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
About us:The College of Chemistry and Materials Engineering(CME)in Wenzhou University(Zhejiang Province,China)is looking for postdoctoral candidates(up to 25)specialized in Chemistry,Chemical Engineering and Materials...About us:The College of Chemistry and Materials Engineering(CME)in Wenzhou University(Zhejiang Province,China)is looking for postdoctoral candidates(up to 25)specialized in Chemistry,Chemical Engineering and Materials Science.The collegehas its Chemistry program ranking ESI Top 6‰ worldwide,and Materials Scienceprogram ranking 589th in the world since 2023.展开更多
About us:The College of Chemistry and Materials Engineering(CME)in Wenzhou University(Zhejiang Province,China)is looking for postdoctoral candidates(up to 25)specialized in Chemistry,Chemical Engineering and Materials...About us:The College of Chemistry and Materials Engineering(CME)in Wenzhou University(Zhejiang Province,China)is looking for postdoctoral candidates(up to 25)specialized in Chemistry,Chemical Engineering and Materials Science.The college has its Chemistry program ranking ESI Top 6%o worldwide,and Materials Science program ranking 589th in the world since2023.The college has led publications appearing in journals such as Nat.Catal.,Nat.Commun.,Sci.Adv.,J.Am.Chem.Soc.,Angew.Chem.展开更多
From the club-like limbs of the mantis shrimp to the texture of a cicada's wing,recently reported studies of the structures found in living creatures are fostering innovations in synthetic materials.The work shows...From the club-like limbs of the mantis shrimp to the texture of a cicada's wing,recently reported studies of the structures found in living creatures are fostering innovations in synthetic materials.The work shows how biological research can underpin the development of novel materials that adopt key attributes or functions of natural substances with the goal of applying them in improved,often high-technology products[1].展开更多
The convergence of materials science and biotechnology has catalyzed the development of innovative platforms,including nanotechnology,smart sensors,and supramolecular materials,significantly advancing the progress in ...The convergence of materials science and biotechnology has catalyzed the development of innovative platforms,including nanotechnology,smart sensors,and supramolecular materials,significantly advancing the progress in the field of life sciences[1−7].Among them,supramolecular materials have garnered increasing attention in life sciences owing to their distinctive self-assembly capabilities and intelligent responsiveness[8−12].展开更多
Digital twins(DTs)are rapidly emerging as transformative tools in materials science and engineering,enabling real-time data integration,predictive modeling,and virtual testing.This study presents a systematic bibliome...Digital twins(DTs)are rapidly emerging as transformative tools in materials science and engineering,enabling real-time data integration,predictive modeling,and virtual testing.This study presents a systematic bibliometric review of 1106 peer-reviewed articles published in the last decade in Scopus and Web of Science.Using a five-stage methodology,the review examines publication trends,thematic areas,citation metrics,and keyword patterns.The results reveal exponential growth in scientific output,with Materials Theory,Computation,and Data Science as the most represented area.A thematic analysis of the most cited documents identifies four major research streams:foundational frameworks,DTs in additive manufacturing,sector-specific applications,and intelligent production systems.Keyword co-occurrence and strategic mapping show a strong foundation in modeling,simulation,and optimization,with growing links to machine learning and sustainability.The review highlights current challenges and proposes future research directions for advancing DTs in materials science.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
Leveraging big data analytics and advanced algorithms to accelerate and optimize the process of molecular and materials design, synthesis, and application has revolutionized the field of molecular and materials scienc...Leveraging big data analytics and advanced algorithms to accelerate and optimize the process of molecular and materials design, synthesis, and application has revolutionized the field of molecular and materials science, allowing researchers to gain a deeper understanding of material properties and behaviors,leading to the development of new materials that are more efficient and reliable. However, the difficulty in constructing large-scale datasets of new molecules/materials due to the high cost of data acquisition and annotation limits the development of conventional machine learning(ML) approaches. Knowledgereused transfer learning(TL) methods are expected to break this dilemma. The application of TL lowers the data requirements for model training, which makes TL stand out in researches addressing data quality issues. In this review, we summarize recent progress in TL related to molecular and materials. We focus on the application of TL methods for the discovery of advanced molecules/materials, particularly, the construction of TL frameworks for different systems, and how TL can enhance the performance of models. In addition, the challenges of TL are also discussed.展开更多
