Correction to:Nano-Micro Letters(2025)17:135 https://doi.org/10.1007/s40820-024-01634-8 Following publication of the original article[1],the authors reported that the corresponding author would like to update the emai...Correction to:Nano-Micro Letters(2025)17:135 https://doi.org/10.1007/s40820-024-01634-8 Following publication of the original article[1],the authors reported that the corresponding author would like to update the email address from xingcai@stanford.edu to drtea1@wteao.com.Also,the corresponding author’s affiliation can be expanded.展开更多
Composed of natural materials but constructed using artificial structures through ingenious design,metamaterials possess properties beyond nature.Unlike traditional materials studies,metamaterials research requires gr...Composed of natural materials but constructed using artificial structures through ingenious design,metamaterials possess properties beyond nature.Unlike traditional materials studies,metamaterials research requires great human creativity in order to realize the desired properties and thereby the required functionalities through design.Such properties and functionalities are not necessarily available in nature,and their design can break through the existing materials ideology.This paper reviews progress in metamaterials research over the past 20 years in terms of the materials innovations that have achieved the designation of “meta.” In particular,we discuss future trends in metamaterials in the fields of both fundamental science and engineering.展开更多
NJmat is a user-friendly,data-driven machine learning interface designed for materials design and analysis.The platform integrates advanced computational techniques,including natural language processing(NLP),large lan...NJmat is a user-friendly,data-driven machine learning interface designed for materials design and analysis.The platform integrates advanced computational techniques,including natural language processing(NLP),large language models(LLM),machine learning potentials(MLP),and graph neural networks(GNN),to facili-tate materials discovery.The platform has been applied in diverse materials research areas,including perovskite surface design,catalyst discovery,battery materials screening,structural alloy design,and molecular informatics.By automating feature selection,predictive modeling,and result interpretation,NJmat accelerates the development of high-performance materials across energy storage,conversion,and structural applications.Additionally,NJmat serves as an educational tool,allowing students and researchers to apply machine learning techniques in materials science with minimal coding expertise.Through automated feature extraction,genetic algorithms,and interpretable machine learning models,NJmat simplifies the workflow for materials informatics,bridging the gap between AI and experimental materials research.The latest version(available at https://figshare.com/articles/software/NJmatML/24607893(accessed on 01 January 2025))enhances its functionality by incorporating NJmatNLP,a module leveraging language models like MatBERT and those based on Word2Vec to support materials prediction tasks.By utilizing clustering and cosine similarity analysis with UMAP visualization,NJmat enables intuitive exploration of materials datasets.While NJmat primarily focuses on structure-property relationships and the discovery of novel chemistries,it can also assist in optimizing processing conditions when relevant parameters are included in the training data.By providing an accessible,integrated environment for machine learning-driven materials discovery,NJmat aligns with the objectives of the Materials Genome Initiative and promotes broader adoption of AI techniques in materials science.展开更多
The advancement of materials has played a pivotal role in the advancement of human civilization,and the emergence of artificial intelligence(AI)-empowered materials science heralds a new era with substantial potential...The advancement of materials has played a pivotal role in the advancement of human civilization,and the emergence of artificial intelligence(AI)-empowered materials science heralds a new era with substantial potential to tackle the escalating challenges related to energy,environment,and biomedical concerns in a sustainable manner.The exploration and development of sustainable materials are poised to assume a critical role in attaining technologically advanced solutions that are environmentally friendly,energy-efficient,and conducive to human well-being.This review provides a comprehensive overview of the current scholarly progress in artificial intelligence-powered materials science and its cutting-edge applications.We anticipate that AI technology will be extensively utilized in material research and development,thereby expediting the growth and implementation of novel materials.AI will serve as a catalyst for materials innovation,and in turn,advancements in materials innovation will further enhance the capabilities of AI and AI-powered materials science.Through the synergistic collaboration between AI and materials science,we stand to realize a future propelled by advanced AI-powered materials.展开更多
