Liquefied natural gas storage and transportation as well as space propulsion systems have sparked inter-est in the martensitic transformation and behaviours of 316 L stainless steels(SS)under ultra-cryogenic deformati...Liquefied natural gas storage and transportation as well as space propulsion systems have sparked inter-est in the martensitic transformation and behaviours of 316 L stainless steels(SS)under ultra-cryogenic deformation.In this study,high-resolution transmission electron microscopy(HRTEM)and molecular dy-namics(MD)simulations were used to investigate the atomic arrangements and crystalline defects of deformation-induced γ-austenite→ε-martensite→α'-martensite and γ→α'martensitic transforma-tions in 316 L SS at 15 and 173 K.Theγ→εtransformation involves the glide of Shockley partial dislocations on(111)γplanes without a change in atomic spacing.The formation of anα'inclusion in a singleε-band is achieved by a continuous lattice distortion,accompanied by the formation of a tran-sition zone ofα'and the expansion of the average atomic spacings due to dislocation shuffling.Asα'grows further intoγ,the orientation relationship(OR)of theα'changes by lattice bending.This pro-cess follows the Bogers-Burgers-Olson-Cohen model despite it not occurring on intersecting shear bands.Stacking faults and twins can also serve as nucleation sites forα'at 173 K.We also found that direct transformation of γ→α'occurs by the glide of √6aγ[11(2)]/12 dislocations on every(111)γplane with misfit dislocations.Overall,this study provides,for the first time,insights into the atomic-scale mech-anisms of various two-step and one-step martensitic transformations induced by cryogenic deformation and corresponding local strain,enhancing our understanding of the role of martensitic transformation under ultra-cryogenic-temperature deformation in controlling the properties.展开更多
Multiple principal element alloys(MPEAs),also known as high-entropy alloys,have attracted significant attention because of their exceptional mechanical and thermal properties.A critical factor influencing these proper...Multiple principal element alloys(MPEAs),also known as high-entropy alloys,have attracted significant attention because of their exceptional mechanical and thermal properties.A critical factor influencing these properties is suggested to be the presence of chemical short-range order(SRO),characterized by specific atomic arrangements occurring more frequently than in a random distribution.Despite extensive efforts to elucidate SRO,particularly in face-centered cubic(fcc)3d transition metal-based MPEAs,several key aspects remain under debate:the conditions under which SRO forms,the reliability of characterization methods for detecting SRO,and its quantitative impact on mechanical performance.This review summarizes the challenges and unresolved issues in this emerging field,drawing comparisons with well-established research on SRO in binary alloys over the past few decades.Through this cross-system comparison,we aim to provide new insights into SRO from a comprehensive perspective.展开更多
Crystal structure prediction(CSP)is a foundational computational technique for determining the atomic arrangements of crystalline materials,especially under high-pressure conditions.While CSP plays a critical role in ...Crystal structure prediction(CSP)is a foundational computational technique for determining the atomic arrangements of crystalline materials,especially under high-pressure conditions.While CSP plays a critical role in materials science,traditional approaches often encounter significant challenges related to computational efficiency and scalability,particularly when applied to complex systems.Recent advances in machine learning(ML)have shown tremendous promise in addressing these limitations,enabling the rapid and accurate prediction of crystal structures across a wide range of chemical compositions and external conditions.This review provides a concise overview of recent progress in ML-assisted CSP methodologies,with a particular focus on machine learning potentials and generative models.By critically analyzing these advances,we highlight the transformative impact of ML in accelerating materials discovery,enhancing computational efficiency,and broadening the applicability of CSP.Additionally,we discuss emerging opportunities and challenges in this rapidly evolving field.展开更多
Demand for simple and effective gas sensing sensors is growing rapidly due to the growing threat of triethylamine(TEA).Semiconductor tin oxide(SnO_(2))is one of the most widely used sensing materials for metal oxide g...Demand for simple and effective gas sensing sensors is growing rapidly due to the growing threat of triethylamine(TEA).Semiconductor tin oxide(SnO_(2))is one of the most widely used sensing materials for metal oxide gas sensors.In recent years,a lot of binary ternary compound researches have been carried out.In this paper,five different SnO_(2) samples were synthesized by simple synthesis method to understand the internal relationship and obtain different gas sensing characteristics.Based on the low temperature nitrogen adsorption tests and the atomic arrangement model,it can be inferred that different exposed surfaces play a key role in TEA sensing properties.In addition,the TEA sensing activity relationship of SnO_(2) exposed crystal faces is proposed as listed:(200)>(101)>(110).展开更多
