Single-phase face-centered cubic(fcc)high/medium-entropy alloys(H/MEAs)exhibit a much higher tendency to form nanoscale deformation twins than conventional fcc metals with similar low stacking fault energies(SFEs).Thi...Single-phase face-centered cubic(fcc)high/medium-entropy alloys(H/MEAs)exhibit a much higher tendency to form nanoscale deformation twins than conventional fcc metals with similar low stacking fault energies(SFEs).This extraordinary propensity for nanotwin formation in H/MEAs cannot therefore be ex-plained by their low SFEs alone.Here,using in situ compression tests of CrCoNi in comparison with Ag nanopillars inside a transmission electron microscope,we found that in the CrCoNi MEA,a high density of nanoscale twins continuously formed with an average thickness of 4.6 nm.In contrast,for similar experiments on Ag with almost identical SFE,following the nucleation of a few twins,they could further thicken to above one hundred nanometers by twin boundary migration.Molecular dynamics calculations indicated that in the highly-concentrated CrCoNi solid solution,the magnitude of the energy barriers for nucleating a stacking fault as a twin precursor in the pristine lattice and for the thickening of an existing twin both span a wide range and largely overlap with each other.Therefore,twin thickening through successive addition of atomic layers is prone to discontinuation,giving way to the nucleation of new twins at other sites where a lower energy barrier is encountered for partial-dislocation mediated fault formation.展开更多
Calculations of point defect energetics with Density Functional Theory(DFT)can provide valuable insight into several optoelectronic,thermodynamic,and kinetic properties.These calculations commonly use methods ranging ...Calculations of point defect energetics with Density Functional Theory(DFT)can provide valuable insight into several optoelectronic,thermodynamic,and kinetic properties.These calculations commonly use methods ranging from semi-local functionals with a-posteriori corrections to more computationally intensive hybrid functional approaches.For applications of DFT-based high-throughput computation for data-driven materials discovery,point defect properties are of interest,yet are currently excluded from available materials databases.This work presents a benchmark analysis of automated,semi-local point defect calculations with a-posteriori corrections,compared to 245“gold standard”hybrid calculations previously published.We consider three different a-posteriori correction sets implemented in an automated workflow,and evaluate the qualitative and quantitative differences among four different categories of defect information:thermodynamic transition levels,formation energies,Fermi levels,and dopability limits.We highlight qualitative information that can be extracted from high-throughput calculations based on semi-local DFT methods,while also demonstrating the limits of quantitative accuracy.展开更多
In traditional body-centered cubic(bcc)metals,the core properties of screw dislocations play a critical role in plastic deformation at low temperatures.Recently,much attention has been focused on refractory high-entro...In traditional body-centered cubic(bcc)metals,the core properties of screw dislocations play a critical role in plastic deformation at low temperatures.Recently,much attention has been focused on refractory high-entropy alloys(RHEAs),which also possess bcc crystal structures.However,unlike face-centered cubic high-entropy alloys(HEAs),there have been far fewer investigations into bcc HEAs,specifically on the possible effects of chemical short-range order(SRO)in these multiple principal element alloys on dislocation mobility.Here,using density functional theory,we investigate the distribution of dislocation core properties in MoNbTaW RHEAs alloys,and how they are influenced by SRO.The average values of the core energies in the RHEA are found to be larger than those in the corresponding pure constituent bcc metals,and are relatively insensitive to the degree of SRO.However,the presence of SRO is shown to have a large effect on narrowing the distribution of dislocation core energies and decreasing the spatial heterogeneity of dislocation core energies in the RHEA.It is argued that the consequences of the mechanical behavior of HEAs is a change in the energy landscape of the dislocations,which would likely heterogeneously inhibit their motion.展开更多
