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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。本刊由伟德1946_伟德国际_伟德国际平台与英国自然出版集团(Nature Publishing Group,NPG)以伙伴关系合作出版。
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Strong hopping induced Dzyaloshinskii–Moriya interaction and skyrmions in elemental cobalt
Hu-Bin Luo, Hong-Bin Zhang and J. Ping Liu 
npj Computational Materials 5:50 (2019)
doi:https://www.nature.com/articles/s41524-019-0187-y
Published online:18 April 2019
Abstract| Full Text | PDF OPEN

摘要:Dzyaloshinskii–Moriya相互作用(DMI)是一种磁交换相互作用,它的存在会使磁矩在空间排列上按一定手性旋转。这种手性特点正是形成磁性斯格明子的必要物理条件。磁性材料中的DMI由电子自旋轨道耦合与晶体中心反演对称缺失共同导致。现如今发现的具有非中心对称的斯格明子材料中均含有非磁元素。本工作发现,具有β-Mn型亚稳结构的纯钴中可以产生很强的DMI。不同近邻原子间的DMI差异很大,其强弱变化与电子跃迁强弱变化具有直接的对应关系。p轨道在电子跃迁中扮演着重要的角色。虽然不同近邻原子对的DMI由于方向不同在一定程度相互抵消,但其净效应足以让该材料产生具有左手手性的布洛赫型磁螺旋结构。自旋动力学模拟结果表明0 K下使磁螺旋结构转变为稳定斯格明子的临界磁场为2.9 T   

Abstract:The Dzyaloshinskii–Moriya interaction (DMI) is well known to favor a chiral rotation of the magnetic moments, which accounts for the emergence of the skyrmions. The DMI is a combined effect of spin–orbit coupling with broken inversion symmetry in magnets. Most of the noncentrosymmetric magnetic materials that bear skyrmions involve nonmagnetic elements. This work shows that strong DMIs exist in elemental cobalt with a β-Mn-type metastable structure. The variation of DMI among different cobalt pairs largely follows the variation of hopping magnitude in which p electrons play an important role. Although the DMIs between different atomic pairs partly cancel with each other, the net interaction is suffcient to result in a left-handed Bloch-type spiral. Spin dynamics simulation shows that a critical magnetic field of 2.9 T stabilizes skyrmions at 0 K . 

Editorial Summary

Skyrmionic Materials: Toward Higher Temperature

寻找高应用温区的斯格明子材料非常重要。本研究通过理论计算发现一种纯钴低对称相中的磁相互作用既满足高居里温度条件,同时还存在强DMI。这种材料可通过施加较低的外场产生斯格明子,具有良好的应用前景。来自伟德国际平台宁波材料技术与工程研究所刘平研究员团队的罗湖斌博士与德国达姆斯塔特工业大学的张洪彬博士合作,通过第一原理计算发现β-Mn型钴单质具有超过1000 K的居里温度,而且,即使不存在可提供强自旋轨道耦合的重金属元素,其中两种钴近邻原子对间仍能产生强DMI。分析发现强DMI的产生与这些原子间的电子跃迁显著强于其它近邻原子对的现象密切相关,且p轨道在电子跃迁中扮演了重要角色。能量计算表明其基态磁结构为布洛赫型的磁螺旋。基于计算获得的磁参数,自旋动力学模拟表明外加2.9 T的磁场可以让磁螺旋转变为斯格明子态。这些结果为开发高应用温区的斯格明子材料提供了重要理论参考

Looking for skyrmionic materials with high Curie temperature is thus a cutting-edge area in this field. This study predicts theoretically that a low-symmetry cobalt phase possesses magnetic interactions that produces a Curie temperature higher than 1000 K with meanwhile strong DMI in two of the inequivalent nearest-neighbored Co pairs. The relatively low magnetic field required to fully stabilize skyrmions indicates that this material is promising in skyrmionics applications. This work was reported by Dr. Hubin Luo in Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, in collaboration with Dr. Hongbin Zhang in TU-Darmstadt, Germany. They found that the emergence of strong DMIs in certain Co pairs is closely related to the significant electronic hopping between them mediated by the p orbitals, even though there is no heavy metal to provide strong spin-orbit coupling. The energy calculation showed that left-handed spirals are the ground states. Based on the calculated magnetic interactions, spin dynamics simulation showed that a critical magnetic field of 2.9 T is enough to transform the spirals to skyrmions. This finding paves a way to high-temperature applications for skyrmionic materials.

Spin coherence in two-dimensional materials (二维材料中的自旋相干性)
Meng YeHosung Seo & Giulia Galli 
npj Computational Materials 5:44 (2019)
doi:s41524-019-0182-3
Published online:09 April 2019
Abstract| Full Text | PDF OPEN

摘要:半导体固体中的自旋缺陷是实现量子比特的理想平台。在低温强磁场条件下,中心自旋退相干主要是由核自旋翻转跃迁时带来的磁场涨落引起的。利用自旋哈密顿量和团簇展开方法,我们研究了二维(2D)材料中缺陷的电子自旋相干性,其中包括δ掺杂层状金刚石、薄膜硅、MoS2h-BN。我们证明了同位素纯化在二维材料中比在三维材料中要有效得多,这使得在同位素纯二硫化钼单层中,自旋相干时间异常长,超过了30毫秒   

Abstract:Spin defects in semiconducting solids are promising platforms for the realization of quantum bits. At low temperature and in the presence of a large magnetic field, the central spin decoherence is mainly due to the fluctuating magnetic field induced by nuclear spin flip-flop transitions. Using spin Hamiltonians and a cluster expansion method, we investigate the electron spin coherence of defects in two-dimensional (2D) materials, including delta-doped diamond layers, thin Si films, MoS2, and h-BN. We show that isotopic purification is much more effective in 2D than in three-dimensional materials, leading to an exceptionally long spin coherence time of more than 30ms in an isotopically pure monolayer of MoS2. 

