key challenges in the development of microbial electrochemical hydrogen production.Transition metal-based(TM-based)electrocatalysts are introduced as an astoni...Designing high-performance electrocatalysts is one of the key challenges in the development of microbial electrochemical hydrogen production.Transition metal-based(TM-based)electrocatalysts are introduced as an astonishing alternative for future catalysts by addressing several disadvantages,like the high cost and low performance of noble metal and metal-free electrocatalysts,respectively.In this critical review,a comprehensive analysis of the major development of all families of TMbased catalysts from the beginning development of microbial electrolysis cells in the last 15 years is presented.Importantly,pivotal design parameters such as selecting efficient synthesis methods based on the type of material,main criteria during each synthesizing method,and the pros and cons of various procedures are highlighted and compared.Moreover,procedures for tuning and tailoring the structures,advanced strategies to promote active sites,and the potential for implementing novel unexplored TM-based hybrid structures suggested.Furthermore,consideration for large-scale application of TM-based catalysts for future mass production,including life cycle assessment,cost assessment,economic analysis,and recently pilot-scale studies were highlighted.Of great importance,the potential of utilizing artificial intelligence and advanced computational methods such as active learning,microkinetic modeling,and physics-informed machine learning in designing high-performance electrodes in successful practices was elucidated.Finally,a conceptual framework for future studies and remaining challenges on different aspects of TM-based electrocatalysts in microbial electrolysis cells is proposed.展开更多
Proton exchange membrane water electrolysis (PEMWE) has garnered significant attention as apivotal technology for converting surplus electricity into hydrogen for long-term storage, as well asfor providing high-purity...Proton exchange membrane water electrolysis (PEMWE) has garnered significant attention as apivotal technology for converting surplus electricity into hydrogen for long-term storage, as well asfor providing high-purity hydrogen for aerospace and high-end manufacturing applications. Withthe ongoing commercialization of PEMWE, advancing iridium-based oxygen evolution reaction(OER) catalysts remains imperative to reconcile stringent requirements for high activity, extendedlongevity, and minimized noble metal loading. The review provides a systematic analysis of theintegrated design of iridium-based catalysts in PEMWE, starting from the fundamentals of OER,including the operation environment of OER catalysts, catalytic performance evaluation withinPEMWE, as well as catalytic and dissolution mechanisms. Subsequently, the catalyst classificationand preparation/characterization techniques are summarized with the focus on the dynamic structure-property relationship. Guided by these understandings, an overview of the design strategiesfor performance enhancement is presented. Specifically, we construct a mathematical frameworkfor cost-performance optimization to offer quantitative guidance for catalyst design. Finally, futureperspectives are proposed, aiming to establish a theoretical framework for rational catalyst design.展开更多
Powder bed fusion(PBF)in metallic additive manufacturing offers the ability to produce intricate geometries,high-strength components,and reliable products.However,powder processing before energy-based binding signific...Powder bed fusion(PBF)in metallic additive manufacturing offers the ability to produce intricate geometries,high-strength components,and reliable products.However,powder processing before energy-based binding significantly impacts the final product’s integrity.Processing maps guide efficient process design to minimize defects,but creating them through experimentation alone is challenging due to the wide range of parameters,necessitating a comprehensive computational parametric analysis.In this study,we used the discrete element method to parametrically analyze the powder processing design space in PBF of stainless steel 316L powders.Uniform lattice parameter sweeps are often used for parametric analysis,but are computationally intensive.We find that non-uniform parameter sweep based on the low discrepancy sequence(LDS)algorithm is ten times more efficient at exploring the design space while accurately capturing the relationship between powder flow dynamics and bed packing density.We introduce a multi-layer perceptron(MLP)model to interpolate parametric causalities within the LDS parameter space.With over 99%accuracy,it effectively captures these causalities while requiring fewer simulations.Finally,we generate processing design maps for machine setups and powder selections for efficient process design.We find that recoating speed has the highest impact on powder processing quality,followed by recoating layer thickness,particle size,and inter-particle friction.展开更多
