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  《npj 计算材料学》是在线出版、完全开放获取的国际学术期刊。发表结合计算模拟与设计的材料学一流的研究成果。本刊由中国科学院上海硅酸盐研究所与英国自然出版集团(Nature Publishing Group,NPG)以伙伴关系合作出版。
  主编为陈龙庆博士,美国宾州大学材料科学与工程系、工程科学与力学系、数学系的杰出教授。
  共同主编为陈立东研究员,中国科学院上海硅酸盐研究所研究员高性能陶瓷与超微结构国家重点实验室主任。
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The origin of uniaxial negative thermal expansion in layered perovskites(层状钙钛矿中单轴负热膨胀的起源) 
Chris AblittSarah CraddockMark S. SennArash A. Mostofi & Nicholas C. Bristowe
npj Computational Materials 3:44 (2017)
doi:10.1038/s41524-017-0040-0
Published online:16 October 2017
Abstract| Full Text | PDF OPEN

摘要:为什么ABO3钙钛矿在宽温度范围内通常不会呈现负热膨胀(NTE),而同一化学家族的层状钙钛矿却常常会发生?通常认为有两个关键因素决定了NTE的程度:1)存在驱动收缩的软声子模式(具有负的Grüneisen参数)和2)各向异性弹性柔量使材料易于沿着特定轴线作NTE所需的变形。考虑到ABO3和层状钙钛矿在其高对称相中通常具有等量的组分,热膨胀性能如此不同令人惊奇。采用第一原理计算和对称性分析,本研究显示,在分层钙钛矿中,八面体氧的分层和压缩旋转两个效应的组合,导致由对称破裂而引起的弹性各向异性显著增强。这一特征只存在于具有某种对称性的层状钙钛矿,它可以使层状钙钛矿在大的温度范围内保持单轴NTE。这一重要研究结果提示,对称性和弹性张量可以作为描述因子进行高通量筛选和引导材料设计。   

Abstract:Why is it that ABO3 perovskites generally do not exhibit negative thermal expansion (NTE) over a wide temperature range, whereas layered perovskites of the same chemical family often do? It is generally accepted that there are two key ingredients that determine the extent of NTE: the presence of soft phonon modes that drive contraction (have negative Grüneisen parameters); and anisotropic elastic compliance that predisposes the material to the deformations required for NTE along a specific axis. This difference in thermal expansion properties is surprising since both ABO3 and layered perovskites often possess these ingredients in equal measure in their high-symmetry phases. Using first principles calculations and symmetry analysis, we show that in layered perovskites there is a significant enhancement of elastic anisotropy due to symmetry breaking that results from the combined effect of layering and condensed rotations of oxygen octahedra. This feature, unique to layered perovskites of certain symmetry, is what allows uniaxial NTE to persist over a large temperature range. This fundamental insight means that symmetry and the elastic tensor can be used as descriptors in high-throughput screening and to direct materials design. 

Editorial Summary

Negative thermal expansion: symmetry controls the behavior of perovskites(负热膨胀:对称性控制着钙钛矿的行为) 

对称破裂是层状钙钛矿单轴负热膨胀(NTE)的主要原因。来自英国帝国理工学院、华威大学和肯特大学的研究人员发现,是原子因素导致具有ABO3通式的钙钛矿氧化物材料,表现出与它们的层状对称物(称为Ruddlesden-Popper氧化物)极为不同的热膨胀性能。研究人员采用第一原理计算发现,层状钙钛矿中某些结构构型可能偏离完全对称的位置,而普通钙钛矿中结构构型被固定得更为牢固。层状钙钛矿中普遍存在的这种特征,允许单轴负热膨胀,即在很宽的温度范围内,随着温度升高,材料的收缩得以持续。这一基础的成果将有助于新型NTE材料的高通量筛选,并指引着未来的材料设计。

Symmetry breaking is a major cause of uniaxial negative thermal expansion (NTE) in layered perovskites. Researchers at Imperial College, the University of Warwick and the University of Kent have discovered the atomic factors causing perovskite oxides, materials with the general formula ABO3, to show very different thermal expansion properties from their layered counterparts, known as Ruddlesden-Popper oxides. Using first-principles calculations, the researchers found that in layered perovskites certain structural motifs can deviate from a perfectly symmetric arrangement, whereas in regular perovskites they are more firmly fixed. This feature, prevalent in layered perovskites, is what allows uniaxial negative thermal expansion, i.e., the contraction of the material with increased temperature, to persist over a large temperature range. This fundamental insight could aid high-throughput screening for new NTE materials and help direct future materials design.