Editorial Summary

Spin coherence: a special property in 2D materials(自旋相干: 2D材料的一种特殊性能

本研究探讨了二维(2D)材料中自旋量子比特的相干性,并提出了寻找理想骨架材料的策略。来自美国芝加哥大学和阿贡国家实验室的Giulia Galli教授等通过模拟揭示了材料的维度和晶体几何在控制固体中自旋量子比特退相干方面的作用,其重要性不亚于核自旋浓度。该研究的一个重要结果是,同位素纯化在二维环境中比在SiC等传统三维材料中要有效得多。他们还证明,在二维材料中,在不牺牲核自旋的情况下,可在具有多核自旋环境的固体中设计出较长的自旋相干时间。此外,他们还发展了一套定量方法,用以研究高核自旋浴(I > 1/2)对缺陷自旋量子比特的自旋相干时间(T2)的影响。他们确定了多个物理参数在控制量子比特退相干中的作用;这种定量研究对于寻找有前景的自旋量子比特骨架材料至关重要。总的来说,他们预测单层MoS2δ掺杂层状金刚石和薄膜硅可以作为自旋量子比特的骨架材料。然而对于h-BN,由于硼原子核具有较大的旋磁比,其T2的优化较为困难。本研究预测经同位素纯化的MoS2层的T2约为30 ms

Coherence of spin qubits in 2D materials was studied and strategies to search for ideal host materials was proposed. A Team led by Prof. Giulia Galli from the University of Chicago, and Argonne National Laboratory, Lemont, USA, revealed the role of dimensionality and crystal geometry in controlling the decoherence of spin qubits in solids by using simulations, which is as important as nuclear spin concentration. A key result of their study is that isotopic purification is much more effective in 2D than in conventional 3D materials such as Si and C. They also demonstrated that in 2D, long spin-coherence times may be engineered in solids with multi-nuclear-spin environments, without sacrificing nuclear spins. In addition, this study provided a quantitative understanding of the influence of high nuclear spin baths (I>1/2) on the spin coherence time T2 of a defect-based spin qubit. They identified the role of multiple physical parameters in controlling the qubit decoherence; such identification is critical in searching for promising host materials for spin qubits. Overall, they predicted that single-layer MoS2 layers, delta-doped diamond slabs, and Si thin slabs can be promising hosts for spin qubits, while the T2 of h-BN appears to be much more challenging to engineer, due to the large gyromagnetic ratio of the boron nuclei. In particular, this study showed that T2 of an isotopically purified layer of MoS2 is of the order of 30ms.

Orbitally driven giant thermal conductance associated with abnormal strain dependence in hydrogenated graphene-like borophene类石墨烯型氢化硼烯中由高电子密度促使的极高热导以及反常应力效应研究
Jia He, Dengfeng Li*, Yan Ying, Chunbao Feng, Junjie He, Chengyong Zhong, Hangbo Zhou,Ping Zhou, Gang Zhang* 
npj Computational Materials 5:47 (2019)
doi:s41524-019-0183-2
Published online:10 April 2019
Abstract| Full Text | PDF OPEN

摘要:在固体中声子和电子可以进行热能传输,然而在大多数二维材料中,电子对热导的贡献要远小于声子。本论文通过第一性原理结合非平衡格林函数理论,研究了最近通过实验制备出的类石墨烯型氢化硼烯的电子热导和声子热导,得到声子热导高达4.07 nWK-1nm-2,可以与石墨烯相比拟(4.1 nWK-1nm-2),而且其电子热导高达3.6 nWK-1nm-2,这几乎是石墨烯的十倍。从而类石墨烯型氢化硼烯的总热导是石墨烯的两倍,这也是目前报道的热导最高的二维材料。而且,我们发现沿扶手椅方向的拉伸应变导致载流子浓度的增加,从而显著增加电子热导,电子热导的增加抵消了声子热导的降低,导致了总热导随扶手椅方向拉伸应变的异常增加。本文证实类石墨烯型氢化硼烯由于存在高电子密度使得热导极高,这与其他二维材料有很大的区别   

Abstract:Heat energy in solids is carried by phonons and electrons. However, in most two-dimensional (2D) materials, the contribution from electrons to total thermal conduction is much lower than that for phonons. In this work, through first-principles calculations combined with non-equilibrium Green’s function theory, we studied electron and phonon thermal conductance in recently synthesized 2D hydrogen boride. The hexagonal boron network with bridging hydrogen atoms is suggested to exhibit comparable lattice thermal conductance (4.07 nWK-1nm-2) as graphene (4.1 nWK-1nm-2), and similar electron thermal conductance (3.6 nWK-1nm-2), which is almost ten times that of graphene. As a result, total thermal conductance of 2D hydrogen boride is about two-fold of graphene, being the highest value in all known 2D materials. Moreover, tensile strain along the armchair direction leads to an increase in carrier density, signifificantly increasing electron thermal conductance. The increase in electron thermal conductance offsets the reduction in phonon thermal conductance, contributing to an abnormal increase in thermal conductance. We demonstrate that the high electron density governs extraordinarily high thermal conductance in 2D hydrogen boride, distinctive among 2D materials. 