Peri-implantitis is a bacterial infection that causes soft tissue inflammatory lesions and alveolar bone resorption,ultimately resulting in implant failure.Dental implants for clinical use barely have antibacterial pr...Peri-implantitis is a bacterial infection that causes soft tissue inflammatory lesions and alveolar bone resorption,ultimately resulting in implant failure.Dental implants for clinical use barely have antibacterial properties,and bacterial colonization and biofilm formation on the dental implants are major causes of peri-implantitis.Treatment strategies such as mechanical debridement and antibiotic therapy have been used to remove dental plaque.However,it is particularly important to prevent the occurrence of peri-implantitis rather than treatment.Therefore,the current research spot has focused on improving the antibacterial properties of dental implants,such as the construction of specific micro-nano surface texture,the introduction of diverse functional coatings,or the application of materials with intrinsic antibacterial properties.The aforementioned antibacterial surfaces can be incorporated with bioactive molecules,metallic nanoparticles,or other functional components to further enhance the osteogenic properties and accelerate the healing process.In this review,we summarize the recent developments in biomaterial science and the modification strategies applied to dental implants to inhibit biofilm formation and facilitate bone-implant integration.Furthermore,we summarized the obstacles existing in the process of laboratory research to reach the clinic products,and propose corresponding directions for future developments and research perspectives,so that to provide insights into the rational design and construction of dental implants with the aim to balance antibacterial efficacy,biological safety,and osteogenic property.展开更多
The exponential growth of literature is constraining researchers’access to comprehensive information in related fields.While natural language processing(NLP)may offer an effective solution to literature classificatio...The exponential growth of literature is constraining researchers’access to comprehensive information in related fields.While natural language processing(NLP)may offer an effective solution to literature classification,it remains hindered by the lack of labelled dataset.In this article,we introduce a novel method for generating literature classification models through semi-supervised learning,which can generate labelled dataset iteratively with limited human input.We apply this method to train NLP models for classifying literatures related to several research directions,i.e.,battery,superconductor,topological material,and artificial intelligence(AI)in materials science.The trained NLP‘battery’model applied on a larger dataset different from the training and testing dataset can achieve F1 score of 0.738,which indicates the accuracy and reliability of this scheme.Furthermore,our approach demonstrates that even with insufficient data,the not-well-trained model in the first few cycles can identify the relationships among different research fields and facilitate the discovery and understanding of interdisciplinary directions.展开更多
The authors regret to inform that the whole“Acknowledgements”section is missing due to the composing process of the editing.The“Acknowledgements”information that should be added is as follows.
The authors regret that the funding number in the Acknowledgment Section is incorrect.The correct funding project and number should be“the National Key Research and Development Program of China(No.2022YFB3808700)”.T...The authors regret that the funding number in the Acknowledgment Section is incorrect.The correct funding project and number should be“the National Key Research and Development Program of China(No.2022YFB3808700)”.The authors would like to apologise for any inconvenience caused.展开更多
Aiming at the problem of weak integration of innovation ability and ideological education of postgraduates in materials major,this paper explores postgraduates’cultivation work under the support of Liaocheng Universi...Aiming at the problem of weak integration of innovation ability and ideological education of postgraduates in materials major,this paper explores postgraduates’cultivation work under the support of Liaocheng University.It is found that the cultivation of the innovation ability of postgraduates in materials can be the realization path and sublimation carrier of ideological education,ideological education can provide spiritual support and methodological guidance for the former,and the organic integration of the two is feasible.Constructing the fit relationship between innovation ability and ideological education,institutionalizing tutor guidance,establishing tutor+counselor+professional teacher communication mechanism,and taking disciplinary competitions as a handhold can achieve the integration of innovation ability cultivation and ideological education of graduate students in materials major.展开更多