 

Ferroic glasses (铁素玻璃)) 
Yuanchao Ji,Dong WangYu WangYumei ZhouDezhen XueKazuhiro OtsukaYunzhi Wang &Xiaobing Ren
npj Computational Materials 3:43 (2017)
doi:10.1038/s41524-017-0039-6
Published online:12 October 2017
Abstract| Full Text | PDF OPEN

摘要:铁素玻璃(为应变玻璃、弛豫器和簇自旋玻璃的新总称)是处于冷冻无序状态的铁素体系,是长程有序铁素态的共轭态——铁素体。铁素玻璃显示出铁素体中所没有的一些非凡性质,如,在宽泛温度范围内出现的细电滞回线和性能渐进变化。除了铁素玻璃和铁素体之外,还存在第三种铁素态,即玻璃-铁素体(铁素玻璃和铁素体的复合物),由铁素玻璃的结晶转变而制造,拥有铁素玻璃和铁素体均没有的优越性能。温度-缺陷-浓度通用相图显示,这三类铁素材料(铁素体、铁素玻璃和玻璃-铁素体)对应于三种转变(分别为铁素相变、铁素玻璃转变和铁素玻璃结晶转变)。此外,通过构建相位场模型可再现三个转变的微结构演化和相图,揭示了点缺陷在形成铁素玻璃和玻璃-铁素体中的重要作用。这种相图可用来设计有非凡特性的各种铁素玻璃和玻璃-铁素体。   

Abstract: Ferroic glasses (strain glass, relaxor and cluster spin glass) refer to frozen disordered states in ferroic systems; they are conjugate states to the long-range ordered ferroic states—the ferroic crystals. Ferroic glasses exhibit unusual properties that are absent in ferroic crystals, such as slim hysteresis and gradual property changes over a wide temperature range.In addition to ferroic glasses and ferroic crystals, a third ferroic state, a glass-ferroic (i.e., a composite of ferroic glass and ferroic crystal), can be produced by the crystallization transition of ferroic glasses.It can have a superior property not possessed by its two components.These three classes of ferroic materials (ferroic crystal, ferroic glass and glass-ferroic) correspond to three transitions (ferroic phase transition, ferroic glass transition and crystallization transition of ferroic glass, respectively), as demonstrated in a generic temperature vs. defect-concentration phase diagram.Moreover, through constructing a phase field model, the microstructure evolution of three transitions and the phase diagram can be reproduced, which reveals the important role of point defects in the formation of ferroic glass and glass-ferroic.The phase diagram can be used to design various ferroic glasses and glass-ferroics that may exhibit unusual properties. 

First-principles calculation of intrinsic defect chemistry and self-doping in PbTe(第一性原理计算PbTe的内在缺陷化学和自掺杂) 
Anuj GoyalPrashun GoraiEric S. Toberer & Vladan Stevanović
npj Computational Materials 3:42 (2017)
doi:10.1038/s41524-017-0047-6 
Published online:10 October 2017
Abstract| Full Text | PDF OPEN

摘要:半导体掺杂本质上受限于其内在缺陷化学。在许多热电材料中,由于强烈的自旋-轨道相互作用导致的窄带隙使固有缺陷化学和自掺杂的原子层次的精确预测变得充满挑战。本研究采用不同层级的理论来模拟PbTe中的点缺陷,将计算结果进行相互类比和对比,并与大量实验数据比对。结果发现,要精确地再现PbTe的固有缺陷化学和已知的自掺杂行为,就必须1)超越密度泛函理论的半局部GGA近似,2)包含自旋-轨道耦合,和3)利用多体GW理论来描述单个带边位置。包含自旋-轨道耦合的杂化HSE函数与G0W0带边偏移的组合,是唯一无需实验数据输入,既可以精确捕获PbTe中随着合成条件的变化导致的本征导电类型,又可以测定载流子浓度的方法。本研究结果再次确认了单个带边位置在缺陷计算中的关键作用,并展示在这些具有挑战的窄带隙材料中可以准确地预测掺杂能力。   

Abstract:Semiconductor dopability is inherently limited by intrinsic defect chemistry.In many thermoelectric materials, narrow band gaps due to strong spin–orbit interactions make accurate atomic level predictions of intrinsic defect chemistry and self-doping computationally challenging.Here we use different levels of theory to model point defects in PbTe, and compare and contrast the results against each other and a large body of experimental data. We find that to accurately reproduce the intrinsic defect chemistry and known self-doping behavior of PbTe, it is essential to (a) go beyond the semi-local GGA approximation to density functional theory, (b) include spin–orbit coupling, and (c) utilize many-body GW theory to describe the positions of individual band edges. The hybrid HSE functional with spin–orbit coupling included, in combination with the band edge shifts from G0W0 is the only approach that accurately captures both the intrinsic conductivity type of PbTe as function of synthesis conditions as well as the measured charge carrier concentrations, without the need for experimental inputs. Our results reaffirm the critical role of the position of individual band edges in defect calculations, and demonstrate that dopability can be accurately predicted in such challenging narrow band gap materials. 

