To promote the development of global carbon neutrality,perovskite solar cells(PSCs)have become a research hotspot in related fields.How to obtain PSCs with expected performance and explore the potential factors affect...To promote the development of global carbon neutrality,perovskite solar cells(PSCs)have become a research hotspot in related fields.How to obtain PSCs with expected performance and explore the potential factors affecting device performance are the research priorities in related fields.Although some classical computational methods can facilitate material development,they typically require complex mathematical approximations and manual feature screening processes,which have certain subjectivity and one-sidedness,limiting the performance of the model.In order to alleviate the above challenges,this paper proposes a machine learning(ML)model based on neural networks.The model can assist both PSCs design and analysis of their potential mechanism,demonstrating enhanced and comprehensive auxiliary capabilities.To make the model have higher feasibility and fit the real experimental process more closely,this paper collects the corresponding real experimental data from numerous research papers to develop the model.Compared with other classical ML methods,the proposed model achieved better overall performance.Regarding analysis of underlying mechanism,the relevant laws explored by the model are consistent with the actual experiment results of existing articles.The model exhibits great potential to discover complex laws that are difficult for humans to discover directly.In addition,we also fabricated PSCs to verify the guidance ability of the model in this paper for real experiments.Eventually,the model achieved acceptable results.This work provides new insights into integrating ML methods and PSC design techniques,as well as bridging photovoltaic power generation technology and other fields.展开更多
The design and developmental steps for an auxiliary machining module utilizing a database framework are discussed in this work to contribute to an improvement in workshop operations. The underlining objective is for t...The design and developmental steps for an auxiliary machining module utilizing a database framework are discussed in this work to contribute to an improvement in workshop operations. The underlining objective is for the provision of easily accessible and applicable machining operations data to enable and improve job accuracy and conformity to industrial standards. The design of the database for the decision support system is based on a relational frame with Microsoft Access Application package and Microsoft Structured Query Language Server, which serves as the back end of the module. A user interface designed on .Net Framework 3.5 and the windows installer 3.1 running on windows XP operating system serve as the software front end. The developed module is to serve as a decision support system for machine tool operations.展开更多
In order to improve the scheduling efficiency of photolithography,bottleneck process of wafer fabrications in the semiconductor industry,an effective estimation of distribution algorithm is proposed for scheduling pro...In order to improve the scheduling efficiency of photolithography,bottleneck process of wafer fabrications in the semiconductor industry,an effective estimation of distribution algorithm is proposed for scheduling problems of parallel litho machines with reticle constraints,where multiple reticles are available for each reticle type.First,the scheduling problem domain of parallel litho machines is described with reticle constraints and mathematical programming formulations are put forward with the objective of minimizing total weighted completion time.Second,estimation of distribution algorithm is developed with a decoding scheme specially designed to deal with the reticle constraints.Third,an insert-based local search with the first move strategy is introduced to enhance the local exploitation ability of the algorithm.Finally,simulation experiments and analysis demonstrate the effectiveness of the proposed algorithm.展开更多
The lost information caused by feature interaction is restored by using auxiliary faces (AF) and virtual links (VL). The delta volume of the interacted features represented by concave attachable connected graph (CACG)...The lost information caused by feature interaction is restored by using auxiliary faces (AF) and virtual links (VL). The delta volume of the interacted features represented by concave attachable connected graph (CACG) can be decomposed into several isolated features represented by complete concave adjacency graph (CCAG). We can recognize the feature’s sketchy type by using CCAG as a hint; the exact type of the feature can be attained by deleting the auxiliary faces from the isolated feature. United machining feature (UMF) is used to represent the features that can be machined in the same machining process. It is important to the rationalizing of the process plans and reduce the time costing in machining. An example is given to demonstrate the effectiveness of this method.展开更多
Titanium(Ti)alloys are widely used in high-tech fields like aerospace and biomedical engineering.Laser additive manufacturing(LAM),as an innovative technology,is the key driver for the development of Ti alloys.Despite...Titanium(Ti)alloys are widely used in high-tech fields like aerospace and biomedical engineering.Laser additive manufacturing(LAM),as an innovative technology,is the key driver for the development of Ti alloys.Despite the significant advancements in LAM of Ti alloys,there remain challenges that need further research and development efforts.To recap the potential of LAM high-performance Ti alloy,this article systematically reviews LAM Ti alloys with up-to-date information on process,materials,and properties.Several feasible solutions to advance LAM Ti alloys are reviewed,including intelligent process parameters optimization,LAM process innovation with auxiliary fields and novel Ti alloys customization for LAM.The auxiliary energy fields(e.g.thermal,acoustic,mechanical deformation and magnetic fields)can affect the melt pool dynamics and solidification behaviour during LAM of Ti alloys,altering microstructures and mechanical performances.Different kinds of novel Ti alloys customized for LAM,like peritecticα-Ti,eutectoid(α+β)-Ti,hybrid(α+β)-Ti,isomorphousβ-Ti and eutecticβ-Ti alloys are reviewed in detail.Furthermore,machine learning in accelerating the LAM process optimization and new materials development is also outlooked.This review summarizes the material properties and performance envelops and benchmarks the research achievements in LAM of Ti alloys.In addition,the perspectives and further trends in LAM of Ti alloys are also highlighted.展开更多
基金financially supported by the National Natural Science Foundation of China(NSFC)project(Authorization Number:61771261)。
文摘To promote the development of global carbon neutrality,perovskite solar cells(PSCs)have become a research hotspot in related fields.How to obtain PSCs with expected performance and explore the potential factors affecting device performance are the research priorities in related fields.Although some classical computational methods can facilitate material development,they typically require complex mathematical approximations and manual feature screening processes,which have certain subjectivity and one-sidedness,limiting the performance of the model.In order to alleviate the above challenges,this paper proposes a machine learning(ML)model based on neural networks.The model can assist both PSCs design and analysis of their potential mechanism,demonstrating enhanced and comprehensive auxiliary capabilities.To make the model have higher feasibility and fit the real experimental process more closely,this paper collects the corresponding real experimental data from numerous research papers to develop the model.Compared with other classical ML methods,the proposed model achieved better overall performance.Regarding analysis of underlying mechanism,the relevant laws explored by the model are consistent with the actual experiment results of existing articles.The model exhibits great potential to discover complex laws that are difficult for humans to discover directly.In addition,we also fabricated PSCs to verify the guidance ability of the model in this paper for real experiments.Eventually,the model achieved acceptable results.This work provides new insights into integrating ML methods and PSC design techniques,as well as bridging photovoltaic power generation technology and other fields.
