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
Chinese Space Station(CSS)has been fully deployed by the end of 2022,and the facility has entered into the application and development phase.It has conducted scientific research projects in various fields,such as spac...Chinese Space Station(CSS)has been fully deployed by the end of 2022,and the facility has entered into the application and development phase.It has conducted scientific research projects in various fields,such as space life science and biotechnology,space materials science,microgravity fundamental physics,fluid physics,combustion science,space new technologies,and applications.In this review,we introduce the progress of CSS development and provide an overview of the research conducted in Chinese Space Station and the recent scientific findings in several typical research fields.Such compelling findings mainly concern the rapid solidification of ultra-high temperature alloy melts,dynamics of fluid transport in space,gravity scaling law of boiling heat transfer,vibration fluidization phenomenon of particulate matter,cold atom interferometer technology under high microgravity and related equivalence principle testing,the full life cycle of rice under microgravity and so forth.Furthermore,the planned scientific research and corresponding prospects of Chinese space station in the next few years are presented.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
Molecular dynamics (MD) is a computer simulation technique that helps to explore the behavior and properties of molecules and atoms. MD has been used in research and development in many spaces, including materials sci...Molecular dynamics (MD) is a computer simulation technique that helps to explore the behavior and properties of molecules and atoms. MD has been used in research and development in many spaces, including materials science and engineering and nanotechnology. MD has been proven useful in topics like the nano-engineering of construction materials, correcting graphene planar defects, studying self-assembling bio-materials, and the densification, consolidation, and sintering of nanocrystalline materials.展开更多
The recent developments of electron tomography(ET) based on transmission electron microscopy(TEM) and scanning transmission electron microscopy(STEM) in the field of materials science were introduced. The variou...The recent developments of electron tomography(ET) based on transmission electron microscopy(TEM) and scanning transmission electron microscopy(STEM) in the field of materials science were introduced. The various types of ET based on TEM as well as STEM were described in detail, which included bright-field(BF)-TEM tomography, dark-field(DF)-TEM tomography, weak-beam dark-field(WBDF)-TEM tomography, annular dark-field(ADF)-TEM tomography, energy-filtered transmission electron microscopy(EFTEM) tomography, high-angle annular dark-field(HAADF)-STEM tomography, ADF-STEM tomography, incoherent bright field(IBF)-STEM tomography, electron energy loss spectroscopy(EELS)-STEM tomography and X-ray energy dispersive spectrometry(XEDS)-STEM tomography, and so on. The optimized tilt series such as dual-axis tilt tomography, on-axis tilt tomography, conical tilt tomography and equally-sloped tomography(EST) were reported. The advanced reconstruction algorithms, such as discrete algebraic reconstruction technique(DART), compressed sensing(CS) algorithm and EST were overviewed. At last, the development tendency of ET in materials science was presented.展开更多
Since its outbreak,the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)has strongly influenced the life of the general public around the world.Based on its fast spread and high mortality,there is a need for...Since its outbreak,the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)has strongly influenced the life of the general public around the world.Based on its fast spread and high mortality,there is a need for novel therapeutic treatments to overcome this global health crisis.While medicinal chemistry is focused on the development of highly selective and affine inhibitors toward a specific target enzyme,material science is focused on the development of nanomaterials for selective drug delivery.Based on the individual strengths,these disciplines could synergistically act together and help overcome the limitations of the respective approach.Herein,the combination of medicinal chemistry with material science to overcome health problems with the example of SARS-CoV-2 is critically discussed.展开更多
Since its launch in 2011, the Materials Genome Initiative(MGI) has drawn the attention of researchers from academia,government, and industry worldwide. As one of the three tools of the MGI, the use of materials data...Since its launch in 2011, the Materials Genome Initiative(MGI) has drawn the attention of researchers from academia,government, and industry worldwide. As one of the three tools of the MGI, the use of materials data, for the first time, has emerged as an extremely significant approach in materials discovery. Data science has been applied in different disciplines as an interdisciplinary field to extract knowledge from data. The concept of materials data science has been utilized to demonstrate its application in materials science. To explore its potential as an active research branch in the big data era, a three-tier system has been put forward to define the infrastructure for the classification, curation and knowledge extraction of materials data.展开更多
Materials science is an interdisciplinary field applying the properties of matter to various areas of science and engineering. This scientific field investigates the relationship between the structure of materials at ...Materials science is an interdisciplinary field applying the properties of matter to various areas of science and engineering. This scientific field investigates the relationship between the structure of materials at atomic or molecular scales and their macroscopic properties. It incorporates elements of applied physics and chemistry. With significant media attention focused on nanoscience and nanotechnology in recent years, materials science has been propelled to the forefront at many universities. Materials science encompasses various classes of materials, including electronic materials, functional ceramics, magnesium, material and processes for flat-panel displays, eco/environmental materials, sustainable energy materials, transportation materials, electronic packaging materials, etc.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
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
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.
