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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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Accelerated design and characterization of non-uniform cellular materials via a machine-learning based framework(使用机器学习加速非均匀二维多孔材料的设计与表征
Chunping Ma, Zhiwei Zhang, Benjamin Luce, Simon Pusateri, BinglinXie, Mohammad H. Rafiei & Nan Hu
npj Computational Materials 6:40(2020)
doi:s41524-020-0309-6
Published online:23 April 2020

Abstract| Full Text | PDF OPEN

摘要:多孔材料广泛存在于人工与自然结构中,其性能高度依赖于它们的几何排列。将基本单元进行非均匀排列可以显著改变材料的力学特性,但这同时也给材料设计带来了新的挑战。为此该研究提出了一种基于机器学习的框架,以快速预测非均匀胞元材料的非线性力学性能并且反向设计材料的几何构型。结果表明,通过选取合适的神经网络架构和参数,该框架可以预测设计域内任意非均匀多孔材料的非线性力-位移响应曲线。此外,该框架借由机器学习模型的预测数据构建数据库,可以生成与所需响应曲线相匹配的多孔材料构型。该研究通过有限元模拟验证了预测的准确性,并从力学角度指出了可能造成预测误差的原因。该框架在单元层面上提高了多孔材料的设计效率,并为系统层面上结构功能的可编程性设计开辟了新途径。 

Abstract:Cellular materials, widely found in engineered and nature systems, are highly dependent on their geometric arrangement. A non-uniform arrangement could lead to a significant variation of mechanical properties while bringing challenges in material design. Here, this proof-of-concept study demonstrates a machine-learning based framework with the capability of accelerated characterization and pattern generation. Results showed that the proposed framework is capable of predicting the mechanical response curve of any given geometric pattern within the design domain under appropriate neural network architecture and parameters. Additionally, the framework is capable of generating matching geometric patterns for a targeted response through a databank constructed from our machine learning model. The accuracy of the predictions was verified with finite element simulations and the sources of errors were identified. Overall, our machine-learning based framework can boost the design efficiency of cellular materials at unit level, and open new avenues for the programmability of function at system level.

Editorial Summary

Challenges in design cellular materials with complex shapes? Let the machine learning do the job异构多孔材料表征难?机器学习来帮忙!

  多孔材料(cellular materials)以其轻质高强的特点和出色的吸能减振属性已被广泛应用在不同领域中,但目前多数研究通过假设材料在空间内的周期性分布,从而只考虑一个二维平面内的基本材料单元。几何对称的多孔材料所设计出的构件或结构往往只具备单一的力学性能。若将基本单元设计成非对称几何并考虑其空间中的非均匀组合,将会大大提升多孔材料在结构层面的属性定制。为了解决几何异构性多带来的挑战,来自美国俄亥俄州立大学助理教授胡楠(现全职于华南理工*)的团队提出了一种基于机器学习的框架,能够快速预测设计域内任意多孔材料的非线性力学响应曲线,并可根据所需要的响应生成匹配的多孔材料基本单元构型。该框架先使用一定数量的数据集训练深度神经网络,再以此预测设计域内所有可能的多孔材料的响应并构建数据库,以搜索数据库的方式生成与目标响应曲线匹配的材料构型。如此则可使用更简洁的神经网络架构和更少的训练时间,实现正向的响应预测与反向的材料设计。相较于针对个别弹性参数进行预测和设计的已有研究,该研究能够对耦合了多种非线性过程(几何、材料、接触)的多孔材料压缩曲线进行预测和材料设计。研究结果表明,该框架在使用全部可能材料构型的20%作为训练数据集时,即可满足多种目标响应曲线的材料设计需求。该研究中还从力学角度探讨了造成预测误差的可能原因,指出材料孔间的复杂接触行为可能使得相似的构型具有相异的响应。该框架在单元层面上提高了多孔材料的设计效率,并为结构层面上功能的可编程性设计开辟了新途径。在3D打印逐渐普及的今天,实现可定制属性的材料也将为开发多功能器件和智能结构带来新的机遇。    

  *胡楠博士入选第十五批国家“海外高层次人才引进计划”青年项目,于20201月入职华南理工大学??翁庾楦崭兆榻?,诚邀青年学者加盟开展博士后科研工作??翁庾橹饕铝τ诓牧?/span>-结构一体化设计研究,以结构化材料为研究主体,研发具有属性可定制、功能可调节的多尺度智能结构和器件。更多信息请参见链接:http://www2.scut.edu.cn/jtxy/2020/0303/c1891a363978/page.htm 。

  Cellular materials have been widely used in different fields due to their low weight-to-strength ratio and excellent energy absorption properties, but most existing studies usually focus on a basic unit cell with an assumption of a periodic cell pattern, leading to a structure remains unchanged in characteristics once in operation. In contrast, asymmetric cells and a non-uniform spatial arrangement could enable tailorable material properties. To accelerate the design and characterization of cellular materials with complex shapes, a research team led by Dr. Nan Hu from the Ohio State University, USA (currently full-time at South China University of Technology, China)proposed a machine-learning based framework that is capable of predicting the mechanical response of the cellular materials in a given geometric domain. The framework uses a low number of data to train a deep neural network, and then predicts the response of all possible non-uniform cellular materials. With a data bank built in the same process, the framework is also able to generates a geometric pattern for a given response curve. The merit of the framework takes advantage of a more concise neural network architecture and less training time to achieve an acceptable forward response prediction and backward material design. Compared with existing studies on predicting single property, this framework can predict and tailor the entire response curve coupled with a variety of nonlinearity (geometry, materials, contacts). The results show that their proposed framework can accelerate meet the material pattern design process by using only 20% of possible patterns as the training data. The prediction errors of the framework were identified which is associated with the complex contact behavior between the material cells. The framework improves the design efficiency of cellular materials at the unit level, and opens up a new route for the programmable design of cellular materials at the structural level. As we enter the era of additive manufacturing, it has become possible to fabricate cellular materials with customized geometries and harness these materials to design smart devices and structures with tailored properties, which motivates us to search novel methods of computational-aided material design.

