导航

HEAS Data Platform · 材料科学计算数据库

Tc

传统材料 TRA 弹性数据 ELA

MP-ID: mp-867351 · 空间群: P6_3/mmc (#194)

基础信息

化学式
Tc
MP-ID
mp-867351
元素数
1
位点数
4
密度
11.4215
g/cm³
体积
56.99
ų
晶胞参数 a
2.7394
Å
晶胞参数 b
2.7394
Å
晶胞参数 c
8.7697
Å
α 角
90.00
°
β 角
90.00
°
γ 角
120.00
°
空间群
P6_3/mmc
点群
6/mmm
晶体系统
Hexagonal
布拉维格子
Hexagonal P
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
37.93 2.3724 7.9 (1,0,-1,0)
37.93 2.3724 15.8 (1,-1,0,0)
39.34 2.2900 42.7 (1,0,-1,1)
39.34 2.2900 85.5 (1,-1,0,1)
41.17 2.1924 100.0 (0,0,0,4)
43.37 2.0865 96.8 (1,0,-1,2)
43.37 2.0865 96.8 (0,1,-1,2)
43.37 2.0865 96.8 (1,-1,0,2)
49.48 1.8421 21.8 (1,0,-1,3)
49.48 1.8421 43.6 (1,-1,0,3)
57.21 1.6101 4.7 (1,0,-1,4)
57.21 1.6101 9.3 (1,-1,0,4)
66.27 1.4103 17.7 (1,0,-1,5)
66.27 1.4103 8.8 (1,-1,0,5)
68.51 1.3697 21.3 (1,1,-2,0)
68.51 1.3697 21.3 (2,-1,-1,0)
68.51 1.3697 21.3 (1,-2,1,0)
76.56 1.2444 17.3 (1,0,-1,6)
76.56 1.2444 34.5 (1,-1,0,6)
81.97 1.1755 4.8 (2,0,-2,1)
81.97 1.1755 4.8 (0,2,-2,1)
81.97 1.1755 4.8 (2,-2,0,1)
83.16 1.1616 24.8 (1,1,-2,4)
83.16 1.1616 24.8 (2,-1,-1,4)
获取直接链接

能量属性

形成能/原子
0.00415
eV/atom
能量/原子
-25.96051
eV/atom
凸包距离
0.0042
eV/atom
未修正能量
-25.9605
eV/atom
体积/原子
14.25
ų
c/a 比
3.2014

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
0.0000
μB
磁有序
Unknown
磁性位点数
0
磁化强度/体积
0.000000
μB/ų

弹性属性

体积模量 KVRH
299.670
GPa
剪切模量 GVRH
149.971
GPa
杨氏模量 E
385.590
GPa
泊松比 ν
0.286
Pugh 比 K/G
1.998
维氏硬度估算
13.682
GPa
韧性
Brittle
各向异性
0.066
拉梅 λ
199.689
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
Tc · 1.000
元素家族
N/A
溶质分数
0.000
间隙分数
0.000

传统材料特征

ROM 混合特征雷达
评级与分类
评级 Tier
A
评分
0.570
家族
Pure Metal
基质元素
Tc · 1.000

弹性数据特征

弹性模量对比 (GPa)
弹性特征
弹性各向异性 AU
0.0660
均匀泊松比 ν
0.2860
均匀度
0.2860

关联任务

引用参考

Materials Project 官方页面
https://materialsproject.org/materials/mp-867351
参考引用

The crystal structure and related material properties of Tc were obtained from the Materials Project database (MP-ID: mp-867351, 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_Tc
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   2.73935562
_cell_length_b   2.73935496
_cell_length_c   8.76968444
_cell_angle_alpha   90.00000000
_cell_angle_beta   90.00000000
_cell_angle_gamma   119.99998335
_symmetry_Int_Tables_number   1
_chemical_formula_structural   Tc
_chemical_formula_sum   Tc4
_cell_volume   56.99167192
_cell_formula_units_Z   4
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
  Tc  Tc0  1  -0.00000000  -0.00000000  -0.00000000  1.0
  Tc  Tc1  1  0.33333300  0.66666600  0.25000000  1.0
  Tc  Tc2  1  -0.00000000  -0.00000000  0.50000000  1.0
  Tc  Tc3  1  0.66666600  0.33333300  0.75000000  1.0
获取直接链接