One of the most accurate approaches for calculating lattice thermal conductivity,κ_(l),is solving the Boltzmann transport equation starting from third-order anharmonic force constants.In addition to the underlying ap...One of the most accurate approaches for calculating lattice thermal conductivity,κ_(l),is solving the Boltzmann transport equation starting from third-order anharmonic force constants.In addition to the underlying approximations of ab-initio parameterization,two main challenges are associated with this path:high computational costs and lack of automation in the frameworks using this methodology,which affect the discovery rate of novel materials with ad-hoc properties.Here,the Automatic Anharmonic Phonon Library(AAPL)is presented.It efficiently computes interatomic force constants by making effective use of crystal symmetry analysis,it solves the Boltzmann transport equation to obtain κ_(l),and allows a fully integrated operation with minimum user intervention,a rational addition to the current high-throughput accelerated materials development framework AFLOW.An“experiment vs.theory”study of the approach is shown,comparing accuracy and speed with respect to other available packages,and for materials characterized by strong electron localization and correlation.Combining AAPL with the pseudo-hybrid functional ACBN0 is possible to improve accuracy without increasing computational requirements.展开更多
We present a combination of machine learning and high throughput calculations to predict the points defects behavior in binary intermetallic(A–B)compounds,using as an example systems with the cubic B2 crystal structu...We present a combination of machine learning and high throughput calculations to predict the points defects behavior in binary intermetallic(A–B)compounds,using as an example systems with the cubic B2 crystal structure(with equiatomic AB stoichiometry).To the best of our knowledge,this work is the first application of machine learning-models for point defect properties.High throughput first principles density functional calculations have been employed to compute intrinsic point defect energies in 100 B2 intermetallic compounds.The systems are classified into two groups:(i)those for which the intrinsic defects are antisites for both A and B rich compositions,and(ii)those for which vacancies are the dominant defect for either or both composition ranges.The data was analyzed by machine learning-techniques using decision tree,and full and reduced multiple additive regression tree(MART)models.Among these three schemes,a reduced MART(r-MART)model using six descriptors(formation energy,minimum and difference of electron densities at the Wigner–Seitz cell boundary,atomic radius difference,maximal atomic number and maximal electronegativity)presents the highest fit(98%)and predictive(75%)accuracy.This model is used to predict the defect behavior of other B2 compounds,and it is found that 45%of the compounds considered feature vacancies as dominant defects for either A or B rich compositions(or both).The ability to predict dominant defect types is important for the modeling of thermodynamic and kinetic properties of intermetallic compounds,and the present results illustrate how this information can be derived using modern tools combining high throughput calculations and data analytics.展开更多
Metallic glasses(MGs)possess remarkably high strength but often display only minimal tensile ductility due to the formation of catastrophic shear bands.Purposely enhancing the inherent heterogeneity to promote distrib...Metallic glasses(MGs)possess remarkably high strength but often display only minimal tensile ductility due to the formation of catastrophic shear bands.Purposely enhancing the inherent heterogeneity to promote distributed flow offers new possibilities in improving the ductility of monolithic MGs.Here,we report the effect of the spatial heterogeneity of elasticity,resulting from the inherently inhomogeneous amorphous structures,on the deformation behavior of MGs,specifically focusing on the ductility using multiscale modeling methods.A highly heterogeneous,Gaussian-type shear modulus distribution at the nanoscale is revealed by atomistic simulations in Cu_(64)Zr_(36) MGs,in which the soft population of the distribution exhibits a marked propensity to undergo the inelastic shear transformation.By employing a mesoscale shear transformation zone dynamics model,we find that the organization of such nanometer-scale shear transformation events into shear-band patterns is dependent on the spatial heterogeneity of the local shear moduli.A critical spatial correlation length of elastic heterogeneity is identified for the simulated MGs to achieve the best tensile ductility,which is associated with a transition of shear-band formation mechanisms,from stress-dictated nucleation and growth to structure-dictated strain percolation,as well as a saturation of elastically soft sites participating in the plastic flow.This discovery is important for the fundamental understanding of the role of spatial heterogeneity in influencing the deformation behavior of MGs.We believe that this can facilitate the design and development of new ductile monolithic MGs by a process of tuning the inherent heterogeneity to achieve enhanced ductility in these high-strength metallic alloys.展开更多