Editorial Summary

Thermoelectrics: Atomic-level modeling(热电:原子层次上的建模)

PbTe中缺陷的精确建模,需要结合自旋-轨道耦合杂化函数和Green函数理论。热电材料(可将热转换为电能,反之亦然)的掺杂对此类材料的改进来说至关重要;然而,大多数建模方法在原子级别都以失败告终,特别当存在自旋-轨道耦合效应能改变能带位置时。在本研究中,Stevanovic等采用基于第一性原理的密度泛函理论,准确地再现了PbTe的电子结构。他们证实,能与实验结果一致、可为内在缺陷化学建模的唯一方法,是将自旋-轨道耦合的杂化函数(基于屏蔽的库仑势)与通过G0W0近似计算的带边偏移(计算描述扩展系统激发态属性的Green函数理论)相结合。这种层次的理解,对PbTe中掺杂的预测是非常必要的。

Accurate modeling of defects in PbTe lies on the combination of hybrid functionals with spin-orbit coupling and Green function theory. Dopability of thermoelectric materials (that can convert thermal into electrical energy and vice versa) is crucial for their improvement; however most modeling approaches fail on an atomic level, especially if spin-orbit coupling effects (that modify the band position) are present. In this work, Vladan Stevanovic and coauthors manage to accurately reproduce the electronic structure of PbTe with first-principles based density functional theory. They prove that the only approach that can model the intrinsic defect chemistry, in agreement with experimental results, is the combination of hybrid functionals (based on a screened Coulomb potential) with spin-orbit coupling and the band edge shifts calculated through the G0W0 approximation (which calculates the Green function theory that models excited-state properties of extended systems). Such level of understanding is necessary to predict the dopability of PbTe.

 

Chemically intuited, large-scale screening of MOFs by machine learning techniques (通过机器学习技术辅以化学直觉,作大规模金属-有机框架材料筛选) 
Giorgos BorboudakisTaxiarchis StergiannakosMaria FrysaliEmmanuel KlontzasIoannis Tsamardinos & George E. Froudakis
npj Computational Materials 3:40 (2017)
doi:10.1038/s41524-017-0045-8
Published online:02 October 2017
Abstract| Full Text | PDF OPEN

摘要:本研究报道一种新型计算方法,应用于机器学习技术,可对有储气性能的金属-有机框架材料(Metal–organic frameworks,MOFs)作大规模筛选。该方法结合化学结构导向,在第一原理方法的计算准确性和经典方法的计算速度之间作了平衡。结果表明,采用机器学习方法和自动化分析方案,MOF的化学性质确实是可预测的(随机而不是确定的),其预测准确性随着样本量的增加而增加。初步研究结果表明,这种方法不仅有望用于储气MOF,也有望用于其他涉及材料科学的诸多应用方面。   

Abstract: A novel computational methodology for large-scale screening of Metal–organic frameworks (MOFs) is applied to gas storage with the use of machine learning technologies. This approach is a promising trade-off between the accuracy of ab initio methods and the speed of classical approaches, strategically combined with chemical intuition.The results demonstrate that the chemical properties of MOFs are indeed predictable (stochastically, not deterministically) using machine learning methods and automated analysis protocols, with the accuracy of predictions increasing with sample size. Our initial results indicate that this methodology is promising to apply not only to gas storage in MOFs but in many other material science projects. 

Editorial Summary

Machine learning: Quickly screening materials for effective gas storage(机器学习:快速筛选有效储气材料) 

基于本研究结果,现在可以通过人工智能快速而准确地预测具有气体储存性能的金属-有机框架材料(MOF)。来自美国克里特大学的Froudakis开发了一种机器学习方法,以根据化学结构预测具有吸附H2/CO2性能的多孔MOF材料,有望应用于催化和气体储存。之前此类方法要么太慢,要么不够精确。本研究中,Froudakis等通过已知特性来训练该机器学习方法识别MOF中的某些结构特征,从而将“化学直觉”编入其算法中。然后,他们将该方法应用于新的MOF的大规模筛选,通过测试发现,所作的几个预测与实验数据相匹配。通过这种技术,有望更快地发现用于二氧化碳封存或氢气储存的新材料。

The gas storage properties of metal-organic frameworks can now be quickly and accurately predicted by artificial intelligence. George Froudakis at the University of Crete has developed a machine learning approach to predict the H2/CO2 adsorption properties of metal-organic frameworks (MOFs), highly porous materials promising for catalysis and gas storage, based on their chemical structure. Previous methods were either too slow, or not accurate enough.Here, Froudakis and his team encoded ‘chemical intuition’ into their algorithm by training it to recognize certain structural features in MOFs with known properties. Then, when they applied the method to large-scale screening tests of new MOFs they found their predictions matched with experimental data. With this technique, it is hoped that new materials for CO2 sequestration or hydrogen storage will be discovered more quickly.