Prediction of room-temperature half-metallicity in layered halide double perovskites (层状卤化物双钙钛矿中室温半金属的预测)
Jian XuChangsong XuJian-Bo LiuLaurent BellaicheHongjun XiangBai-Xin LiuBing Huang
npj Computational Materials 5:144(2019)
doi:s41524-019-0252-6
Published online:22 November 2019

Abstract| Full Text | PDF OPEN

摘要:具有引人入胜的物理特性且具有完全自旋极化电流的半金属铁磁体(HMF)是高效自旋电子器件的关键候选材料。但是,同时具有高居里温度(Tc)、宽半金属间隙(ΔHM)和大块体磁晶各向异性能量(MAE)的HMF非常罕见,这极大地限制了其室温(RT)下的应用。本研究通过对层状卤化双钙钛矿材料进行筛选,从理论上确定了具有良好结晶的、动态的和热稳定性的Cs4FePb2Cl12,具有固有的半金属基态,Tc高达~450 K。有趣的是,块体Cs4FePb2Cl12中的长程铁磁有序,由不同阴离子Cl p轨道介导、相邻Fe原子d轨道之间强烈的超-超交换相互作用所致。层状Cs4FePb2Cl12即使在单层限制下,也可以很好地保持高Tc,即单层Cs4FePb2Cl12Tc~370 K,这对纳米器件的应用至关重要。此外,与文献中报道的最佳HMF相比,本研究中块体Cs4FePb2Cl12和单层Cs4FePb2Cl12均能表现出宽的ΔHM ~0.55 eV和大的MAE> 320 μeV/ Fe。我们的发现可以大大扩展了LHDP应用于高温自旋电子的潜力。 

Abstract:Half-metallic ferromagnets (HMFs) that possess intriguing physical properties with completely spin-polarized current are key candidates for high-efficiency spintronic devices. However, HMFs that could simultaneously have high Curie temperature (Tc), wide half-metallic gap (ΔHM), and large bulk magnetocrystalline anisotropy energy (MAE) are very rare, which significantly restrict their room-temperature (RT) applications. In this article, through materials screening in layered halide double perovskites (LHDPs), we have theoretically identified that Cs4FePb2Cl12, which has good crystallographic, dynamic and thermal stabilities, possesses an intrinsic half-metallic ground-state with a high Tc~450K. Interestingly, the long-range ferromagnetic ordering in bulk Cs4FePb2Cl12 is contributed by the strong super-superexchange interactions between the neighboring Fe d orbitals mediated by different anionic Cl p orbitals. The high Tc of layered Cs4FePb2Cl12 can be well maintained even in the monolayer limitation, i.e., Tc~370K for Cs4FePb2Cl12 monolayer, which is critical for nanoscale device applications. Moreover, both bulk and monolayer Cs4FePb2Cl12 can exhibit wide ΔHM~0.55eV and large MAE >320μeV/Fe, comparable to that of the best HMFs reported in the literature. Our findings can significantly extend the potentials of LHDPs for high-temperature spintronic applications.

Editorial Summary

Prediction of room-temperature half-metallicity in layered halide double perovskites层状卤化物双钙钛矿:室温下的半金属

  该研究确定了一种层状卤化双钙钛矿材料(HMFs),Cs4FePb2Cl12,具有高Tc、宽ΔHM和大MAE的半金属基态。清华大学材料科学与工程学院先进材料(MOE)重点实验室的刘建波和北京计算科学研究中心的黄兵共同领导的团队,使用基于第一性原理计算方法,在大量LHDPs中筛选了具有标准化学组成的Cs4MB2X12材料。有趣的是,在几种具有良好动态和热稳定性的化合物中,他们确定Cs4FePb2Cl12可表现出半金属基态,其计算的Tc高于RTTc ~450 K)。同时,Cs4FePb2Cl12的ΔHM~0.55 eV较宽、MAE~380 μeV/ Fe较大,使Cs4FePb2Cl12成为自旋电子学中最好的半金属材料之一。值得注意的是,当Cs4FePb2Cl12层的厚度减小到单层时,它仍可以以高Tc~370 K和强MAE~318 μeV / Fe维持半金属性。Cs4FePb2Cl12的磁耦合和MAE均可用施加外部应变加以有效地操纵。s4FePb2Cl12单层的发现,丰富了2D磁体家族,也有望应用于从传感到数据存储的广泛领域。 

  A layered halide double perovskites (LHDPs), Cs4FePb2Cl12, displaying a half-metallic ground-state with high Tc, wide ΔHM and large MAE, is identified through materials screening. A team co-led by Jian-Bo Liu from the Key Laboratory of Advanced Materials (MOE), School of Materials Science and Engineering, Tsinghua University, and Bing Huang from the Beijing Computational Science Research Center, China, explored the possibility of the existence of half-metallicity in LHDPs using first-principles calculations based computational material screening in a large number of LHDPs with the stoichiometries of Cs4MB2X12. Among several compounds that have good dynamic and thermal stabilities, interestingly, they identified that the Cs4FePb2Cl12 can exhibit a half-metallic ground-state with a calculated Tc above RT (Tc~450K). Meanwhile, Cs4FePb2Cl12 has a wide ΔHM~0.55eV and a large MAE~380μeV/Fe, which ranks Cs4FePb2Cl12 as one of the best half-metallic materials for spintronics. Remarkably, when the thickness of layered Cs4FePb2Cl12 is reduced to monolayer, it can still sustain the half-metallicity with a high Tc~370K and a strong MAE~318μeV/Fe. The external strain can be applied to efficiently manipulate the magnetic coupling and MAE of Cs4FePb2Cl12. 

  The discovery of Cs4FePb2Cl12 monolayer can enrich the 2D magnets family, and this material is expected to have applications from sensing to data storage.

Wannier Koopmans method calculations for transition metal oxide band gaps 利用Wannier Koopmans Method方法计算过渡金属氧化物带隙)
 Mouyi Weng, Feng Pan, Lin-Wang Wang
npj Computational Materials 6:33(2020)
doi:s41524-020-0302-0
Published online:03 April 2020

Abstract| Full Text | PDF OPEN

摘要:人们常用的普通的密度泛函理论(density functional theory, DFT)一般会有低估材料带隙的计算问题。Wannier–Koopmans method, WKM 是最近发展出来的一套可以计算得到与更复杂的计算方法有相近带隙大小的方法。目前,这种方法已经被应用到了一般的半导体,卤化碱离子晶体,二维材料和有机晶体等材料中。我们在这篇文章中,应用WKM方法到过渡金属氧化物材料中。我们把过渡金属氧化物分为两类材料,分别为d0d10这一类闭壳系统和d轨道被部分占据的开壳系统(也通常被称为莫特绝缘体)。我们发现WKM计算方法在d0d10两类材料中有很好的计算结果,而在部分占据的d轨道体系中计算存在问题。这样的计算问题也在同样为平均场理论计算的GW计算方法中存在。我们认为WKM计算不准确的原因主要来自于d轨道中占据的wannier函数与非占据的wannier函数的之间的相互作用。我们也同时发现,在含有许多内层电子的赝势的计算中,我们需要在Hartree项和交换关联泛函中去除掉d轨道的wannier函数与内层电子的相互作用来使得我们的计算更为准确。 

Abstract:The widely used density functional theory (DFT) has a major drawback of underestimating the band gaps of materials. Wannier–Koopmans method (WKM) was recently developed for band gap calculations with accuracy on a par with more complicated methods. WKM has been tested for main group covalent semiconductors, alkali halides, 2D materials, and organic crystals. Here we apply the WKM to another interesting type of material system: the transition metal (TM) oxides. TM oxides can be classified as either with d0 or d10 closed shell occupancy or partially occupied open shell configuration, and the latter is known to be strongly correlated Mott insulators. We found that, while WKM provides adequate band gaps for the d0 and d10 TM oxides, it fails toprovide correct band gaps for the group with partially occupied d states. This issue is also found in other mean-field approaches like the GW calculations. We believe that the problem comes from a strong interaction between the occupied and unoccupied d-state Wannier functions in a partially occupied d-state system. We also found that, for pseudopotential calculations including deep core levels, it is necessary to remove the electron densities of these deep core levels in the Hartree and exchange–correlation energy functional when calculating the WKM correction parameters for the d-state Wannier functions.