In this paper,the main research work and related reports of materials science research in China’s space technology field during 2020-2022 are summarized.This paper covers Materials Sciences in Space Environment,Mater...In this paper,the main research work and related reports of materials science research in China’s space technology field during 2020-2022 are summarized.This paper covers Materials Sciences in Space Environment,Materials Sciences for Space Environment,Materials Behavior in Space Environment and Space experimental hardware for material investigation.With the rapid development of China’s space industry,more scientists will be involved in materials science,space technology and earth science researches.In the future,a series of disciplines such as space science,machinery,artificial intelligence,digital twin and big data will be further integrated with materials science,and space materials will also usher in new development opportunities.展开更多
The prediction of chemical synthesis pathways plays a pivotal role in materials science research. Challenges, such as the complexity of synthesis pathways and the lack of comprehensive datasets, currently hinder our a...The prediction of chemical synthesis pathways plays a pivotal role in materials science research. Challenges, such as the complexity of synthesis pathways and the lack of comprehensive datasets, currently hinder our ability to predict these chemical processes accurately. However, recent advancements in generative artificial intelligence(GAI), including automated text generation and question–answering systems, coupled with fine-tuning techniques, have facilitated the deployment of large-scale AI models tailored to specific domains. In this study, we harness the power of the LLaMA2-7B model and enhance it through a learning process that incorporates 13878 pieces of structured material knowledge data.This specialized AI model, named Mat Chat, focuses on predicting inorganic material synthesis pathways. Mat Chat exhibits remarkable proficiency in generating and reasoning with knowledge in materials science. Although Mat Chat requires further refinement to meet the diverse material design needs, this research undeniably highlights its impressive reasoning capabilities and innovative potential in materials science. Mat Chat is now accessible online and open for use, with both the model and its application framework available as open source. This study establishes a robust foundation for collaborative innovation in the integration of generative AI in materials science.展开更多
Activities of space materials science research in China have been continuously supported by two main national programs.One is the China Space Station(CSS)program since 1992,and the other is the Strategic Priority Prog...Activities of space materials science research in China have been continuously supported by two main national programs.One is the China Space Station(CSS)program since 1992,and the other is the Strategic Priority Program(SPP)on Space Science since 2011.In CSS plan in 2019,eleven space materials science experimental projects were officially approved for execution during the construction of the space station.In the SPP Phase Ⅱ launched in 2018,seven pre-research projects are deployed as the first batch in 2018,and one concept study project in 2019.These pre-research projects will be cultivated as candidates for future selection as space experiment projects on the recovery of scientific experimental satellites in the future.A new apparatus of electrostatic levitation system for ground-based research of space materials science and rapid solidification research has been developed under the support of the National Natural Science Foundation of China.In order to promote domestic academic activities and to enhance the advancement of space materials science in China,the Space Materials Science and Technology Division belong to the Chinese Materials Research Society was established in 2019.We also organized scientists to write five review papers on space materials science as a special topic published in the journal Scientia Sinica to provide valuable scientific and technical references for Chinese researchers.展开更多
By analyzing the feasibility and necessity of implementing ideological and political education and online and offline mixed practice teaching in the course of basic experiment of materials science, this paper explores...By analyzing the feasibility and necessity of implementing ideological and political education and online and offline mixed practice teaching in the course of basic experiment of materials science, this paper explores the teaching reform measures of basic experiment of materials science, establishes the online and offline mixed practice teaching mode, organically integrates ideological and political elements into the experimental teaching content system and constructs the formative evaluation system of basic experiment of materials science, thus improving the teaching quality. Through the implementation of the curriculum reform, we can stimulate the sense of social responsibility and mission of contemporary college students, improve their ideological and political literacy and then achieve the goal of talent cultivation in the new era.展开更多
