Specimens of materials for prospective use in chambers of nuclear fusion reactors with inertial plasma confinement,namely,W,ODS steels,Eurofer 97 steel,a number of ceramics,etc.,have been irradiated by dense plasma fo...Specimens of materials for prospective use in chambers of nuclear fusion reactors with inertial plasma confinement,namely,W,ODS steels,Eurofer 97 steel,a number of ceramics,etc.,have been irradiated by dense plasma focus devices and a laser in the Q-switchedmode of operation with a wide range of parameters,including some that noticeably exceeded those expected in reactors.By means of 1-ns laser interferometry and neutron measurements,the characteristics of plasma streams and fast ion beams,as well as the dynamics of their interaction with solid-state targets,have been investigated.3D profilometry,optical and scanning electron microscopy,atomic emission spectroscopy,X-ray elemental and structural analyses,and precise weighing of specimens before and after irradiation have provided data on the roughening threshold and the susceptibility to damage of the materials under investigation.Analysis of the results,together with numerical modeling,has revealed the important role of shock waves in the damage processes.It has been shown that a so-called integral damage factor may be used only within restricted ranges of the irradiation parameters.It has also been found that in the irradiation regime with well-developed gasdynamic motion of secondary plasma,the overall amount of radiation energy is spent preferentially either on removing large masses of cool matter from the material surface or on heating a small amount of plasma to high temperature(and,consequently,imparting to it a high velocity),depending on the power flux density and characteristics of the pulsed irradiation.展开更多
The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-lear...The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-learning(DL)-driven CV in four key areas of materials science:microstructure-based performance prediction,microstructure information generation,microstructure defect detection,and crystal structure-based property prediction.The CV has significantly reduced the cost of traditional experimental methods used in material performance prediction.Moreover,recent progress made in generating microstructure images and detecting microstructural defects using CV has led to increased efficiency and reliability in material performance assessments.The DL-driven CV models can accelerate the design of new materials with optimized performance by integrating predictions based on both crystal and microstructural data,thereby allowing for the discovery and innovation of next-generation materials.Finally,the review provides insights into the rapid interdisciplinary developments in the field of materials science and future prospects.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
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
The authors are very sorry for their carelessness that a wrong Fig.9 was uploaded,and a corrected one has been shown below:This corrigendum does not affect the overall structure and analysis process of the study.The a...The authors are very sorry for their carelessness that a wrong Fig.9 was uploaded,and a corrected one has been shown below:This corrigendum does not affect the overall structure and analysis process of the study.The authors would like to apologize for any inconvenience caused.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
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
The authors regret for the missing of copyright attributions in the captions of Fig.1(d)and Fig.7 in the original publication.Please note the corrections do not affect the experimental results and conclusions.In the o...The authors regret for the missing of copyright attributions in the captions of Fig.1(d)and Fig.7 in the original publication.Please note the corrections do not affect the experimental results and conclusions.In the originally published article,Fig.1(d)and Fig.7 were adapted from previously published figures in the cited literature.展开更多
Corresponding author’s name was incorrectly written as“Dadang Guo”instead of“Dagang Guo”.The correct author name should be“Dagang Guo”.The authors would like to apologise for any inconvenience caused.