Antiphase boundaries(APBs)are planar defects that play a critical role in strengthening Ni-based superalloys,and their sensitivity to alloy composition offers a flexible tuning parameter for alloy design.Here,we repor...Antiphase boundaries(APBs)are planar defects that play a critical role in strengthening Ni-based superalloys,and their sensitivity to alloy composition offers a flexible tuning parameter for alloy design.Here,we report a computational workflow to enable the development of sufficient data to train machine-learning(ML)models to automate the study of the effect of composition on the(111)APB energy in Ni_(3)Al-based alloys.We employ ML to leverage this wealth of data and identify several physical properties that are used to build predictive models for the APB energy that achieve a cross-validation error of 0.033 J m^(−2).We demonstrate the transferability of these models by predicting APB energies in commercial superalloys.Moreover,our use of physically motivated features such as the ordering energy and stoichiometry-based features opens the way to using existing materials properties databases to guide superalloy design strategies to maximize the APB energy.展开更多
The formation of complex hierarchical nanostructures has attracted a lot of attention from both the fundamental science and potential applications point of view.Spherulite structures with radial fibrillar branches hav...The formation of complex hierarchical nanostructures has attracted a lot of attention from both the fundamental science and potential applications point of view.Spherulite structures with radial fibrillar branches have been found in various solids;however,their growth mechanisms remain poorly understood.Here,we report real time imaging of the formation of two-dimensional(2D)iron oxide spherulite nanostructures in a liquid cell using transmission electron microscopy(TEM).By tracking the growth trajectories,we show the characteristics of the reaction front and growth kinetics.Our observations reveal that the tip of a growing branch splits as the width exceeds certain sizes(5.5–8.5 nm).The radius of a spherulite nanostructure increases linearly with time at the early stage,transitioning to nonlinear growth at the later stage.Furthermore,a thin layer of solid is accumulated at the tip and nanoparticles from secondary nucleation also appear at the growing front which later develop into fibrillar branches.The spherulite nanostructure is polycrystalline with the co-existence of ferrihydrite and Fe3O4 through-out the growth.A growth model is further established,which provides rational explanations on the linear growth at the early stage and the nonlinearity at the later stage of growth.展开更多
While rhenium is an ideal material for rapid thermal cycling applications under high temperatures,such as rocket engine nozzles,its high cost limits its widespread use and prompts an exploration of viable cost-effecti...While rhenium is an ideal material for rapid thermal cycling applications under high temperatures,such as rocket engine nozzles,its high cost limits its widespread use and prompts an exploration of viable cost-effective substitutes.In prior work,we identified a promising pool of candidate substitute alloys consisting of Mo,Ru,Ta,and W.In this work we demonstrate,based on density functional theory melting temperature calculations,that one of the candidates,Mo_(0.292)Ru_(0.555)Ta_(0.031)W_(0.122),exhibits a high melting temperature(around 2626 K),thus supporting its use in high-temperature applications.展开更多
Quantum motion of atoms known as zero-point vibration was recently proposed to explain a long-standing discrepancy between theoretically computed and experimentally measured low-temperature plastic strength of iron an...Quantum motion of atoms known as zero-point vibration was recently proposed to explain a long-standing discrepancy between theoretically computed and experimentally measured low-temperature plastic strength of iron and possibly other metals with high atomic masses.This finding challenges the traditional notion that quantum motion of atoms is relatively unimportant in solids comprised of heavy atoms.Here we report quantum dynamic simulations of quantum effects on dislocation motion within the exact formalism of Ring-Polymer Molecular Dynamics(RPMD).To extend the reach of quantum atomistic simulations to length and time scales relevant for extended defects in materials,we implemented RPMD in the open-source code LAMMPS thus making the RPMD method widely available to the community.We use our RPMD/LAMMPS approach for direct calculations of dislocation mobility and its effects on the yield strength ofα-iron.Our simulation results establish that quantum effects are noticeable at temperatures below 50 K but account for only a modest(≈13% at T=0 K)overall reduction in the Peierls barrier,at variance with the factor of two reduction predicted earlier based on the more approximate framework of harmonic transition state theory.Our results confirm that zero-point vibrations provide ample additional agitation for atomic motion that increases with decreasing temperature,however its enhancing effect on dislocation mobility is largely offset by an increase in the effective atom size,an effect known as quantum dispersion that has not been accounted for in the previous calculations.展开更多