A pump operating as a turbine(PAT)is a type of hydraulic machine capable of functioning both as a pump and as a turbine by reversing the flow direction.The pump-as-turbine(PAT)approach presents an effective method of ...A pump operating as a turbine(PAT)is a type of hydraulic machine capable of functioning both as a pump and as a turbine by reversing the flow direction.The pump-as-turbine(PAT)approach presents an effective method of hydropower generation,particularly suitable for addressing the increasing global energy demands in rural and remote areas.In addition to its adaptability,PAT-based micro-hydropower systems typically incur lower operating costs than conventional hydrodynamic turbines,despite requiring higher initial investment.Recent research has focused on integrating PATs into pipe distribution systems to harness untapped hydraulic energy.This study presents the development and performance evaluation of a novel pump operating as a turbine(PAT)impeller,designed to enhance hydropower recovery in water distribution systems.A three-dimensional(3D)impeller model was created using Catia software,integrating airfoil(hydrofoil)geometries into the blade profile to improve the efficiency of power extraction during turbine operation.Unlike conventional designs,the new impeller configuration generates additional force components aligned with the rotor’s direction of rotation,thereby increasing the moment about the axis and enhancing angular velocity.Computational fluid dynamics(CFD)simulations performed in ANSYS Fluent confirmed that the redesigned PAT significantly improves both performance and efficiency,demonstrating superior power recovery compared to the original design.The results highlight the potential of integrating PAT systems with optimized blade geometries into water distribution networks,offering a viable solution for energy recovery and head reduction during periods of low demand.展开更多
This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification ...This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification of distillation processes,optimization of process parameters for distillation processes and recent research progress in dynamic control strategies.Firstly,the feasibility of using thermodynamic topological theories such as residual curve,phase equilibrium line and distillation boundary line to analyze different separation regions is discussed,and the rationality of distillation process design is discussed by using its feasibility.Secondly,the application of molecular simulation methods such as molecular dynamics simulation and quantum chemical calculation in the screening of entrainer is discussed for the extractive distillation process.The thermal coupling mechanism of different distillation processes is used to explore the process of different process intensifications.Next,a mixed integer nonlinear optimization strategy for the distillation process based on different algorithms is introduced.Finally,the improvement of dynamic control strategies for different distillation processes in recent years is summarized.This work focuses on the application of process intensification and system optimization in the design of distillation process,and analyzes the challenges,prospects,and development trends of distillation technology in the separation of multicomponent azeotropes.展开更多
Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is co...Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is constrained by issues like unclear fundamental principles,complex experimental cycles,and high costs.Machine learning,as a novel artificial intelligence technology,has the potential to deeply engage in the development of additive manufacturing process,assisting engineers in learning and developing new techniques.This paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing,particularly in model design and process development.Firstly,it introduces the background and significance of machine learning-assisted design in additive manufacturing process.It then further delves into the application of machine learning in additive manufacturing,focusing on model design and process guidance.Finally,it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing.展开更多
The path to searching for sustainable energy has never stopped since thedepletion of fossil fuels can lead to serious environmental pollution andenergy shortages.Using water electrolysis to produce hydrogen has beenpr...The path to searching for sustainable energy has never stopped since thedepletion of fossil fuels can lead to serious environmental pollution andenergy shortages.Using water electrolysis to produce hydrogen has beenproven to be a prioritized approach for green resource production.It is highlycrucial to explore inexpensive and high-performance electrocatalysts foraccelerating hydrogen evolution reaction(HER)and apply them to industrialcases on a large scale.Here,we summarize the different mechanisms of HERin different pH settings and review recent advances in non-noble-metal-basedelectrocatalysts.Then,based on the previous efforts,we discuss severaluniversal strategies for designing pH-independent catalysts and showdirections for the future design of pH-universal catalysts.展开更多