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
In the era of big data,reinforcement learning(RL)has emerged as a powerful data-driven optimization approach in materials science,enabling unprecedented advances in material design and performance improvement.Unlike t...In the era of big data,reinforcement learning(RL)has emerged as a powerful data-driven optimization approach in materials science,enabling unprecedented advances in material design and performance improvement.Unlike traditional trial-and-error and physics-based approaches,RL agents autonomously identify optimal strategies across high-dimensional and dynamic design spaces by iterative interactions with complex environments.This capability makes RL especially effective for target optimization and sequential decision-making in challenging materials science problems.In this review,we present a comprehensive overview of fundamental RL algorithms,including Q-learning,deep Q-networks(DQN),actor-critic methods,and deep deterministic policy gradient(DDPG).Then,the core mechanisms,advantages,limitations,and representative applications of RL in materials discovery,property optimization,process control,and manufacturing are discussed systematically.Lastly,key future research directions and opportunities are outlined.The perspectives presented herein aim to foster interdisciplinary collaboration and drive innovation at the frontier of AI‑driven materials science.展开更多
Cement stands as a dominant contributor to global energy consumption and carbon emissions in the construction industry.With the upgrading of infrastructure and the improvement of building standards,traditional cement ...Cement stands as a dominant contributor to global energy consumption and carbon emissions in the construction industry.With the upgrading of infrastructure and the improvement of building standards,traditional cement fails to reconcile ecological responsibility with advanced functional performance.By incorporating tailored fillers into cement matrices,the resulting composites achieve enhanced thermoelectric(TE)conversion capabilities.These materials can harness solar radiation from building envelopes and recover waste heat from indoor thermal gradients,facilitating bidirectional energy conversion.This review offers a comprehensive and timely overview of cementbased thermoelectric materials(CTEMs),integrating material design,device fabrication,and diverse applications into a holistic perspective.It summarizes recent advancements in TE performance enhancement,encompassing fillers optimization and matrices innovation.Additionally,the review consolidates fabrication strategies and performance evaluations of cement-based thermoelectric devices(CTEDs),providing detailed discussions on their roles in monitoring and protection,energy harvesting,and smart building.We also address sustainability,durability,and lifecycle considerations of CTEMs,which are essential for real-world deployment.Finally,we outline future research directions in materials design,device engineering,and scalable manufacturing to foster the practical application of CTEMs in sustainable and intelligent infrastructure.展开更多
Coal cinder is an abundant byproduct of the extensive consumption of coal in industrial production and daily life.Making full use of the cinder is conducive to a low-carbon economy.In this study,inspired by the burnin...Coal cinder is an abundant byproduct of the extensive consumption of coal in industrial production and daily life.Making full use of the cinder is conducive to a low-carbon economy.In this study,inspired by the burning of coal,a new method for constructing a silica-based composite porous material(SiO_(2)-CPM)was developed by combusting a siloxane-modified anthracite coal gel(CSiO_(2) gel).During this process,the combustion product was directly converted into a porous material,and the calorific value of the coal remained nearly unchanged(~98%of the original calorific value was retained),demonstrating the viability of this method for energy-efficient applications.The SiO_(2)-CPM exhibited an ultra-low thermal conductivity(0.036 W/(m·K)at room temperature),outperforming conventional insulation materials(e.g.,cotton~0.05 W/(m·K)).Additionally,it showed enhanced mechanical strength(fracture stress of 41.8 kPa)compared to the powder state of the coal cinder.Experimental results indicate that the amount of siloxane,structure-directing agent,and an acidic environment were critical for mechanical enhancement.The SiO_(2)-CPM showed good dimensional stability against thermal expansion and exhibited excellent thermal insulation and fire resistance even at 900℃.Meanwhile,the SiO_(2)-CPM with complex geometry could be easily fabricated using this method owing to the excellent shaping ability of the CSiO_(2) gel.Compared to conventional methods such as sol-gel synthesis or freeze-drying,this approach for fabricating SiO_(2)-CPM is simpler and cost-effective and allows the direct utilization of coal cinder post-combustion.展开更多