A multi-phase field model is employed to study the microstructural evolution of an alloy undergoing liquid dealloying,specifically considering the role of grain boundaries.A semi-implicit time-stepping algorithm using...A multi-phase field model is employed to study the microstructural evolution of an alloy undergoing liquid dealloying,specifically considering the role of grain boundaries.A semi-implicit time-stepping algorithm using spectral methods is implemented,which enables simulating large 2D and 3D domains over long time scales while still maintaining a realistic interfacial thickness.Simulations reveal a mechanism of coupled grain–boundary migration to maintain equilibrium contact angles with the topologically complex solid–liquid interface,which locally accelerates diffusion-coupled growth of a liquid channel into the precursor.This mechanism asymmetrically disrupts the ligament connectivity of the dealloyed structure in qualitative agreement with published experimental observations.The grain boundary migration-assisted corrosion channels form even for precursors with small amounts of the dissolving alloy species,below the parting limit.The activation of this grain boundary dealloying mechanism depends strongly on grain boundary mobility.展开更多
Classical Monte Carlo simulation of the Heisenberg model poorly describes many thermodynamic phenomena due to its neglect of the quantum nature of spins.Alternatively,we discuss how to semiclassically approach the qua...Classical Monte Carlo simulation of the Heisenberg model poorly describes many thermodynamic phenomena due to its neglect of the quantum nature of spins.Alternatively,we discuss how to semiclassically approach the quantum problem and demonstrate a simple method for introducing a locally approximate form of spin quantization.While the procedure underestimates magnetic short-range order,our results suggest a simple correction for recovering realistic spin–spin correlations above the critical temperature.Moreover,ensemble fluctuations are found to provide reasonably accurate thermodynamics,largely reproducing quantum mechanically calculated heat capacities and experimental magnetometry for ferromagnetic Fe and antiferromagnetic RbMnF3.Extensions of the method are proposed to address remaining inaccuracies.展开更多
基金supported by the National Natural Science Foundation of China(Nos.52231001,51971167,and 52031011)the Xi’an Science and Technology Plan(No.2017xasjl014)+4 种基金B.G.gratefully acknowledges the financial support of the project from the Ministry of Science and Technology of China(No.2017YFA0700703)the support by the National Natural Science Foundation of China(No.92060102)E.M.and J.D.acknowledge the support at CAID by XJTU.J.D.acknowledges support from the National Natural Science Foundation of China(No.12004294)the HPC platform of Xi’an Jiaotong Universitysupported by the Office of Science,Office of Basic Energy Sciences,Materials Sciences and Engineering Division,of the U.S.Department of Energy under Contract No.DE-AC02-05-CH11231.
文摘Single-phase face-centered cubic(fcc)high/medium-entropy alloys(H/MEAs)exhibit a much higher tendency to form nanoscale deformation twins than conventional fcc metals with similar low stacking fault energies(SFEs).This extraordinary propensity for nanotwin formation in H/MEAs cannot therefore be ex-plained by their low SFEs alone.Here,using in situ compression tests of CrCoNi in comparison with Ag nanopillars inside a transmission electron microscope,we found that in the CrCoNi MEA,a high density of nanoscale twins continuously formed with an average thickness of 4.6 nm.In contrast,for similar experiments on Ag with almost identical SFE,following the nucleation of a few twins,they could further thicken to above one hundred nanometers by twin boundary migration.Molecular dynamics calculations indicated that in the highly-concentrated CrCoNi solid solution,the magnitude of the energy barriers for nucleating a stacking fault as a twin precursor in the pristine lattice and for the thickening of an existing twin both span a wide range and largely overlap with each other.Therefore,twin thickening through successive addition of atomic layers is prone to discontinuation,giving way to the nucleation of new twins at other sites where a lower energy barrier is encountered for partial-dislocation mediated fault formation.