Editorial Summary

Solving the band gap problems in DFT: Wannier-Koopmans methodsDFT计算能带带隙偏?。?span class="xfzh">WKM方法替代

  在普通的平面波Kohn-Sham方程计算的密度泛函理论(DFT)中,通过理论计算得到的带隙往往会小于实际实验得到的带隙。我们使用一种基于普通DFTWKMWannier-Koopmans Method)计算方法可以得到与实验一致的带隙大小和电子结构。WKM计算方法在一般的半导体,离子晶体,有机共价晶体,和二维材料和等材料都被测试可以得到与实验一致的带隙计算结果。来自美国的劳伦斯伯克利国家实验室的汪林望博士与北京大学深圳研究生院的潘锋教授合作,使用WKM方法针对过渡金属氧化物进行了研究。研究发现在Hartree项和交换关联泛函中去除掉d轨道的wannier函数与内层电子的相互作用可以在d0d10闭壳系统中得到与实验一致的带隙大小。而WKM方法在部分占据的d轨道体系中计算还存在计算不准确的问题,这样的问题主要是由于d轨道中占据的wannier函数与非占据的wannier函数的之间的相互作用引起的。总结起来,该研究一方面为d0d10闭壳系统的过渡金属氧化物的计算提供了一套计算方法,同时也分析了部分占据的d轨道开壳系统的过渡金属氧化物的WKM计算结果,为后续开发WKM计算方法在开壳过渡金属氧化物体系中的计算提供了开发思路。

  In plane wave Kohn-Sham density functional theory calculations, band gap underestimation is a common problem. A calculation approach called Wannier-Koopmans method (WKM) can get band gaps as experimental does in common semi-conductor materials, ionic alkali halide materials, covalence organic crystals and 2d materials. This research focus on transition metal oxide. Dr. Lin-wang Wang from the Lawrence Berkeley National Laboratory and Professor Pan Feng from the Peking University Shenzhen Graduate School applied WKM on transition metal oxides. It is found that removing the electron densities of these deep core levels in the Hartree and exchange–correlation energy functional can help WKM get similar band gaps as experiments do for d0 and d10 close-shell transition metal oxides. However, WKM fails to provide correct band gaps for the materials with partially occupied open-shell d states. It is believed that the problem comes from a strong interaction between the occupied and unoccupied d-state Wannier functions in a partially occupied d-state system. In conclusion, on the one hand, this work provided a set of calculation approach for transition metal oxides with closed-shell d0 and d10 states, on the other hand, this work analyzed the WKM calculation results of t the partially occupied d-orbit open-shell systems, for subsequent improvement for WKM.

Predicting densities and elastic moduli of SiO2-based glasses by machine learning (用机器学习预测SiO2基玻璃的密度和弹性模量)
Yong-Jie Hu, Ge Zhao, Mingfei Zhang, Bin Bin, Tyler Del Rose, Qian Zhao, Qun Zu, Yang Chen, Xuekun Sun, Maarten de Jong and Liang Qi
npj Computational Materials 6:25(2020)
doi:s41524-020-0291-z
Published online:20 March 2020

Abstract| Full Text | PDF OPEN

摘要:高弹性模量、低重量的SiO2基玻璃的化学设计是一个重要的研究课题。然而,由于弹性模量是原子间键和键序在不同尺度上的复函数,在合成前很难找到一个根据玻璃成分预测弹性模量的通用表达式。本研究中我们证明了机器学习(ML)技术可以有效地预测SiO2基玻璃的密度和弹性模量,该技术跨越了复杂的成分空间,除了SiO2之外,还含有多种(>10)类型的添加剂氧化物。我们的机器学习方法依赖于高通量分子动力学(MD)模拟产生的训练集,一组精心构建的描述符,将经验统计建模与原子间键的基本物理联系起来,利用梯度增压机(GBM-LASSO)实现最小绝对收缩和选择算子,建立统计学习/预测模型。通过大量的仿真和实验数据,对ML模型的预测结果进行了综合比较和验证。该模型只需对一组由二元和三元玻璃样品组成的数据集进行训练,就可以预测训练集以外k-nary-SiO2基玻璃的密度和弹性模量。作为潜在应用的一个例子,我们的GBM-LASSO模型被用于对多组分玻璃系统的大量(~105)组分进行快速、低成本筛选,以构建一个组分-特性数据库,该数据库允许对玻璃密度和弹性特性进行富有成效的总览。 

Abstract:Chemical design of SiO2-based glasses with high elastic moduli and low weight is of great interest. However, it is difficult to find a universal expression to predict the elastic moduli according to the glass composition before synthesis since the elastic moduli are a complex function of interatomic bonds and their ordering at different length scales. Here we show that the densities and elastic moduli of SiO2-based glasses can be efficiently predicted by machine learning (ML) techniques across a complex compositional space with multiple (>10) types of additive oxides besides SiO2. Our machine learning approach relies on a training set generated by high-throughput molecular dynamic (MD) simulations, a set of elaborately constructed descriptors that bridges the empirical statistical modeling with the fundamental physics of interatomic bonding, and a statistical learning/predicting model developed by implementing least absolute shrinkage and selection operator with a gradient boost machine (GBM-LASSO). The predictions of the ML model are comprehensively compared and validated with a large amount of both simulation and experimental data. By just training with a data set only composed of binary and ternary glass samples, our model shows very promising capabilities to predict the density and elastic moduli for k-nary SiO2-based glasses beyond the training set. As an example of its potential applications, our GBM-LASSO model was used to perform a rapid and low-cost screening of many (~105) compositions of a multicomponent glass system to construct a compositional-property database that allows for a fruitful overview on the glass density and elastic properties.