Prolonged exposure to n-butanol, a common hazardous volatile organic compound(VOC) in the environment, can lead to a broad range of adverse health effects. Therefore, detecting n-butanol safely and efficiently at low ...Prolonged exposure to n-butanol, a common hazardous volatile organic compound(VOC) in the environment, can lead to a broad range of adverse health effects. Therefore, detecting n-butanol safely and efficiently at low concentrations becomes critical for both environmental monitoring and human health. In this study, a novel Eu/Ce-codoped MOF-ZnO gas sensor was developed for the sensitive detection of n-butanol gas under ultraviolet activation at ambient temperature. A series of Eu/Ce-ZnO nanomaterials were synthesized via a simple co-precipitation route, by carefully designing the varied mass ratios of Eu and Ce incorporated into pristine ZnO derived from MOF precursors. The gas testing results revealed that introducing an appropriate amount of Eu and Ce would enlarge the specific surface area and enrich the oxygen vacancy content compared to pristine MOF-ZnO. Upon UV irradiation, the 0.03 wt% Eu 0.04 wt% Ce-ZnO sensor achieved a superior response of 611 for100 ppm n-butanol at room temperature, 15.28 times higher than that of pristine MOF-ZnO(40). Furthermore, the sensor presented rapid response/recovery times(15 s/28 s) and excellent selectivity. The above contributions pave the way for the promising development of highly sensitive, ultraviolet-enhanced gas sensors for ambient temperature detection of VOCs.展开更多
In the context of the global energy low-carbon transition,phase change energy storage technology becomes a key technology to solve the problem of intermittent renewable energy.Oriented phase change composites(OCPCMs)r...In the context of the global energy low-carbon transition,phase change energy storage technology becomes a key technology to solve the problem of intermittent renewable energy.Oriented phase change composites(OCPCMs)receive widespread attention in practical energy storage applications due to their unique oriented thermally conductive structure,which achieves significant thermal conductivity enhancement in specific directions while retaining the high energy storage capacity of the phase change components.This review systematically summarizes the overall analysis of OCPCMs from synthesis and preparation to application scenarios in recent years.Herein,we introduce the analysis of the heat transfer mechanism of the materials and explore the advantages of the oriented structure in OCPCMs in the heat transfer behavior from a bionic perspective.We then focus on summarizing and generalizing the methods for preparing OCPCMs,giving suggestions for suitable methods according to different scenarios.Besides,we discuss the application of finite element simulation methods to the monitoring of the thermal management behavior of OCPCMs,and look into the potential future application areas of such materials.Finally,it is hoped that this review will provide guidance for the academic community in developing high-performance OCPCMs.展开更多
As silicon-based transistors face fundamental scaling limits,the search for breakthrough alternatives has led to innovations in 3D architectures,heterogeneous integration,and sub-3 nm semiconductor body thicknesses.Ho...As silicon-based transistors face fundamental scaling limits,the search for breakthrough alternatives has led to innovations in 3D architectures,heterogeneous integration,and sub-3 nm semiconductor body thicknesses.However,the true effectiveness of these advancements lies in the seamless integration of alternative semiconductors tailored for next-generation transistors.In this review,we highlight key advances that enhance both scalability and switching performance by leveraging emerging semiconductor materials.Among the most promising candidates are 2D van der Waals semiconductors,Mott insulators,and amorphous oxide semiconductors,which offer not only unique electrical properties but also low-power operation and high carrier mobility.Additionally,we explore the synergistic interactions between these novel semiconductors and advanced gate dielectrics,including high-K materials,ferroelectrics,and atomically thin hexagonal boron nitride layers.Beyond introducing these novel material configurations,we address critical challenges such as leakage current and long-term device reliability,which become increasingly crucial as transistors scale down to atomic dimensions.Through concrete examples showcasing the potential of these materials in transistors,we provide key insights into overcoming fundamental obstacles—such as device reliability,scaling down limitations,and extended applications in artificial intelligence—ultimately paving the way for the development of future transistor technologies.展开更多
Thermally activated delayed fluorescence(TADF) emitters show great potential in photodynamic therapy(PDT) and bioimaging,leveraging their structural adaptability,efficient reverse intersystem crossing(RISC),robust pho...Thermally activated delayed fluorescence(TADF) emitters show great potential in photodynamic therapy(PDT) and bioimaging,leveraging their structural adaptability,efficient reverse intersystem crossing(RISC),robust photosensitizing capability,and high photoluminescence quantum yields(PLQYs).Herein,we developed a new class of donor-acceptor-donor(D-A-D)-type TADF materials by connecting the highly twisted indolizine-benzophenone electron acceptors with a series of electron donors including phenoxazine,phenothiazine and 9,9-dimethyl-9,10-dihydroacridine.These materials exhibit enhanced TADF properties,aggregation-induced emission(AIE),alongside high reactive oxygen species(ROS) generation efficiency,effectively mitigating aggregation-caused quenching observed in traditional fluorophores.Among them,IDP-p-PXZ,incorporating the phenoxazine donor,stands out with the smallest singlet-triplet splitting energy(ΔE_(ST)) and the highest spin-orbit coupling matrix elements(SOCMEs).Upon encapsulation into 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000](DSPE-PEG2000) nanoparticles(NPs),IDP-p-PXZ demonstrates extended delayed fluorescence lifetimes in air,an exceptionally fast intersystem crossing(ISC) rate constant(k_(ISC)) of 3.4×10^(7)s^(-1),and a radiative rate constant(k_(r)) of 5.05×10^(6)s^(-1).These NPs exhibit superior biocompatibility,efficient cellular internalization,and potent ROS production,enabling effective simultaneous PDT and confocal fluorescence imaging in HeLa cells.展开更多