基金This work was primarily funded by the U.S.Department of Energy,Office of Science,Office of Basic Energy Sciences,Materials Sciences and Engineering Division under Contract No.DE-AC02-05-CH11231:Materials Project program KC23MPThis research used resources of the National Energy Research Scientific Computing Center,which is supported by the Office of Science of the U.S.Department of Energy under Contract No.DE-AC02-05-CH11231+1 种基金This work was partially performed under the auspices of the U.S.DOE by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344DB would like to thank Chris G.Van de Walle,Nick Adamski,Andrew Rowberg,and Mark Turiansky along with all of the attendees of the 2018 Gordon Research Conference for Point Defects in Semiconductors for many constructive discussions on this paper’s topic.
文摘Calculations of point defect energetics with Density Functional Theory(DFT)can provide valuable insight into several optoelectronic,thermodynamic,and kinetic properties.These calculations commonly use methods ranging from semi-local functionals with a-posteriori corrections to more computationally intensive hybrid functional approaches.For applications of DFT-based high-throughput computation for data-driven materials discovery,point defect properties are of interest,yet are currently excluded from available materials databases.This work presents a benchmark analysis of automated,semi-local point defect calculations with a-posteriori corrections,compared to 245“gold standard”hybrid calculations previously published.We consider three different a-posteriori correction sets implemented in an automated workflow,and evaluate the qualitative and quantitative differences among four different categories of defect information:thermodynamic transition levels,formation energies,Fermi levels,and dopability limits.We highlight qualitative information that can be extracted from high-throughput calculations based on semi-local DFT methods,while also demonstrating the limits of quantitative accuracy.
基金This work was supported by the US Department of Energy,Office of Science,Office of Basic Energy Sciences,Materials Sciences and Engineering Division,under contract no.DE-AC02-05-CH11231 within the Damage Tolerance in Structural Materials(KC 13)program.
文摘In traditional body-centered cubic(bcc)metals,the core properties of screw dislocations play a critical role in plastic deformation at low temperatures.Recently,much attention has been focused on refractory high-entropy alloys(RHEAs),which also possess bcc crystal structures.However,unlike face-centered cubic high-entropy alloys(HEAs),there have been far fewer investigations into bcc HEAs,specifically on the possible effects of chemical short-range order(SRO)in these multiple principal element alloys on dislocation mobility.Here,using density functional theory,we investigate the distribution of dislocation core properties in MoNbTaW RHEAs alloys,and how they are influenced by SRO.The average values of the core energies in the RHEA are found to be larger than those in the corresponding pure constituent bcc metals,and are relatively insensitive to the degree of SRO.However,the presence of SRO is shown to have a large effect on narrowing the distribution of dislocation core energies and decreasing the spatial heterogeneity of dislocation core energies in the RHEA.It is argued that the consequences of the mechanical behavior of HEAs is a change in the energy landscape of the dislocations,which would likely heterogeneously inhibit their motion.
基金support by the DOE(DE-AC02-05CH11231),specifically the Basic Energy Sciences program under Grant#EDCBEEpartial support by DOD-ONR(N00014-13-1-0635,N00014-11-1-0136,and N00014-15-1-2863)the Alexander von Humboldt Foundation for financial support(Fritz-Haber-Institut der Max-Planck-Gesellschaft,14195 Berlin-Dahlem,Germany).
文摘One of the most accurate approaches for calculating lattice thermal conductivity,κ_(l),is solving the Boltzmann transport equation starting from third-order anharmonic force constants.In addition to the underlying approximations of ab-initio parameterization,two main challenges are associated with this path:high computational costs and lack of automation in the frameworks using this methodology,which affect the discovery rate of novel materials with ad-hoc properties.Here,the Automatic Anharmonic Phonon Library(AAPL)is presented.It efficiently computes interatomic force constants by making effective use of crystal symmetry analysis,it solves the Boltzmann transport equation to obtain κ_(l),and allows a fully integrated operation with minimum user intervention,a rational addition to the current high-throughput accelerated materials development framework AFLOW.An“experiment vs.theory”study of the approach is shown,comparing accuracy and speed with respect to other available packages,and for materials characterized by strong electron localization and correlation.Combining AAPL with the pseudo-hybrid functional ACBN0 is possible to improve accuracy without increasing computational requirements.