文摘The design and developmental steps for an auxiliary machining module utilizing a database framework are discussed in this work to contribute to an improvement in workshop operations. The underlining objective is for the provision of easily accessible and applicable machining operations data to enable and improve job accuracy and conformity to industrial standards. The design of the database for the decision support system is based on a relational frame with Microsoft Access Application package and Microsoft Structured Query Language Server, which serves as the back end of the module. A user interface designed on .Net Framework 3.5 and the windows installer 3.1 running on windows XP operating system serve as the software front end. The developed module is to serve as a decision support system for machine tool operations.
基金Supported by the National High Technology Research and Development Programme of China(No.2009AA043000)the National Natural Science Foundation of China(No.61273035,71471135)
文摘In order to improve the scheduling efficiency of photolithography,bottleneck process of wafer fabrications in the semiconductor industry,an effective estimation of distribution algorithm is proposed for scheduling problems of parallel litho machines with reticle constraints,where multiple reticles are available for each reticle type.First,the scheduling problem domain of parallel litho machines is described with reticle constraints and mathematical programming formulations are put forward with the objective of minimizing total weighted completion time.Second,estimation of distribution algorithm is developed with a decoding scheme specially designed to deal with the reticle constraints.Third,an insert-based local search with the first move strategy is introduced to enhance the local exploitation ability of the algorithm.Finally,simulation experiments and analysis demonstrate the effectiveness of the proposed algorithm.
文摘The lost information caused by feature interaction is restored by using auxiliary faces (AF) and virtual links (VL). The delta volume of the interacted features represented by concave attachable connected graph (CACG) can be decomposed into several isolated features represented by complete concave adjacency graph (CCAG). We can recognize the feature’s sketchy type by using CCAG as a hint; the exact type of the feature can be attained by deleting the auxiliary faces from the isolated feature. United machining feature (UMF) is used to represent the features that can be machined in the same machining process. It is important to the rationalizing of the process plans and reduce the time costing in machining. An example is given to demonstrate the effectiveness of this method.
基金financially supported by the Young Individual Research Grants(Grant No:M22K3c0097)Singapore RIE 2025 plan and Singapore Aerospace Programme Cycle 16(Grant No:M2215a0073)led by C Tan+2 种基金supported by the Singapore A*STAR Career Development Funds(Grant No:C210812047)the National Natural Science Foundation of China(52174361 and 52374385)the support by US NSF DMR-2104933。
文摘Titanium(Ti)alloys are widely used in high-tech fields like aerospace and biomedical engineering.Laser additive manufacturing(LAM),as an innovative technology,is the key driver for the development of Ti alloys.Despite the significant advancements in LAM of Ti alloys,there remain challenges that need further research and development efforts.To recap the potential of LAM high-performance Ti alloy,this article systematically reviews LAM Ti alloys with up-to-date information on process,materials,and properties.Several feasible solutions to advance LAM Ti alloys are reviewed,including intelligent process parameters optimization,LAM process innovation with auxiliary fields and novel Ti alloys customization for LAM.The auxiliary energy fields(e.g.thermal,acoustic,mechanical deformation and magnetic fields)can affect the melt pool dynamics and solidification behaviour during LAM of Ti alloys,altering microstructures and mechanical performances.Different kinds of novel Ti alloys customized for LAM,like peritecticα-Ti,eutectoid(α+β)-Ti,hybrid(α+β)-Ti,isomorphousβ-Ti and eutecticβ-Ti alloys are reviewed in detail.Furthermore,machine learning in accelerating the LAM process optimization and new materials development is also outlooked.This review summarizes the material properties and performance envelops and benchmarks the research achievements in LAM of Ti alloys.In addition,the perspectives and further trends in LAM of Ti alloys are also highlighted.