A multi-world mechanism is developed for modeling evolutionary design process from conceptual design to detailed design. In this mechanism, the evolutionary design database is represented by a sequence of worlds corre...A multi-world mechanism is developed for modeling evolutionary design process from conceptual design to detailed design. In this mechanism, the evolutionary design database is represented by a sequence of worlds corresponding to the design descriptions at different design stages. In each world, only the differences with its ancestor world are recorded. When the design descriptions in one world are changed, these changes are then propagated to its descendant worlds automatically. Case study is conducted to show the effectiveness of this evolutionary design database model.展开更多
基金National Natural Science Foundation of China(U22A20191)。
文摘Brazing filler metals are widely applied,which serve as an industrial adhesive in the joining of dissimilar structures.With the continuous emergence of new structures and materials,the demand for novel brazing filler metals is ever-increasing.It is of great significance to investigate the optimized composition design methods and to establish systematic design guidelines for brazing filler metals.This study elucidated the fundamental rules for the composition design of brazing filler metals from a three-dimensional perspective encompassing the basic properties of applied brazing filler metals,formability and processability,and overall cost.The basic properties of brazing filler metals refer to their mechanical properties,physicochemical properties,electromagnetic properties,corrosion resistance,and the wettability and fluidity during brazing.The formability and processability of brazing filler metals include the processes of smelting and casting,extrusion,rolling,drawing and ring-making,as well as the processes of granulation,powder production,and the molding of amorphous and microcrystalline structures.The cost of brazing filler metals corresponds to the sum of materials value and manufacturing cost.Improving the comprehensive properties of brazing filler metals requires a comprehensive and systematic consideration of design indicators.Highlighting the unique characteristics of brazing filler metals should focus on relevant technical indicators.Binary or ternary eutectic structures can effectively enhance the flow spreading ability of brazing filler metals,and solid solution structures contribute to the formability.By employing the proposed design guidelines,typical Ag based,Cu based,Zn based brazing filler metals,and Sn based solders were designed and successfully applied in major scientific and engineering projects.
基金the National Natural Science Foundation of China(No.52275378)the National Key Laboratory for Precision Hot Processing of Metals(6142909200208)。
文摘The big-tapered profiled ring disk is a key component of engines for rockets and missiles.A new forming technology,as called spinning-rolling process,has been proposed previously for the high performance,high efficiency and low-cost manufacturing of the component.Blank design is the key part of plastic forming process design.For spinning-rolling process,the shape and size of the blank play a crucial role in process stability,deformation behavior and dimensional accuracy.So this work proposes a blank design method to determine the geometry structure and sizes of the blank.The mathematical model for calculating the blank size has been deduced based on volume conservation and neutral layer length invariance principle.The FE simulation and corresponding trial production of an actual big-tapered profiled ring disk show that the proposed blank design method is applicative.In order to obtain a preferred blank,the influence rules of blank size determined by different deformation degrees(rolling ratio k)on the spinning-rolling process are revealed by comprehensive FE simulations.Overall considering the process stability,circularity of the deformed ring disk and forming forces,a reasonable range of deformation degree(rolling ratio k)is recommended for the blank design of the new spinning-rolling process.
基金Supported by Huang Ruisong's National Famous Old Traditional Chinese Medicine Expert Inheritance Studio Construction Project[GuoZhongYiYaoRenJiaoHan(2022)75]Hospital Pharmacy Research Project of Guangxi Pharmaceutical Association(GXYXH-202404)+4 种基金2024 Youth Science Fund Project of International Zhuang Medical Hospital(2024GZYJKT005)High-level Traditional Chinese Medicine Key Discipline Construction Project of National Administration of Traditional Chinese Medicine(ZYYZDXK-2023165)National Old Pharmaceutical Workers Inheritance Studio Construction Project of National Administration of Traditional Chinese Medicine[GuoZhongYiYaoRenJiaoHan(2024)255]Talent Cultivation Project-"Young Crop Project"of International Zhuang Medical Hospital Affiliated to Guangxi University of Chinese Medicine(2022001)Guangxi Traditional Chinese Medicine Multidisciplinary Innovation Team Project(GZKJ2309).