Editorial Summary

Machine learning: density and elastic modulus of glasses机器学习: 快速预测玻璃的密度和弹性

  SiO2基玻璃在各种工业领域有广泛的应用。密度和弹性模量是SiO2基玻璃最常见的两种性能。但SiO2玻璃的弹性模量是氧化物化学成分的复杂因素综合作用的结果,很难开发理论模型来探索多种添加剂氧化物的混合效应,很难直接用于发现新的玻璃成分,很难定量地解释与玻璃化学有关的优化结果。然而,现在,这种情况改变了! 

  来自Michigan大学的齐亮教授等,将机器学习(ML)方法与高通量MD模拟相结合,建立了一个定量准确的模型,根据玻璃成分,预测SiO2基玻璃的密度和弹性模量。研究了Li2O、Na2O、K2O、CaO、SrO、Al2O3、Y2O3、La2O3、Ce2O3、Eu2O3、Er2O3、B2O3ZrO213种添加剂的效果。训练集是使用MD模拟生成的,以均匀采样组成二元和三元系统的一部分的密度和弹性。从用于MD模拟的力场势和元素摩尔分数中精心构造了一组描述符,以囊括其物理和成分信息。通过大量的模拟和实验数据的验证,模型不仅在训练集的组成范围内,而且在训练集的高维组成空间内,都对SiO2基玻璃的密度和弹性模量具有很好的预测能力。所建立的ML模型可用于快速筛选玻璃组成特性,从而对一般多组分玻璃体系的密度和弹性特性进行有效的预测,特别是未探索的组成区域。

  SiO2 based glass is widely used in various industrial fields. Density and elastic modulus are the two most common properties of SiO2 based glass. In particular, how to find new glass components to obtain high elastic modulus and low density is of great significance to the development of today's reinforced and durable SiO2 glass materials. Different from crystal materials, the elastic modulus of SiO2 based glass is not only determined by the bonding strength of atoms, but also depends on many other physical properties at different scales, such as the formation of cation coordination, atomic ring, chain, layer and polyhedral atomic clusters, even the structure at meso scale. In addition, different valence cations are introduced into the oxide additive, which not only changes the bonding strength between cations and oxygen, but also changes the degree of network polymerization. Therefore, the elastic modulus of SiO2 glass is a complex function of oxide chemical composition. It is difficult to develop a theoretical model to explore the mixing effect of various additive oxides, to find new glass composition directly, and to quantitatively explain the optimization results related to glass chemistry.  

  Liang Qi and his collaborators from Michigan University, through the combination of machine learning (ML) method and high-throughput MD simulation, established a quantitative and accurate model to predict the density and elastic modulus of SiO2 based glass according to the glass composition. The effects of 13 additives such as Li2O、Na2O、K2O、CaO、SrO、Al2O3、Y2O3、La2O3、Ce2O3、Eu2O3、Er2O3、B2O3 and ZrO2 were studied. The training set is generated by MD simulation, and the density and elasticity characteristics of a part of binary and ternary system are uniformly sampled. A set of descriptors is carefully constructed from force field potential and element mole fraction for molecular dynamics simulation to contain physical and component information. Through a large number of simulation and experimental data validation, the model not only in the composition range of the training set, but also in the high-dimensional composition space of the training set, has a good prediction ability for the density and elastic modulus of SiO2 based glass. The established ML model can be used to quickly screen the composition characteristics of glass, so as to effectively predict the density and elastic properties of general multicomponent glass systems, especially the unexplored composition areas.

High-throughput discovery of high Curie point two-dimensional ferromagnetic materials (高居里点二维铁磁材料的高通量发现)
Arnab KabirajMayank Kumar & Santanu Mahapatra
npj Computational Materials 6:35(2020)
doi:s41524-020-0300-2
Published online:08 April 2020

Abstract| Full Text | PDF OPEN

摘要:由于二维材料的计算涉及人工密集的复杂过程,因此二维材料数据库存储了大量铁磁材料但却没有他们重要的居里温度信息。本研究中,我们开发了一种全自动的、基于硬件加速的、基于动态翻译的计算机代码,该代码执行基于第一原理的计算,然后执行基于Heisenberg模型的蒙特卡洛模拟,以根据晶体结构估算居里温度。我们使用此代码对数据库中的786种材料进行高通量扫描,以发现居里点超过400 K26种材料。为快速进行数据挖掘,我们通过穷尽搜索模型空间以及超参数来获得具有广义化学特征,进一步使用这些结果来开发端到端机器学习模型。使用此数据驱动模型,我们从不同来源发现了更多的居里点材料。这种材料信息学与最近的实验非常吻合,有望促进二维磁性的实际应用。 

Abstract:Databases for two-dimensional materials host numerous ferromagnetic materials without the vital information of Curie temperature since its calculation involves a manually intensive complex process.In this work, we develop a fully automated, hardware-accelerated, dynamic-translation based computer code, which performs first principles-based computations followed by Heisenberg model-based Monte Carlo simulations to estimate the Curie temperature from the crystal structure.We employ this code to conduct a high-throughput scan of 786 materials from a database to discover 26 materials with a Curie point beyond 400?K.For rapid data mining, we further use these results to develop an end-to-end machine learning model with generalized chemical features through an exhaustive search of the model space as well as the hyperparameters.We discover a few more high Curie point materials from different sources using this data-driven model. Such material informatics, which agrees well with recent experiments, is expected to foster practical applications of two-dimensional magnetism.

Editorial Summary

High-throughput discovery of high Curie point two-dimensional ferromagnetic materials高居里点二维铁磁材料的高通量发现

  到目前为止,人们已对许多2D铁磁(FM)材料进行了计算预测,包括成百上千个条目的通用2D材料数据库。但是,这些数据库都没有包含与实际应用相关的2D铁磁材料的最关键参数:转变温度或居里点(TC)。 

  来自印度科学研究院(IISc)班加罗尔电子系统工程系纳米级设备研究实验室的ArnabKabiraj,以新近提出的近乎能最优地、详尽地搜索和预测体材料的共线、实验验证基态及低能自旋态的算法为基础,开发了一个算法。该算法首先执行基于第一原理的计算,然后执行基于Heisenberg模型的Monte Carlo模拟,以便依据任何2D磁性材料晶体结构准确地预测居里点。即使在有GPU(图形处理单元)加速功能的工作站级计算机上,该代码上的软件工程技术也能使其以高通量方式执行严格的计算。作者使用此代码从合适的数据库中成功地确定了一些材料的居里点。令他们惊讶的是,在经过规范的仔细检查后,归类为FM786种材料中,有近47%被证明是反铁磁(AFM)的??梢猿晒θ范ㄆ渲械?/span>157种材料的TC和其他磁性能,其中26种的TC超过400 K。有几种材料的预测TC与实测的极为相符,这证明了他们高通量方法的科学性。为更快地发现高TC材料,他们使用这157个数据点进一步开发了机器学习(ML)管道。使用这种ML模型,他们最终从文献和其他数据库中识别出了一些高TC2DFM材料。

  So far, a plethora of 2D ferromagnetic (FM) materials have been computationally predicted, including a few general-purpose 2D materials databases containing hundreds to thousands of entries.However, none of these databases contain the most crucial parameter for 2DFM materials relevant for practical applications: the transition temperature or Curie point (TC). 