Editorial Summary

极高热导-反常应力效应:类石墨烯型氢化硼烯的奇迹

在固体中声子和电子可以进行热能传输,是否存在一种二维材料同时具有高的电子热导和声子热导元素周期表中硼与碳相邻,是否存在一种由硼构成的二维材料比石墨烯更高的热导本工作由重庆邮电大学的李登峰教授课题组和新加坡高性能计算研究院张刚教授课题组合作完成,他们基于第一性原理和非平衡格林函数法研究了类石墨烯型氢化硼烯(hydrogenated graphene-like borophene)的弹道热输运性质,给出了声子和电子对热导的贡献,发现类石墨烯型氢化硼烯具有高的声子热导和电子热导,声子热导为4.07 nWK-1nm-2,与石墨烯(4.1nWK-1nm-2)相近;电子热导几乎是石墨烯的10倍,从而类石墨烯型氢化硼烯总的热导是石墨烯的2倍,是目前报道的热导最大的二维材料。另外,我们研究了类石墨烯型氢化硼烯热输运性质的应变效应,在费米面上,沿扶手椅方向的拉伸应变会产生更高的电子态密度,从而有效地将更多的电子态引入,导致电子热导的增加,且在此方向增加的电子热导弥补了声子热导的减小,从而总热导随拉伸应变的增加而增加。相反,在锯齿形方向施加16%的应变时会产生带隙,从而完全“关闭”电子通道,导致电子热导为零。这与扶手椅方向的应变效应相反

We investigated phonon, mechanical and electronic properties of 2D hydrogen boride. Based on the first-principles calculation provided phonon property and electronic band structure, combined with quantum transport theory, we predicted phonon and electrical thermal conductance. The phonon thermal conductance of 2D hydrogen boride is close to that of graphene, while its electrical thermal conductance is almost ten times over graphene. This happens due to the high electron density of state at Fermi level. Moreover, at the Fermi level, the tensile strain along armchair-direction gives a higher electronic density of states, which effectively brings more states toward electrical thermal conductance. In contrast, zigzag-direction tensile strain induces bandgap opening at the Γ-point, which can fully “close” the electron channel, leading to zero electrical thermal conductance. This is the opposite of the armchair-direction strain effect. Our work reveals giant thermal conductance in 2D hydrogen boride, a new boron based 2D material synthesized experimentally.

Numerical prediction of colloidal phase separation by direct computation of Navier–Stokes equation (使用直接计算Navier-Stokes方程对胶体相分离作数值预测)
Michio Tateno & Hajime Tanaka 
npj Computational Materials 5:40 (2019)
doi:s41524-019-0178-z
Published online:02 April 2019
Abstract| Full Text | PDF OPEN

摘要:数值预测含软物质和含生物质液体的非平衡过程是非常必要的。然而,这却是一件极具挑战性的工作,主要因为在不同层次上的组成部件的运动(如大胶体分子和小溶剂分子)是通过动量守恒以一种复杂的方式时空耦合的。本研究以包含液体的软材料为例,严格考查胶体相分离数值模拟的可预测性。我们使用粗粒度流体动力学模拟来解决这个问题,并且在没有任何可调参数的情况下,几乎完美地再现了用三维共聚焦显微镜观察到的胶体结构和拓扑演化。此外,与非流体动力学模拟结果的比较表明了胶体相分离中多体流体动力相互作用的基本重要性。本计算方法的预测能力,不仅有助于对软物质、生物质和活性物质的动力学行为和自组织的基本了解,而且有助于胶体材料的计算机辅助设计   

Abstract:Numerical prediction of out-of-equilibrium processes in soft and bio matter containing liquids is highly desirable. However, it is quite challenging primarily because the motions of the components at different hierarchical levels (e.g., large colloids and small solvent molecules) are spatio-temporally coupled in a complicated manner via momentum conservation. Here we critically examine the predictability of numerical simulations for colloidal phase separation as a prototype example of self-organization of soft materials containing a liquid. We use coarse-grained hydrodynamic simulations to tackle this problem, and succeed in almost perfectly reproducing the structural and topological evolution experimentally observed by three-dimensional confocal microscopy without any adjustable parameters. Furthermore, comparison with non-hydrodynamic simulations shows the fundamental importance of many-body hydrodynamic interactions in colloidal phase separation. The predictive power of our computational approach may significantly contribute to not only the basic understanding of the dynamical behavior and self-organization of soft, bio and active matter but also the computer-aided design of colloidal materials. 

Editorial Summary

Colloidal phase separation: FPD simulation胶体相分离预测:粗粒度流体动力学模拟 

在两种不同粒径胶体的实验中,团簇形成和网络形成相分离的粗化动力学几乎可以完美再现。本工作由东京大学工业科学研究所的Tanaka教授等人完成,他们发现在没有任何可调参数的流体颗粒动力学(FPD)数值模拟中,通过对胶体势和温度(或热噪声)的精确匹配,可以再现胶体相分离,而最广泛使用的粗粒度方法布朗动力学(BD)模拟则完全不能。这一发现证明了多体流体动力相互作用在胶体悬浮液动态结构形成中的基础性重要地位。更重要的是,这表明基于包括FPD模拟在内的Navier-Stokes方程直接计算的模拟方法对胶体悬浮液中的非平衡过程具有较高的预测能力,这不仅有助于对这些现象的基本物理理解,而且有助于胶体材料的计算机辅助设计

Coarsening dynamics of cluster-forming and network-forming phase separation in experiments using colloids with two different sizes can be almost perfectly reproduced. Prof. Hajime Tanaka from the Institute of Industrial Science, University of Tokyo, Japan, found that Fluid Particle Dynamics (FPD) numerical simulations without any adjustable parameters after careful matching of the intercolloid potential and the temperature (or, thermal noise) could reproduce the colloidal phase separation, while Brownian dynamics (BD) simulations, the most widely used coarse-grained method, could not at all. This finding demonstrates the fundamental importance of many-body hydrodynamic interactions in the dynamical structural formation of colloidal suspensions. More importantly, it indicates that simulation methods based on direct computation of the Navier–Stokes equation including FPD simulation has a high predictive power for nonequilibrium processes in colloidal suspensions, which may significantly contribute to not only the basic physical understanding of these phenomena but also the computer-aided design of colloidal materials.