 

Metallic and highly conducting two-dimensional atomic arrays of sulfur enabled by molybdenum disulfide nanotemplate (通过二硫化钼纳米模板激活而具有金属性和高导电率的二维硫原子排布) 
Shuze Zhu,Xiumei Geng,Yang Han,Mourad Benamara,Liao Chen,Jingxiao Li,Ismail Bilgin&Hongli Zhu
npj Computational Materials 3:41 (2017)
doi:10.1038/s41524-017-0041-z
Published online:05 October 2017
Abstract| Full Text | PDF OPEN

摘要:在自然界中,硫单质是一种绝缘体。研究发现,一维硫原子链呈现金属性和导电性,然而二维硫单质的电性能尚不清晰。本研究发现,二硫化钼层状结构可作为一类纳米模板来生长和形成二维硫单质。通过密度泛函理论的计算表明,处于二硫化钼层-层之间的硫原子由于受到空间的约束限制,可形成具有高度金属性的三角形平面结构。并且,这些平面结构激活了该杂合结构(由二硫化钼层和硫原子层构成)的高导电性和金属性。实验测得该杂合结构的电导率达到223 S / m。包括X射线光电子能谱(XPS)、透射电子显微镜(TEM)和选区电子衍射(SAED)等多项实验观测与计算结果一致。由于杂合结构的导电性能优异,在无导电添加剂的情况下,电流密度(小于30,000 mV/s)与扫描速率成线性相关。采用这种杂合结构作为电极,双电极超级电容器电池在离子液体电解质中的功率密度为106Wh/kg,能量密度达到47.5Wh/kg。本研究结果为采用二维材料及其范德华力异质结构作为纳米模板,来预测和设计外来原子的全新材料性质提供了新的方法。   

Abstract:Element sulfur in nature is an insulating solid. While it has been tested that one-dimensional sulfur chain is metallic and conducting, the investigation on two-dimensional sulfur remains elusive. We report that molybdenum disulfide layers are able to serve as the nanotemplate to facilitate the formation of two-dimensional sulfur. Density functional theory calculations suggest that confined in-between layers of molybdenum disulfide, sulfur atoms are able to form two-dimensional triangular arrays that are highly metallic. As a result, these arrays contribute to the high conductivity and metallic phase of the hybrid structures of molybdenum disulfide layers and two-dimensional sulfur arrays. The experimentally measured conductivity of such hybrid structures reaches up to 223 S/m. Multiple experimental results, including X-ray photoelectron spectroscopy (XPS), transition electron microscope (TEM), selected area electron diffraction (SAED), agree with the computational insights. Due to the excellent conductivity, the current density is linearly proportional to the scan rate until 30,000 mV s−1without the attendance of conductive additives. Using such hybrid structures as electrode, the two-electrode supercapacitor cells yield a power density of 106 Wh  kg−1and energy density ~47.5 Wh kg−1 in ionic liquid electrolytes. Our findings offer new insights into using two-dimensional materials and their Van der Waals heterostructures as nanotemplates to pattern foreign atoms for unprecedented material properties. 

Editorial Summary

2D hybrids: alternating layers of MoS2and atomic sulfur(2D杂合:MoS2和硫单质的交替层状结构)

以二硫化钼(MoS2)层状结构作为纳米模板,可制备出二维元素硫。由美国东北大学朱红丽率领的团队采用密度泛函理论的计算发现,夹在MoS2层状结构之间的硫原子由于受到MoS2层与层之间的限制,可排列形成具有二维结构特征的三角形阵列。这些阵列具有金属性,因此有助于杂合结构(由MoS2层和二维硫层交替组成)出现金属相,表现出导电性。实验测得该杂合结构具有高达223 S/m的电导率。该方法可拓展到以纳米模板为依托,实现其它二维杂合材料的制备和设计。

Molybdenum disulfide (MoS2) layers can be used as templates for the formation of two-dimensional elemental sulfur. A team led by Hongli Zhu at Northeastern University used density functional theory calculations to show that the sulfur atoms sandwiched between MoS2 layers can arrange themselves into two-dimensional atomic layers, featuring a triangular array structure that results from the intrinsic triangular pattern of the parent sulfur atoms within MoS2. These arrays are metallic, and thus contribute to the metallic phase and associated conductivity of the resulting hybrid structure composed of alternating MoS2 layers and two-dimensional sulfur layers. The experimentally synthesized compounds show conductivity up to 223 S/m. This strategy may be used for engineering of two-dimensional material hybrids by means of nano-template patterns.