The development of shape-customizable and bulk flexible electrochemical devices through processing technologies as versatile as those used for plastics promises to revolutionize the future of battery technology.Howeve...The development of shape-customizable and bulk flexible electrochemical devices through processing technologies as versatile as those used for plastics promises to revolutionize the future of battery technology.However,this pursuit has been fundamentally hindered by the absence of transformative battery materials capable of delivering the necessary electrochemical functions,robust interface adhesion,and,crucially,the suitable rheological properties required for on-demand shaping.In this work,we introduce a concept of a multifunctional plasticine electrode matrix(PEM)featuring nano-interpenetrating networks(nano-IPN)to address this challenge.Utilizing the nonflammable liquid-electrolyte hydration combined with conductive nanomaterials,we have realized a PEM in the form of a multifunctional nanocomposite that integrates ion and electron conduction,component binding,non-flammability,and plasticine-like moldability.With this PEM,we have successfully fabricated a variety of bulk-flexible electrodes with high mass loading of active material(AM)(>70 wt%)using industry-friendly extrusion and compression molding techniques.Moreover,these high AM-loading composite electrodes achieve an unparalleled bulk conformability and flexibility,remaining structurally intact even under severe mechanical stress.Ultimately,we have successfully produced shape-patternable and flexible batteries via extrusion molding.This study underscores the potential of the PEM to revolutionize battery microstructures,interfaces,manufacturing processes,and performance characteristics.展开更多
Metamaterials programmed with target rate-dependent mechanical properties are efficient platforms for realizing advanced functionalities.Yet,the loading rate-dependent mechanical property programming has received limi...Metamaterials programmed with target rate-dependent mechanical properties are efficient platforms for realizing advanced functionalities.Yet,the loading rate-dependent mechanical property programming has received limited attention.Here,the“stair-building”strategy is employed in the rate domain by combining the bistability with viscoelasticity.An arbitrary target curve in the programmable space can be approximated by a“stair”built by two kinds of“bricks”.The“bricks”can be realized by a dual-bistable unit,constructed by two bistable structures in series.The dual-bistable unit can switch between two efficient stable phases without inducing changes in the global morphology.Such a unit exhibits N-shaped stress-strain curves at both efficient stable phases with different peak values,resulting in different heights of“bricks”.Moreover,the N-shaped curves have rate-dependent peak values,indicating that the heights of“bricks”change with loading rate.The“stair-building”strategy is realized by array-structured mechanical metamaterials based on dual-bistable units.Different stress-strain curves under various loading rates can be reprogrammed in the same piece of metamaterial by intentionally selecting the efficient stable phases of units.Besides,the rate effect of the metamaterial can also be tuned by reprogramming stress-strain curves under both low and high loading rates,respectively.This reprogrammable metamaterial is promising in smart vibration isolators and adaptive energy absorbers.展开更多
文摘Specimens of materials for prospective use in chambers of nuclear fusion reactors with inertial plasma confinement,namely,W,ODS steels,Eurofer 97 steel,a number of ceramics,etc.,have been irradiated by dense plasma focus devices and a laser in the Q-switchedmode of operation with a wide range of parameters,including some that noticeably exceeded those expected in reactors.By means of 1-ns laser interferometry and neutron measurements,the characteristics of plasma streams and fast ion beams,as well as the dynamics of their interaction with solid-state targets,have been investigated.3D profilometry,optical and scanning electron microscopy,atomic emission spectroscopy,X-ray elemental and structural analyses,and precise weighing of specimens before and after irradiation have provided data on the roughening threshold and the susceptibility to damage of the materials under investigation.Analysis of the results,together with numerical modeling,has revealed the important role of shock waves in the damage processes.It has been shown that a so-called integral damage factor may be used only within restricted ranges of the irradiation parameters.It has also been found that in the irradiation regime with well-developed gasdynamic motion of secondary plasma,the overall amount of radiation energy is spent preferentially either on removing large masses of cool matter from the material surface or on heating a small amount of plasma to high temperature(and,consequently,imparting to it a high velocity),depending on the power flux density and characteristics of the pulsed irradiation.