文摘Chinese Space Station(CSS)has been fully deployed by the end of 2022,and the facility has entered into the application and development phase.It has conducted scientific research projects in various fields,such as space life science and biotechnology,space materials science,microgravity fundamental physics,fluid physics,combustion science,space new technologies,and applications.In this review,we introduce the progress of CSS development and provide an overview of the research conducted in Chinese Space Station and the recent scientific findings in several typical research fields.Such compelling findings mainly concern the rapid solidification of ultra-high temperature alloy melts,dynamics of fluid transport in space,gravity scaling law of boiling heat transfer,vibration fluidization phenomenon of particulate matter,cold atom interferometer technology under high microgravity and related equivalence principle testing,the full life cycle of rice under microgravity and so forth.Furthermore,the planned scientific research and corresponding prospects of Chinese space station in the next few years are presented.
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.
文摘Molecular dynamics (MD) is a computer simulation technique that helps to explore the behavior and properties of molecules and atoms. MD has been used in research and development in many spaces, including materials science and engineering and nanotechnology. MD has been proven useful in topics like the nano-engineering of construction materials, correcting graphene planar defects, studying self-assembling bio-materials, and the densification, consolidation, and sintering of nanocrystalline materials.
基金Projects(51071125,51201135)supported by the National Natural Science Foundation of ChinaProject(B08040)supported by the Program of Introducing Talents of Discipline to Universities,China
文摘The recent developments of electron tomography(ET) based on transmission electron microscopy(TEM) and scanning transmission electron microscopy(STEM) in the field of materials science were introduced. The various types of ET based on TEM as well as STEM were described in detail, which included bright-field(BF)-TEM tomography, dark-field(DF)-TEM tomography, weak-beam dark-field(WBDF)-TEM tomography, annular dark-field(ADF)-TEM tomography, energy-filtered transmission electron microscopy(EFTEM) tomography, high-angle annular dark-field(HAADF)-STEM tomography, ADF-STEM tomography, incoherent bright field(IBF)-STEM tomography, electron energy loss spectroscopy(EELS)-STEM tomography and X-ray energy dispersive spectrometry(XEDS)-STEM tomography, and so on. The optimized tilt series such as dual-axis tilt tomography, on-axis tilt tomography, conical tilt tomography and equally-sloped tomography(EST) were reported. The advanced reconstruction algorithms, such as discrete algebraic reconstruction technique(DART), compressed sensing(CS) algorithm and EST were overviewed. At last, the development tendency of ET in materials science was presented.
文摘Since its outbreak,the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)has strongly influenced the life of the general public around the world.Based on its fast spread and high mortality,there is a need for novel therapeutic treatments to overcome this global health crisis.While medicinal chemistry is focused on the development of highly selective and affine inhibitors toward a specific target enzyme,material science is focused on the development of nanomaterials for selective drug delivery.Based on the individual strengths,these disciplines could synergistically act together and help overcome the limitations of the respective approach.Herein,the combination of medicinal chemistry with material science to overcome health problems with the example of SARS-CoV-2 is critically discussed.
基金Project supported by the National Key R&D Program of China(Grant No.2016YFB0700503)the National High Technology Research and Development Program of China(Grant No.2015AA03420)+2 种基金Beijing Municipal Science and Technology Project,China(Grant No.D161100002416001)the National Natural Science Foundation of China(Grant No.51172018)Kennametal Inc
文摘Since its launch in 2011, the Materials Genome Initiative(MGI) has drawn the attention of researchers from academia,government, and industry worldwide. As one of the three tools of the MGI, the use of materials data, for the first time, has emerged as an extremely significant approach in materials discovery. Data science has been applied in different disciplines as an interdisciplinary field to extract knowledge from data. The concept of materials data science has been utilized to demonstrate its application in materials science. To explore its potential as an active research branch in the big data era, a three-tier system has been put forward to define the infrastructure for the classification, curation and knowledge extraction of materials data.
文摘Materials science is an interdisciplinary field applying the properties of matter to various areas of science and engineering. This scientific field investigates the relationship between the structure of materials at atomic or molecular scales and their macroscopic properties. It incorporates elements of applied physics and chemistry. With significant media attention focused on nanoscience and nanotechnology in recent years, materials science has been propelled to the forefront at many universities. Materials science encompasses various classes of materials, including electronic materials, functional ceramics, magnesium, material and processes for flat-panel displays, eco/environmental materials, sustainable energy materials, transportation materials, electronic packaging materials, etc.
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.
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.