  A group led by ArnabKabiraj from Nano-Scale Device Research Laboratory, Department of Electronic Systems Engineering, Indian Institute of Science (IISc) Bangalore, India, recently based on an algorithm which can search and predict the collinear, experimentally be verified ground and low-energy spin states for bulk materials, almost optimally and exhaustively, developed a code, which performs first principles-based computations followed by Heisenberg model-based Monte Carlo simulations to predict successfully the Curie point accurately from any magnetic 2D material crystal structure. Software engineering on this code makes it capable to execute such rigorous calculations in a high-throughput manner, even on a workstation-grade computer with GPU (graphical processing unit) acceleration. They use this code to determine the Curie points of materials from a suitable database. To their surprise, almost 47% of the 786 materials classified as FM, turned out to be antiferromagnetic upon close inspection by their code. The TC and other magnetic properties could be successfully determined for 157 materials, among which 26 materials reveal beyond 400?K Curie point. Close agreement with experimentally measured TC for a few materials validates their high-throughput methodology. In pursuit of faster discovery of high-TC materials, the authors further develop a machine-learning (ML) pipeline using these 157 data points. Using this ML model, they finally identify a few high TC 2DFM materials from the literature and other databases

High-performance phosphorene electromechanical actuators (高性能磷烯电致驱动器)
Bozhao Wu, Hui-Xiong Deng, Xiangzheng Jia, Langquan Shui, Enlai Gao* & Ze Liu*
npj Computational Materials 6:27(2020)
doi:s41524-020-0297-6
Published online:20 March 2020

Abstract| Full Text | PDF OPEN

摘要:磷烯是可以从块体黑磷中剥离出来的二维材料,具有独特的力、热、电和光学性质。本工作采用量子力学计算方法展示了高度各向异性的二维结构赋予磷烯优异的电致驱动性能。向磷烯注入电荷后,其最大驱动应力是7.0 GPa,相应的最大驱动应变高达36.6%,该性能与生物肌肉(20-40%)相当,比石墨烯(4.7%)大7倍多。同时,磷烯的最大体积功密度(207.7 J/cm3)比天然肌肉(0.008-0.04 J/cm3)高出3个数量级,比石墨烯(35.3 J/cm3)大近6倍。原子和电子结构分析揭示了磷烯具有这种优异电致驱动性能的内在机制。最后,力学测试检查了注入的电荷对磷烯力学行为的影响,结果显示在一定的力-电荷载共同作用下磷烯的结构仍保持结构完整。本工作为发展纳米电致驱动器提供了参考。 

Abstract:Phosphorene, a two-dimensional material that can be exfoliated from black phosphorus, exhibits remarkable mechanical, thermal, electronic, and optical properties. In this work, we demonstrate that the unique structure of pristine phosphorene endows this material with exceptional quantum-mechanical performance by using first-principles calculations. Upon charge injection, the maximum actuation stress is 7.0 GPa, corresponding to the maximum actuation strain as high as 36.6% that is over seven times larger than that of graphene (4.7%) and comparable with natural muscle (20-40%). Meanwhile, the maximum volumetric work density of phosphorene (207.7 J/cm3) is about three orders of magnitude larger than natural muscle (0.008–0.04 J/cm3) and approximately six times larger than graphene (35.3 J/cm3). The underlying mechanism of this exceptional electromechanical performance in phosphorene is well revealed from the analysis of atomic structure and electronic structure. Finally, the influence of charge on the mechanical behaviors of phosphorene is examined by mechanical tests, indicating the sufficient structural integrity of phosphorene under the combined electromechanical loading. These findings shed light on phosphorene for promising applications in developing nanoelectromechanical actuators.

Editorial Summary

High-performance phosphorene electromechanical actuators高性能磷烯驱动器

  天然肌肉在刺激下会产生显著的机械响应??⒎律嗽旒∪獠牧暇哂蟹岣坏挠τ们熬?。许多具有刺激-响应特性的材料已经得到广泛研究,例如形状记忆合金,陶瓷和聚合物。近年来,随着二维材料的持续发展以及对驱动器件小型化需求的日益增长,基于二维材料发展纳米致动器件逐渐引起业界关注。来自武汉大学的刘泽教授、高恩来副研究员与中国科学院半导体研究所的邓惠雄研究员合作研究计算发现磷烯的独特结构赋予了其优异电致驱动性能。通过向高度各向异性的磷烯注入电荷,可以产生与生物肌肉比拟的驱动应变,同时也产生比生物肌肉高出3个数量级的体积功密度。通过原子和电子结构层面的分析,揭示了磷烯优异电致驱动性能的内在机制。最后,力学测试表明在一定的力-电荷载共同作用下,磷烯的结构仍保持结构完整。该研究为发展纳米致动器提供了理论参考。

  Natural muscle exhibits remarkable mechanical response under the stimulus, and the development of artificial muscle materials has a wide range of application prospects. Many materials with stimulus-response properties have been extensively studied, such as shape memory alloys, electroactive ceramics and polymers. Recently, with the discover of two-dimensional materials and the increasing demand for nanoactuator devices, the development of nano-actuated devices based on two-dimensional materials has gradually attracted industrial attentions. A team of Wuhan University and the Chinese Academy of Sciences, found that by injecting charge into phosphorene, it can show a large actuation strain comparable to natural muscles, and also has a volume work density that is 3 orders of magnitude higher than natural muscles. Through the analysis of atomic and electronic structure, the mechanism of high electromechanical performance of phosphorene is revealed. Finally, mechanical tests show that the structure of the phosphorene remains good integrity under the combined electromechanical loading. This work provides a theoretical foundation for phosphorene as high-performance nanoelectromechanical actuators.