A new type of grain-interior planar defect in a ceramic phase in TiC doped cemented tungsten carbides was discovered.It is unique in that the monolayers of metal atoms exist stably in ceramic grains.The planar defects...A new type of grain-interior planar defect in a ceramic phase in TiC doped cemented tungsten carbides was discovered.It is unique in that the monolayers of metal atoms exist stably in ceramic grains.The planar defects were induced by the ordered heteroatoms distributing on certain crystal planes of the matrix,which are distinct from the known planar defects such as phase-,grain-,and twin-boundaries,stacking faults,and complexions.Detailed characterization on the atomic scale was performed for the composition,structure,and crystallography of the planar defects,and their energy state and stability were evaluated by modeling.It was found that the Ti monolayer assists nucleation of the new WC crystal along the normal direction to its basal plane.Due to the disturbance of the heteroatom layer,the deposition of W and C atoms deviates from the regular sites occupied in the perfect crystal lattice,resulting in variations of the W–C arrangement in the grain structure.Experiments confirmed that tailoring the distribution density of the planar defects could give the best comprehensive mechanical performance with simultaneously outstanding strength and fracture toughness in the materials containing the grain-interior planar defects.This study provides a new strategy to greatly enhance the mechanical properties of materials by introducing and tailoring planar defects in the grain interiors.展开更多
Global optimization of crystal compositions is a significant yet computationally intensive method to identify stable structures within chemical space.The specific physical properties linked to a threedimensional atomi...Global optimization of crystal compositions is a significant yet computationally intensive method to identify stable structures within chemical space.The specific physical properties linked to a threedimensional atomic arrangement make this an essential task in the development of new materials.We present a method that efficiently uses active learning of neural network force fields for structure relaxation,minimizing the required number of steps in the process.This is achieved by neural network force fields equipped with uncertainty estimation,which iteratively guide a pool of randomly generated candidates toward their respective local minima.Using this approach,we are able to effectively identify themost promising candidates for further evaluation using density functional theory(DFT).Our method not only reliably reduces computational costs by up to two orders of magnitude across the benchmark systemsSi_(16),Na_(8)Cl_(8),Ga_(8)As_(8)and Al_(4)O_(6)but also excels in finding themost stable minimum for the unseen,more complex systems Si46 and Al16O24.Moreover,we demonstrate at the example of Si_(16)that our method can find multiple relevant local minima while only adding minor computational effort.展开更多
Crystal phase is an intrinsic structural parameter to determine the physicochemical properties and functionalities of materials.The unconventional phases of materials with distinct atomic arrangements from their therm...Crystal phase is an intrinsic structural parameter to determine the physicochemical properties and functionalities of materials.The unconventional phases of materials with distinct atomic arrangements from their thermodynamically stable phases have attracted enormous attention.Phase engineering has recently made fruitful achievements in electrocatalysis field to optimize the performance of various electrochemical reactions.In this review,theoretical and experimental advances made in phase engineering of electrocatalysts are summarized.First,we introduce basic understanding on crystal phases of catalysts to show the dialectical relationship between bulk phase and surface catalytic layer,and highlight the multiple functions of phase engineering in catalysis studies.We then describe phase-controlled synthesis of materials through various experimental methods such as wet-chemical method,phase transition,and template growth.As a focus,we discuss the wide usage of phase engineering strategy in different kinds of electrocatalytic materials,and particular emphasis is given to establishment of reasonable crystal phase-activity relationship.Finally,we propose several future directions for developing more desirable electrocatalysts by rational crystal phase design.展开更多
基金supported by the Henry Royce Institute for Advanced Materials,funded through Engineering and Physical Sciences Research Council(EPSRC)grants EP/R00661X/1,EP/S019367/1,EP/P025021/1,and EP/P025498/1.