 

Voltage-driven charge-mediated fast 180 degree magnetization switching in nanoheterostructure at room temperature (室温下纳米异质结构的快速180度磁化切换:电压驱动、电荷介导)
Min YiHongbin Zhang & Bai-Xiang Xu
npj Computational Materials 3:38 (2017)
doi:10.1038/s41524-017-0043-x
Published online:22 September  2017
Abstract| Full Text | PDF OPEN

摘要:依赖电压而无需电流驱动的180°磁化切换为自旋电子学的革命提供了可能性。本研究通过第一性原理计算和有限温度下磁化动力学模拟相结合,模拟了室温下电压驱动的电荷介质180°磁化切换。发现电场(E)诱导的界面电荷可对纳米磁体的磁各向异性(K)有巨大的调制作用。特别地,K显示出相对于E和外延应变的线性变化。采用所获K的磁化动力学模拟表明,E脉冲可以实现平面和垂直方向180°的磁化切换。温度效应造成磁性180°切换很不稳定,其状态具有随机性。统计分析表明,通过控制E的大小和脉冲宽度,可以在室温下实现快速(约4 ns)和低误差率的180°切换。该研究为微型纳米级自旋电子器件的合理设计提供了启发,避免了热涨落对体系性能的较大影响。   

Abstract: Voltage-driven 180° magnetization switching without electric current provides the possibility for revolutionizing the spintronics. We demonstrated the voltage-driven charge-mediated 180° magnetization switching at room temperature by combining first-principles calculations and temperature-dependent magnetization dynamics simulation. The electric field (E)-induced interface charge is found to allow a giant modulation of the magnetic anisotropy (K) of the nanomagnet. Particularly K is revealed to vary linearly with respect toE and the epitaxial strain. Magnetization dynamics simulations using the so-obtained K show that both in-plane and perpendicular 180° switching can be achieved by E pulses. The temperature effect renders the 180° switching as probability events. Statistical analysis indicates a fast (around 4 ns) and low-error-probability 180° switching achievable at room temperature by controlling the magnitude of E and the pulse width. The study inspires the rational design of miniaturized nanoscale spintronic devices where thermal fluctuation has a great impact. 

Editorial Summary

Spintronics: simulations predict room temperature voltage-driven magnetization switching(自旋电子学:模拟预测室温电压驱动磁化切换)

计算模拟表明,电压诱导的界面电荷变化可导致Pt / FePt / MgO异质结在室温下的180°磁化切换。德国达姆施塔特技术大学的Min Yi、Hongbin Zhang和许旭祥,通过第一性原理计算和有限温度下磁化动力学模拟相结合,研究了横向尺寸为几十纳米的外延Pt / FePt / MgO异质结。发现电场在FePt / MgO界面处诱导电荷变化,并通过影响FePt层中的磁晶各向异性改变异质结的易磁化轴。通过调谐电场、外延应变和磁化动力学,在平面和垂直方向的平衡磁态下,可在室温下实现平面和垂直方向180°的磁化切换。这些结果为电压驱动磁性开关器件的设计提供了深入认识。

Simulations show that voltage-induced interfacial charge variation results in 180° magnetization switching at room temperature in a Pt/FePt/MgOheterostructure. Min Yi, Hongbin Zhang and Bai-Xiang Xu from TechnischeUniversität Darmstadt in Germany study an epitaxial Pt/FePt/MgOheterostructure with a lateral size of several tens of nanometers, by combining first-principles calculations and temperature-dependent magnetization dynamics simulations. The electric field induces charge variation at the FePt/MgO interface, which alters the magnetic easy axis of the heterostructure by affecting the magnetocrystalline anisotropy energy in the FePt layer. By tuning the electric field, epitaxial strain and magnetization dynamics, in-plane and perpendicular 180° magnetization switching is achievable at room temperature in the case of in-plane and perpendicular equilibrium magnetic state, respectively. These results provide insight into the design of voltage-driven magnetic switching devices.

Phonon broadening in high entropy alloys(高熵合金中的声子宽频化)
Fritz KörmannYuji IkedaBlazej Grabowski & Marcel H. F. Sluiter
npj Computational Materials 3:36 (2017)
doi:10.1038/s41524-017-0037-8
Published online:01 September  2017
Abstract| Full Text | PDF OPEN

摘要:耐火高熵合金具有突出的特性,有望成为下一代用于高温环境的材料。高温中,晶格振动(声子)将强烈影响材料的性质。声子对材料性能的影响主要体现在热力学稳定性、热力学函数、弹性性能和热导率。与完美晶体和有序合金相比,多组分无规合金(高熵合金)中固有的质量和力常数涨落可引起显著的声子散射和声子频率的宽化。尽管这一现象很重要,但迄今为止对高熵合金中的声子散射和声子宽频化还少有研究。本研究从理论的角度试图解决这个挑战,采用第一原理计算来系统地研究质量和力常数涨落对12个具有体心立方结构的随机合金的声子谱的影响。这些结构包含二元合金到五组分的高熵合金,并探讨合金化学组分的复杂性如何影响材料的晶格振动行为。研究发现,质量和力常数涨落对声子的影响都需考虑,缺一不可。若忽略其中任何一项,物理图像将出现明显错误,如声子带隙的错误估算。本研究分析了声子行为如何影响宏观热力学量,尤其是振动熵。随着合金中元素种类的增加,振动熵也相应变大,其变化可能与构型熵的变化一样大,并严重影响材料的相稳定性。本研究结果基于以下合金:MoTa、MoTaNb、MoTaNbW、MoTaNbWV、VW、VWNb、VWTa、VWNbTa、VTaNbTi、VWNbTaTi、HfZrNb和HfMoTaTiZr。   