文摘[Objectives]To optimize the optimal extraction process of Qingdu Jianpi Mixture.[Methods]Taking water addition ratio,extraction time and extraction times as process investigation factors,psoralen content,astilbin content and dry extract yield as evaluation indicators,the main influencing factors and level range of the extraction process of Qingdu Jianpi Mixture were determined on the basis of single factor test method,and the optimal weight coefficient was screened by AHP-entropy method mixed with weighting method.Combined with L_(9)(3^(4))orthogonal experiment,the best extraction process was obtained.At the same time,thin-layer chromatographic identification was used to identify Ficus simplicissima Lour.and Smilax glabra Roxb.in the medicinal liquid.[Results]The best extraction process:add 1:12 water to the prescription decoction pieces,extract under reflux for 2 times,1.5 h per time,and combine the filtrate to 250 mL.Thin layer chromatography analysis showed that the spots of Ficus simplicissima Lour.and Smilax glabra Roxb.in the medicinal solution were the same as those of reference substances at the corresponding positions,and the negative control had no interference.[Conclusions]The experimental method is reasonable and feasible,and the process is reliable,which can provide experimental reference for the subsequent application of in-hospital preparations and research and development of Qingdu Jianpi Mixture.
基金financial support from The University of Manchester
文摘Conceptual process design (CPD) research focuses on finding design alternatives that address various design problems. It has a long history of well-established methodologies to answer these complex questions, such as heuristics, mathematical programming, and pinch analysis. Nonetheless, progress continues from different formulations of design problems using bottom-up approaches, to the utilization of new tools such as artificial intelligence (AI). It was not until recently that AI methods were involved again in assisting the decision-making steps for chemical engineers. This has led to a gap in understanding AI's capabilities and limitations within the field of CPD research. Thus, this article aims to provide an overview of conventional methods for process synthesis, integration, and intensification approaches and survey emerging AI-assisted process design applications to bridge the gap. A review of all AI-assisted methods is highlighted, where AI is used as a key component within a design framework, to explain the utility of AI with comparative examples. The studies were categorized into supervised and reinforcement learning based on the machine learning training principles they used to enhance the understanding of requirements, benefits, and challenges that come with it. Furthermore, we provide challenges and prospects that can facilitate or hinder the progress of AI-assisted approaches in the future.
文摘In the year 1971,the world’s biggest structural biology collaboration name—The Research Collaboratory for Structural Bioinformatics(RCSB),was formed to gather all the structural biologists at a single platform and then extended out to be the world’s most extensive structural data repository named RCSB-Protein Data Bank(PDB)(https://www.rcsb.org/)that has provided the service for more than 50 years and continues its legacy for the discoveries and repositories for structural data.The RCSB has evolved from being a collaboratory network to a full-fledged database and tool with a huge list of protein structures,nucleic acid-containing structures,ModelArchive,and AlphaFold structures,and the best is that it is expanding day by day with computational advancement with tools and visual experiences.In this review article,we have discussed how RCSB has been a successful collaboratory network,its expansion in each decade,and how it has helped the ground-breaking research.The PDB tools that are helping the researchers,yearly data deposition,validation,processing,and suggestions that can help the developer improve for upcoming years are also discussed.This review will help future researchers understand the complete history of RCSB and its developments in each decade and how various future collaborative networks can be developed in various scientific areas and can be successful by keeping RCSB as a case study.
基金supported by Henan Province Science and Technology Research Project(Grant No.242103810058)Natural Science Foundation of Henan(Grant No.252300421104)+3 种基金National Natural Science Foundation of China(Grant No.52102346)Henan Key Research and Development Project(Grant No.231111230100)Heluo Youth Talent Project(Grant No.2024HLTJ14)Henan Postdoctoral Research Initiation Project(Grant No.HN2022040 and HN2022048).