Highly selective phonon diffusive scattering in superionic layered AgCrSe2  (快离子层状AgCrSe2中的高选择性声子扩散散射)
Chen Wang and Yue Chen
npj Computational Materials 6:26(2020)
doi:s41524-020-0295-8
Published online:20 March 2020

Abstract| Full Text | PDF OPEN

摘要:具有刚性晶体晶格和类液体流动子结构共存的快离子材料,已成为一种很有前途的热电材料。然而,由于对快离子态声子行为的认识不足,仍然无法进一步揭示热诱导类液体原子动力学与反常热输运性质之间的内在联系。本研究采用一种混合方案,从从头计算的分子动力学出发,直接描述非简谐声子准粒子,表明以Ag原子为主的低能横向声子完全消失,而纵向光学声子在快离子跃迁过程中基本保持完整。超低的热导率源于原子级的结构不均匀性,最终可以归结为扩散声子动力学。我们的研究还表明,超大的选择性声子扩散散射可以被静水压引起的Ag原子类液体流动的失活所抵消。这些结果证明了离子得快离子特性在声子散射中的决定性作用,并为相关快离子材料的新的声子工程策略铺平了道路。 

Abstract:Superionic materials that exhibit coexistence of rigid crystalline lattices and liquid-likefluctuating substructures have emerged as promising thermoelectric materials. The inadequate understanding of the phonon behavior in the superionic state, however, still prevents further revealing of the underlying correlation between the thermally induced liquid-like atomic dynamics and anomalous thermal transport properties. Herein, by adopting a hybrid scheme to directly characterize anharmonic phonon quasiparticles from ab-initio molecular dynamics, we manifest that low-energy transverse phonons dominated by Ag atoms totally collapse, whereas longitudinal optical phonons remain largely intact during the superionic transition. The ultralow thermal conductivity originates from the atomic level structural heterogeneity can be ultimately attributed to diffusive phonon dynamics. Our study also reveals that the extremely large selective phonon diffusive scattering can be counteracted by hydrostatic pressure induced deactivation of the liquid-like flow of Ag atoms. These results demonstrate the decisive role of ion superionicity in phonon scattering across superionic transition and may pave the way for new phonon engineering strategies in related superionic materials.

Editorial Summary

Superionic Conductor: the mystery of solid-liquid coexistence快离子导体: 固液共存的奥秘

  凝聚态体系的热传导可以看作热平衡位置间的原子微扩散,其扩散重排平均时间是区分固体和液体的内在标准。液体中的扩散时间极短而固体中的晶格位置间的扩散时间很长。然而,层状快离子晶体既具有长程的液相离子扩散率,又具有固态的亚晶格结构,是一种罕见的材料。由于传统解释类液体离子的非简谐性的三声子散射机制无法处理层状扩散系统,因此相关的理论方法亟待改进。 

  来自香港大学机械工程系的Yue Chen团队提出了一种有效混合方案来代替三声子散射机制。层状AgCrSe2快离子化合物表现出超低的液态状热导率。尽管已经提出了多种声子散射框架来解释类似液体的导热性,但是由于缺乏模式化的非谐声子计算和相应的动量分辨非弹性中子散射,尚无法完全揭示其细致的微观机理。他们用从头算分子动力学模拟显示,主要参与Ag贡献的声子被有选择地散射,而纵向光学声子在快离子状态下保持良好。此外,本研究结果表明,流体静水压可以抵消热诱导类液体Ag流的扩散散射,这可能为进一步的声子工程提供了一种选择。

  The heat conduction of condensed system can be regarded as the micro diffusion of atoms between equilibrium positions, in which the average rearrangement time is the internal standard to distinguish solid from liquid. Compared with the negligible diffusion time in liquid, the jump time between well-defined lattice positions in crystalline solid is huge. However, layered superionic crystal is a rare material, which has a long range of liquid-phase ion diffusion rate, while maintaining the solid sublattice. The traditional three phonon scattering mechanism is used to explain the anharmonicity of liquid like ions. Because it can't deal with the layered diffusion system, the mechanism badly needs to be further improved. 

  A team led by Prof. Yue Chen from the Department of mechanical engineering of Hong Kong University put forward an effective hybrid scheme to replace the three phonon scattering mechanism. The layered AgCrSe2 superionic compound exhibits ultralow liquid-like thermal conductivity. Although the supercell structure used is complex, this method has been proved to be effective. Ab initio molecular dynamics simulation shows that the acoustic phonons, which are mainly related to Ag contribution, are selectively scattered, while the longitudinal optical phonons are well maintained in the superionic state. In addition, their results show that hydrostatic pressure can counteract the diffusion scattering of thermally induced liquid like Ag flow, which may provide a choice for further phonon engineering.

Comprehensive scan for nonmagnetic Weyl semimetals with nonlinear optical response (非磁性Weyl半金属及其非线性光学的高通量计算)
Qiunan XuYang ZhangKlaus KoepernikWujun ShiJeroen van den BrinkClaudia Felser & Yan Sun
npj Computational Materials 6:32(2020)
doi:s41524-020-0301-1
Published online:03 April 2020

Abstract| Full Text | PDF OPEN

摘要:近年来第一原理计算越来越多得被用来发展非磁性拓扑材料数据库。这些拓扑材料主要受时间反演对称性或晶体对称性?;?,但是不受这些对称性?;さ?/span>Weyl半金属则不能通过基于对称性的判断标准来预测。迄今为止, Weyl半金属材料目录以及其中Weyl点在k-空间的位置的信息依然没有完成。Weyl半金属数据库的缺少使非磁性拓扑材料数据库不完整。在此工作中,我们发展了一套有效搜索Weyl点的自动算法,并建立了非磁性Weyl半金属数据库,这些半金属的Weyl点分布于费米能附近。这里我们采用无机晶体结构数据库(ICSD)中的晶体结构实验结果。最终我们发现了46个非磁性Weyl半金属拥有相对干净的费米面,同时Weyl点离费米能不超过300meV。其中有9个为手性结构,这类结构能够实现量子化旋光光伏效应(Q-CPGE)。另外我们还研究了非线性光学响应并得到了大的移位电流。最重要的是,我们所发展的这套有力的工具不仅可以发掘非磁性Weyl半金属,而且可以用于磁性拓扑半金属的搜索。 

Abstract:First-principles calculations have recently been used to develop comprehensive databases of nonmagnetic topological materials that are protected by time-reversal or crystalline symmetry. However, owing to the low symmetry requirement of Weyl points, a symmetry-based approach to identifying topological states cannot be applied to Weyl semimetals (WSMs). To date, WSMs with Weyl points in arbitrary positions are absent from the well-known databases. In this work, we develop an efficient algorithm to search for Weyl points automatically and establish a database of nonmagnetic WSMs with Weyl points near the Fermi level based on the experimental non-centrosymmetric crystal structures in the Inorganic Crystal Structure Database (ICSD). In total, 46 Weyl semimetals were discovered to have nearly clean Fermi surfaces and Weyl points within 300 meV of the Fermi level. Nine of them are chiral structures which may exhibit the quantized circular photogalvanic effect. In addition, the nonlinear optical response is studied and the giant shift current is explored. Besides nonmagnetic WSMs, our powerful tools can also be used in the discovery of magnetic topological materials.

