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Ca6Tc2N6Cl

高熵材料 HEA

MP-ID: mp-3292047 · 空间群: R-3 (#148)

基础信息

化学式
Ca6Tc2N6Cl
MP-ID
mp-3292047
元素数
4
位点数
15
密度
4.0145
g/cm³
体积
229.97
ų
晶胞参数 a
6.1626
Å
晶胞参数 b
6.1626
Å
晶胞参数 c
6.1626
Å
α 角
95.96
°
β 角
95.96
°
γ 角
95.96
°
空间群
R-3
点群
-3
晶体系统
Trigonal
布拉维格子
Trigonal R
稳定性
是
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
14.55 6.0881 27.1 (0,1,0)
14.55 6.0881 54.3 (1,0,0)
19.39 4.5783 58.9 (1,0,-1)
19.39 4.5783 29.5 (0,1,-1)
24.33 3.6591 10.4 (1,1,-1)
24.33 3.6591 5.2 (1,-1,1)
31.29 2.8583 55.3 (2,0,-1)
31.29 2.8583 25.7 (0,1,-2)
33.91 2.6433 64.1 (2,-1,-1)
34.43 2.6047 16.6 (0,2,1)
34.43 2.6047 100.0 (2,1,0)
35.41 2.5349 33.6 (1,-1,-2)
35.41 2.5349 67.1 (2,1,-1)
39.36 2.2891 26.5 (2,0,-2)
39.61 2.2755 21.5 (2,1,1)
42.18 2.1427 8.0 (2,-1,-2)
42.18 2.1427 15.9 (2,1,-2)
44.46 2.0377 22.1 (2,2,0)
44.65 2.0294 9.4 (3,0,0)
45.44 1.9958 3.9 (3,0,-1)
45.44 1.9958 1.3 (0,1,-3)
48.93 1.8616 8.3 (1,3,0)
48.93 1.8616 16.7 (3,1,0)
49.11 1.8553 14.3 (3,1,-1)
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能量属性

形成能/原子
-1.22873
eV/atom
能量/原子
-11.56767
eV/atom
凸包距离
0.0000
eV/atom
未修正能量
-11.5677
eV/atom
体积/原子
15.33
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
0.7567
μB
磁有序
FM
磁性位点数
2
磁化强度/体积
0.003290
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
Ca · 0.400
元素家族
Alkali-AlkEarth
溶质分数
0.600
间隙分数
0.400

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
1.1822
高熵判据(>1.0 视为高熵)
混合熵 ΔS
9.8290
J/mol·K
Ω 参数
0.1057
Ω > 1.1 利于固溶体形成
原子尺寸错配 δr
41.426%
δr < 6.6% 利于单相固溶
电负性差 Δχ
0.9577
越小混合越稳定
价电子浓度 VEC
3.800
价电子浓度,影响相稳定性
混合焓 ΔH_mix
-75.010
kJ/mol 且负值为放热混合
熵归一化
0.8528
固溶体倾向
0
相趋势
AM

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-3292047
参考引用

The crystal structure and related material properties of Ca6Tc2N6Cl were obtained from the Materials Project database (MP-ID: mp-3292047, 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_Ca6Tc2N6Cl
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   6.16264264
_cell_length_b   6.16264301
_cell_length_c   6.16264251
_cell_angle_alpha   95.95857710
_cell_angle_beta   95.95858548
_cell_angle_gamma   95.95858151
_symmetry_Int_Tables_number   1
_chemical_formula_structural   Ca6Tc2N6Cl
_chemical_formula_sum   'Ca6 Tc2 N6 Cl1'
_cell_volume   229.96520195
_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
  Ca  Ca0  1  0.61261705  0.11224566  0.78414382  1.0
  Ca  Ca1  1  0.11224566  0.78414382  0.61261705  1.0
  Ca  Ca2  1  0.78414382  0.61261705  0.11224566  1.0
  Ca  Ca3  1  0.38738295  0.88775434  0.21585618  1.0
  Ca  Ca4  1  0.88775434  0.21585618  0.38738295  1.0
  Ca  Ca5  1  0.21585618  0.38738295  0.88775434  1.0
  Tc  Tc6  1  0.62211387  0.62211387  0.62211387  1.0
  Tc  Tc7  1  0.37788613  0.37788613  0.37788613  1.0
  N  N8  1  0.72926286  0.85769439  0.46933386  1.0
  N  N9  1  0.85769439  0.46933386  0.72926286  1.0
  N  N10  1  0.46933386  0.72926286  0.85769439  1.0
  N  N11  1  0.27073714  0.14230561  0.53066614  1.0
  N  N12  1  0.14230561  0.53066614  0.27073714  1.0
  N  N13  1  0.53066614  0.27073714  0.14230561  1.0
  Cl  Cl14  1  0.00000000  0.00000000  0.00000000  1.0
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