文摘Proton exchange membrane water electrolyzer(PEMWE)is crucial for the storage and conversion of renewable energy.However,the harsh anode environment and the oxygen evolution reaction(OER),which involves a four-electron transfer,result in a significant overpotential that limits the overall efficiency of hydrogen production.Identifying active sites in the OER is crucial for understanding the reaction mechanism and guiding the development of novel electrocatalysts with high activity,cost-effectiveness,and durability.Herein,we summarize the widely accepted OER mechanism in acidic media,in situ characterization and monitoring of active sites during the reaction,and provide a general understanding of the active sites on various catalysts in the OER,including Ir-based metals,Ir-based oxides,carbon/oxide-supported Ir,Ir-based perovskite oxides,and Ir-based pyrochlore oxides.For each type of electrocatalysts,reaction pathways and actual active sites are proposed based on in situ characterization techniques and theoretical calculations.Finally,the challenges and strategic research directions associated with the design of highly efficient Ir-based electrocatalysts are discussed,offering new insights for the further scientific advancement and practical application of acidic OER.
基金supported by the National Natural Science Foundation of China(No.52074246)the National Defense Basic Scientific Research Program of China(No.JCKY2020408B002)+1 种基金the Key R&D Program of Shanxi Province(No.202102050201011)the Shanxi Province Graduate Innovation Project(No.2021Y591).
文摘Casting technology is a fundamental and irreplaceable method in advanced manufacturing.The design and optimization of casting processes are crucial for producing high-performance,complex metal components.Transitioning from traditional process design based on"experience+experiment"to an integrated,intelligent approach is essential for achieving precise control over microstructure and properties.This paper provides a comprehensive and systematic review of intelligent casting process design and optimization for the first time.First,it explores process design methods based on casting simulation and integrated computational materials engineering(ICME).It then examines the application of machine learning(ML)in process design,highlighting its efficiency and existing challenges,along with the development of integrated intelligent design platforms.Finally,future research directions are discussed to drive further advancements and sustainable development in intelligent casting design and optimization.
基金Supported by Major Special Projects of Public Bidding in Shanxi Province of China(Grant No.20201101020)Central Guidance on Local Science and Technology Development Fund Project of China(Grant No.YDZJSX2022A053)Open Fund Subjectof National Key Laboratory of Material Forming and Mold Technology of China(Grant No.P2024-002)。
文摘The forming quality of metal bipolar plate(BPP)flow channels in proton exchange membrane fuel cells(PEMFCs)is a key factor affecting battery performance.A flow channel with straight sidewalls and a low thinning rate can enhance battery output.Roll forming,as a new technology for BPP production,offers advantages such as a low thinning rate and high efficiency.However,existing roll curve design methods struggle to accommodate both low thinning rates and straight sidewall angles simultaneously.This study aims to develop flow channels with right-angled sidewalls,which provide benefits such as a low thinning rate,reduced residual stress,and high accuracy.A roller tooth profile was designed to achieve a flow channel with right-angled sidewalls and minimal thinning.Simulations and experiments were conducted to validate the feasibility of this novel design method for the roll forming process.The study investigated the effects of roller tooth parameters on sidewall angle,thinning rate,and residual stress.A multifactor evaluation method was developed to optimize the tip fillet radius and the tooth profile backlash of the roller.The results indicated that the tip fillet radius and the tooth profile backlash were negatively correlated with the sidewall angle.As the tip fillet radius and tooth profile backlash increased,the thinning rate and residual stress decreased.With a tip fillet radius of 0.25 mm and a tooth profile backlash of 0.19 mm,the flow channel achieved an approximately right-angled sidewall,a maximum thinning rate of 7.7%,a 29.6%reduction in maximum residual stress,and maximum and average residual stress imbalance values of 7.1%and 3.2%,respectively.This study proposes a new design method for a right-angled sidewall runner roller gear profile,facilitating the roll forming of metal BPPs with right-angled sidewalls and minimal thinning.This method provides theoretical support for the large-scale application of roll forming in the manufacture of PEMFC BPPs.
