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HEAS Data Platform · 材料科学计算数据库

LiBeAs

弹性数据 ELA

MP-ID: mp-9562 · 空间群: P4/nmm (#129)

基础信息

化学式
LiBeAs
MP-ID
mp-9562
元素数
3
位点数
6
密度
3.5062
g/cm³
体积
86.08
ų
晶胞参数 a
3.7366
Å
晶胞参数 b
3.7366
Å
晶胞参数 c
6.1651
Å
α 角
90.00
°
β 角
90.00
°
γ 角
90.00
°
空间群
P4/nmm
点群
4/mmm
晶体系统
Tetragonal
布拉维格子
Tetragonal P
稳定性
是
堆积分数
0.6800

X 射线衍射

衍射图谱
横轴为 2θ (°),纵轴为相对强度,CuKa , λ=1.5406 Å
衍射峰(Top 24)
2θd (Å)Ihkl
14.37 6.1651 7.4 (0,0,1)
27.92 3.1955 100.0 (1,0,1)
28.97 3.0826 20.5 (0,0,2)
33.93 2.6422 33.4 (1,1,0)
37.84 2.3778 7.7 (1,0,2)
45.20 2.0061 33.1 (1,1,2)
48.74 1.8683 15.8 (2,0,0)
50.70 1.8007 17.3 (1,0,3)
56.75 1.6221 3.7 (1,1,3)
57.11 1.6129 26.1 (2,1,1)
57.70 1.5977 11.6 (2,0,2)
60.02 1.5413 2.1 (0,0,4)
63.31 1.4691 3.3 (2,1,2)
65.51 1.4248 4.3 (1,0,4)
67.79 1.3824 1.0 (2,0,3)
70.77 1.3313 3.4 (1,1,4)
71.40 1.3211 5.0 (2,2,0)
72.97 1.2965 11.5 (2,1,3)
77.40 1.2330 1.0 (0,0,5)
78.32 1.2209 5.2 (3,0,1)
78.82 1.2143 4.6 (2,2,2)
80.85 1.1889 3.7 (2,0,4)
81.45 1.1816 5.2 (3,1,0)
82.35 1.1709 2.8 (1,0,5)
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能量属性

形成能/原子
-0.47838
eV/atom
能量/原子
-3.91787
eV/atom
凸包距离
0.0000
eV/atom
未修正能量
-7.7357
eV/atom
体积/原子
14.35
ų
c/a 比
1.6499

电子属性

金属性
非金属
带隙
1.006
eV
直接带隙
否
导带底 CBM
N/A
eV

磁性属性

磁性
是
总磁矩
0.0000
μB
磁有序
Unknown
磁性位点数
0
磁化强度/体积
0.000000
μB/ų

弹性属性

体积模量 KVRH
54.336
GPa
剪切模量 GVRH
35.547
GPa
杨氏模量 E
87.549
GPa
泊松比 ν
0.231
Pugh 比 K/G
1.529
维氏硬度估算
6.832
GPa
韧性
Ductile
各向异性
1.792
拉梅 λ
30.638
GPa

特征分析

组成概览

元素组成(原子分数)
组成信息
主元 / 基质元素
Li · 0.333
元素家族
Alkali-AlkEarth
溶质分数
0.667
间隙分数
0.000

弹性数据特征

弹性模量对比 (GPa)
弹性特征
弹性各向异性 AU
1.7920
均匀泊松比 ν
0.2310
Debye 温度
771.7
K
声速
3,527.4
m/s
均匀度
0.2310

关联任务

引用参考

Materials Project 官方页面
https://materialsproject.org/materials/mp-9562
参考引用

The crystal structure and related material properties of LiBeAs were obtained from the Materials Project database (MP-ID: mp-9562, database version v2026.04.13).

文献引用

Horton, M.K., Huck, P., Yang, R.X. et al. Accelerated data-driven materials science with the Materials Project. Nat. Mater. 24, 1522–1532 (2025). https://doi.org/10.1038/s41563-025-02272-0

BibTeX
@article{Horton2025,
  author  = {Horton, Matthew K. and Huck, Patrick and Yang, Ruo Xi and Munro, Jason M. and Dwaraknath, Shyam and Ganose, Alex M. and Kingsbury, Ryan S. and Wen, Mingjian and Shen, Jimmy X. and Mathis, Tyler S. and Kaplan, Aaron D. and Berket, Karlo and Riebesell, Janosh and George, Janine and Rosen, Andrew S. and Spotte-Smith, Evan W. C. and McDermott, Matthew J. and Cohen, Orion A. and Dunn, Alex and Kuner, Matthew C. and Rignanese, Gian-Marco and Petretto, Guido and Waroquiers, David and Griffin, Sinead M. and Neaton, Jeffrey B. and Chrzan, Daryl C. and Asta, Mark and Hautier, Geoffroy and Cholia, Shreyas and Ceder, Gerbrand and Ong, Shyue Ping and Jain, Anubhav and Persson, Kristin A.},
  title   = {Accelerated data-driven materials science with the Materials Project},
  journal = {Nature Materials},
  year    = {2025},
  volume  = {24},
  number  = {10},
  pages   = {1522--1532},
  month   = {oct},
  doi     = {10.1038/s41563-025-02272-0},
  issn    = {1476-4660},
  url     = {https://doi.org/10.1038/s41563-025-02272-0},
  abstract = {The Materials Project was launched formally in 2011 to drive materials discovery forwards through high-throughput computation and open data. More than a decade later, the Materials Project has become an indispensable tool used by more than 600,000 materials researchers around the world. This Perspective describes how the Materials Project, as a data platform and a software ecosystem, has helped to shape research in data-driven materials science. We cover how sustainable software and computational methods have accelerated materials design while becoming more open source and collaborative in nature. Next, we present cases where the Materials Project was used to understand and discover functional materials. We then describe our efforts to meet the needs of an expanding user base, through technical infrastructure updates ranging from data architecture and cloud resources to interactive web applications. Finally, we discuss opportunities to better aid the research community, with the vision that more accessible and easy-to-understand materials data will result in democratized materials knowledge and an increasingly collaborative community.}
}

晶体结构 3D 渲染

加载 3D 结构...

样式: Ball & Stick
原始 CIF 数据
# generated using pymatgen
data_LiBeAs
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   3.73657199
_cell_length_b   3.73657199
_cell_length_c   6.16510828
_cell_angle_alpha   90.00000000
_cell_angle_beta   90.00000000
_cell_angle_gamma   90.00000000
_symmetry_Int_Tables_number   1
_chemical_formula_structural   LiBeAs
_chemical_formula_sum   'Li2 Be2 As2'
_cell_volume   86.07705831
_cell_formula_units_Z   2
loop_
 _symmetry_equiv_pos_site_id
 _symmetry_equiv_pos_as_xyz
  1  'x, y, z'
loop_
 _atom_site_type_symbol
 _atom_site_label
 _atom_site_symmetry_multiplicity
 _atom_site_fract_x
 _atom_site_fract_y
 _atom_site_fract_z
 _atom_site_occupancy
  Li  Li0  1  0.25000000  0.25000000  0.34689442  1.0
  Li  Li1  1  0.75000000  0.75000000  0.65310558  1.0
  Be  Be2  1  0.25000000  0.75000000  0.00000000  1.0
  Be  Be3  1  0.75000000  0.25000000  0.00000000  1.0
  As  As4  1  0.25000000  0.25000000  0.77650437  1.0
  As  As5  1  0.75000000  0.75000000  0.22349563  1.0
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