基金supported by the Office of Science of the U.S.Department of Energy under Contract No.DEAC02-05CH11231.
文摘We present a combination of machine learning and high throughput calculations to predict the points defects behavior in binary intermetallic(A–B)compounds,using as an example systems with the cubic B2 crystal structure(with equiatomic AB stoichiometry).To the best of our knowledge,this work is the first application of machine learning-models for point defect properties.High throughput first principles density functional calculations have been employed to compute intrinsic point defect energies in 100 B2 intermetallic compounds.The systems are classified into two groups:(i)those for which the intrinsic defects are antisites for both A and B rich compositions,and(ii)those for which vacancies are the dominant defect for either or both composition ranges.The data was analyzed by machine learning-techniques using decision tree,and full and reduced multiple additive regression tree(MART)models.Among these three schemes,a reduced MART(r-MART)model using six descriptors(formation energy,minimum and difference of electron densities at the Wigner–Seitz cell boundary,atomic radius difference,maximal atomic number and maximal electronegativity)presents the highest fit(98%)and predictive(75%)accuracy.This model is used to predict the defect behavior of other B2 compounds,and it is found that 45%of the compounds considered feature vacancies as dominant defects for either A or B rich compositions(or both).The ability to predict dominant defect types is important for the modeling of thermodynamic and kinetic properties of intermetallic compounds,and the present results illustrate how this information can be derived using modern tools combining high throughput calculations and data analytics.
基金This work was supported by the U.S.Department of Energy,Office of Science,Basic Energy Sciences(BES),by Award no.DE-SC0016164 for NW and LL,and through the BES Materials Sciences and Engineering Division for JD,MA,and ROR under Contract No.DE-AC02-05CH11231 to the Mechanical Behavior of Materials Program(KC13)at Lawrence Berkeley National Laboratory(LBNL)The study made use of the resources of the National Energy Research Scientific Computing Center at LBNL,which is also supported by the Office of Basic Energy Sciences of the U.S.Department of Energy under Contract No.DE-AC02-05CH11231.
文摘Metallic glasses(MGs)possess remarkably high strength but often display only minimal tensile ductility due to the formation of catastrophic shear bands.Purposely enhancing the inherent heterogeneity to promote distributed flow offers new possibilities in improving the ductility of monolithic MGs.Here,we report the effect of the spatial heterogeneity of elasticity,resulting from the inherently inhomogeneous amorphous structures,on the deformation behavior of MGs,specifically focusing on the ductility using multiscale modeling methods.A highly heterogeneous,Gaussian-type shear modulus distribution at the nanoscale is revealed by atomistic simulations in Cu_(64)Zr_(36) MGs,in which the soft population of the distribution exhibits a marked propensity to undergo the inelastic shear transformation.By employing a mesoscale shear transformation zone dynamics model,we find that the organization of such nanometer-scale shear transformation events into shear-band patterns is dependent on the spatial heterogeneity of the local shear moduli.A critical spatial correlation length of elastic heterogeneity is identified for the simulated MGs to achieve the best tensile ductility,which is associated with a transition of shear-band formation mechanisms,from stress-dictated nucleation and growth to structure-dictated strain percolation,as well as a saturation of elastically soft sites participating in the plastic flow.This discovery is important for the fundamental understanding of the role of spatial heterogeneity in influencing the deformation behavior of MGs.We believe that this can facilitate the design and development of new ductile monolithic MGs by a process of tuning the inherent heterogeneity to achieve enhanced ductility in these high-strength metallic alloys.
基金This work is partly performed under the auspices of the U.S.Department of Energy(DOE)by the Lawrence Livermore National Laboratory(LLNL)under Contract No.DE-AC52-07NA27344The authors are grateful for project funding from the High-Performance Computing for Materials(HPC4Mtls)Program of the DOE Vehicle Technologies Office under Cooperative Research and Development Agreement(CRADA)No.TC02309+2 种基金Computing support for this work comes from the LLNL Institutional Computing facilities,and the National Energy Research Scientific Computing Center(NERSC),a DOE Office of Science User Facility operated under Contract No.DE-AC02-05-CH11231E.C.acknowledges a fellowship through the National Science Foundation Graduate Research Fellowship Program under Grant No.DGE-1752814M.A.acknowledges support for his contributions by the U.S.Department of Energy,Office of Science,Office of Basic Energy Sciences,Materials Sciences and Engineering Division,under Contract No.DE-AC02-05-CH11231 within the Materials Project program(KC23MP).All figures are produced using matplotlib79.