基金the financial support of the Natural Science Foundation of Hubei Province,China (Grant No.2022CFB770)。
文摘In the foundry industries,process design has traditionally relied on manuals and complex theoretical calculations.With the advent of 3D design in casting,computer-aided design(CAD)has been applied to integrate the features of casting process,thereby expanding the scope of design options.These technologies use parametric model design techniques for rapid component creation and use databases to access standard process parameters and design specifications.However,3D models are currently still created through inputting or calling parameters,which requires numerous verifications through calculations to ensure the design rationality.This process may be significantly slowed down due to repetitive modifications and extended design time.As a result,there are increasingly urgent demands for a real-time verification mechanism to address this issue.Therefore,this study proposed a novel closed-loop model and software development method that integrated contextual design with real-time verification,dynamically verifying relevant rules for designing 3D casting components.Additionally,the study analyzed three typical closed-loop scenarios of agile design in an independent developed intelligent casting process system.It is believed that foundry industries can potentially benefit from favorably reduced design cycles to yield an enhanced competitive product market.
文摘This review presents a comprehensive and forward-looking analysis of how Large Language Models(LLMs)are transforming knowledge discovery in the rational design of advancedmicro/nano electrocatalyst materials.Electrocatalysis is central to sustainable energy and environmental technologies,but traditional catalyst discovery is often hindered by high complexity,fragmented knowledge,and inefficiencies.LLMs,particularly those based on Transformer architectures,offer unprecedented capabilities in extracting,synthesizing,and generating scientific knowledge from vast unstructured textual corpora.This work provides the first structured synthesis of how LLMs have been leveraged across various electrocatalysis tasks,including automated information extraction from literature,text-based property prediction,hypothesis generation,synthesis planning,and knowledge graph construction.We comparatively analyze leading LLMs and domain-specific frameworks(e.g.,CatBERTa,CataLM,CatGPT)in terms of methodology,application scope,performance metrics,and limitations.Through curated case studies across key electrocatalytic reactions—HER,OER,ORR,and CO_(2)RR—we highlight emerging trends such as the growing use of embedding-based prediction,retrieval-augmented generation,and fine-tuned scientific LLMs.The review also identifies persistent challenges,including data heterogeneity,hallucination risks,lack of standard benchmarks,and limited multimodal integration.Importantly,we articulate future research directions,such as the development of multimodal and physics-informedMatSci-LLMs,enhanced interpretability tools,and the integration of LLMswith selfdriving laboratories for autonomous discovery.By consolidating fragmented advances and outlining a unified research roadmap,this review provides valuable guidance for both materials scientists and AI practitioners seeking to accelerate catalyst innovation through large language model technologies.
基金part of a research project, PIF 726175Alfaisal University and its Office of Research & Innovation for their continuous support throughout this study。
文摘Direct electrolysis of seawater to produce green hydrogen is a more environmentally friendly process than freshwater electrolysis.The renewable energy sector exhibits tremendous interest in practical seawater electrolysis techniques due to its substantial capacity to mitigate the need for freshwater consumption.With the low catalytic efficiency of the current seawater splitting process and the poor reliability of its operation,the process suffers from severe corrosion caused by chloride ions,as well as anodic competition between oxygen evolution and chlorine oxidation reactions.This review provides an overview of the latest electrocatalyst developments for promoting selectivity and stability in seawater electrolysis.Using the characterization and simulation results,as well as active machine learning,advanced electrocatalytic materials can be designed and developed,a research direction that will become increasingly important in the future.A variety of strategies are discussed in detail for designing advanced electrocatalysts in seawater electrolysis,including the surface protective layer,structural regulation by heteroatom doping and vacancies,porous structure,core-shell construction,and 3D hetero-structure construction to hinder chlorine evolution reactions.Finally,future perspectives and challenges for green hydrogen production from seawater electrolysis are also described.