Porous organic frameworks(POFs)have become a highly sought-after research domain that offers a promising avenue for developing cutting-edge nanostructured materials,both in their pristine state and when subjected to v...Porous organic frameworks(POFs)have become a highly sought-after research domain that offers a promising avenue for developing cutting-edge nanostructured materials,both in their pristine state and when subjected to various chemical and structural modifications.Metal–organic frameworks,covalent organic frameworks,and hydrogen-bonded organic frameworks are examples of these emerging materials that have gained significant attention due to their unique properties,such as high crystallinity,intrinsic porosity,unique structural regularity,diverse functionality,design flexibility,and outstanding stability.This review provides an overview of the state-of-the-art research on base-stable POFs,emphasizing the distinct pros and cons of reticular framework nanoparticles compared to other types of nanocluster materials.Thereafter,the review highlights the unique opportunity to produce multifunctional tailoring nanoparticles to meet specific application requirements.It is recommended that this potential for creating customized nanoparticles should be the driving force behind future synthesis efforts to tap the full potential of this multifaceted material category.展开更多
Phase-field method,as a powerful and popular approach to predict the mesoscale microstructure evolution in various materials science,provides a bridge from atomic-scale methods to the macroscale and has been widely us...Phase-field method,as a powerful and popular approach to predict the mesoscale microstructure evolution in various materials science,provides a bridge from atomic-scale methods to the macroscale and has been widely used at an ever-increasing rate.This paper aims to briefly review the origin,basic idea,and development of phase-field models in a historical manner.The focus is placed on the classical and state-of-the-art applications in China,including liquid–solid,solid–solid,gas–solid,ferroelectrics/ferromagnetics phase transformation,and crack propagation-fracture.After introducing the academic activities in the phase-field community in China,some suggestions for the future development directions of phase-field method are finally mentioned.展开更多
Laser-heated diamond-anvil cell (LHDAC) is emerging as the most suitable, economical and versatile tool for the measurement of a large spectrum of physical properties of materials under extreme pressure and temperatur...Laser-heated diamond-anvil cell (LHDAC) is emerging as the most suitable, economical and versatile tool for the measurement of a large spectrum of physical properties of materials under extreme pressure and temperature conditions. In this review, the recent developments in the instrumentation, pressure and temperature measurement techniques, results of experimental investigations from the literature were discussed. Also, the future scope of the technique in various avenues of science was explored.展开更多
There is growing interest in applying machine learning techniques in the field of materials science.However,the interpretation and knowledge extracted from machine learning models is a major concern,particularly as fo...There is growing interest in applying machine learning techniques in the field of materials science.However,the interpretation and knowledge extracted from machine learning models is a major concern,particularly as formulating an explicit model that provides insight into physics is the goal of learning.In the present study,we propose a framework that utilizes the filtering ability of feature engineering,in conjunction with symbolic regression to extract explicit,quantitative expressions for the band gap energy from materials data.We propose enhancements to genetic programming with dimensional consistency and artificial constraints to improve the search efficiency of symbolic regression.We show how two descriptors attributed to volumetric and electronic factors,from 32 possible candidates,explicitly express the band gap energy of Na Cl-type compounds.Our approach provides a basis to capture underlying physical relationships between materials descriptors and target properties.展开更多
Quantitative analysis of populations having a geometric structure,which has developed into a special scientific subject called microstructology or stereology,is of great importance to the characterization and evaluati...Quantitative analysis of populations having a geometric structure,which has developed into a special scientific subject called microstructology or stereology,is of great importance to the characterization and evaluation of microstructures and their evolution in various processes.This paper, besides a brief discussion on those topics such as the recent developments of computer assisted image analysis,mathematical morphology,and fractal analysis,will mainly focus on the scope,fundamen- tals,present status,and perspectives of classical stereology.Several case examples of its application to materials science will also be given.展开更多
The authors regret<to remove Prof.Jien-Wei Yeh from the authorship for some reason.The removal is agreed by Prof.Jien-Wei Yeh>.The authors would like to apologise for any inconvenience caused.
