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K3NaFeCl6

高熵材料 HEA

MP-ID: mp-752477 · 空间群: R-3m (#166)

基础信息

化学式
K3NaFeCl6
MP-ID
mp-752477
元素数
4
位点数
11
密度
2.0502
g/cm³
体积
331.14
ų
晶胞参数 a
7.7768
Å
晶胞参数 b
7.7768
Å
晶胞参数 c
7.7768
Å
α 角
111.56
°
β 角
111.56
°
γ 角
111.56
°
空间群
R-3m
点群
-3m
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
13.77 6.4305 95.2 (1,0,-1)
15.05 5.8872 84.6 (1,0,0)
23.97 3.7127 4.9 (2,-1,-1)
23.97 3.7126 2.5 (1,1,-2)
26.93 3.3109 17.1 (1,1,0)
27.75 3.2153 37.9 (2,0,-2)
30.37 2.9436 13.3 (0,0,2)
30.37 2.9436 26.5 (2,0,0)
31.71 2.8218 100.0 (2,1,-2)
33.48 2.6765 24.1 (2,-1,1)
33.48 2.6765 12.1 (2,1,-1)
34.72 2.5840 83.1 (3,-1,-1)
38.96 2.3117 11.7 (1,1,1)
39.05 2.3066 3.5 (3,-1,0)
39.05 2.3066 1.8 (3,0,-1)
41.51 2.1754 2.4 (2,1,0)
41.60 2.1711 55.5 (2,-2,2)
41.60 2.1711 27.8 (2,2,-2)
42.16 2.1435 17.7 (3,0,-3)
42.63 2.1209 9.5 (3,-2,-2)
44.02 2.0571 2.7 (3,-2,1)
44.02 2.0571 1.3 (3,1,-2)
45.01 2.0142 1.3 (3,1,-3)
46.26 1.9624 27.4 (3,0,0)
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能量属性

形成能/原子
-1.87730
eV/atom
能量/原子
-4.08612
eV/atom
凸包距离
0.0518
eV/atom
未修正能量
-3.7512
eV/atom
体积/原子
30.10
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
是
总磁矩
4.0004
μB
磁有序
FM
磁性位点数
1
磁化强度/体积
0.012080
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
Cl · 0.545
元素家族
Metalloid-Nonmetal
溶质分数
0.455
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
1.1210
高熵判据(>1.0 视为高熵)
混合熵 ΔS
9.3196
J/mol·K
Ω 参数
38.6222
Ω > 1.1 利于固溶体形成
原子尺寸错配 δr
37.158%
δr < 6.6% 利于单相固溶
电负性差 Δχ
1.0868
越小混合越稳定
价电子浓度 VEC
3.818
价电子浓度,影响相稳定性
混合焓 ΔH_mix
0.093
kJ/mol 且负值为放热混合
熵归一化
0.8086
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-752477
参考引用

The crystal structure and related material properties of K3NaFeCl6 were obtained from the Materials Project database (MP-ID: mp-752477, 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_K3NaFeCl6
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   7.77682688
_cell_length_b   7.77682688
_cell_length_c   7.77682698
_cell_angle_alpha   111.55878121
_cell_angle_beta   111.55878121
_cell_angle_gamma   111.55878944
_symmetry_Int_Tables_number   1
_chemical_formula_structural   K3NaFeCl6
_chemical_formula_sum   'K3 Na1 Fe1 Cl6'
_cell_volume   331.14347329
_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
  K  K0  1  0.00000000  0.50000000  0.50000000  1.0
  K  K1  1  0.50000000  0.00000000  0.50000000  1.0
  K  K2  1  0.50000000  0.50000000  0.00000000  1.0
  Na  Na3  1  0.00000000  0.00000000  0.00000000  1.0
  Fe  Fe4  1  0.50000000  0.50000000  0.50000000  1.0
  Cl  Cl5  1  0.53165900  0.80549000  0.80549000  1.0
  Cl  Cl6  1  0.19451000  0.46834100  0.19451000  1.0
  Cl  Cl7  1  0.19451000  0.19451000  0.46834100  1.0
  Cl  Cl8  1  0.80549000  0.53165900  0.80549000  1.0
  Cl  Cl9  1  0.80549000  0.80549000  0.53165900  1.0
  Cl  Cl10  1  0.46834100  0.19451000  0.19451000  1.0
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