Composite topological nodal lines penetrating the Brillouin zone in orthorhombic AgF2 (正交相AgF2中穿越布里渊区的复合节点线态)
Dexi Shao, Huaiqiang Wang, Tong Chen, Pengchao Lu, Qinyan Gu, Li Sheng, Dingyu Xing & Jian Sun 
npj Computational Materials 5:53 (2019)
doi:s41524-019-0190-3
Published online:23 April 2019
Abstract| Full Text | PDF OPEN

摘要:最近人们发现非简单空间群可以带来很多奇异的能带交叉。在本文中,基于对称性分析,我们发现了具有时间反演对称性的正交相空间群(No.61)的材料具有对称性驱动的能带交叉,包含节点面,四度简并线以及沙漏型狄拉克环。由于轮换对称性,这些态总是三个成组出现。我们以真实体系正交相AgF2为例,采用第一性计算的方法研究了它的能带结构。具体而言,在不考虑自旋轨道耦合的情况下,除了上述对称性驱动的能带简并外,该体系还表现出了穿越布里渊区的节点链态以及类似浑天仪型的新奇节点态。如果考虑了自旋轨道耦合,我们发现该体系具有一个新的沙漏型狄拉克环/链的能带构型,并具有穿越布里渊区的特点,该特点来源于一个限制在布里渊区内的狄拉克环的劈裂。根据体边对应关系,我们还计算了相应的表面态来探索这些体态的简并现象。文末还讨论了这些新奇的穿越布里渊区的节点态在两种特殊的单轴向应变下的演化   

Abstract:It has recently been found that nonsymmorphic symmetries can bring many exotic band crossings. Here, based on symmetry analysis, we predict that materials with time-reversal symmetry in the space group of Pbca (No. 61) possess rich symmetry-enforced band crossings, including nodal surfaces, fourfold degenerate nodal lines and hourglass Dirac loops, which appear in triplets as ensured by the cyclic permutation symmetry. We take Pbca AgF2 as an example in real systems and studied its band structures with ab initio calculations. Specifically, in the absence of spin-orbit coupling (SOC), besides the above-mentioned band degeneracies, this system features a nodal chain and a nodal armillary sphere penetrating the Brillouin zone (BZ). While with SOC, we find a new configuration of the hourglass Dirac loop/chain with the feature traversing the Brillouin zone, which originates from the splitting of a Dirac loop confined in the Brillouin zone. Furthermore, guided by the bulk-surface correspondence, we calculated the surface states to explore these bulk nodal phenomena. The evolution of these interesting nodal phenomena traversing the Brillouin zone under two specific uniaxial strains is also discussed. 

Editorial Summary

Interesting composite topological nodal lines: penetrating the Brillouin zone重要发现:AgF2中存在系列特殊复合拓扑节点线 

该研究发现正交相的AgF2体系是一种复合的穿越布里渊区的拓扑节点线半金属,并用自定义的非常规对称性指标对其作了分类。来自南京大学的孙建教授和邢定钰院士领导的团队,采用对称性分析和第一性原理计算研究了正交相AgF2体系,发现其存在一系列环绕或穿越整个布里渊区的复合拓扑半金属态,包括节点面、四度简并网、节点链、浑天仪型节点、沙漏型狄拉克环等等。有意思的是,上述穿越布里渊区的节点线态,均对应于不同的拓扑指标和对称性指标。在不考虑自旋轨道耦合时,正交相空间群会诱导出环绕整个布里渊区的节点面和四度简并网态。在考虑自旋轨道耦合时,布里渊区的表面会出现沙漏型狄拉克环态。作者在AgF2中发现了更多特殊的简并态:1)不考虑自旋轨道耦合时,该体系表现出了穿越布里渊区的节点链与浑天仪样节点态。 2)考虑自旋轨道耦合时,体系中出现了一种新的沙漏型狄拉克环/链的构型,由一般沙漏型狄拉克圆圈态劈裂成两条穿越布里渊区的狄拉克环态而构成。他们对此定义了一个新的对称性指标,用来对所有沙漏型狄拉克环态作了分类。他们的发现为利用对称性指标理论研究高对称点、线、面上存在节点态的拓扑半金属态提供了一个完美的实例

The Pbca AgF2 is a composite topological nodal semimetal with its nodal lines penetrating the Brillouin zone, which is classified with an unconventional symmetry indicators. A team co-led by Prof. Jian Sun and Prof. Dingyu Xing from the Nanjing University, China, revealed that there exist composite topological nodal lines encircling/penetrating the Brillouin zone in Pbca AgF2, including nodal surfaces, four-fold degenerate nodal nets, nodal chains, nodal armillary spheres and hourglass Dirac loops. It is interesting that the feature of traversing the Brillouin zone corresponds to different topological indexes and symmetry indicators. Specifically, in the absence of spin-orbit coupling (SOC), the space group of Pbca induces the symmetry-enforced nodal surfaces and four-fold nodal net encircling the whole Brillouin zone. While with SOC, symmetry-enforced hourglass Dirac loops appear on the surface of the Brillouin zone. The authors take AgF2 as an example and find more special degeneracies. Firstly, this system features a nodal chain and a nodal armillary sphere penetrating the Brillouin zone without SOC. Secondly, a new configuration of the hourglass Dirac loop (type-II) with the feature traversing the Brillouin zone with SOC originates from the splitting of a Dirac loop confined in the Brillouin zone. At last, all the nontrivial nodal states are stable under two specific uniaxial strains with respect to the Pbca symmetry. This results supply a perfect example to study the topological semimetals with their nodes lying in the high-symmetry point/line/surface using the unconventional symmetry indicators.