Submission Papers appearing in the Journal comprise Editorials,Rapid Communications,Perspectives,Tutorials,Feature Articles,Reviews,Research Articles,which should contain original information,theoretical or experiment...Submission Papers appearing in the Journal comprise Editorials,Rapid Communications,Perspectives,Tutorials,Feature Articles,Reviews,Research Articles,which should contain original information,theoretical or experimental,on any topics in the field of polymer science and polymer material science.Papers already published or scheduled to be published elsewhere should not be submitted and certainly will not be accepted.展开更多
Osteoarthritis(OA)is a widespread joint disorder that has emerged as a significant global healthcare challenge.Over the past decade,advancements in material science and medicine have transformed the development of fun...Osteoarthritis(OA)is a widespread joint disorder that has emerged as a significant global healthcare challenge.Over the past decade,advancements in material science and medicine have transformed the development of functional materials aimed at addressing the complex issues associated with the diagnosis and treatment of OA.This review synthesizes the latest advancements in various types of intelligent micro-structured materials and their design principles.By examining the exceptional structural characteristics of materials with unique properties such as tailored attributes,controllability,biocompatibility,and bioactivity,we emphasize the design of composite materials for precise and early intervention in OA.This is achieved through advanced imaging techniques and machine learning-based analysis,alongside the customization of micro-structured material properties to align with the biological and mechanical requirements of specific joint tissues.This review offers an in-depth analysis of the transformative potential of advanced technologies and artificial intelligence(AI)in the development of innovative solutions for OA diagnosis and therapy.It aims to inform future research and inspire the creation of next-generation smart materials with unprecedented performance,thereby enhancing our capabilities in the prevention and treatment of OA.展开更多
This paper focuses on ACF artificial cartilage biomimetic energy-absorbing materials,exploring the entire process from fundamental research to industrial transformation.By analyzing the key nodes and technological bre...This paper focuses on ACF artificial cartilage biomimetic energy-absorbing materials,exploring the entire process from fundamental research to industrial transformation.By analyzing the key nodes and technological breakthroughs in the research and development journey,as well as the market strategies and collaboration models in the transformation practices,this study reveals the profound insights ACF provides to the technological innovation ecosystem in terms of concepts,mechanisms,and resource integration,and constructs a universally applicable and forward-looking paradigm for technological innovation.Aiming to provide comprehensive and in-depth case studies for materials science and the entire technological innovation system,facilitating the innovative development and progress in related areas.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
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
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.
文摘About us:The College of Chemistry and Materials Engineering(CME)in Wenzhou University(Zhejiang Province,China)is looking for postdoctoral candidates(up to 25)specialized in Chemistry,Chemical Engineering and Materials Science.The collegehas its Chemistry program ranking ESI Top 6‰ worldwide,and Materials Scienceprogram ranking 589th in the world since 2023.
文摘About us:The College of Chemistry and Materials Engineering(CME)in Wenzhou University(Zhejiang Province,China)is looking for postdoctoral candidates(up to 25)specialized in Chemistry,Chemical Engineering and Materials Science.The college has its Chemistry program ranking ESI Top 6%o worldwide,and Materials Science program ranking 589th in the world since2023.The college has led publications appearing in journals such as Nat.Catal.,Nat.Commun.,Sci.Adv.,J.Am.Chem.Soc.,Angew.Chem.
文摘From the club-like limbs of the mantis shrimp to the texture of a cicada's wing,recently reported studies of the structures found in living creatures are fostering innovations in synthetic materials.The work shows how biological research can underpin the development of novel materials that adopt key attributes or functions of natural substances with the goal of applying them in improved,often high-technology products[1].
基金supported by the National Natural Science Foundation of China(22101043)the Fundamental Research Funds for the Central Universities(N2205013,N232410019,N2405013)+3 种基金Natural Science Foundation of Liaoning Province(2023-MSBA-068)the Opening Fund of State Key Laboratory of Heavy Oil Processing(SKLHOP202203006)the Key Laboratory of Functional Molecular Solids,Ministry of Education(FMS2023005)Northeastern University。
文摘The convergence of materials science and biotechnology has catalyzed the development of innovative platforms,including nanotechnology,smart sensors,and supramolecular materials,significantly advancing the progress in the field of life sciences[1−7].Among them,supramolecular materials have garnered increasing attention in life sciences owing to their distinctive self-assembly capabilities and intelligent responsiveness[8−12].
