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Cu2Ag(SO5)2

高熵材料 HEA

MP-ID: mp-1104602 · 空间群: C2/m (#12)

基础信息

化学式
Cu2Ag(SO5)2
MP-ID
mp-1104602
元素数
4
位点数
15
密度
3.9682
g/cm³
体积
192.11
ų
晶胞参数 a
5.4118
Å
晶胞参数 b
5.4118
Å
晶胞参数 c
8.3068
Å
α 角
64.25
°
β 角
64.25
°
γ 角
67.98
°
空间群
C2/m
点群
2/m
晶体系统
Monoclinic
布拉维格子
Monoclinic C
稳定性
否
堆积分数
0.5240

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
12.51 7.0756 3.4 (0,0,1)
18.70 4.7444 1.9 (1,0,0)
18.83 4.7126 77.2 (1,0,1)
19.79 4.4863 78.1 (1,1,1)
23.68 3.7566 32.1 (1,1,2)
25.17 3.5378 31.4 (0,0,2)
25.79 3.4550 1.3 (1,0,-1)
26.07 3.4184 100.0 (1,0,2)
29.52 3.0255 6.0 (1,-1,0)
31.92 2.8041 64.5 (1,1,-1)
32.18 2.7818 88.3 (1,-1,1)
32.53 2.7525 26.7 (1,1,3)
33.92 2.6426 48.5 (2,1,1)
34.14 2.6261 22.2 (2,1,2)
35.80 2.5084 15.6 (2,0,1)
36.28 2.4764 30.4 (1,0,-2)
36.62 2.4538 3.7 (1,0,3)
37.93 2.3722 24.7 (2,0,0)
38.19 2.3563 51.0 (2,0,2)
38.33 2.3483 11.8 (2,1,0)
38.92 2.3140 18.8 (2,1,3)
40.20 2.2431 9.6 (2,2,2)
42.98 2.1042 5.1 (1,1,-2)
43.70 2.0714 1.0 (1,1,4)
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能量属性

形成能/原子
-1.22566
eV/atom
能量/原子
-5.81205
eV/atom
凸包距离
0.0682
eV/atom
未修正能量
-5.3541
eV/atom
体积/原子
12.81
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
1.0009
μB
磁有序
FM
磁性位点数
4
磁化强度/体积
0.005210
μB/ų

弹性属性

弹性数据暂不开放

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 · 0.667
元素家族
Metalloid-Nonmetal
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
0.9882
高熵判据(>1.0 视为高熵)
混合熵 ΔS
8.2155
J/mol·K
Ω 参数
1.0835
Ω > 1.1 利于固溶体形成
原子尺寸错配 δr
37.670%
δr < 6.6% 利于单相固溶
电负性差 Δχ
0.6244
越小混合越稳定
价电子浓度 VEC
5.667
价电子浓度,影响相稳定性
混合焓 ΔH_mix
-2.667
kJ/mol 且负值为放热混合
熵归一化
0.7128
固溶体倾向
0
相趋势
IM

关联任务

引用参考

Materials Project 官方页面
https://materialsproject.org/materials/mp-1104602
参考引用

The crystal structure and related material properties of Cu2Ag(SO5)2 were obtained from the Materials Project database (MP-ID: mp-1104602, 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_Cu2Ag(SO5)2
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   5.41178351
_cell_length_b   5.41178351
_cell_length_c   8.30683076
_cell_angle_alpha   64.25399194
_cell_angle_beta   64.25399194
_cell_angle_gamma   67.98064276
_symmetry_Int_Tables_number   1
_chemical_formula_structural   Cu2Ag(SO5)2
_chemical_formula_sum   'Cu2 Ag1 S2 O10'
_cell_volume   192.11000278
_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
  Cu  Cu0  1  0.00000000  0.50000000  0.00000000  1.0
  Cu  Cu1  1  0.50000000  0.00000000  0.00000000  1.0
  Ag  Ag2  1  0.50000000  0.50000000  0.50000000  1.0
  S  S3  1  0.08057700  0.08057700  0.70750400  1.0
  S  S4  1  0.91942300  0.91942300  0.29249600  1.0
  O  O5  1  0.17553900  0.17553900  0.80847000  1.0
  O  O6  1  0.82446100  0.82446100  0.19153000  1.0
  O  O7  1  0.19714800  0.19714800  0.50294600  1.0
  O  O8  1  0.80285200  0.80285200  0.49705400  1.0
  O  O9  1  0.75854200  0.17169100  0.76042500  1.0
  O  O10  1  0.17169100  0.75854200  0.76042500  1.0
  O  O11  1  0.24145800  0.82830900  0.23957500  1.0
  O  O12  1  0.82830900  0.24145800  0.23957500  1.0
  O  O13  1  0.66643600  0.66643600  0.95814700  1.0
  O  O14  1  0.33356400  0.33356400  0.04185300  1.0
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