Abstract: Refractory high entropy alloys feature outstanding properties making them a promising materials class for next-generation high-temperature applications. At high temperatures, materials properties are strongly affected by lattice vibrations (phonons). Phonons critically influence thermal stability, thermodynamic and elastic properties, as well as thermal conductivity. In contrast to perfect crystals and ordered alloys, the inherently present mass and force constant fluctuations in multi-component random alloys (high entropy alloys) can induce significant phonon scattering and broadening. Despite their importance, phonon scattering and broadening have so far only scarcely been investigated for high entropy alloys. We tackle this challenge from a theoretical perspective and employ ab initio calculations to systematically study the impact of force constant and mass fluctuations on the phonon spectral functions of 12 body-centered cubic random alloys, from binaries up to 5-component high entropy alloys, addressing the key question of how chemical complexity impacts phonons. We find that it is crucial to include both mass and force constant fluctuations. If one or the other is neglected, qualitatively wrong results can be obtained such as artificial phonon band gaps. We analyze how the results obtained for the phonons translate into thermodynamically integrated quantities, specifically the vibrational entropy. Changes in the vibrational entropy with increasing the number of elements can be as large as changes in the configurational entropy and are thus important for phase stability considerations. The set of studied alloys includes MoTa, MoTaNb, MoTaNbW, MoTaNbWV, VW, VWNb, VWTa, VWNbTa, VTaNbTi, VWNbTaTi, HfZrNb, HfMoTaTiZr. 

Editorial Summary

High entropy alloys: Theoretical perspectives on phonons(高熵合金:声子的理论研究)

与传统合金相比,高熵合金在单个“晶格”内具有五种甚至更多种元素的同数量原子,并表现出一些非凡的物理性质。所有这些性质都受晶格振动(即声子)的影响,彰显了构造声子激发和声子间相互作用模型的重要性。来自荷兰代尔夫特理工大学的FritzKörmann和来自日本京都大学的池田宇池博士等对12种不同的耐火合金进行了第一性原理的计算,以解决合金化学组分的复杂性如何影响材料的晶格振动行为。结果表明,原子质量和力常数二者都可影响声子频率,并且在元素较多的合金中,其振动熵的变化幅度与构型熵的相当。这项基于理论计算角度的声子宽频化研究为高温高熵合金的设计开辟了道路。

In contrast to conventional alloys, high entropy alloys possess five or more equiatomic elemental species within a single lattice, resulting in some extraordinary physical properties. All these properties are linked to the lattice vibrations, i.e. phonons, indicating the importance of modelling of phonon excitations and their interactions. A team led by Fritz Körmann at Netherlands’ Delft University of Technology and Yuji Ikeda at Kyoto University in Japan performed first-principles calculations on 12 different refractory alloys to address the key question of how the chemical complexity impacts phonons. Results show that both atomic mass and force constants contribute to the phonon energies, and changes in the vibrational entropy with more elements could be comparable to the configurational entropy. Research into the computationally designed phonon broadening may open an avenue towards tailored high temperature high entropy alloys.

Atomic-scale structural signature of dynamic heterogeneities in metallic liquids(金属液体中动态异质性的原子尺度结构特征) 
Alain Pasturel & Noel Jakse
npj Computational Materials 3:33 (2017)
doi:10.1038/s41524-017-0034-y
Published online:17 August 2017
Abstract| Full Text | PDF OPEN

摘要:液体如果具有足够高的冷却速度,将会越过其平衡熔融温度,并可在固化之前保持在亚稳、过冷状态。过冷液体的研究展示了几个有趣的动态现象,同时,由于液体结构和液体动力学之间存在明显的却又难以识别的联系,揭示与这些现象之间潜在的结构联系仍是一个重大挑战。第一性原理的从头算分子动力学(AIMD)模拟在原子尺度细节方面的描述是特别有效的方法,足以指导实验。基于把Cr加入Al基液体中的AIMD研究,我们首次证明:组分扩散的解耦与过冷状态下动态异质性之间存在紧密联系。此外,我们还证明了两种现象的起源都与结构异性(structural heterogeneity)相关,结构异性由化学短序列(CSRO)和局部五倍拓扑(ISRO)在液相短程之间的强相互作用引起,它在过冷时发展成以二十面体为主的中程序列(IMRO)。本研究结果表明,温度相关的金属-金属耦合分布函数中也观测到这种结构特征,从而为更详细的实验研究奠定了基础。   

Abstract: With sufficiently high cooling rates, liquids will cross their equilibrium melting temperatures and can be maintained in a metastable undercooled state before solidifying. Studies of undercooled liquids reveal several intriguing dynamic phenomena and because explicit connections between liquid structure and liquids dynamics are difficult to identify, it remains a major challenge to capture the underlying structural link to these phenomena. Ab initio molecular dynamics (AIMD) simulations are yet especially powerful in providing atomic-scale details otherwise not accessible in experiments. Through the AIMD-based study of Cr additions in Al-based liquids, we evidence for the first time a close relationship between the decoupling of component diffusion and the emergence of dynamic heterogeneities in the undercooling regime. In addition, we demonstrate that the origin of both phenomena is related to a structural heterogeneity caused by a strong interplay between chemical short-range order (CSRO) and local fivefold topology (ISRO) at the short-range scale in the liquid phase that develops into an icosahedral-based medium-range order (IMRO) upon undercooling. Finally, our findings reveal that this structural signature is also captured in the temperature dependence of partial pair-distribution functions which opens up the route to more elaborated experimental studies. 

