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HEAS Data Platform · 材料科学计算数据库

CaInCu4

高熵材料 HEA 传统材料 TRA 弹性数据 ELA

MP-ID: mp-570769 · 空间群: F-43m (#216)

基础信息

化学式
CaInCu4
MP-ID
mp-570769
元素数
3
位点数
6
密度
7.3187
g/cm³
体积
92.82
ų
晶胞参数 a
5.0821
Å
晶胞参数 b
5.0821
Å
晶胞参数 c
5.0821
Å
α 角
60.00
°
β 角
60.00
°
γ 角
60.00
°
空间群
F-43m
点群
-43m
晶体系统
Cubic
布拉维格子
Cubic F
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
21.41 4.1496 30.8 (0,0,1)
21.41 4.1495 15.4 (0,1,0)
21.41 4.1495 15.4 (1,0,0)
24.78 3.5936 46.3 (1,1,0)
35.32 2.5411 30.8 (1,1,2)
35.32 2.5411 30.8 (0,1,-1)
35.32 2.5411 30.8 (1,2,1)
35.32 2.5411 61.7 (1,0,-1)
35.32 2.5411 30.8 (1,-1,0)
41.68 2.1670 100.0 (1,0,2)
41.68 2.1670 100.0 (0,1,2)
41.68 2.1670 100.0 (1,1,-1)
41.68 2.1670 50.0 (2,2,1)
41.68 2.1670 50.0 (1,-1,1)
41.68 2.1670 50.0 (0,2,1)
41.68 2.1670 50.0 (2,1,0)
41.68 2.1670 50.0 (1,-1,-1)
41.68 2.1670 50.0 (2,0,1)
43.62 2.0748 54.7 (0,0,2)
43.62 2.0748 54.7 (2,2,2)
43.62 2.0748 54.7 (0,2,0)
43.62 2.0748 54.7 (2,0,0)
50.81 1.7968 17.2 (2,2,0)
55.75 1.6489 1.0 (1,1,3)
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能量属性

形成能/原子
-0.18193
eV/atom
能量/原子
-12.34927
eV/atom
凸包距离
0.0205
eV/atom
未修正能量
-12.3493
eV/atom
体积/原子
15.47
ų
c/a 比
-

电子属性

金属性
金属
带隙
0
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
83.946
GPa
剪切模量 GVRH
39.309
GPa
杨氏模量 E
102.005
GPa
泊松比 ν
0.297
Pugh 比 K/G
2.136
维氏硬度估算
4.052
GPa
韧性
Brittle
各向异性
0.251
拉梅 λ
57.740
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
Cu · 0.667
元素家族
3d-TM
溶质分数
0.333
间隙分数
0.000

高熵合金特征

综合指标雷达(归一化)
元素类别占比
混合熵 ΔS/R
0.8676
高熵判据(>1.0 视为高熵)
混合熵 ΔS
7.2129
J/mol·K
Ω 参数
0.7162
Ω > 1.1 利于固溶体形成
原子尺寸错配 δr
18.417%
δr < 6.6% 利于单相固溶
电负性差 Δχ
0.3294
越小混合越稳定
价电子浓度 VEC
8.167
价电子浓度,影响相稳定性
混合焓 ΔH_mix
-11.711
kJ/mol 且负值为放热混合
熵归一化
0.7897
固溶体倾向
0
相趋势
IM

传统材料特征

ROM 混合特征雷达
评级与分类
评级 Tier
A
评分
0.777
家族
Cu-based Alloy
基质元素
Cu · 0.667

弹性数据特征

弹性模量对比 (GPa)
弹性特征
弹性各向异性 AU
0.2510
均匀泊松比 ν
0.2970
Debye 温度
309.1
K
声速
2,587.8
m/s
均匀度
0.2970

关联任务

引用参考

Materials Project 官方页面
https://materialsproject.org/materials/mp-570769
参考引用

The crystal structure and related material properties of CaInCu4 were obtained from the Materials Project database (MP-ID: mp-570769, database version v2026.09.28).

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_CaInCu4
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   5.08212819
_cell_length_b   5.08213301
_cell_length_c   5.08213813
_cell_angle_alpha   59.99997327
_cell_angle_beta   59.99994187
_cell_angle_gamma   59.99990734
_symmetry_Int_Tables_number   1
_chemical_formula_structural   CaInCu4
_chemical_formula_sum   'Ca1 In1 Cu4'
_cell_volume   92.81593143
_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
  Ca  Ca0  1  0.00000100  -0.00000000  0.99999900  1.0
  In  In1  1  0.24999900  0.25000000  0.25000000  1.0
  Cu  Cu2  1  0.62427484  0.12717247  0.62427584  1.0
  Cu  Cu3  1  0.62427484  0.62427584  0.12717247  1.0
  Cu  Cu4  1  0.12717347  0.62427584  0.62427584  1.0
  Cu  Cu5  1  0.62427484  0.62427584  0.62427584  1.0
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