Editorial Summary

Nonmagnetic Weyl semimetals database in the way of topological big data德国马普孙岩团队:非磁性Weyl半金属数据库的突破

  近年来,拓扑能带理论和计算方法的发展使得理论计算工作者们有能力建立拓扑材料数据库。目前,拓扑材料数据库的发展与建立主要通过对称性分析得到,这是由于大部分拓扑材料由时间反演对称或者晶体结构对称?;?。受先天对称性的限制,此类算法不能应用于Weyl半金属的预测。该研究发展了一套新颖有效的方法,主要针对非磁性非中心反演Weyl半金属,并将其应用到Weyl半金属材料数据库的发展。德国马普固体化学物理研究所的孙岩和Claudia Felser与莱布尼茨固体材料研究所的Jeroen van den Brink的合作团队,通过对贝利相的高通量计算,高效地得到了非磁性Weyl半金属数据库并对其非线性光学进行了系统研究,从中发现一些Weyl半金属具有很强的二阶光伏效应。该研究克服了传统寻找Weyl点方法耗费大量计算资源的难点?,即Weyl点不受时间反演对称和晶体对称?;ひ约凹扑隳芟恫畹挠跋?,可简单有效地从晶体结构数据库出发得到Weyl半金属以及其中Weyl点在能量和k-空间中的分布。除了第一类Weyl半金属和第二类Weyl半金属,我们还得到了9个具有手性结构的材料,这类材料有望实现量子化旋光光伏效应(Q-CPGE),同时个别材料拥有位于可见光范围内的大的移位电流。随着Weyl半金属材料数据库的建立,非磁性拓扑材料数据库终于完备。该研究提出的贝利相计算方法可以扩展到磁性拓扑材料,从而可大大加速拓扑材料数据库的发展。

  As the development of topological band theory and numerical methodology, it enables the computational material community to establish the topological material databases. So far, the development of topological material databases is based on the symmetry analysis, because most of topological materials are protected by time reversal or crystalline symmetry. However, the Weyl semimetals only needs the translation symmetry and hence cannot predicted by symmetry predictors. In this work, an efficient method to establish a nonmagnetic non-centrosymmetric Weyl semimetal database is developed. Based on the new developed methodology, a team of researchers from Max Planck Institute for Chemical Physics of Solids (MPI CPfS Dresden) and Leibniz Institute for Solid State and Materials Research(IFW Dresden) led by Dr. Yan Sun, Prof. Claudia Felser, and Prof. Jeroen van den Brink obtained the nonmagnetic Weyl semimetal database, and studied their nonlinear optical response. Beside the database itself, this work solved two long standing difficulties: Weyl points are not protected by symmetry and the traditional method to search for Weyl points cost a lot of computational resources. In addition to the Type-I Weyl semimetals and Type-II Weyl semimetals, nine chiral structures which can host quantized circular photogalvanic effect (Q-CPGE) are predicted. The analysis of nonlinear optical response in these Weyl semimetals provides interesting candidates with big shift current in visible spectrum. The development of Weyl semimetal database finally completes the nonmagnetic topological materials database. The method used in this work can be generalized into magnetic systems and stimulate the development of topological material databases.

Ambipolar device simulation based on the drift-diffusion model in ion-gated transition metal dichalcogenide transistors (基于漂移扩散模型的离子栅极过渡金属二卤化物晶体管双极器件模拟)
Akiko Ueda, Yijin Zhang, Nobuyuki Sano, Hiroshi Imamura and Yoshihiro Iwasa
npj Computational Materials 6:24(2020)
doi:s41524-020-0293-x
Published online:20 March 2020

Abstract| Full Text | PDF OPEN

摘要:离子栅极是研究电子功能的有力工具,研究包括超导电性在内的从低电压晶体管到栅极诱导电子相位的调控。二维(2D)材料是一种典型的沟道材料,具有多种栅诱导现象。这种离子栅极晶体管器件的模拟,虽然对器件结构的未来设计意义重大,但至今尚未见报道。本研究建立了二维材料WSe2单分子层上离子液体的漂移扩散(DD)模型,成功模拟了晶体管结构中的输运特性、电位分布和载流子密度分布。特别是,该模拟解释了与带隙能量相当的栅极电压下的双极性行为,也解释了在一些实验论文中报道的通道中p-n结的形成。通过离子栅极,肖特基势垒的电位分布发生戏剧性的变化,这种特殊的行为成为可能。研究显示,耦合到泊松方程的DD模型是一个能很好地解释和预测更好功能的离子栅极晶体管的平台,包括解释和预测自旋、波谷以及光学自由度。 

Abstract:Ionic gating is known as a powerful tool for investigation of electronic functionalities stemming from low voltage transistoroperation to gate-induced electronic phase control including superconductivity. Two-dimensional (2D) material is one of thearchetypal channel materials which exhibit a variety of gate-induced phenomena. Nevertheless, the device simulations on such iongated transistor devices have never been reported, despite its importance for the future design of device structures. In this paper, we developed a drift-diffusion (DD) model on a 2D material, WSe2 monolayer, attached with an ionic liquid, and succeeded insimulating the transport properties, potential profile, carrier density distributions in the transistor configuration. In particular, the simulation explains the ambipolar behavior with the gate voltage comparable to the band gap energy, as well as the formation ofp-n junctions in the channel reported in several experimental papers. Such peculiar behavior becomes possible by the dramaticchange of the potential profiles at the Schottky barrier by the ionic gating. The present result indicates that the DD model coupledto the Poisson equation is a fascinating platform to explain and predict further functionalities of ion-gated transistors throughincluding the spin, valley, and optical degrees of freedom.

Editorial Summary

A key for designing new transistors: drift-diffusion model小而美: 离子栅极过渡金属二卤化物晶体管

  现代电子工业要求器件集成度越来越高,器件尺寸越来越小,在离子栅极晶体管中,由于它的强栅耦合,使得工作电压大大降低,使人们能够调控包括超导电性在内的电子相。相关的材料体系非常丰富,包括碳纳米管、有机半导体、氧化物材料、石墨烯和过渡金属二羟基化合物(TMDs)。其中,TMDs可以适用于电子和自旋电子学的各种应用,是下一代晶体管的良好候选器件。离子栅极有助于实现传统MOSFET难以实现的功能,为了提高离子栅极的功能,必须了解器件工作机理。在晶体管工作的理论研究中,漂移扩散(DD)方法是一种计算模拟器件内载流子的传输特性、能带分布和空间分布的有力工具。但却到目前位置还没有关于其模拟TMDs离子门晶体管的报道。 