文摘Antiphase boundaries(APBs)are planar defects that play a critical role in strengthening Ni-based superalloys,and their sensitivity to alloy composition offers a flexible tuning parameter for alloy design.Here,we report a computational workflow to enable the development of sufficient data to train machine-learning(ML)models to automate the study of the effect of composition on the(111)APB energy in Ni_(3)Al-based alloys.We employ ML to leverage this wealth of data and identify several physical properties that are used to build predictive models for the APB energy that achieve a cross-validation error of 0.033 J m^(−2).We demonstrate the transferability of these models by predicting APB energies in commercial superalloys.Moreover,our use of physically motivated features such as the ordering energy and stoichiometry-based features opens the way to using existing materials properties databases to guide superalloy design strategies to maximize the APB energy.
基金This project was supported by the U.S.Department of Energy(DOE),Office of Science,Office of Basic Energy Sciences(BES),Materials Sciences and Engineering Division under Contract No.DE-AC02-05-CH11231 within the in-situ TEM(KC22ZH)program.Work at the Molecular Foundry was supported by the Office of Science,Office of Basic Energy Sciences,of the U.S.Department of Energy under Contract No.DE-AC02-05CH11231.We acknowledge Gatan Inc.for the advanced K2 IS camera and Dr.Ming Pan and Dr.Cory Czarnik for their help with part of experimental set up in this work.W.J.Z.acknowledges the support from Tianjin University Graduate School International Academic Exchange Fund.M.R.H.was funded by KAUST project under H.M.Z.at UC Berkeley.
文摘The formation of complex hierarchical nanostructures has attracted a lot of attention from both the fundamental science and potential applications point of view.Spherulite structures with radial fibrillar branches have been found in various solids;however,their growth mechanisms remain poorly understood.Here,we report real time imaging of the formation of two-dimensional(2D)iron oxide spherulite nanostructures in a liquid cell using transmission electron microscopy(TEM).By tracking the growth trajectories,we show the characteristics of the reaction front and growth kinetics.Our observations reveal that the tip of a growing branch splits as the width exceeds certain sizes(5.5–8.5 nm).The radius of a spherulite nanostructure increases linearly with time at the early stage,transitioning to nonlinear growth at the later stage.Furthermore,a thin layer of solid is accumulated at the tip and nanoparticles from secondary nucleation also appear at the growing front which later develop into fibrillar branches.The spherulite nanostructure is polycrystalline with the co-existence of ferrihydrite and Fe3O4 through-out the growth.A growth model is further established,which provides rational explanations on the linear growth at the early stage and the nonlinearity at the later stage of growth.
基金This reanch wa suppomad by Nadional Science Foundadon undar gant DM 1839039by Office of Nival Rsearch under grans N0001416-1-3124,N0001417-12202,and N0001420-1-2225+1 种基金by Biown University though the use of the facillties at its Center for Computation and Wsualkatan.This work uses the Exaeme Science and Enginering Discoray Eninonment(XSEDE),which is supported by Natiional Science Faundation grant number ACI-1548562via tha nesaurce Stampade2 at the Texas Adhancad Campuing Cenaar(TACC)thraugh allocation DMRD50013N。
文摘While rhenium is an ideal material for rapid thermal cycling applications under high temperatures,such as rocket engine nozzles,its high cost limits its widespread use and prompts an exploration of viable cost-effective substitutes.In prior work,we identified a promising pool of candidate substitute alloys consisting of Mo,Ru,Ta,and W.In this work we demonstrate,based on density functional theory melting temperature calculations,that one of the candidates,Mo_(0.292)Ru_(0.555)Ta_(0.031)W_(0.122),exhibits a high melting temperature(around 2626 K),thus supporting its use in high-temperature applications.