文摘Digital twins(DTs)are rapidly emerging as transformative tools in materials science and engineering,enabling real-time data integration,predictive modeling,and virtual testing.This study presents a systematic bibliometric review of 1106 peer-reviewed articles published in the last decade in Scopus and Web of Science.Using a five-stage methodology,the review examines publication trends,thematic areas,citation metrics,and keyword patterns.The results reveal exponential growth in scientific output,with Materials Theory,Computation,and Data Science as the most represented area.A thematic analysis of the most cited documents identifies four major research streams:foundational frameworks,DTs in additive manufacturing,sector-specific applications,and intelligent production systems.Keyword co-occurrence and strategic mapping show a strong foundation in modeling,simulation,and optimization,with growing links to machine learning and sustainability.The review highlights current challenges and proposes future research directions for advancing DTs in materials science.
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National Key R&D Program of China (No. 2021YFC2100100)Shanghai Science and Technology Project (No. 21JC1403400, 23JC1402300)。
文摘Leveraging big data analytics and advanced algorithms to accelerate and optimize the process of molecular and materials design, synthesis, and application has revolutionized the field of molecular and materials science, allowing researchers to gain a deeper understanding of material properties and behaviors,leading to the development of new materials that are more efficient and reliable. However, the difficulty in constructing large-scale datasets of new molecules/materials due to the high cost of data acquisition and annotation limits the development of conventional machine learning(ML) approaches. Knowledgereused transfer learning(TL) methods are expected to break this dilemma. The application of TL lowers the data requirements for model training, which makes TL stand out in researches addressing data quality issues. In this review, we summarize recent progress in TL related to molecular and materials. We focus on the application of TL methods for the discovery of advanced molecules/materials, particularly, the construction of TL frameworks for different systems, and how TL can enhance the performance of models. In addition, the challenges of TL are also discussed.
文摘Submission Papers appearing in the Journal comprise Editorials,Rapid Communications,Perspectives,Tutorials,Feature Articles,Reviews,Research Articles,which should contain original information,theoretical or experimental,on any topics in the field of polymer science and polymer material science.Papers already published or scheduled to be published elsewhere should not be submitted and certainly will not be accepted.
基金supported by the National Key Research and Development Program of China(No.2023YFC2509200)the National Natural Science Foundation of China(Nos.82470998,82270995,81970956)+1 种基金Zhejiang Science Foundation for Distinguished Young Scholars(LR24H140001)The Science and Technology Department of the State Administration of Traditional Chinese Medicine and the Zhejiang Provincial Administration of Traditional Chinese Medicine jointly established the Science and Technology Plan(GZY-ZJ-KJ-24086)。
文摘Osteoarthritis(OA)is a widespread joint disorder that has emerged as a significant global healthcare challenge.Over the past decade,advancements in material science and medicine have transformed the development of functional materials aimed at addressing the complex issues associated with the diagnosis and treatment of OA.This review synthesizes the latest advancements in various types of intelligent micro-structured materials and their design principles.By examining the exceptional structural characteristics of materials with unique properties such as tailored attributes,controllability,biocompatibility,and bioactivity,we emphasize the design of composite materials for precise and early intervention in OA.This is achieved through advanced imaging techniques and machine learning-based analysis,alongside the customization of micro-structured material properties to align with the biological and mechanical requirements of specific joint tissues.This review offers an in-depth analysis of the transformative potential of advanced technologies and artificial intelligence(AI)in the development of innovative solutions for OA diagnosis and therapy.It aims to inform future research and inspire the creation of next-generation smart materials with unprecedented performance,thereby enhancing our capabilities in the prevention and treatment of OA.
文摘This paper focuses on ACF artificial cartilage biomimetic energy-absorbing materials,exploring the entire process from fundamental research to industrial transformation.By analyzing the key nodes and technological breakthroughs in the research and development journey,as well as the market strategies and collaboration models in the transformation practices,this study reveals the profound insights ACF provides to the technological innovation ecosystem in terms of concepts,mechanisms,and resource integration,and constructs a universally applicable and forward-looking paradigm for technological innovation.Aiming to provide comprehensive and in-depth case studies for materials science and the entire technological innovation system,facilitating the innovative development and progress in related areas.
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.