Automated estimation of materials parameter from X-ray absorption and electron energy-loss spectra with similarity measures 自动估测材料参数:基于X射线吸收谱和电子能量损失谱的相似性度量
Yuta SuzukiHideitsu HinoMasato Kotsugi & Kanta Ono 
npj Computational Materials 5:39 (2019)
doi:s41524-019-0176-1
Published online:29 March 2019
Abstract| Full Text | PDF OPEN

摘要:近十年来,材料信息学显著加速了新材料发现和材料性能分析。加速的关键动力之一是对于高通量实验测量结果的实时分析,因此从实验数据中快速并准确估测材料性能变得越来越重要。由于光谱数据包含材料性能的重要信息,其被广泛地应用于新材料发现。为实现材料参数的自动估测,一个关键的问题是相似性度量或者核函数的选取。该度量必须最小程度地受到谱峰移动、展宽及噪声的影响。然而,如何选取合适的度量并基于实验测量自动估测材料参数仍是目前有待解决的问题。本研究探讨了用于X射线吸收谱和电子能量损失谱的主要的相似性度量方法。在所有测量中,相似性度量与材料参数(晶体场参数)良好对应。其Pearson相关系数相对于噪声和峰展宽影响最小。我们从光谱的相似性获得了晶体场参数10 Dq的回归模型。该回归模型能够从光谱中自动估算材料参数(10 Dq)。该方法有望从大规模实验数据的数据集中提取出材料参数   

Abstract:Materials informatics has significantly accelerated the discovery and analysis of materials in the past decade. One of the key contributors to accelerated materials discovery is the use of on-the-fly data analysis with high-throughput experiments, which has given rise to the need for accelerated and accurate automated estimation of the properties of materials. In this regard, spectroscopic data are widely used for materials discovery because these data include essential information about materials. An important requirement for the realisation of the automated estimation of materials parameters is the selection of a similarity measure, or kernel function. The required measure should be robust in terms of peak shifting, peak broadening, and noise. However, the determination of appropriate similarity measures for spectra and the automated estimation of materials parameters from these spectra currently remain unresolved. We examined major similarity measures to evaluate the similarity of both X-ray absorption and electron energy-loss spectra. The Pearson's correlation coefficient was the highest for the robustness against noise and peak broadening. We obtained the regression model for the crystal-field parameter 10Dq from the similarity of the spectra. The regression model enabled the materials parameter, that is, 10Dq, to be automatically estimated from the spectra. With regard to research progress in similarity measures, this methodology would make it possible to extract the materials parameter from a large-scale dataset of experimental data. 

Editorial Summary

Automated estimation of materials parameter: from similarity measures材料参数自动估测:基于相似性度量 

基于相似性度量,可以基于构建的回归模型自动和快速地估计材料的重要属性,如晶体场参数10Dq。由日本材料结构科学研究所和国立材料科学研究所(NIMS)的Kanta Ono教授领导的研究小组,探讨了用于X射线吸收和电子能量损失谱的相似性测量方法。基于实验谱的相似度量,他们针对晶体场参数10Dq构建了回归模型,该模型可以从实验谱中自动估测材料的晶体场参数。值得注意的是,他们通过相似性度量可减少实验中需要测量的点,可显著加速材料的表征和材料性质的自动提取,这两者对于材料信息学来说,都是必不可少的。总之,他们的结果有望真正集成高通量制造、表征和即时数据分析,为将来实现真正的高通量新材料发现做出贡献

The interplay between nanofiber strength, adhesion, geometry and flexibility on the resistance of amyloids to mechanical detachment from surfaces is computational analyzed and highlighted. Sinan Keten, et al. from the Northwestern University, USA, proposed a generic coarse-grained model for single amyloid nanofibers, inspired from the Ecoli cross-beta protein structure called curli, to reveal mechanisms of the detachment behavior of single nanofibers when pulled normal to a substrate through a parametric study that looked at energetic and geometric effects. They discovered three different detachment modes, namely, the “break” mode, the “hinge” mode and the “peel” mode. By examining four parameters, the cohesive strength, the adhesion strength, the bending stiffness and the stretching stiffness; they combined these variables to composite parameters that facilitate simpler phase diagrams. Tuning the two composite parameters pertaining to adhesion vs. cohesive or elasticity, a phase diagram to classify regions defined by the three detachment modes can be plotted. Owing to the discrete nature of the subunits making up the amyloid, the competition between the nanofiber cohesive strength and the adhesion strength governs the phase diagram. Because of vertical peeling and high axial stiffness of amyloids, the bending stiffness is more important than the stretching stiffness. These findings may guide future studies on biofilm removal from surfaces, design of biofilm-based materials, or microbial manufacturing of bio-adhesives.

Adhesive behavior and detachment mechanisms of bacterial amyloid nanofibers (细菌淀粉样纳米纤维的粘附行为和分离机制)
Ao Wang & Sinan Keten 
npj Computational Materials 5:29 (2019)
doi:s41524-019-0154-7
Published online:01 March 2019
Abstract| Full Text | PDF OPEN

摘要:淀粉样纳米纤维(如卷曲纳米纤维)能够强烈粘附于非生物表面。然而,单根纳米纤维的粘附性能以及该性能对物理性质的依赖,仍有待表征。本研究进行了粗粒度分子动力学模拟,以确定单个淀粉样纤维从非生物表面的分离机制。采用源自curli纳米纤维亚基CsgA的通用模型,我们发现淀粉样纳米纤维从非生物表面以恒定速率扯下来时,经历三种不同的剥离过程。通过参数研究所建立的计算相图表明,具有高吸附能的强纳米纤维,通过平滑地剥离而从基材上分开,而弱纤维则较早地出现断裂。在中间比率下,纳米纤维与基底表面会形成铰链,而剥离纳米纤维的所要做的工,将是粘合能量的两倍,因为在脱吸附期间需要额外的能量来弯曲纳米纤维。改变淀粉样亚基的几何结构发现,对于较厚的纳米纤维,剥离所需的工减少,这表明淀粉样的带状单体结构可以更好地提高粘合性能。我们的结果证明了淀粉样纳米纤维的尺寸、可粘合性和紧密粘合性是如何通过优化而抵抗机械剥离的   

