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CuAsO3

高熵材料 HEA 传统材料 TRA 弹性数据 ELA

MP-ID: mp-776320 · 空间群: R-3 (#148)

基础信息

化学式
CuAsO3
MP-ID
mp-776320
元素数
3
位点数
10
密度
5.6764
g/cm³
体积
109.10
ų
晶胞参数 a
5.7878
Å
晶胞参数 b
5.7878
Å
晶胞参数 c
5.7878
Å
α 角
51.33
°
β 角
51.33
°
γ 角
51.33
°
空间群
R-3
点群
-3
晶体系统
Trigonal
布拉维格子
Trigonal R
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
17.70 5.0120 14.2 (1,1,1)
23.66 3.7598 34.1 (1,1,0)
31.48 2.8419 100.0 (2,1,1)
35.82 2.5067 28.4 (1,-1,0)
35.82 2.5067 56.9 (1,0,-1)
35.83 2.5060 4.0 (2,2,2)
36.34 2.4721 15.3 (2,1,2)
36.34 2.4721 7.6 (2,2,1)
40.22 2.2419 14.2 (2,1,0)
43.39 2.0857 2.8 (2,0,0)
48.42 1.8799 21.9 (2,0,2)
48.42 1.8799 10.9 (2,2,0)
51.57 1.7723 31.5 (3,1,2)
51.57 1.7723 15.7 (3,2,1)
51.95 1.7602 3.6 (1,1,3)
51.95 1.7602 7.3 (3,1,1)
53.10 1.7248 4.1 (3,3,2)
54.96 1.6707 3.4 (3,3,3)
57.48 1.6033 2.9 (2,-1,1)
57.48 1.6033 1.5 (2,1,-1)
61.67 1.5040 29.1 (3,1,0)
64.37 1.4472 20.2 (2,-1,-1)
64.37 1.4472 10.1 (1,1,-2)
64.71 1.4405 5.8 (3,0,2)
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能量属性

形成能/原子
-1.25880
eV/atom
能量/原子
-5.98144
eV/atom
凸包距离
0.0949
eV/atom
未修正能量
-5.5692
eV/atom
体积/原子
10.91
ų
c/a 比
1.0000

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
否
总磁矩
0.0001
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
50.551
GPa
剪切模量 GVRH
6.569
GPa
杨氏模量 E
18.889
GPa
泊松比 ν
0.438
Pugh 比 K/G
7.695
维氏硬度估算
0.000
GPa
韧性
Brittle
各向异性
-11.393
拉梅 λ
46.172
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 · 0.600
元素家族
Metalloid-Nonmetal
溶质分数
0.400
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
0.9503
高熵判据(>1.0 视为高熵)
混合熵 ΔS
7.9005
J/mol·K
Ω 参数
0.0000
Ω > 1.1 利于固溶体形成
原子尺寸错配 δr
35.943%
δr < 6.6% 利于单相固溶
电负性差 Δχ
0.6915
越小混合越稳定
价电子浓度 VEC
5.200
价电子浓度,影响相稳定性
混合焓 ΔH_mix
0.000
kJ/mol 且负值为放热混合
熵归一化
0.8650
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
B
评分
0.471
家族
O-rich Multi-Component
基质元素
O · 0.600

弹性数据特征

弹性模量对比 (GPa)
弹性特征
弹性各向异性 AU
-11.3930
均匀泊松比 ν
0.4380
Debye 温度
235.2
K
声速
1,224.0
m/s
均匀度
0.4380

关联任务

引用参考

Materials Project 官方页面
https://materialsproject.org/materials/mp-776320
参考引用

The crystal structure and related material properties of CuAsO3 were obtained from the Materials Project database (MP-ID: mp-776320, 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_CuAsO3
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   5.78777091
_cell_length_b   5.78777091
_cell_length_c   5.78777135
_cell_angle_alpha   51.32919719
_cell_angle_beta   51.32919719
_cell_angle_gamma   51.32920558
_symmetry_Int_Tables_number   1
_chemical_formula_structural   CuAsO3
_chemical_formula_sum   'Cu2 As2 O6'
_cell_volume   109.09535595
_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
  Cu  Cu0  1  0.86932900  0.86932900  0.86932900  1.0
  Cu  Cu1  1  0.13067100  0.13067100  0.13067100  1.0
  As  As2  1  0.66221700  0.66221700  0.66221700  1.0
  As  As3  1  0.33778300  0.33778300  0.33778300  1.0
  O  O4  1  0.55112600  0.93465700  0.29938100  1.0
  O  O5  1  0.70061900  0.44887400  0.06534300  1.0
  O  O6  1  0.06534300  0.70061900  0.44887400  1.0
  O  O7  1  0.93465700  0.29938100  0.55112600  1.0
  O  O8  1  0.29938100  0.55112600  0.93465700  1.0
  O  O9  1  0.44887400  0.06534300  0.70061900  1.0
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