文摘Correction to:Nano-Micro Letters(2025)17:135 https://doi.org/10.1007/s40820-024-01634-8 Following publication of the original article[1],the authors reported that the corresponding author would like to update the email address from xingcai@stanford.edu to drtea1@wteao.com.Also,the corresponding author’s affiliation can be expanded.
基金supported by the National Key Research and Development Program of China (2022YFB3806000)the Key Program of National Natural Science Foundation of China (52332006)。
文摘Composed of natural materials but constructed using artificial structures through ingenious design,metamaterials possess properties beyond nature.Unlike traditional materials studies,metamaterials research requires great human creativity in order to realize the desired properties and thereby the required functionalities through design.Such properties and functionalities are not necessarily available in nature,and their design can break through the existing materials ideology.This paper reviews progress in metamaterials research over the past 20 years in terms of the materials innovations that have achieved the designation of “meta.” In particular,we discuss future trends in metamaterials in the fields of both fundamental science and engineering.
基金supported by the Jiangsu Provincial Science and Technology Project Basic Research Program(Natural Science Foundation of Jiangsu Province)(No.BK20211283).
文摘NJmat is a user-friendly,data-driven machine learning interface designed for materials design and analysis.The platform integrates advanced computational techniques,including natural language processing(NLP),large language models(LLM),machine learning potentials(MLP),and graph neural networks(GNN),to facili-tate materials discovery.The platform has been applied in diverse materials research areas,including perovskite surface design,catalyst discovery,battery materials screening,structural alloy design,and molecular informatics.By automating feature selection,predictive modeling,and result interpretation,NJmat accelerates the development of high-performance materials across energy storage,conversion,and structural applications.Additionally,NJmat serves as an educational tool,allowing students and researchers to apply machine learning techniques in materials science with minimal coding expertise.Through automated feature extraction,genetic algorithms,and interpretable machine learning models,NJmat simplifies the workflow for materials informatics,bridging the gap between AI and experimental materials research.The latest version(available at https://figshare.com/articles/software/NJmatML/24607893(accessed on 01 January 2025))enhances its functionality by incorporating NJmatNLP,a module leveraging language models like MatBERT and those based on Word2Vec to support materials prediction tasks.By utilizing clustering and cosine similarity analysis with UMAP visualization,NJmat enables intuitive exploration of materials datasets.While NJmat primarily focuses on structure-property relationships and the discovery of novel chemistries,it can also assist in optimizing processing conditions when relevant parameters are included in the training data.By providing an accessible,integrated environment for machine learning-driven materials discovery,NJmat aligns with the objectives of the Materials Genome Initiative and promotes broader adoption of AI techniques in materials science.
基金the support from Stanfordthe support from CUHKHKU
文摘The advancement of materials has played a pivotal role in the advancement of human civilization,and the emergence of artificial intelligence(AI)-empowered materials science heralds a new era with substantial potential to tackle the escalating challenges related to energy,environment,and biomedical concerns in a sustainable manner.The exploration and development of sustainable materials are poised to assume a critical role in attaining technologically advanced solutions that are environmentally friendly,energy-efficient,and conducive to human well-being.This review provides a comprehensive overview of the current scholarly progress in artificial intelligence-powered materials science and its cutting-edge applications.We anticipate that AI technology will be extensively utilized in material research and development,thereby expediting the growth and implementation of novel materials.AI will serve as a catalyst for materials innovation,and in turn,advancements in materials innovation will further enhance the capabilities of AI and AI-powered materials science.Through the synergistic collaboration between AI and materials science,we stand to realize a future propelled by advanced AI-powered materials.
基金supported by the National Key Research and Development Program of China(2023YFC2412600)the National Natural Science Foundation of China(52271243,52171233,82370924,82170929)+3 种基金the Beijing Natural Science Foundation(L212014)the Beijing Nova Program(20230484459)the National Clinical Key Discipline Construction Project(PKUSSNKP-T202103)the Research Foundation of Peking University School and Hospital of Stomatology(PKSS20230104).