基金financially supported by the National Science Fund for Distinguished Young Scholars,China(No.52025041)the National Natural Science Foundation of China(Nos.52450003,U2341267,and 52174294)+1 种基金the National Postdoctoral Program for Innovative Talents,China(No.BX20240437)the Fundamental Research Funds for the Central Universities,China(Nos.FRF-IDRY-23-037 and FRF-TP-20-02C2)。
文摘The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-learning(DL)-driven CV in four key areas of materials science:microstructure-based performance prediction,microstructure information generation,microstructure defect detection,and crystal structure-based property prediction.The CV has significantly reduced the cost of traditional experimental methods used in material performance prediction.Moreover,recent progress made in generating microstructure images and detecting microstructural defects using CV has led to increased efficiency and reliability in material performance assessments.The DL-driven CV models can accelerate the design of new materials with optimized performance by integrating predictions based on both crystal and microstructural data,thereby allowing for the discovery and innovation of next-generation materials.Finally,the review provides insights into the rapid interdisciplinary developments in the field of materials science and future prospects.
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.
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The authors are very sorry for their carelessness that a wrong Fig.9 was uploaded,and a corrected one has been shown below:This corrigendum does not affect the overall structure and analysis process of the study.The authors would like to apologize for any inconvenience caused.
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].
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.
文摘The authors regret for the missing of copyright attributions in the captions of Fig.1(d)and Fig.7 in the original publication.Please note the corrections do not affect the experimental results and conclusions.In the originally published article,Fig.1(d)and Fig.7 were adapted from previously published figures in the cited literature.
文摘Corresponding author’s name was incorrectly written as“Dadang Guo”instead of“Dagang Guo”.The correct author name should be“Dagang Guo”.The authors would like to apologise for any inconvenience caused.
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supported by the National Natural Science Foundation of China(Nos.52571028,52301029)the Fundamental Research Funds for the Central Universities(No.06500165)+2 种基金the Guangdong Basic and Applied Basic Research Foundation(No.2022A1515140006)the AVIC Heavy Machinery Innovation Fund(ZJQT-2025-06)the Young Elite Scientists Sponsorship Program by CAST(No.2023QNRC001).
文摘In the era of big data,reinforcement learning(RL)has emerged as a powerful data-driven optimization approach in materials science,enabling unprecedented advances in material design and performance improvement.Unlike traditional trial-and-error and physics-based approaches,RL agents autonomously identify optimal strategies across high-dimensional and dynamic design spaces by iterative interactions with complex environments.This capability makes RL especially effective for target optimization and sequential decision-making in challenging materials science problems.In this review,we present a comprehensive overview of fundamental RL algorithms,including Q-learning,deep Q-networks(DQN),actor-critic methods,and deep deterministic policy gradient(DDPG).Then,the core mechanisms,advantages,limitations,and representative applications of RL in materials discovery,property optimization,process control,and manufacturing are discussed systematically.Lastly,key future research directions and opportunities are outlined.The perspectives presented herein aim to foster interdisciplinary collaboration and drive innovation at the frontier of AI‑driven materials science.
基金supported by the National Natural Science Foundation of China(No.52242305).