Abstract:Amyloid nanofibers, such as curli nanofibers, have proven capable of adhering strongly to abiotic surfaces. owever, the adhesive performance of individual nanofibers and the dependence of this performance on physical properties remain to be characterized. We carried out coarse-grained molecular dynamics simulations to determine the detachment mechanisms of single amyloid fibers from surfaces. Taking a generic model inspired from the curli nanofiber subunit CsgA, we discover that the amyloid nanofibers can undergo three different peeling processes when pulled at a constant rate normal to the surface. Computational phase diagrams built from parametric studies indicate that strong nanofibers with high cohesive energy detach by peeling smoothly away from the substrate while weak fibers break prematurely. At intermediate ratios, hinge formation occurs and the work of peeling the nanofiber is twice the adhesive energy due to the additional energy required to bend the nanofiber during desorption. Varying the geometry of amyloid subunits revealed that the work of peeling decreases for thicker nanofibers, suggesting that the tape-like monomeric structure of amyloids may facilitate better adhesive performance. Our results demonstrate how the dimensions and adhesive and cohesive properties of the amyloid nanofibers can be optimized to resist mechanical peeling. 

Editorial Summary

Adhesion and detachment mechanisms: inspired by bacterial粘附和分离机制:来自细菌的启发 

该研究计算分析并强调了纳米纤维强度、粘附性、几何形状和柔韧性之间的相互作用,以及淀粉样纤维对基底表面机械分离的抵抗力。来自美国西北大学的Sinan Keten等,受一种叫curli的大肠杆菌交叉β蛋白结构的启发,提出了一种用于单个淀粉样纳米纤维的通用粗粒模型。他们通过考察能量效应和几何效应,对单个纳米纤维的分离行为作广泛表征,从而揭示了纳米纤维被从基底上垂直地拉扯分离时的分子机理。他们发现了三种不同的分离模式,即“中断”模式、“铰链”模式和“剥离”模式。他们研究了四种参数:粘附强度、内聚强度、弯曲刚度和拉伸刚度;将这些变量组合成复合参数,可简化相图。他们调整了与粘附力与粘合力或弹性有关的两个复合参数以绘制了相图,从而对三个脱离模式定义的区域作了分类。由于构成淀粉样纤维的亚基存在离散性,纳米纤维内聚强度和粘附强度之间的竞争决定了相图。由于淀粉的垂直剥离和高轴向刚度,弯曲刚度比拉伸刚度更重要。这些发现可能指导未来关于从基底表面去除生物膜的研究,和基于生物膜材料或生物粘合剂的设计和微生物制造研究

The interplay between nanofiber strength, adhesion, geometry and flexibility on the resistance of amyloids to mechanical detachment from surfaces is computational analyzed and highlighted. Sinan Keten, et al. from the Northwestern University, USA, proposed a generic coarse-grained model for single amyloid nanofibers, inspired from the Ecoli cross-beta protein structure called curli, to reveal mechanisms of the detachment behavior of single nanofibers when pulled normal to a substrate through a parametric study that looked at energetic and geometric effects. They discovered three different detachment modes, namely, the “break” mode, the “hinge” mode and the “peel” mode. By examining four parameters, the cohesive strength, the adhesion strength, the bending stiffness and the stretching stiffness; they combined these variables to composite parameters that facilitate simpler phase diagrams. Tuning the two composite parameters pertaining to adhesion vs. cohesive or elasticity, a phase diagram to classify regions defined by the three detachment modes can be plotted. Owing to the discrete nature of the subunits making up the amyloid, the competition between the nanofiber cohesive strength and the adhesion strength governs the phase diagram. Because of vertical peeling and high axial stiffness of amyloids, the bending stiffness is more important than the stretching stiffness. These findings may guide future studies on biofilm removal from surfaces, design of biofilm-based materials, or microbial manufacturing of bio-adhesives.

Active learning in materials science with emphasis on adaptive sampling using uncertainties for targeted design (材料科学中强调自适应采样的主动学习:使用不确定性针对目标进行设计)
Turab LookmanPrasanna V. BalachandranDezhen Xue & Ruihao Yuan 
npj Computational Materials 5:21 (2019)
doi:s41524-019-0153-8
Published online:18 February 2019
Abstract| Full Text | PDF OPEN

摘要:根据目标性能有效搜索巨大的材料候选空间是新材料探索的主要挑战之一,而基于传统试错的探索方法难以实现上述目标。我们讨论了几种效用函数并证明了其在材料科学应用中的作用,及其对实验和计算研究的影响。本文综述了基于信息科学方法来加速搜索和发现新材料的途径。具体地,主动学习可通过迭代的方式对搜索空间进行有效导航,由此识别有希望的候选材料,从而指导实验和计算。该方法依赖于不确定性的使用,并以近似模型和效用函数进行预测,通过决策过程确定数据的优先级。我们讨论了几种效用函数,并展示了其在材料科学领域的应用。我们总结了上述方法在多重材料性能和多重精度数据中的推广,指出了材料信息学这一新兴领域的挑战、未来方向和机遇   

Abstract:One of the main challenges in materials discovery is efficiently exploring the vast search space for targeted properties as approaches that rely on trial-and-error are impractical. We review how methods from the information sciences enable us to accelerate the search and discovery of new materials. In particular, active learning allows us to effectively navigate the search space iteratively to identify promising candidates for guiding experiments and computations. The approach relies on the use of uncertainties and making predictions from a surrogate model together with a utility function that prioritizes the decision making process on unexplored data. We discuss several utility functions and demonstrate their use in materials science applications, impacting both experimental and computational research. We summarize by indicating generalizations to multiple properties and multifidelity data, and identify challenges, future directions and opportunities in the emerging field of materials informatics. 