文摘Peri-implantitis is a bacterial infection that causes soft tissue inflammatory lesions and alveolar bone resorption,ultimately resulting in implant failure.Dental implants for clinical use barely have antibacterial properties,and bacterial colonization and biofilm formation on the dental implants are major causes of peri-implantitis.Treatment strategies such as mechanical debridement and antibiotic therapy have been used to remove dental plaque.However,it is particularly important to prevent the occurrence of peri-implantitis rather than treatment.Therefore,the current research spot has focused on improving the antibacterial properties of dental implants,such as the construction of specific micro-nano surface texture,the introduction of diverse functional coatings,or the application of materials with intrinsic antibacterial properties.The aforementioned antibacterial surfaces can be incorporated with bioactive molecules,metallic nanoparticles,or other functional components to further enhance the osteogenic properties and accelerate the healing process.In this review,we summarize the recent developments in biomaterial science and the modification strategies applied to dental implants to inhibit biofilm formation and facilitate bone-implant integration.Furthermore,we summarized the obstacles existing in the process of laboratory research to reach the clinic products,and propose corresponding directions for future developments and research perspectives,so that to provide insights into the rational design and construction of dental implants with the aim to balance antibacterial efficacy,biological safety,and osteogenic property.
基金funded by the Informatization Plan of Chinese Academy of Sciences(Grant No.CASWX2021SF-0102)the National Key R&D Program of China(Grant Nos.2022YFA1603903,2022YFA1403800,and 2021YFA0718700)+1 种基金the National Natural Science Foundation of China(Grant Nos.11925408,11921004,and 12188101)the Chinese Academy of Sciences(Grant No.XDB33000000)。
文摘The exponential growth of literature is constraining researchers’access to comprehensive information in related fields.While natural language processing(NLP)may offer an effective solution to literature classification,it remains hindered by the lack of labelled dataset.In this article,we introduce a novel method for generating literature classification models through semi-supervised learning,which can generate labelled dataset iteratively with limited human input.We apply this method to train NLP models for classifying literatures related to several research directions,i.e.,battery,superconductor,topological material,and artificial intelligence(AI)in materials science.The trained NLP‘battery’model applied on a larger dataset different from the training and testing dataset can achieve F1 score of 0.738,which indicates the accuracy and reliability of this scheme.Furthermore,our approach demonstrates that even with insufficient data,the not-well-trained model in the first few cycles can identify the relationships among different research fields and facilitate the discovery and understanding of interdisciplinary directions.
基金National Science and Technology Major Project(2017-VI-0003-0073)Youth Innovation Promotion Association CAS under grant No.2021192+3 种基金National Natural Science Foundation of China(NSFC)under grant Nos.52130002 and 51901230IMR Innovation Fund(2023-ZD01)Liaoning"Unveiling and Commanding"Science and Technology plan(2022-37)KC Wong Education Foundation(GJTD-2020-09).
文摘The authors regret to inform that the whole“Acknowledgements”section is missing due to the composing process of the editing.The“Acknowledgements”information that should be added is as follows.
文摘The authors regret that the funding number in the Acknowledgment Section is incorrect.The correct funding project and number should be“the National Key Research and Development Program of China(No.2022YFB3808700)”.The authors would like to apologise for any inconvenience caused.
基金Liaocheng University Graduate Education Teaching Reform Research Project(322091909)。
文摘Aiming at the problem of weak integration of innovation ability and ideological education of postgraduates in materials major,this paper explores postgraduates’cultivation work under the support of Liaocheng University.It is found that the cultivation of the innovation ability of postgraduates in materials can be the realization path and sublimation carrier of ideological education,ideological education can provide spiritual support and methodological guidance for the former,and the organic integration of the two is feasible.Constructing the fit relationship between innovation ability and ideological education,institutionalizing tutor guidance,establishing tutor+counselor+professional teacher communication mechanism,and taking disciplinary competitions as a handhold can achieve the integration of innovation ability cultivation and ideological education of graduate students in materials major.