文摘Cement stands as a dominant contributor to global energy consumption and carbon emissions in the construction industry.With the upgrading of infrastructure and the improvement of building standards,traditional cement fails to reconcile ecological responsibility with advanced functional performance.By incorporating tailored fillers into cement matrices,the resulting composites achieve enhanced thermoelectric(TE)conversion capabilities.These materials can harness solar radiation from building envelopes and recover waste heat from indoor thermal gradients,facilitating bidirectional energy conversion.This review offers a comprehensive and timely overview of cementbased thermoelectric materials(CTEMs),integrating material design,device fabrication,and diverse applications into a holistic perspective.It summarizes recent advancements in TE performance enhancement,encompassing fillers optimization and matrices innovation.Additionally,the review consolidates fabrication strategies and performance evaluations of cement-based thermoelectric devices(CTEDs),providing detailed discussions on their roles in monitoring and protection,energy harvesting,and smart building.We also address sustainability,durability,and lifecycle considerations of CTEMs,which are essential for real-world deployment.Finally,we outline future research directions in materials design,device engineering,and scalable manufacturing to foster the practical application of CTEMs in sustainable and intelligent infrastructure.
基金supported by the National Natural Science Foundation of China(No.52573220)the National Key R&D Program of China(No.2023YFC3404201)+1 种基金the Fundamental Research Funds for the Central Universities(No.FRF-IDRY-GD24-005)the State Key Laboratory of Solid Waste Reuse for Building Materials(No.SWR-2022-009).
文摘Coal cinder is an abundant byproduct of the extensive consumption of coal in industrial production and daily life.Making full use of the cinder is conducive to a low-carbon economy.In this study,inspired by the burning of coal,a new method for constructing a silica-based composite porous material(SiO_(2)-CPM)was developed by combusting a siloxane-modified anthracite coal gel(CSiO_(2) gel).During this process,the combustion product was directly converted into a porous material,and the calorific value of the coal remained nearly unchanged(~98%of the original calorific value was retained),demonstrating the viability of this method for energy-efficient applications.The SiO_(2)-CPM exhibited an ultra-low thermal conductivity(0.036 W/(m·K)at room temperature),outperforming conventional insulation materials(e.g.,cotton~0.05 W/(m·K)).Additionally,it showed enhanced mechanical strength(fracture stress of 41.8 kPa)compared to the powder state of the coal cinder.Experimental results indicate that the amount of siloxane,structure-directing agent,and an acidic environment were critical for mechanical enhancement.The SiO_(2)-CPM showed good dimensional stability against thermal expansion and exhibited excellent thermal insulation and fire resistance even at 900℃.Meanwhile,the SiO_(2)-CPM with complex geometry could be easily fabricated using this method owing to the excellent shaping ability of the CSiO_(2) gel.Compared to conventional methods such as sol-gel synthesis or freeze-drying,this approach for fabricating SiO_(2)-CPM is simpler and cost-effective and allows the direct utilization of coal cinder post-combustion.
基金supported by the National Natural Science Foundation of China (Grant No. 12304467)the China Postdoctoral Science Foundation (Grant No. 2023M732175)。
文摘Prolonged exposure to n-butanol, a common hazardous volatile organic compound(VOC) in the environment, can lead to a broad range of adverse health effects. Therefore, detecting n-butanol safely and efficiently at low concentrations becomes critical for both environmental monitoring and human health. In this study, a novel Eu/Ce-codoped MOF-ZnO gas sensor was developed for the sensitive detection of n-butanol gas under ultraviolet activation at ambient temperature. A series of Eu/Ce-ZnO nanomaterials were synthesized via a simple co-precipitation route, by carefully designing the varied mass ratios of Eu and Ce incorporated into pristine ZnO derived from MOF precursors. The gas testing results revealed that introducing an appropriate amount of Eu and Ce would enlarge the specific surface area and enrich the oxygen vacancy content compared to pristine MOF-ZnO. Upon UV irradiation, the 0.03 wt% Eu 0.04 wt% Ce-ZnO sensor achieved a superior response of 611 for100 ppm n-butanol at room temperature, 15.28 times higher than that of pristine MOF-ZnO(40). Furthermore, the sensor presented rapid response/recovery times(15 s/28 s) and excellent selectivity. The above contributions pave the way for the promising development of highly sensitive, ultraviolet-enhanced gas sensors for ambient temperature detection of VOCs.
