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K3Cu3P2

弹性数据 ELA

MP-ID: mp-7439 · 空间群: R-3m (#166)

基础信息

化学式
K3Cu3P2
MP-ID
mp-7439
元素数
3
位点数
8
密度
3.3253
g/cm³
体积
184.71
ų
晶胞参数 a
7.4199
Å
晶胞参数 b
7.4199
Å
晶胞参数 c
7.4199
Å
α 角
44.83
°
β 角
44.83
°
γ 角
44.83
°
空间群
R-3m
点群
-3m
晶体系统
Trigonal
布拉维格子
Trigonal R
稳定性
是
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
13.29 6.6620 100.0 (1,1,1)
18.64 4.7591 10.4 (1,0,0)
20.18 4.3996 15.6 (1,1,0)
25.46 3.4985 1.1 (2,1,1)
26.76 3.3310 9.2 (2,2,2)
28.82 3.0974 79.7 (2,2,1)
31.63 2.8291 19.9 (1,0,-1)
34.44 2.6040 15.6 (1,2,0)
34.44 2.6040 15.6 (2,1,0)
36.42 2.4669 20.2 (3,2,2)
36.96 2.4318 52.6 (1,1,-1)
37.81 2.3796 29.5 (0,2,0)
37.81 2.3796 14.7 (2,0,0)
40.63 2.2207 8.2 (3,3,3)
41.03 2.1998 15.4 (2,2,0)
41.03 2.1998 30.8 (2,0,2)
41.90 2.1563 35.7 (3,2,1)
43.32 2.0889 3.9 (3,1,1)
48.99 1.8593 8.0 (3,3,1)
49.42 1.8442 1.7 (2,0,-1)
50.09 1.8210 2.2 (2,1,-1)
52.30 1.7492 29.5 (4,2,2)
52.38 1.7468 6.1 (4,3,2)
54.61 1.6804 3.8 (2,3,0)
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能量属性

形成能/原子
-0.40729
eV/atom
能量/原子
-8.98220
eV/atom
凸包距离
0.0000
eV/atom
未修正能量
-8.9822
eV/atom
体积/原子
23.09
ų
c/a 比
1.0000

电子属性

金属性
非金属
带隙
1.287
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
25.523
GPa
剪切模量 GVRH
10.614
GPa
杨氏模量 E
27.965
GPa
泊松比 ν
0.317
Pugh 比 K/G
2.405
维氏硬度估算
0.000
GPa
韧性
Brittle
各向异性
3.982
拉梅 λ
18.447
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
K · 0.375
元素家族
Alkali-AlkEarth
溶质分数
0.625
间隙分数
0.250

弹性数据特征

弹性模量对比 (GPa)
弹性特征
弹性各向异性 AU
3.9820
均匀泊松比 ν
0.3170
Debye 温度
237.4
K
声速
2,000.0
m/s
均匀度
0.3170

关联任务

引用参考

Materials Project 官方页面
https://materialsproject.org/materials/mp-7439
参考引用

The crystal structure and related material properties of K3Cu3P2 were obtained from the Materials Project database (MP-ID: mp-7439, 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_K3Cu3P2
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   7.41985542
_cell_length_b   7.41985581
_cell_length_c   7.41985581
_cell_angle_alpha   44.82627222
_cell_angle_beta   44.82626881
_cell_angle_gamma   44.82626771
_symmetry_Int_Tables_number   1
_chemical_formula_structural   K3Cu3P2
_chemical_formula_sum   'K3 Cu3 P2'
_cell_volume   184.70655395
_cell_formula_units_Z   1
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
  K  K0  1  0.90814348  0.90814348  0.90814348  1.0
  K  K1  1  0.50000000  0.50000000  0.50000000  1.0
  K  K2  1  0.09185652  0.09185652  0.09185652  1.0
  Cu  Cu3  1  0.50000000  0.00000000  0.50000000  1.0
  Cu  Cu4  1  0.50000000  0.50000000  -0.00000000  1.0
  Cu  Cu5  1  -0.00000000  0.50000000  0.50000000  1.0
  P  P6  1  0.25702121  0.25702121  0.25702121  1.0
  P  P7  1  0.74297879  0.74297879  0.74297879  1.0
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