基金Supported by the National Natural Science Fundation of China(51873146)。
文摘In this paper,the main research work and related reports of materials science research in China’s space technology field during 2020-2022 are summarized.This paper covers Materials Sciences in Space Environment,Materials Sciences for Space Environment,Materials Behavior in Space Environment and Space experimental hardware for material investigation.With the rapid development of China’s space industry,more scientists will be involved in materials science,space technology and earth science researches.In the future,a series of disciplines such as space science,machinery,artificial intelligence,digital twin and big data will be further integrated with materials science,and space materials will also usher in new development opportunities.
基金supported by the Informatization Plan of the Chinese Academy of Sciences (Grant No. CASWX2023SF-0101)the Key Research Program of Frontier Sciences, CAS (Grant No. ZDBS-LY-7025)+1 种基金the Youth Innovation Promotion Association CAS (Grant No. 2021167)the Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDB33020000)。
文摘The prediction of chemical synthesis pathways plays a pivotal role in materials science research. Challenges, such as the complexity of synthesis pathways and the lack of comprehensive datasets, currently hinder our ability to predict these chemical processes accurately. However, recent advancements in generative artificial intelligence(GAI), including automated text generation and question–answering systems, coupled with fine-tuning techniques, have facilitated the deployment of large-scale AI models tailored to specific domains. In this study, we harness the power of the LLaMA2-7B model and enhance it through a learning process that incorporates 13878 pieces of structured material knowledge data.This specialized AI model, named Mat Chat, focuses on predicting inorganic material synthesis pathways. Mat Chat exhibits remarkable proficiency in generating and reasoning with knowledge in materials science. Although Mat Chat requires further refinement to meet the diverse material design needs, this research undeniably highlights its impressive reasoning capabilities and innovative potential in materials science. Mat Chat is now accessible online and open for use, with both the model and its application framework available as open source. This study establishes a robust foundation for collaborative innovation in the integration of generative AI in materials science.
基金Supports by the Strategic Priority Research Program on Space Science,the Chinese Academy of Sciences(XDA15013200,XDA15013700,XDA15013800,XDA15051200)the China’s Manned Space Station Project(TGJZ800-2-RW024)and the National Natural Science Foundation of China(51327901)。
文摘Activities of space materials science research in China have been continuously supported by two main national programs.One is the China Space Station(CSS)program since 1992,and the other is the Strategic Priority Program(SPP)on Space Science since 2011.In CSS plan in 2019,eleven space materials science experimental projects were officially approved for execution during the construction of the space station.In the SPP Phase Ⅱ launched in 2018,seven pre-research projects are deployed as the first batch in 2018,and one concept study project in 2019.These pre-research projects will be cultivated as candidates for future selection as space experiment projects on the recovery of scientific experimental satellites in the future.A new apparatus of electrostatic levitation system for ground-based research of space materials science and rapid solidification research has been developed under the support of the National Natural Science Foundation of China.In order to promote domestic academic activities and to enhance the advancement of space materials science in China,the Space Materials Science and Technology Division belong to the Chinese Materials Research Society was established in 2019.We also organized scientists to write five review papers on space materials science as a special topic published in the journal Scientia Sinica to provide valuable scientific and technical references for Chinese researchers.
文摘By analyzing the feasibility and necessity of implementing ideological and political education and online and offline mixed practice teaching in the course of basic experiment of materials science, this paper explores the teaching reform measures of basic experiment of materials science, establishes the online and offline mixed practice teaching mode, organically integrates ideological and political elements into the experimental teaching content system and constructs the formative evaluation system of basic experiment of materials science, thus improving the teaching quality. Through the implementation of the curriculum reform, we can stimulate the sense of social responsibility and mission of contemporary college students, improve their ideological and political literacy and then achieve the goal of talent cultivation in the new era.
