导航

HEAS Data Platform · 材料科学计算数据库

LiCoCuO4

高熵材料 HEA

MP-ID: mp-754020 · 空间群: P-1 (#2)

基础信息

化学式
LiCoCuO4
MP-ID
mp-754020
元素数
4
位点数
14
密度
4.7409
g/cm³
体积
135.49
ų
晶胞参数 a
5.8157
Å
晶胞参数 b
5.7540
Å
晶胞参数 c
5.8099
Å
α 角
59.96
°
β 角
59.86
°
γ 角
91.26
°
空间群
P-1
点群
-1
晶体系统
Triclinic
布拉维格子
Triclinic P
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
18.62 4.7647 100.0 (1,0,1)
18.71 4.7432 76.0 (0,1,1)
18.95 4.6820 72.9 (1,0,0)
19.14 4.6370 91.9 (0,1,0)
35.99 2.4951 6.7 (2,-1,1)
36.12 2.4868 16.2 (2,-1,0)
36.13 2.4859 11.8 (1,-2,-1)
36.37 2.4700 14.2 (2,1,2)
36.42 2.4669 11.9 (0,1,2)
36.43 2.4665 13.6 (1,-2,0)
36.43 2.4662 12.4 (1,0,2)
36.57 2.4573 10.6 (1,2,2)
36.97 2.4317 10.4 (2,1,1)
36.97 2.4316 9.0 (1,0,-1)
37.12 2.4218 9.4 (0,1,-1)
37.21 2.4162 9.5 (1,2,1)
37.76 2.3824 16.1 (2,0,2)
37.94 2.3716 15.3 (0,2,2)
38.45 2.3410 14.3 (2,0,0)
38.84 2.3185 14.1 (0,2,0)
43.79 2.0674 67.7 (2,-2,0)
44.76 2.0250 62.8 (0,0,2)
44.83 2.0217 63.4 (2,2,2)
48.08 1.8925 4.7 (3,0,2)
获取直接链接

能量属性

形成能/原子
-1.25379
eV/atom
能量/原子
-5.95856
eV/atom
凸包距离
0.0668
eV/atom
未修正能量
-5.3320
eV/atom
体积/原子
9.68
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
2.0076
μB
磁有序
FiM
磁性位点数
3
磁化强度/体积
0.014820
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 · 0.571
元素家族
Metalloid-Nonmetal
溶质分数
0.429
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
1.1537
高熵判据(>1.0 视为高熵)
混合熵 ΔS
9.5922
J/mol·K
Ω 参数
1.2581
Ω > 1.1 利于固溶体形成
原子尺寸错配 δr
41.185%
δr < 6.6% 利于单相固溶
电负性差 Δχ
0.9592
越小混合越稳定
价电子浓度 VEC
5.286
价电子浓度,影响相稳定性
混合焓 ΔH_mix
-4.138
kJ/mol 且负值为放热混合
熵归一化
0.8322
固溶体倾向
0
相趋势
IM

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-754020
参考引用

The crystal structure and related material properties of LiCoCuO4 were obtained from the Materials Project database (MP-ID: mp-754020, 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_LiCoCuO4
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   5.81568746
_cell_length_b   5.75396065
_cell_length_c   5.80989902
_cell_angle_alpha   59.95685016
_cell_angle_beta   59.85717141
_cell_angle_gamma   91.25651279
_symmetry_Int_Tables_number   1
_chemical_formula_structural   LiCoCuO4
_chemical_formula_sum   'Li2 Co2 Cu2 O8'
_cell_volume   135.49119981
_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
  Li  Li0  1  0.50000000  0.00000000  0.50000000  1.0
  Li  Li1  1  0.50000000  0.50000000  0.00000000  1.0
  Co  Co2  1  0.00000000  0.50000000  0.50000000  1.0
  Co  Co3  1  0.50000000  0.00000000  0.00000000  1.0
  Cu  Cu4  1  0.00000000  0.00000000  0.50000000  1.0
  Cu  Cu5  1  0.00000000  0.00000000  0.00000000  1.0
  O  O6  1  0.74781000  0.79313300  0.96572100  1.0
  O  O7  1  0.26034100  0.75691900  0.45343400  1.0
  O  O8  1  0.75426400  0.24021300  0.97760500  1.0
  O  O9  1  0.78938700  0.75209700  0.49127000  1.0
  O  O10  1  0.21061300  0.24790300  0.50873000  1.0
  O  O11  1  0.24573600  0.75978700  0.02239500  1.0
  O  O12  1  0.73965900  0.24308100  0.54656600  1.0
  O  O13  1  0.25219000  0.20686700  0.03427900  1.0
获取直接链接