文摘Liquefied natural gas storage and transportation as well as space propulsion systems have sparked inter-est in the martensitic transformation and behaviours of 316 L stainless steels(SS)under ultra-cryogenic deformation.In this study,high-resolution transmission electron microscopy(HRTEM)and molecular dy-namics(MD)simulations were used to investigate the atomic arrangements and crystalline defects of deformation-induced γ-austenite→ε-martensite→α'-martensite and γ→α'martensitic transforma-tions in 316 L SS at 15 and 173 K.Theγ→εtransformation involves the glide of Shockley partial dislocations on(111)γplanes without a change in atomic spacing.The formation of anα'inclusion in a singleε-band is achieved by a continuous lattice distortion,accompanied by the formation of a tran-sition zone ofα'and the expansion of the average atomic spacings due to dislocation shuffling.Asα'grows further intoγ,the orientation relationship(OR)of theα'changes by lattice bending.This pro-cess follows the Bogers-Burgers-Olson-Cohen model despite it not occurring on intersecting shear bands.Stacking faults and twins can also serve as nucleation sites forα'at 173 K.We also found that direct transformation of γ→α'occurs by the glide of √6aγ[11(2)]/12 dislocations on every(111)γplane with misfit dislocations.Overall,this study provides,for the first time,insights into the atomic-scale mech-anisms of various two-step and one-step martensitic transformations induced by cryogenic deformation and corresponding local strain,enhancing our understanding of the role of martensitic transformation under ultra-cryogenic-temperature deformation in controlling the properties.
基金supported by the Shanghai Key Laboratory of Material Frontiers Research in Extreme Environments,China(Grant No.22dz2260800)the Shanghai Science and Technology Committee,China(Grant No.22JC1410300).
文摘Multiple principal element alloys(MPEAs),also known as high-entropy alloys,have attracted significant attention because of their exceptional mechanical and thermal properties.A critical factor influencing these properties is suggested to be the presence of chemical short-range order(SRO),characterized by specific atomic arrangements occurring more frequently than in a random distribution.Despite extensive efforts to elucidate SRO,particularly in face-centered cubic(fcc)3d transition metal-based MPEAs,several key aspects remain under debate:the conditions under which SRO forms,the reliability of characterization methods for detecting SRO,and its quantitative impact on mechanical performance.This review summarizes the challenges and unresolved issues in this emerging field,drawing comparisons with well-established research on SRO in binary alloys over the past few decades.Through this cross-system comparison,we aim to provide new insights into SRO from a comprehensive perspective.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFA1402304)the National Natural Science Foundation of China(Grant Nos.12034009,12374005,52288102,52090024,and T2225013)+1 种基金the Fundamental Research Funds for the Central Universitiesthe Program for JLU Science and Technology Innovative Research Team.
文摘Crystal structure prediction(CSP)is a foundational computational technique for determining the atomic arrangements of crystalline materials,especially under high-pressure conditions.While CSP plays a critical role in materials science,traditional approaches often encounter significant challenges related to computational efficiency and scalability,particularly when applied to complex systems.Recent advances in machine learning(ML)have shown tremendous promise in addressing these limitations,enabling the rapid and accurate prediction of crystal structures across a wide range of chemical compositions and external conditions.This review provides a concise overview of recent progress in ML-assisted CSP methodologies,with a particular focus on machine learning potentials and generative models.By critically analyzing these advances,we highlight the transformative impact of ML in accelerating materials discovery,enhancing computational efficiency,and broadening the applicability of CSP.Additionally,we discuss emerging opportunities and challenges in this rapidly evolving field.
基金financially supported by Shandong Provincial Key R&D Plan Program(No.2017GGX10135)Shandong Provincial Science Foundation(No.ZR2018LF013)。
文摘Demand for simple and effective gas sensing sensors is growing rapidly due to the growing threat of triethylamine(TEA).Semiconductor tin oxide(SnO_(2))is one of the most widely used sensing materials for metal oxide gas sensors.In recent years,a lot of binary ternary compound researches have been carried out.In this paper,five different SnO_(2) samples were synthesized by simple synthesis method to understand the internal relationship and obtain different gas sensing characteristics.Based on the low temperature nitrogen adsorption tests and the atomic arrangement model,it can be inferred that different exposed surfaces play a key role in TEA sensing properties.In addition,the TEA sensing activity relationship of SnO_(2) exposed crystal faces is proposed as listed:(200)>(101)>(110).
