导航

HEAS Data Platform · 材料科学计算数据库

CeMg6Mn

高熵材料 HEA 传统材料 TRA

MP-ID: mp-1023140 · 空间群: Amm2 (#38)

基础信息

化学式
CeMg6Mn
MP-ID
mp-1023140
元素数
3
位点数
8
密度
3.2022
g/cm³
体积
176.77
ų
晶胞参数 a
6.8538
Å
晶胞参数 b
6.8538
Å
晶胞参数 c
4.5995
Å
α 角
90.00
°
β 角
90.00
°
γ 角
125.10
°
空间群
Amm2
点群
mm2
晶体系统
Orthorhombic
布拉维格子
Orthorhombic 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
14.56 6.0821 62.5 (1,-1,0)
15.80 5.6074 100.0 (1,0,0)
19.30 4.5995 9.6 (0,0,1)
24.26 3.6686 9.6 (1,-1,1)
25.04 3.5562 20.7 (1,0,1)
26.11 3.4126 35.0 (2,-1,0)
28.25 3.1594 11.9 (1,1,0)
29.37 3.0411 5.5 (2,-2,0)
31.92 2.8037 60.8 (2,0,0)
32.67 2.7406 15.3 (2,-1,1)
34.44 2.6042 4.6 (1,1,1)
35.38 2.5367 56.4 (2,-2,1)
37.57 2.3940 52.1 (2,0,1)
39.17 2.2998 29.0 (0,0,2)
39.70 2.2704 11.3 (3,-2,0)
41.20 2.1910 8.8 (3,-1,0)
42.00 2.1511 8.8 (1,-1,2)
42.48 2.1278 8.2 (1,0,2)
42.48 2.1278 8.2 (0,1,2)
43.61 2.0754 7.1 (2,1,0)
44.50 2.0359 14.6 (3,-2,1)
44.70 2.0274 1.8 (3,-3,0)
45.88 1.9780 3.1 (3,-1,1)
45.88 1.9780 3.1 (1,-3,1)
获取直接链接

能量属性

形成能/原子
0.24206
eV/atom
能量/原子
-2.86817
eV/atom
凸包距离
0.2444
eV/atom
未修正能量
-2.8682
eV/atom
体积/原子
22.10
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
0.0262
μB
磁有序
FM
磁性位点数
1
磁化强度/体积
0.000150
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
Mg · 0.750
元素家族
Alkali-AlkEarth
溶质分数
0.250
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
0.7356
高熵判据(>1.0 视为高熵)
混合熵 ΔS
6.1160
J/mol·K
Ω 参数
3.0865
Ω > 1.1 利于固溶体形成
原子尺寸错配 δr
9.184%
δr < 6.6% 利于单相固溶
电负性差 Δχ
0.1080
越小混合越稳定
价电子浓度 VEC
2.750
价电子浓度,影响相稳定性
混合焓 ΔH_mix
-2.013
kJ/mol 且负值为放热混合
熵归一化
0.6696
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
0.711
家族
Mg-based Alloy
基质元素
Mg · 0.750

关联任务

关联的计算任务 ID(1 个)

引用参考

Materials Project 官方页面
https://materialsproject.org/materials/mp-1023140
参考引用

The crystal structure and related material properties of CeMg6Mn were obtained from the Materials Project database (MP-ID: mp-1023140, 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_CeMg6Mn
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   6.85376076
_cell_length_b   6.85376020
_cell_length_c   4.59952469
_cell_angle_alpha   90.00000000
_cell_angle_beta   90.00000000
_cell_angle_gamma   125.10000056
_symmetry_Int_Tables_number   1
_chemical_formula_structural   CeMg6Mn
_chemical_formula_sum   'Ce1 Mg6 Mn1'
_cell_volume   176.76797319
_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
  Ce  Ce0  1  0.28630748  0.21369252  0.75000000  1.0
  Mg  Mg1  1  0.17658593  0.83472324  0.25000000  1.0
  Mg  Mg2  1  0.66527676  0.32341407  0.25000000  1.0
  Mg  Mg3  1  0.67982618  0.82017382  0.25000000  1.0
  Mg  Mg4  1  0.31667521  0.68022924  0.75000000  1.0
  Mg  Mg5  1  0.81977076  0.18332479  0.75000000  1.0
  Mg  Mg6  1  0.83727683  0.66272317  0.75000000  1.0
  Mn  Mn7  1  0.21828084  0.28171916  0.25000000  1.0
获取直接链接