基金financially supported by the Fundamental Research Funds for the Central Universities(No.FRF-KST-25-001)the Beijing Natural Science Foundation(No.L253029)。
文摘In the context of the global energy low-carbon transition,phase change energy storage technology becomes a key technology to solve the problem of intermittent renewable energy.Oriented phase change composites(OCPCMs)receive widespread attention in practical energy storage applications due to their unique oriented thermally conductive structure,which achieves significant thermal conductivity enhancement in specific directions while retaining the high energy storage capacity of the phase change components.This review systematically summarizes the overall analysis of OCPCMs from synthesis and preparation to application scenarios in recent years.Herein,we introduce the analysis of the heat transfer mechanism of the materials and explore the advantages of the oriented structure in OCPCMs in the heat transfer behavior from a bionic perspective.We then focus on summarizing and generalizing the methods for preparing OCPCMs,giving suggestions for suitable methods according to different scenarios.Besides,we discuss the application of finite element simulation methods to the monitoring of the thermal management behavior of OCPCMs,and look into the potential future application areas of such materials.Finally,it is hoped that this review will provide guidance for the academic community in developing high-performance OCPCMs.
基金supported by the National Research Foundation of Korea(NRF)funded by the Ministry of Science and ICT(MSIT),South Korea(RS-2024-00421181)financially supported in part by National R&D Program(2021M3H4A3A02086430)through NRF(National Research Foundation of Korea)funded by Ministry of Science and ICT+2 种基金the National Research Council of Science&Technology(NST)grant by the Korea government(MSIT)(No.GTL25021-210)The Inter-University Semiconductor Research Center,Institute of Engineering Research,and Soft Foundry Institute at Seoul National University provided research facilities for this workhe grant by the National Research Foundation of Korea(NSF)supported by the Korea government(MIST)(RS-2025-16903034)。
文摘As silicon-based transistors face fundamental scaling limits,the search for breakthrough alternatives has led to innovations in 3D architectures,heterogeneous integration,and sub-3 nm semiconductor body thicknesses.However,the true effectiveness of these advancements lies in the seamless integration of alternative semiconductors tailored for next-generation transistors.In this review,we highlight key advances that enhance both scalability and switching performance by leveraging emerging semiconductor materials.Among the most promising candidates are 2D van der Waals semiconductors,Mott insulators,and amorphous oxide semiconductors,which offer not only unique electrical properties but also low-power operation and high carrier mobility.Additionally,we explore the synergistic interactions between these novel semiconductors and advanced gate dielectrics,including high-K materials,ferroelectrics,and atomically thin hexagonal boron nitride layers.Beyond introducing these novel material configurations,we address critical challenges such as leakage current and long-term device reliability,which become increasingly crucial as transistors scale down to atomic dimensions.Through concrete examples showcasing the potential of these materials in transistors,we provide key insights into overcoming fundamental obstacles—such as device reliability,scaling down limitations,and extended applications in artificial intelligence—ultimately paving the way for the development of future transistor technologies.
基金supported by the National Natural Science Foundation of China (No.22405062)the Guangdong Basic and Applied Basic Research Foundation (No.2021A1515110869)+2 种基金the Shenzhen Science and Technology Program (No.ZDSYS20210623091813040)Innovation Program of Zhanjiang (No.2020LHJH005)Funds for Ph.D.researchers of Guangdong Medical University in 2025 (No.4SG25007G)。
文摘Thermally activated delayed fluorescence(TADF) emitters show great potential in photodynamic therapy(PDT) and bioimaging,leveraging their structural adaptability,efficient reverse intersystem crossing(RISC),robust photosensitizing capability,and high photoluminescence quantum yields(PLQYs).Herein,we developed a new class of donor-acceptor-donor(D-A-D)-type TADF materials by connecting the highly twisted indolizine-benzophenone electron acceptors with a series of electron donors including phenoxazine,phenothiazine and 9,9-dimethyl-9,10-dihydroacridine.These materials exhibit enhanced TADF properties,aggregation-induced emission(AIE),alongside high reactive oxygen species(ROS) generation efficiency,effectively mitigating aggregation-caused quenching observed in traditional fluorophores.Among them,IDP-p-PXZ,incorporating the phenoxazine donor,stands out with the smallest singlet-triplet splitting energy(ΔE_(ST)) and the highest spin-orbit coupling matrix elements(SOCMEs).Upon encapsulation into 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000](DSPE-PEG2000) nanoparticles(NPs),IDP-p-PXZ demonstrates extended delayed fluorescence lifetimes in air,an exceptionally fast intersystem crossing(ISC) rate constant(k_(ISC)) of 3.4×10^(7)s^(-1),and a radiative rate constant(k_(r)) of 5.05×10^(6)s^(-1).These NPs exhibit superior biocompatibility,efficient cellular internalization,and potent ROS production,enabling effective simultaneous PDT and confocal fluorescence imaging in HeLa cells.