基金supported by the National Natural Science Foundation of China(92163107,52171061,52101003,52271085,and 52101032).
文摘A new type of grain-interior planar defect in a ceramic phase in TiC doped cemented tungsten carbides was discovered.It is unique in that the monolayers of metal atoms exist stably in ceramic grains.The planar defects were induced by the ordered heteroatoms distributing on certain crystal planes of the matrix,which are distinct from the known planar defects such as phase-,grain-,and twin-boundaries,stacking faults,and complexions.Detailed characterization on the atomic scale was performed for the composition,structure,and crystallography of the planar defects,and their energy state and stability were evaluated by modeling.It was found that the Ti monolayer assists nucleation of the new WC crystal along the normal direction to its basal plane.Due to the disturbance of the heteroatom layer,the deposition of W and C atoms deviates from the regular sites occupied in the perfect crystal lattice,resulting in variations of the W–C arrangement in the grain structure.Experiments confirmed that tailoring the distribution density of the planar defects could give the best comprehensive mechanical performance with simultaneously outstanding strength and fracture toughness in the materials containing the grain-interior planar defects.This study provides a new strategy to greatly enhance the mechanical properties of materials by introducing and tailoring planar defects in the grain interiors.
基金N.W.A.G.and M.G.contributed to this research while working at the BASLEARN-TU Berlin/BASF Joint Lab for Machine Learning,co-financed by TU Berlin and BASF SE.K.T.S.contributed to this research while working at TU Berlin and BIFOLD with grant number 01IS18037Asupported by JSPS KAKENHI Grant Number JP23H05457 and by JST-CREST Grant Number JPMJCR22O2.We thank Jonas Lederer and Klaus-Robert Müller for insightful discussions and feedback.
文摘Global optimization of crystal compositions is a significant yet computationally intensive method to identify stable structures within chemical space.The specific physical properties linked to a threedimensional atomic arrangement make this an essential task in the development of new materials.We present a method that efficiently uses active learning of neural network force fields for structure relaxation,minimizing the required number of steps in the process.This is achieved by neural network force fields equipped with uncertainty estimation,which iteratively guide a pool of randomly generated candidates toward their respective local minima.Using this approach,we are able to effectively identify themost promising candidates for further evaluation using density functional theory(DFT).Our method not only reliably reduces computational costs by up to two orders of magnitude across the benchmark systemsSi_(16),Na_(8)Cl_(8),Ga_(8)As_(8)and Al_(4)O_(6)but also excels in finding themost stable minimum for the unseen,more complex systems Si46 and Al16O24.Moreover,we demonstrate at the example of Si_(16)that our method can find multiple relevant local minima while only adding minor computational effort.
基金supported by the National Natural Science Foundation of China(Nos.21922507,22179046,and 21621001)the Jilin Province Science and Technology Development Plan(Nos.YDZJ202101ZYTS126 and 20210101403JC)+1 种基金the Science and Technology Research Program of Education Department of Jilin Province(No.JJKH20220998KJ)the 111 Project(No.B17020)。
文摘Crystal phase is an intrinsic structural parameter to determine the physicochemical properties and functionalities of materials.The unconventional phases of materials with distinct atomic arrangements from their thermodynamically stable phases have attracted enormous attention.Phase engineering has recently made fruitful achievements in electrocatalysis field to optimize the performance of various electrochemical reactions.In this review,theoretical and experimental advances made in phase engineering of electrocatalysts are summarized.First,we introduce basic understanding on crystal phases of catalysts to show the dialectical relationship between bulk phase and surface catalytic layer,and highlight the multiple functions of phase engineering in catalysis studies.We then describe phase-controlled synthesis of materials through various experimental methods such as wet-chemical method,phase transition,and template growth.As a focus,we discuss the wide usage of phase engineering strategy in different kinds of electrocatalytic materials,and particular emphasis is given to establishment of reasonable crystal phase-activity relationship.Finally,we propose several future directions for developing more desirable electrocatalysts by rational crystal phase design.
