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Mg(CuO2)2

弹性数据 ELA

MP-ID: mp-1047145 · 空间群: I4_1/amd (#141)

基础信息

化学式
Mg(CuO2)2
MP-ID
mp-1047145
元素数
3
位点数
14
密度
4.5611
g/cm³
体积
156.83
ų
晶胞参数 a
6.5750
Å
晶胞参数 b
6.5750
Å
晶胞参数 c
6.5750
Å
α 角
131.34
°
β 角
131.34
°
γ 角
71.27
°
空间群
I4_1/amd
点群
4/mmm
晶体系统
Tetragonal
布拉维格子
Tetragonal I
稳定性
否
堆积分数
0.7400

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
18.36 4.8321 100.0 (1,0,-1)
28.67 3.1134 7.2 (2,0,-1)
30.02 2.9766 87.7 (2,1,-2)
33.07 2.7087 2.8 (1,-1,1)
33.54 2.6719 59.2 (2,2,-2)
37.21 2.4161 30.4 (2,0,-2)
38.09 2.3628 69.0 (2,-1,-1)
45.26 2.0034 14.1 (3,0,-2)
45.63 1.9884 23.9 (3,2,-3)
47.47 1.9154 38.5 (2,-2,0)
47.82 1.9022 1.5 (3,1,-3)
51.31 1.7806 2.9 (2,-1,-2)
56.40 1.6314 2.1 (3,-1,-2)
57.02 1.6152 1.1 (3,3,-4)
57.19 1.6107 8.6 (3,0,-3)
57.50 1.6029 5.6 (4,1,-3)
59.37 1.5567 60.6 (4,0,-2)
62.39 1.4883 8.0 (4,2,-4)
62.41 1.4879 21.3 (3,-2,-1)
63.28 1.4696 3.5 (4,3,-4)
67.68 1.3844 6.7 (4,-1,-2)
67.95 1.3795 4.5 (4,1,-4)
69.39 1.3544 17.3 (2,-2,2)
70.49 1.3360 8.5 (4,4,-4)
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能量属性

形成能/原子
-1.45718
eV/atom
能量/原子
-5.68872
eV/atom
凸包距离
0.0372
eV/atom
未修正能量
-8.3775
eV/atom
体积/原子
11.20
ų
c/a 比
1.0000

电子属性

金属性
非金属
带隙
0.530
eV
直接带隙
否
导带底 CBM
N/A
eV

磁性属性

磁性
否
总磁矩
0.0000
μB
磁有序
NM
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
60.487
GPa
剪切模量 GVRH
26.547
GPa
杨氏模量 E
69.477
GPa
泊松比 ν
0.309
Pugh 比 K/G
2.278
维氏硬度估算
2.196
GPa
韧性
Brittle
各向异性
6.196
拉梅 λ
42.789
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
O · 0.571
元素家族
Metalloid-Nonmetal
溶质分数
0.429
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
6.1960
均匀泊松比 ν
0.3090
Debye 温度
403.6
K
声速
2,697.7
m/s
均匀度
0.3090

关联任务

关联的计算任务 ID(2 个)

引用参考

Materials Project 官方页面
https://materialsproject.org/materials/mp-1047145
参考引用

The crystal structure and related material properties of Mg(CuO2)2 were obtained from the Materials Project database (MP-ID: mp-1047145, 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_Mg(CuO2)2
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   6.57501060
_cell_length_b   6.57501060
_cell_length_c   6.57501060
_cell_angle_alpha   131.34237459
_cell_angle_beta   131.34237459
_cell_angle_gamma   71.26967911
_symmetry_Int_Tables_number   1
_chemical_formula_structural   Mg(CuO2)2
_chemical_formula_sum   'Mg2 Cu4 O8'
_cell_volume   156.83438154
_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
  Mg  Mg0  1  0.50000000  0.50000000  -0.00000000  1.0
  Mg  Mg1  1  0.25000000  0.75000000  0.50000000  1.0
  Cu  Cu2  1  0.87500000  0.12500000  0.25000000  1.0
  Cu  Cu3  1  0.37500000  0.12500000  0.25000000  1.0
  Cu  Cu4  1  0.87500000  0.62500000  0.75000000  1.0
  Cu  Cu5  1  0.87500000  0.12500000  0.75000000  1.0
  O  O6  1  0.64605903  0.87225097  0.77380806  1.0
  O  O7  1  0.12774903  0.90155708  0.77380806  1.0
  O  O8  1  0.12774903  0.35394097  0.22619194  1.0
  O  O9  1  0.10394097  0.37774903  0.72619194  1.0
  O  O10  1  0.65155708  0.37774903  0.27380806  1.0
  O  O11  1  0.62225097  0.34844292  0.72619194  1.0
  O  O12  1  0.09844292  0.87225097  0.22619194  1.0
  O  O13  1  0.62225097  0.89605903  0.27380806  1.0
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