Editorial Summary

Metallic liquids: Connection between liquid structure and liquid dynamics (金属液体:液体结构和液体动力学之间的连接) 

本研究基于计算模拟结果揭示了金属液体中原子尺度结构和动力学之间存在强烈联系。当液体材料快速冷却时,可避开结晶,形成亚稳态过冷状态。这样的系统表现出一系列有趣的动态现象,但是在实验上很难看到液体结构和液体动力学之间的相互作用。Grenoble Alpes大学的Alain Pasturel和Noel Jakse使用从头算分子动力学模拟表明,铬掺杂的铝基液体中,铬扩散与铝扩散有很强的去耦。这与动态异质性的出现密切相关,因为这两种效应都具有结构性的起源。他们的研究找到了液体结构和液体动力学之间的密切关系,并可能引起更进一步的实验研究。

Simulations show a strong connection between the atomic-scale structure and dynamics in metallic liquids. When a material is cooled rapidly it can avoid crystallization, forming a metastable undercooled state. Such systems exhibit a range of interesting dynamic phenomena but it is experimentally difficult to look at the interplay between the liquid structure and liquid dynamics. Using ab initio molecular dynamic simulations, Alain Pasturel and Noel Jakse from the University Grenoble Alpes show that in chromium-doped aluminum-based liquids there is a strong decoupling of the chromium diffusions from the aluminum diffusion. This is closely related to the emergence of dynamic heterogeneities, as both effects have a structural origin. These insights provide a close connection between structure and liquid dynamics and could lead to more elaborate experimental studies.

 

Construction of ground-state preserving sparse lattice models for predictive materials simulations(构建能保持基态稀有晶格的模型以预测模拟材料) 
Wenxuan HuangAlexander UrbanZiqin RongZhiwei DingChuan Luo & Gerbrand Ceder
npj Computational Materials 3:30 (2017)
doi:10.1038/s41524-017-0032-0
Published online:07 August 2017
Abstract| Full Text | PDF OPEN

摘要:基于第一原理的集群扩展模型是根据从头算热力学理论研究晶体混合的主要方法,可以预测相图和基态。然而,尽管近来取得了一些进展,由于默认参数会导致各种各样的问题,仍需要耗时费力地手动调整参数才能保证构建模型的准确性。本研究提出了一种系统的、数学上可靠的方法,确保基态与参考数据一致的簇扩展模型。基于新开发的压缩感知途径方法,我们建立了集群扩展模型,并采用二次规划对模型参数加以约束。对于锂离子电池阴极有关的两种锂过渡金属氧化物(Li2xFe2(1-x)O2和Li2xTi2(1-x)O2),我们构建了极具挑战的、带有压缩感知能力的簇扩展模型,证明了本方法的强大实用性。研究证明,我们的方法不仅保证了为模型构建而使用的参考结构集的基态准确,而且通过快速收敛迭代保证了样本之外尺寸较大的超胞基态准确。本法提供了一种通用工具,可用来构建强实用的、压缩的、受约束的、有预测功能的物理模型。   

Abstract: First-principles based cluster expansion models are the dominant approach inab initiothermodynamics of crystalline mixtures enabling the prediction of phase diagrams and novel ground states. However, despite recent advances, the construction of accurate models still requires a careful and time-consuming manual parameter tuning process for ground-state preservation, since this property is not guaranteed by default. In this paper, we present a systematic and mathematically sound method to obtain cluster expansion models that are guaranteed to preserve the ground states of their reference data. The method builds on the recently introduced compressive sensing paradigm for cluster expansion and employs quadratic programming to impose constraints on the model parameters. The robustness of our methodology is illustrated for two lithium transition metal oxides with relevance for Li-ion battery cathodes, i.e., Li2x Fe2(1−x)O2 and Li2xTi2(1−x)O2, for which the construction of cluster expansion models with compressive sensing alone has proven to be challenging. We demonstrate that our method not only guarantees ground-state preservation on the set of reference structures used for the model construction, but also show that out-of-sample ground-state preservation up to relatively large supercell size is achievable through a rapidly converging iterative refinement. This method provides a general tool for building robust, compressed and constrained physical models with predictive power.