基金M.A.was supported by the U.S.Department of Energy,Office of Science,Office of Basic Energy Sciences,Materials Sciences and Engineering Division under Contract No.DE-AC02-05-CH11231(Mechanical Behavior of Materials Program(KC13)This work was performed under the auspices of the US Department of Energy by Lawrence Livermore National Laboratory under contract W-7405-Eng-48.
文摘Quantum motion of atoms known as zero-point vibration was recently proposed to explain a long-standing discrepancy between theoretically computed and experimentally measured low-temperature plastic strength of iron and possibly other metals with high atomic masses.This finding challenges the traditional notion that quantum motion of atoms is relatively unimportant in solids comprised of heavy atoms.Here we report quantum dynamic simulations of quantum effects on dislocation motion within the exact formalism of Ring-Polymer Molecular Dynamics(RPMD).To extend the reach of quantum atomistic simulations to length and time scales relevant for extended defects in materials,we implemented RPMD in the open-source code LAMMPS thus making the RPMD method widely available to the community.We use our RPMD/LAMMPS approach for direct calculations of dislocation mobility and its effects on the yield strength ofα-iron.Our simulation results establish that quantum effects are noticeable at temperatures below 50 K but account for only a modest(≈13% at T=0 K)overall reduction in the Peierls barrier,at variance with the factor of two reduction predicted earlier based on the more approximate framework of harmonic transition state theory.Our results confirm that zero-point vibrations provide ample additional agitation for atomic motion that increases with decreasing temperature,however its enhancing effect on dislocation mobility is largely offset by an increase in the effective atom size,an effect known as quantum dispersion that has not been accounted for in the previous calculations.
基金This research used resources of the National Energy Research Scientific Computing Center,a DOE Office of Science User Facility supported by the Office of Science of the U.S.Department of Energy under Contract No.DE-AC02-05CH11231 using NERSC awards BES-ERCAP0020694 and BES-ERCAP0023528.
文摘A multi-phase field model is employed to study the microstructural evolution of an alloy undergoing liquid dealloying,specifically considering the role of grain boundaries.A semi-implicit time-stepping algorithm using spectral methods is implemented,which enables simulating large 2D and 3D domains over long time scales while still maintaining a realistic interfacial thickness.Simulations reveal a mechanism of coupled grain–boundary migration to maintain equilibrium contact angles with the topologically complex solid–liquid interface,which locally accelerates diffusion-coupled growth of a liquid channel into the precursor.This mechanism asymmetrically disrupts the ligament connectivity of the dealloyed structure in qualitative agreement with published experimental observations.The grain boundary migration-assisted corrosion channels form even for precursors with small amounts of the dissolving alloy species,below the parting limit.The activation of this grain boundary dealloying mechanism depends strongly on grain boundary mobility.
基金F.W.was supported by the U.S.Department of Defense through the National Defense Science and Engineering Graduate Fellowship ProgramM.A.and L.-W.W.were supported by the U.S.Department of Energy,Office of Science,Office of Basic Energy Sciences,Materials Sciences and Engineering Division,under Contract No.DE-AC02-05-CH11231(Materials Project program KC23MP and Non-Equilibrium Magnetic Materials program MSMAG,respectively)Computational resources were provided by award BES-ERCAP0021088 of the National Energy Research Scientific Computing Center(NERSC),a U.S.Department of Energy Office of Science User Facility at Lawrence Berkeley National Laboratory,operated under the same contract.
文摘Classical Monte Carlo simulation of the Heisenberg model poorly describes many thermodynamic phenomena due to its neglect of the quantum nature of spins.Alternatively,we discuss how to semiclassically approach the quantum problem and demonstrate a simple method for introducing a locally approximate form of spin quantization.While the procedure underestimates magnetic short-range order,our results suggest a simple correction for recovering realistic spin–spin correlations above the critical temperature.Moreover,ensemble fluctuations are found to provide reasonably accurate thermodynamics,largely reproducing quantum mechanically calculated heat capacities and experimental magnetometry for ferromagnetic Fe and antiferromagnetic RbMnF3.Extensions of the method are proposed to address remaining inaccuracies.
