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TmNi2B2C

高熵材料 HEA 弹性数据 ELA

MP-ID: mp-6754 · 空间群: I4/mmm (#139)

基础信息

化学式
TmNi2B2C
MP-ID
mp-6754
元素数
4
位点数
6
密度
8.3093
g/cm³
体积
63.94
ų
晶胞参数 a
5.7938
Å
晶胞参数 b
5.7938
Å
晶胞参数 c
5.7938
Å
α 角
144.91
°
β 角
144.91
°
γ 角
50.46
°
空间群
I4/mmm
点群
4/mmm
晶体系统
Tetragonal
布拉维格子
Tetragonal I
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 21)
2θd (Å)Ihkl
16.92 5.2410 4.3 (1,1,-1)
26.91 3.3137 65.9 (1,0,0)
34.22 2.6205 36.8 (2,2,-2)
36.37 2.4702 42.3 (2,1,-1)
36.38 2.4698 2.9 (0,0,1)
40.37 2.2342 100.0 (1,1,0)
50.79 1.7975 14.8 (3,2,-2)
52.39 1.7464 25.5 (1,-1,1)
55.46 1.6569 1.0 (2,0,0)
59.87 1.5450 15.7 (1,0,1)
64.08 1.4533 22.9 (3,1,-1)
65.44 1.4263 24.5 (3,3,-2)
65.45 1.4260 15.4 (2,1,0)
68.13 1.3763 5.1 (4,3,-3)
72.08 1.3102 4.6 (4,4,-4)
75.97 1.2526 9.2 (3,2,-1)
77.26 1.2349 7.7 (0,0,2)
83.55 1.1572 3.1 (2,-1,1)
87.28 1.1171 9.7 (2,2,0)
88.49 1.1049 3.2 (5,4,-4)
88.52 1.1046 3.6 (3,0,0)
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能量属性

形成能/原子
-0.52166
eV/atom
能量/原子
-6.96042
eV/atom
凸包距离
0.0000
eV/atom
未修正能量
-6.9604
eV/atom
体积/原子
10.66
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
否
总磁矩
0.0028
μB
磁有序
NM
磁性位点数
0
磁化强度/体积
0.000040
μB/ų

弹性属性

体积模量 KVRH
154.321
GPa
剪切模量 GVRH
73.834
GPa
杨氏模量 E
191.035
GPa
泊松比 ν
0.294
Pugh 比 K/G
2.090
维氏硬度估算
7.456
GPa
韧性
Brittle
各向异性
0.630
拉梅 λ
105.098
GPa

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
Ni · 0.333
元素家族
3d-TM
溶质分数
0.667
间隙分数
0.500

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
1.3297
高熵判据(>1.0 视为高熵)
混合熵 ΔS
11.0548
J/mol·K
Ω 参数
0.6546
Ω > 1.1 利于固溶体形成
原子尺寸错配 δr
28.906%
δr < 6.6% 利于单相固溶
电负性差 Δχ
0.3807
越小混合越稳定
价电子浓度 VEC
7.167
价电子浓度,影响相稳定性
混合焓 ΔH_mix
-38.829
kJ/mol 且负值为放热混合
熵归一化
0.9591
固溶体倾向
0
相趋势
AM

弹性数据特征

弹性模量对比 (GPa)
弹性特征
弹性各向异性 AU
0.6300
均匀泊松比 ν
0.2940
Debye 温度
577.9
K
声速
3,326.9
m/s
均匀度
0.2940

关联任务

引用参考

Materials Project 官方页面
https://materialsproject.org/materials/mp-6754
参考引用

The crystal structure and related material properties of TmNi2B2C were obtained from the Materials Project database (MP-ID: mp-6754, 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_TmNi2B2C
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   5.79376033
_cell_length_b   5.79376033
_cell_length_c   5.79376033
_cell_angle_alpha   144.91258455
_cell_angle_beta   144.91258455
_cell_angle_gamma   50.46481237
_symmetry_Int_Tables_number   1
_chemical_formula_structural   TmNi2B2C
_chemical_formula_sum   'Tm1 Ni2 B2 C1'
_cell_volume   63.94016945
_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
  Tm  Tm0  1  0.00000000  0.00000000  0.00000000  1.0
  Ni  Ni1  1  0.75000000  0.25000000  0.50000000  1.0
  Ni  Ni2  1  0.25000000  0.75000000  0.50000000  1.0
  B  B3  1  0.35800900  0.35800900  0.00000000  1.0
  B  B4  1  0.64199100  0.64199100  0.00000000  1.0
  C  C5  1  0.50000000  0.50000000  0.00000000  1.0
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