文摘Designing high-performance electrocatalysts is one of the key challenges in the development of microbial electrochemical hydrogen production.Transition metal-based(TM-based)electrocatalysts are introduced as an astonishing alternative for future catalysts by addressing several disadvantages,like the high cost and low performance of noble metal and metal-free electrocatalysts,respectively.In this critical review,a comprehensive analysis of the major development of all families of TMbased catalysts from the beginning development of microbial electrolysis cells in the last 15 years is presented.Importantly,pivotal design parameters such as selecting efficient synthesis methods based on the type of material,main criteria during each synthesizing method,and the pros and cons of various procedures are highlighted and compared.Moreover,procedures for tuning and tailoring the structures,advanced strategies to promote active sites,and the potential for implementing novel unexplored TM-based hybrid structures suggested.Furthermore,consideration for large-scale application of TM-based catalysts for future mass production,including life cycle assessment,cost assessment,economic analysis,and recently pilot-scale studies were highlighted.Of great importance,the potential of utilizing artificial intelligence and advanced computational methods such as active learning,microkinetic modeling,and physics-informed machine learning in designing high-performance electrodes in successful practices was elucidated.Finally,a conceptual framework for future studies and remaining challenges on different aspects of TM-based electrocatalysts in microbial electrolysis cells is proposed.
文摘Proton exchange membrane water electrolysis (PEMWE) has garnered significant attention as apivotal technology for converting surplus electricity into hydrogen for long-term storage, as well asfor providing high-purity hydrogen for aerospace and high-end manufacturing applications. Withthe ongoing commercialization of PEMWE, advancing iridium-based oxygen evolution reaction(OER) catalysts remains imperative to reconcile stringent requirements for high activity, extendedlongevity, and minimized noble metal loading. The review provides a systematic analysis of theintegrated design of iridium-based catalysts in PEMWE, starting from the fundamentals of OER,including the operation environment of OER catalysts, catalytic performance evaluation withinPEMWE, as well as catalytic and dissolution mechanisms. Subsequently, the catalyst classificationand preparation/characterization techniques are summarized with the focus on the dynamic structure-property relationship. Guided by these understandings, an overview of the design strategiesfor performance enhancement is presented. Specifically, we construct a mathematical frameworkfor cost-performance optimization to offer quantitative guidance for catalyst design. Finally, futureperspectives are proposed, aiming to establish a theoretical framework for rational catalyst design.
基金supported by the funding provided by Boeing Center for Aviation and Aerospace Safety.
文摘Powder bed fusion(PBF)in metallic additive manufacturing offers the ability to produce intricate geometries,high-strength components,and reliable products.However,powder processing before energy-based binding significantly impacts the final product’s integrity.Processing maps guide efficient process design to minimize defects,but creating them through experimentation alone is challenging due to the wide range of parameters,necessitating a comprehensive computational parametric analysis.In this study,we used the discrete element method to parametrically analyze the powder processing design space in PBF of stainless steel 316L powders.Uniform lattice parameter sweeps are often used for parametric analysis,but are computationally intensive.We find that non-uniform parameter sweep based on the low discrepancy sequence(LDS)algorithm is ten times more efficient at exploring the design space while accurately capturing the relationship between powder flow dynamics and bed packing density.We introduce a multi-layer perceptron(MLP)model to interpolate parametric causalities within the LDS parameter space.With over 99%accuracy,it effectively captures these causalities while requiring fewer simulations.Finally,we generate processing design maps for machine setups and powder selections for efficient process design.We find that recoating speed has the highest impact on powder processing quality,followed by recoating layer thickness,particle size,and inter-particle friction.