Editorial Summary

Materials simulations: Constructing models guaranteed to preserve the ground states(材料模拟:构建能确保维持基态的模型) 

该研究开发了用于材料模拟、不需手动调整输入参数的方法。第一原理密度泛函理论计算是计算材料学研究中最常用的一种工具,但难于应用到含数千个原子的大型结构模拟。这样的系统通常使用集群扩展模型来模拟,但存在一个问题:需要手动调整参数以保持基态——这个调整很重要,因这一调整通常决定了材料的属性。现在来自美国麻省理工学院、加州大学伯克利分校和劳伦斯伯克利国家实验室的Gerbrand Ceder教授(美国2017年新科工程院院士)领导的国际研究团队,提出了构建集群扩展模型的方法,可以保证基态准确而无需手动调整参数。

A method has been developed for performing materials simulations without needing to perform manual parameter tuning for the ground-state. First-principles density functional theory calculations are one of the most commonly used tools for computational materials science research but they cannot easily be applied to large structures that contain many thousands of atoms.In such systems, cluster expansion models are often used but they have a problem: manual parameter tuning is required to preserve the ground-state --- important as this usually governs the materials properties. An international team of researchers led by Gerbrand Ceder from Massachusetts Institute of Technology, the University of California Berkeley and Lawrence Berkeley National Laboratory now present a procedure for constructing cluster expansion models that can preserve the ground states without any need for tuning.

 

Hydrogen embrittlement of grain boundaries in nickel: an atomistic study (镍晶界的氢脆化:原子水平上的研究)
Shan Huang, Dengke ChenJun SongDavid L. McDowell & Ting Zhu
npj Computational Materials 3:28 (2017)
doi:10.1038/s41524-017-0031-1
Published online:14 July 2017
Abstract| Full Text | PDF OPEN

摘要:氢对金属的化学力学性能的削弱作用已有大量观察,但其原子尺度上的作用机理尚不清楚。本研究从原子水平上探讨了氢对镍晶界的脆化作用。通过将晶界划分为由原子组成的多面体堆积单元,可以确定出给定任意晶界的所有可能的氢间隙位点。计算得到各个间隙位点氢的偏聚能并代入Rice-Wang界面脆化热力学理论模型中。通过计算氢偏聚晶界的分离功的变化可以定量评估氢脆化效果。我们研究了快速和慢速分离极限,他们分别对应固定氢浓度和氢化学势条件下的晶界断裂。据此我们还进一步分析了局部电子密度对于氢吸附能的影响,从而揭示了晶界氢脆化的物理极限。   

Abstract: The chemomechanical degradation of metals by hydrogen is widely observed, but not clearly understood at the atomic scale. Here we report an atomistic study of hydrogen embrittlement of grain boundaries in nickel. All the possible interstitial hydrogen sites at a given grain boundary are identified by a powerful geometrical approach of division of grain boundary via polyhedral packing units of atoms.Hydrogen segregation energies are calculated at these interstitial sites to feed into the Rice–Wang thermodynamic theory of interfacial embrittlement. The hydrogen embrittlement effects are quantitatively evaluated in terms of the reduction of work of separation for hydrogen-segregated grain boundaries. We study both the fast and slow separation limits corresponding to grain boundary fracture at fixed hydrogen concentration and fixed hydrogen chemical potential, respectively.We further analyze the influences of local electron densities on hydrogen adsorption energies, thereby gaining insights into the physical limits of hydrogen embrittlement of grain boundaries. 

Editorial Summary

Metals: hydrogen probe divides nickel into grains(金属:氢使镍裂解为晶粒) 

确定金属晶界处所有氢吸附位点,使金属材料失效的定量预测成为可能。由佐治亚理工学院的Ting Zhu领导的国际研究团队发展了一种方法,将氢原子嵌入金属镍晶格中并按照几何结构特征将金属镍划分成由原子组成多面体堆积单元,由此得到了所有可能的氢的吸附位点。通过对被氢吸附的晶界原子水平模拟,发现氢通过电子效应与镍结合并在较高温度下恶化、破坏晶界。晶界强度降低不仅取决于氢嵌入镍中的位置,也取决于晶界处的氢浓度。建立用于量化氢吸附造成金属失效的计算模拟框架将有助于减轻含氢压力容器和管道的失效。

Identifying all hydrogen absorption sites at metallic grain boundaries allows for a quantitative prediction of metal failure. An international team of researchers led by Ting Zhu at Georgia Institute of Technology developed a method to geometrically divide nickel metal into polyhedral packing units of atoms by embedding hydrogen atoms into the nickel atomic lattice. By using atomistic simulations to examine the boundaries through these atomic packing units, they showed that hydrogen binds to nickel via an electronic effect and that grain boundary failure due to hydrogen worsens at higher temperatures. Reducing grain boundary strength therefore depended on the location of hydrogen embedded in nickel as well as hydrogen concentration at the grain boundaries. Establishing a framework to quantify metal failure due to hydrogen absorption may help up mitigate failure in hydrogen-containing pressurized vessels and pipelines.

 
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