基金financial support from the National Natural Science Foundation of China(52473248,52203123,52125301,22279070 and U21A20170)the State Key Laboratory of Polymer Materials Engineering(Grant No:sklpme 2023-1-05 and sklpme 2024-2-04)+2 种基金the Ministry of Science and Technology of China(No.2019YFA0705703)the Sichuan Science and Technology Program(2023NSFSC0991 and 2025ZNSFSC1411)the Fundamental Research Funds for the Central Universities.This research was partially sponsored by the Double First-Class Construction Funds of Sichuan University.
文摘The development of shape-customizable and bulk flexible electrochemical devices through processing technologies as versatile as those used for plastics promises to revolutionize the future of battery technology.However,this pursuit has been fundamentally hindered by the absence of transformative battery materials capable of delivering the necessary electrochemical functions,robust interface adhesion,and,crucially,the suitable rheological properties required for on-demand shaping.In this work,we introduce a concept of a multifunctional plasticine electrode matrix(PEM)featuring nano-interpenetrating networks(nano-IPN)to address this challenge.Utilizing the nonflammable liquid-electrolyte hydration combined with conductive nanomaterials,we have realized a PEM in the form of a multifunctional nanocomposite that integrates ion and electron conduction,component binding,non-flammability,and plasticine-like moldability.With this PEM,we have successfully fabricated a variety of bulk-flexible electrodes with high mass loading of active material(AM)(>70 wt%)using industry-friendly extrusion and compression molding techniques.Moreover,these high AM-loading composite electrodes achieve an unparalleled bulk conformability and flexibility,remaining structurally intact even under severe mechanical stress.Ultimately,we have successfully produced shape-patternable and flexible batteries via extrusion molding.This study underscores the potential of the PEM to revolutionize battery microstructures,interfaces,manufacturing processes,and performance characteristics.
基金supported by the National Natural Science Foundation of China(Grant Nos.12225201,12372126,12002016,and 12172026)the National Key Research and Development Program of China(Grant No.2020YFB1313003)the Fundamental Research Funds for the Central Universities are gratefully acknowledged.
文摘Metamaterials programmed with target rate-dependent mechanical properties are efficient platforms for realizing advanced functionalities.Yet,the loading rate-dependent mechanical property programming has received limited attention.Here,the“stair-building”strategy is employed in the rate domain by combining the bistability with viscoelasticity.An arbitrary target curve in the programmable space can be approximated by a“stair”built by two kinds of“bricks”.The“bricks”can be realized by a dual-bistable unit,constructed by two bistable structures in series.The dual-bistable unit can switch between two efficient stable phases without inducing changes in the global morphology.Such a unit exhibits N-shaped stress-strain curves at both efficient stable phases with different peak values,resulting in different heights of“bricks”.Moreover,the N-shaped curves have rate-dependent peak values,indicating that the heights of“bricks”change with loading rate.The“stair-building”strategy is realized by array-structured mechanical metamaterials based on dual-bistable units.Different stress-strain curves under various loading rates can be reprogrammed in the same piece of metamaterial by intentionally selecting the efficient stable phases of units.Besides,the rate effect of the metamaterial can also be tuned by reprogramming stress-strain curves under both low and high loading rates,respectively.This reprogrammable metamaterial is promising in smart vibration isolators and adaptive energy absorbers.