  来自日本AISTAkiko Ueda以及美国、德国的合作研究团队,开发了一种包括离子液体(IL)作为栅介质的二维层晶体管模型,他们基于DD方法,成功地模拟了离子的分布、电子和空穴通过金属接触面的动力学过程,得到了离子和载流子的能带分布和空间分布,阐明了晶体管运行下的输运机制和基本物理,并对双极晶体管在有机和非晶材料上的机理进行了理论探讨,解释了该DD模型与传统晶体管模拟的DD模型的不同之处。此外,他们还展示了离子栅极WSe2晶体管的器件模拟结果,研究了单极和双极操作下的电流、能带分布和离子/载流子密度分布。他们的模拟结果揭示了双极化传输和通道中p-n结形成的基本物理基础,表明DD模型与poisson方程耦合是研究离子栅极晶体管的有趣工具。通过在DD模型中加入自旋、波谷和自由度,可检验离子栅极晶体管的功能,并可设计其器件结构。

  In the modern electronic industry, it is required that the device integration is higher and higher, and the device size is smaller and smaller. In the IGBT, because of its strong gate coupling, the working voltage is greatly reduced, so that we can control the electronic phase including superconductivity. There are many related material systems, including carbon nanotubes, organic semiconductors, oxide materials, graphene and transition metal dihydroxycompounds (TMDs). Among them, TMDs can be used in electronic and spin electronics applications, and are good candidates for the next generation of transistors. In order to improve the function of the ion gate, we must understand the working mechanism of the device. In the theoretical study of transistor operation, the drift diffusion (DD) method is considered to be a powerful tool for the transport characteristics, band distribution and spatial distribution of carriers in the calculator. However, there is no report on DD simulation of ion gate transistors of TMDs.  

  A two-dimensional layer transistor model including IL as gate has been developed by Akiko Uedafrom AIST, Japan and research teams from USaand Germany. Based on the DD method, the distribution of ions, the dynamics of electrons and holes passing through the metal contact surface have been successfully simulated, and the band and space distribution of ions and carriers have been obtained. The transport mechanism and basis of the transistor under operation have been clarified In this paper, the mechanism of bipolar transistors on organic and amorphous materials is discussed in theory, and the difference between bipolar transistors and traditional DD models is explained. The device simulation results of the IGS wse2 transistor are also presented. The current, band distribution and ion / carrier density distribution under monopole and bipolar operation are studied. The simulation results reveal the basic physical basis of the double polarization transmission and the formation of p-n junction in the channel. It shows that the coupling of DD model and Poisson equation is an interesting tool for the study of IGBT. By adding spin, trough and degree of freedom into DD model, we can test the function of IGBT and design its device structure.

The Exotically Stoichiometric Compounds in Al-S System Under High Pressure (高压下新奇的Al-S化合物)
Sen Shao, Wenji Zhu, Jian Lv, Yanchao Wang, Yue Chen& Yanming Ma
npj Computational Materials 6:11(2020)
doi:s41524-020-0278-9
Published online:04 February 2020

Abstract| 分析亚冠阿尔艾因vs阿尔希拉尔 | PDF OPEN

摘要:铝和硫作为地球上丰度较高的元素,在自然界中只能够形成Al2S3化合物。高压可以改变化合物的化学计量比,形成常压下不能形成的化合物,这对发现具有新奇功能特性的新材料至关重要。我们利用CALYPSOAl-S体系在高压下可能存在的稳定化合物进行了系统的搜索,发现了四种新化学计量比的Al-S化合物(AlS、Al2S、Al3S4AlS2),这些化合物在高压下表现出新奇的物性。例如,在100GPa时,Al3S4是一种潜在的超导体,其超导转变温度为20.9K;Al2S是一种新的电子化合物,铝的价电子能够局域在晶格间隙中,形成阴离子。本工作为实验进一步研究Al-S体系的性质提供了一个可行的方向。 

Abstract:Aluminum and sulfur, as abundant elements in earth, only form Al2S3 in nature at ambient pressure. It has been realized that the stoichiometry of compounds may change under high pressure, which is crucial in the discovery of novel materials. In this work, we systematically perform structure search for Al-S system under pressure. Four binary compounds of Al-S with exotic stoichiometries of AlS, Al2S, Al3S4 and AlS2 are found at high pressure and show exciting physical properties. Particularly, Al3S4 becomes a superconductor with a predicted superconducting transition temperature Tc of 20.9 K at 100 GPa, while the pressure-induced Al2S becomes an electride, where the valence electrons of aluminum strongly localize in the interstices, acting as anions, at a pressure of 70 GPa. The present work provides a viable direction for further experimental study of the properties of Al-S system.

Editorial Summary

Novel structures and properties of Materials under pressure: the discovery of several Al-S compounds高压下材料的奇特性质:多种Al-S化合物的发现

压力能够使物质的电荷重新排布,是产生新奇材料的有力工具。二元硫化物在高压下往往表现出许多有趣的结构和性质。例如,在常压下,H-S体系中唯一稳定的化合物是具有臭鸡蛋气味的硫化氢气体。理论结构预测发现H3S、HS2、H2S3等化合物在高压下也可以稳定存在,并且预测的新型氢化物H3S200GPa时的超导转变温度高达203K。最近理论研究工作还发现硫与第二主族元素Be 1:1混合时,会产生奇特的周期调制结构。由于第I与第II主族硫化物在高压下产生耐人寻味的结构和性质,来自中国吉林大学超硬材料国家重点实验室研究团队进一步研究了SIII主族元素Al在高压下可能存在的化合物和性质。该研究利用课题组自主研发的结构搜索软件CALYPSO结合第一性原理计算,预测了四种新的Al-S化合物AlS,Al2S,Al3S4AlS2。其中Al3S4具有超导电性,在100 GPa时的超导转变温度为20.9K;该研究还发现在70GPa高压作用下Al-S可形成稳定的电子化合物Al2S。该研究为实验研究Al-S体系高压结构和性质提供了理论支撑。

  It is well-known that pressure is considered as a powerful tool to rearrange electrons and create new exotic materials. In this context, binary sulfides are typically systems showing intriguing structure and properties under compression. For example, H2Swith distinctive odour of rotten eggs is the only stable compound in H-S system at ambient conditions. Several novel compounds of H3S,HS2 and H2S3have been predicted under pressures and H3S shows the remarkably high superconducting Tc of 203 K. Furthermore, a modulated structure has been discovered when sulfur is mixed with the IIA group element Be in stoichiometry of 1:1. The intriguing structures and properties of group IA and IIA sulfides motivate researchers to further investigate binary mixtures between S and group IIIA element Al under pressures. A team from the State Key Laboratory of Superhard Materials, Jilin University, China, studies the potential compounds and properties of S and Al under pressure using their in-house-developed structure search software of CALYPSO. Four new aluminum sulfide compounds of AlS, Al2S, Al3S4 and AlS2are predicted. Al3S4is a superconductor with an estimated value of Tc around 20.7 K at 100 GPa and Al2S, as a new electrode, is stable above 70 GPa. This study provides implications for further experimental exploration of Al-S system under high pressure.

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