Editorial Summary

Active learning in Materials science: design accelerated by adaptive sampling using uncertainties材料科学中的主动学习:基于不确定度的适应性采样开展材料设计 

如何有效搜索巨大的材料空间来获得目标性能是当前材料研究的主要挑战之一。计算机科学中的工具有望为解决上述问题提供新的方法和机遇。来自洛斯阿拉莫斯、弗吉尼亚大学和西安交通大学的科学家综述了主动学习,这一计算机工具在加速材料研究和新材料发现方面的应用。该方法依赖于不确定性的使用,其首先基于近似模型来定义一个效用函数,通过最大化效用函数的值来确定下一步最佳的实验和计算体系。通过迭代循环的方式来扩大数据库并优化近似模型,最终可以得到具有目标性能的材料体系。本文综述了主动学习的计算框架,讨论了几种效用函数,并结合压电、光电和磷灰石材料设计等具体实例,展示主动学习在材料科学研究中的应用。本文最后展望了材料信息学这一新兴研究领域中未来的研究方向和面临的主要挑战

Efficiently exploring the vast search space for targeted properties is one of the main challenges in accelerating materials discovery. Tools in computer science may offer enormous opportunities and complementary paradigm for this exploration. Scientists from Los Alamos Lab, University of Virginia and Xi’ an Jiaotong University reviewed the how the active learning, a tool from computer science can be used to accelerate search and discovery of new materials. Emphasizing the uncertainties, this approach uses the prediction of a surrogate model to define a utility function. Then maximizing this function dictates the next experiment or calculation. In a iterative way, the surrogate model and the data base can be updated, and the materials with targeted properties can be obtained. They discussed the framework of this approach, discussed several utility functions and demonstrated the applications in materials science with cases of piezoelectric, optoelectronic and apatite materials. The directions for future research and challenges with respect to the emerging field of materials informatics are also discussed.

Solving the electronic structure problem with machine learning (用机器学习解决电子结构问题)
Anand ChandrasekaranDeepak KamalRohit BatraChiho KimLihua Chen & Rampi Ramprasad 
npj Computational Materials 5:22 (2019)
doi:s41524-019-0162-7
Published online:18 February 2019
Abstract| Full Text | PDF OPEN

摘要:基于求解密度泛函理论(DFTKohn-ShamKS)方程的模拟,已成为现代材料和化学科学中研究和开发过程的重要组成部分。尽管具有很强的普适性,然而求解KS方程计算量很大,因而常规DFT计算一般只能限于几百个原子。本研究报道了一种基于机器学习的方案,可以绕过KS方程的直接求解但实现类似的功能,基于给定原子构型,可直接、快速、准确地预测材料或分子的电子结构。基于新型的旋转不变性表示,将格点周围的原子环境映射到该格点处的电子密度和局部态密度。使用预先计算得到的带有几百万的格点信息的DFT结果来训练的神经网络以得到该映射。本工作提出的方法可以精确获得KS DFT实际计算的结果,但比其快几个数量级。此外,机器学习预测方案与系统尺寸严格成线性关系   

Abstract:Simulations based on solving the Kohn-Sham (KS) equation of density functional theory (DFT) have become a vital component of modern materials and chemical sciences research and development portfolios. Despite its versatility, routine DFT calculations are usually limited to a few hundred atoms due to the computational bottleneck posed by the KS equation. Here we introduce a machine-learning-based scheme to efficiently assimilate the function of the KS equation, and by-pass it to directly, rapidly, and accurately predict the electronic structure of a material or a molecule, given just its atomic configuration. A new rotationally invariant representation is utilized to map the atomic environment around a grid-point to the electron density and local density of states at that grid-point. This mapping is learned using a neural network trained on previously generated reference DFT results at millions of grid-points. The proposed paradigm allows for the high-fidelity emulation of KS DFT, but orders of magnitude faster than the direct solution. Moreover, the machine learning prediction scheme is strictly linear-scaling with system size. 

Editorial Summary

Machine Learning: Predicting Electronic Structures机器学习:快速精确预测电子结构 

本研究开发了基于一种机器学习的方法,可以不直接求解密度泛函理论Kohn-ShamKS)方程,精确预测电子电荷密度和态密度。来自佐治亚理工学院的Rampi Ramprasad领导的团队,报道了一种基于机器学习的方案,可有效地实现KS方程的功能,利用新的旋转不变表示,将格点周围的原子环境映射到该格点处的电子密度和局部态密度。使用预先计算得到的带有几百万的格点信息的DFT结果来训练的神经网络来获得该映射。利用研究方法的可以精确模拟实际求解KS方程的结果,但是速度快几个数量级

A machine learning model that can learn the behavior of the Kohn-Sham (KS) equation of density functional theory (DFT). After training with DFT results, the electron charge density and density of states can be predicted based only on atomic configuration information. A team led by Rampi Ramprasad from Georgia Institute of Technology, reported a machine learning-based approach that effectively assimilates functions of the KS equation, mapping the atomic environment around the grid-points to the electron density and local density at the grid-points by the new rotation-invariant expression. Their proposed typical KS DFT can be high fidelity simulations, several orders of magnitude faster than direct solutions. In addition, using modern graphical processing unit (GPU) architecture, parallelized batch training and prediction schemes, their machine learning prediction methods can be scaled linearly by system size. Other derived properties such as energy, force, dipole moment, etc., can be calculated by the model, leading to a practical and effective DFT simulator, whose accuracy is completely controlled by the theoretical level used to create the original data, and the size and diversity of the training dataset.