文摘A pump operating as a turbine(PAT)is a type of hydraulic machine capable of functioning both as a pump and as a turbine by reversing the flow direction.The pump-as-turbine(PAT)approach presents an effective method of hydropower generation,particularly suitable for addressing the increasing global energy demands in rural and remote areas.In addition to its adaptability,PAT-based micro-hydropower systems typically incur lower operating costs than conventional hydrodynamic turbines,despite requiring higher initial investment.Recent research has focused on integrating PATs into pipe distribution systems to harness untapped hydraulic energy.This study presents the development and performance evaluation of a novel pump operating as a turbine(PAT)impeller,designed to enhance hydropower recovery in water distribution systems.A three-dimensional(3D)impeller model was created using Catia software,integrating airfoil(hydrofoil)geometries into the blade profile to improve the efficiency of power extraction during turbine operation.Unlike conventional designs,the new impeller configuration generates additional force components aligned with the rotor’s direction of rotation,thereby increasing the moment about the axis and enhancing angular velocity.Computational fluid dynamics(CFD)simulations performed in ANSYS Fluent confirmed that the redesigned PAT significantly improves both performance and efficiency,demonstrating superior power recovery compared to the original design.The results highlight the potential of integrating PAT systems with optimized blade geometries into water distribution networks,offering a viable solution for energy recovery and head reduction during periods of low demand.
文摘This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification of distillation processes,optimization of process parameters for distillation processes and recent research progress in dynamic control strategies.Firstly,the feasibility of using thermodynamic topological theories such as residual curve,phase equilibrium line and distillation boundary line to analyze different separation regions is discussed,and the rationality of distillation process design is discussed by using its feasibility.Secondly,the application of molecular simulation methods such as molecular dynamics simulation and quantum chemical calculation in the screening of entrainer is discussed for the extractive distillation process.The thermal coupling mechanism of different distillation processes is used to explore the process of different process intensifications.Next,a mixed integer nonlinear optimization strategy for the distillation process based on different algorithms is introduced.Finally,the improvement of dynamic control strategies for different distillation processes in recent years is summarized.This work focuses on the application of process intensification and system optimization in the design of distillation process,and analyzes the challenges,prospects,and development trends of distillation technology in the separation of multicomponent azeotropes.
基金financially supported by the Technology Development Fund of China Academy of Machinery Science and Technology(No.170221ZY01)。
文摘Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is constrained by issues like unclear fundamental principles,complex experimental cycles,and high costs.Machine learning,as a novel artificial intelligence technology,has the potential to deeply engage in the development of additive manufacturing process,assisting engineers in learning and developing new techniques.This paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing,particularly in model design and process development.Firstly,it introduces the background and significance of machine learning-assisted design in additive manufacturing process.It then further delves into the application of machine learning in additive manufacturing,focusing on model design and process guidance.Finally,it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing.
基金“Pioneer” and “Leading Goose” R&D Program of Zhejiang Province,Grant/Award Numbers:2021C01SA301612, 2023C01235Zhejiang Provincial Key Research and Development Program,Grant/Award Number:2020C01030
文摘The path to searching for sustainable energy has never stopped since thedepletion of fossil fuels can lead to serious environmental pollution andenergy shortages.Using water electrolysis to produce hydrogen has beenproven to be a prioritized approach for green resource production.It is highlycrucial to explore inexpensive and high-performance electrocatalysts foraccelerating hydrogen evolution reaction(HER)and apply them to industrialcases on a large scale.Here,we summarize the different mechanisms of HERin different pH settings and review recent advances in non-noble-metal-basedelectrocatalysts.Then,based on the previous efforts,we discuss severaluniversal strategies for designing pH-independent catalysts and showdirections for the future design of pH-universal catalysts.
基金Selected from Proceedings of the 7th Intemational Conference on Frontiers of Design and Manufacturing (ICFDM'2006).
文摘A multi-world mechanism is developed for modeling evolutionary design process from conceptual design to detailed design. In this mechanism, the evolutionary design database is represented by a sequence of worlds corresponding to the design descriptions at different design stages. In each world, only the differences with its ancestor world are recorded. When the design descriptions in one world are changed, these changes are then propagated to its descendant worlds automatically. Case study is conducted to show the effectiveness of this evolutionary design database model.