基金supported by the Fundamental-Core National Project of the National Research Foundation(NRF)funded by the Ministry of Science and ICT,Republic of Korea(2022R1F1A1072739).
文摘Porous organic frameworks(POFs)have become a highly sought-after research domain that offers a promising avenue for developing cutting-edge nanostructured materials,both in their pristine state and when subjected to various chemical and structural modifications.Metal–organic frameworks,covalent organic frameworks,and hydrogen-bonded organic frameworks are examples of these emerging materials that have gained significant attention due to their unique properties,such as high crystallinity,intrinsic porosity,unique structural regularity,diverse functionality,design flexibility,and outstanding stability.This review provides an overview of the state-of-the-art research on base-stable POFs,emphasizing the distinct pros and cons of reticular framework nanoparticles compared to other types of nanocluster materials.Thereafter,the review highlights the unique opportunity to produce multifunctional tailoring nanoparticles to meet specific application requirements.It is recommended that this potential for creating customized nanoparticles should be the driving force behind future synthesis efforts to tap the full potential of this multifaceted material category.
基金the National Natural Science Foundation of China(Nos.52074246,52201146,52205429,52275390,U1904214)the National Defense Basic Scientific Research Program of China(No.JCKY2020408B002)+1 种基金the Key Research and Development Program of Shanxi Province(No.202102050201011)L.Z.acknowledges the Natural Science Foundation of Hunan Province for Distinguished Young Scholars(No.2021JJ10062).
文摘Phase-field method,as a powerful and popular approach to predict the mesoscale microstructure evolution in various materials science,provides a bridge from atomic-scale methods to the macroscale and has been widely used at an ever-increasing rate.This paper aims to briefly review the origin,basic idea,and development of phase-field models in a historical manner.The focus is placed on the classical and state-of-the-art applications in China,including liquid–solid,solid–solid,gas–solid,ferroelectrics/ferromagnetics phase transformation,and crack propagation-fracture.After introducing the academic activities in the phase-field community in China,some suggestions for the future development directions of phase-field method are finally mentioned.
文摘Laser-heated diamond-anvil cell (LHDAC) is emerging as the most suitable, economical and versatile tool for the measurement of a large spectrum of physical properties of materials under extreme pressure and temperature conditions. In this review, the recent developments in the instrumentation, pressure and temperature measurement techniques, results of experimental investigations from the literature were discussed. Also, the future scope of the technique in various avenues of science was explored.
基金financially supported by the National Key Research and Development Program of China(No.2016YFB0700500)the Guangdong Province Key Area R&D Program(No.2019B010940001)。
文摘There is growing interest in applying machine learning techniques in the field of materials science.However,the interpretation and knowledge extracted from machine learning models is a major concern,particularly as formulating an explicit model that provides insight into physics is the goal of learning.In the present study,we propose a framework that utilizes the filtering ability of feature engineering,in conjunction with symbolic regression to extract explicit,quantitative expressions for the band gap energy from materials data.We propose enhancements to genetic programming with dimensional consistency and artificial constraints to improve the search efficiency of symbolic regression.We show how two descriptors attributed to volumetric and electronic factors,from 32 possible candidates,explicitly express the band gap energy of Na Cl-type compounds.Our approach provides a basis to capture underlying physical relationships between materials descriptors and target properties.
文摘Quantitative analysis of populations having a geometric structure,which has developed into a special scientific subject called microstructology or stereology,is of great importance to the characterization and evaluation of microstructures and their evolution in various processes.This paper, besides a brief discussion on those topics such as the recent developments of computer assisted image analysis,mathematical morphology,and fractal analysis,will mainly focus on the scope,fundamen- tals,present status,and perspectives of classical stereology.Several case examples of its application to materials science will also be given.
文摘The authors regret<to remove Prof.Jien-Wei Yeh from the authorship for some reason.The removal is agreed by Prof.Jien-Wei Yeh>.The authors would like to apologise for any inconvenience caused.