Prediction of Weyl semimetal and antiferromagnetic topological insulator phases in Bi2MnSe4Bi2MnSe4Weyl半金属和反铁磁拓扑绝缘相的预测)
Sugata ChowdhuryKevin F. Garrity & Francesca Tavazza 
npj Computational Materials 5:33 (2019)
doi:s41524-019-0168-1
Published online:07 March 2019
Abstract| Full Text | PDF OPEN

摘要:具有强自旋-轨道耦合和磁相互作用的3D材料为实现具有时间反演对称性破缺的各种稀有和潜在有用的拓扑相提供了机会。在本研究中,我们使用第一性原理计算表明,最近合成的材料Bi2MnSe4显示了自旋轨道诱导的能带反转,这也在非磁性拓扑绝缘体Bi2PbSe4中观测到,与磁相互作用,共同导致出现数个拓扑相。在块体中,Bi2MnSe4的铁磁相在费米能级上的能带交叉具有对称保护,根据自旋的方向,可以导致节点线或Weyl半金属。由于存在时间反演对称性和部分平移对称性的组合,基态层状反铁磁相是一种反铁磁拓扑绝缘体。该相的表面本质上打破了时间反演对称性,以至于可以观测到半整数量子反常霍尔效应。此外,我们还发现,在薄膜中,对于足够厚的板,Bi2MnSe4可为一个带隙高达58 meVChern绝缘体。这种化学计量磁性材料的性能组合使Bi2MnSe4成为可以展现鲁棒拓扑行为的优秀候选   

Abstract:Three-dimensional materials with strong spin–orbit coupling and magnetic interactions represent an opportunity to realize a variety of rare and potentially useful topological phases with broken time-reversal symmetry. In this work, we use first principles calculations to show that the recently synthesized material Bi2MnSe4 displays a combination of spin–orbit-induced band inversion, also observed in non-magnetic topological insulator Bi2PbSe4, with magnetic interactions, leading to several topological phases. In bulk form, the ferromagnetic phase of Bi2MnSe4 has symmetry protected band crossings at the Fermi level, leading to either a nodal line or Weyl semimetal, depending on the direction of the spins. Due to the combination of time reversal symmetry plus a partial translation, the ground state layered antiferromagnetic phase is instead an antiferromagnetic topological insulator. The surface of this phase intrinsically breaks time-reversal symmetry, allowing the observation of the half-integer quantum anomalous Hall effect. Furthermore, we show that in thin film form, for sufficiently thick slabs, Bi2MnSe4 becomes a Chern insulator with a band gap of up to 58meV. This combination of properties in a stoichiometric magnetic material makes Bi2MnSe4 an excellent candidate for displaying robust topological behavior. 

Editorial Summary

Bi2MnSe4: Prediction of Weyl Semi-Metal and Antiferromagnetic Topological Insulation Phases(Bi2MnSe4Weyl半金属和反铁磁拓扑绝缘相的预测 

本研究发现Bi2MnSe4是与Bi2Se3结构相关的几种材料之一,具有自旋-轨道耦合诱导的能带反转,并出现时间反演对称性破缺的拓扑相。来自美国国家标准与技术研究所材料测量实验室的Sugata Chowdhury教授等,使用密度泛函理论和基于Wannier函数的紧束缚模型研究了Bi2MSe4(BMS, M=Pb, Mn)的电子性质,并预测了一系列拓扑非平凡相。他们发现由于Z点处的自旋轨道诱导的能带反转,Bi2MSe4成为时间反演不变拓扑绝缘体。将其能带反转与磁性相结合的研究发现,依据磁性有序的对称性和样品的厚度,Bi2MSe4可以通过时间反演对称性破缺转化到许多不同的拓扑相:节线系统、磁性Weyl半金属、反铁磁拓扑绝缘体或Chern绝缘体,以及半整数量子反常霍尔效应。其能带反转是连接所有这些非平凡拓扑相的基本驱动力。然而,磁序和维数控制着费米能级附近能带的对称性,从而可改变能带反转后半金属相或绝缘相的形成,以及与能带反转相关的拓扑不变量、拓扑表面和拓扑边缘特征的变化。该研究有望通过使用诸如外部磁场或温度等外场微扰来控制样品厚度和自旋有序性,从而实现实验观测到这些密切相关的各种相。Bi2MSe4因其强磁相互作用和显著的带隙,有望成为研究高温下化学计量化合物和时间反演对称性破缺拓扑相的重要材料

Bi2MnSe4, one of several materials related to Bi2Se3 structure, showing spin-orbit-induced energy band reversal, and the appearance of time-reversed symmetrical broken topological phase was reported. Professor Sugata Chowdhury from the National Institute of Standards and Technology of the United States, using density functional theory and Wannier-based tight-binding model, studied the electronic properties of Bi2MSe4 (BMS, M = Pb, Mn) and predicted a series of topologically non-trivial phases. They found that Bi2MSe4 became a time-reversed invariant topological insulator due to the spin-band induced band reversal at Z point. Combining its band reversal with its magnetic properties, it is found that Bi2MSe4 can access many different topological phases with broken time-reversed symmetry depending on the symmetry of the magnetic ordering and the sample thickness: a nodal line system, magnetic Weyl semimetal, antiferromagnetic topological insulator, or Chern insulator, in addition to displaying the half-integer quantum anomalous Hall effect. Its band inversion is the fundamental driving force linking all these non-trivial topological phases. However, the magnetic ordering and dimensionality controls the symmetry of the bands near the Fermi level, which changes the formation of the semi-metal phase or the insulating phase after the energy band is inverted, and the topological invariants and topological surface and edge features related to band inversion. The study is expected to observe these closely related phases by manipulating sample thickness and spin order using perturbations such as external magnetic field or temperature. Due to its strong magnetic interaction and significant band gap, Bi2MSe4 is expected to be an important material for studying stoichiometric compounds and broken time-reversal symmetry topological phases at higher temperatures.

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