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HEAS Data Platform · 材料科学计算数据库

Sc3Sn

传统材料 TRA

MP-ID: mp-1186976 · 空间群: P6_3/mmc (#194)

基础信息

化学式
Sc3Sn
MP-ID
mp-1186976
元素数
2
位点数
8
密度
4.6041
g/cm³
体积
182.91
ų
晶胞参数 a
6.3736
Å
晶胞参数 b
6.3736
Å
晶胞参数 c
5.1993
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
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
16.06 5.5197 24.0 (1,0,-1,0)
16.06 5.5197 12.0 (1,-1,0,0)
23.51 3.7847 51.9 (1,0,-1,1)
23.51 3.7847 25.9 (1,-1,0,1)
28.00 3.1868 12.0 (1,1,-2,0)
28.00 3.1868 12.0 (2,-1,-1,0)
28.00 3.1868 12.0 (1,-2,1,0)
32.44 2.7599 47.6 (2,0,-2,0)
32.44 2.7599 23.8 (2,-2,0,0)
34.50 2.5997 80.4 (0,0,0,2)
36.87 2.4377 100.0 (2,0,-2,1)
36.87 2.4377 100.0 (0,2,-2,1)
36.87 2.4377 100.0 (2,-2,0,1)
38.27 2.3519 9.4 (1,0,-1,2)
43.37 2.0863 1.6 (2,1,-3,0)
43.37 2.0863 1.6 (3,-1,-2,0)
43.37 2.0863 1.6 (3,-2,-1,0)
45.00 2.0144 14.8 (2,-1,-1,2)
45.00 2.0144 7.4 (1,-2,1,2)
46.93 1.9362 10.7 (2,1,-3,1)
46.93 1.9362 5.3 (3,-1,-2,1)
46.93 1.9362 16.0 (3,-2,-1,1)
48.08 1.8923 30.4 (2,0,-2,2)
48.08 1.8923 15.2 (2,-2,0,2)
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能量属性

形成能/原子
-0.50463
eV/atom
能量/原子
-15.24005
eV/atom
凸包距离
0.0000
eV/atom
未修正能量
-15.2400
eV/atom
体积/原子
22.86
ų
c/a 比
0.8158

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
4.6176
μB
磁有序
Unknown
磁性位点数
0
磁化强度/体积
0.025240
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
Sc · 0.750
元素家族
N/A
溶质分数
0.250
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
0.721
家族
Binary Alloy
基质元素
Sc · 0.750

关联任务

关联的计算任务 ID(2 个)

引用参考

Materials Project 官方页面
https://materialsproject.org/materials/mp-1186976
参考引用

The crystal structure and related material properties of Sc3Sn were obtained from the Materials Project database (MP-ID: mp-1186976, 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_Sc3Sn
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   6.37360128
_cell_length_b   6.37360077
_cell_length_c   5.19933882
_cell_angle_alpha   90.00000000
_cell_angle_beta   90.00000000
_cell_angle_gamma   119.99997554
_symmetry_Int_Tables_number   1
_chemical_formula_structural   Sc3Sn
_chemical_formula_sum   'Sc6 Sn2'
_cell_volume   182.91469876
_cell_formula_units_Z   2
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
  Sc  Sc0  1  0.16905064  0.33810228  0.25000000  1.0
  Sc  Sc1  1  0.66189772  0.83094936  0.25000000  1.0
  Sc  Sc2  1  0.16905064  0.83094936  0.25000000  1.0
  Sc  Sc3  1  0.83094936  0.66189772  0.75000000  1.0
  Sc  Sc4  1  0.33810228  0.16905064  0.75000000  1.0
  Sc  Sc5  1  0.83094936  0.16905064  0.75000000  1.0
  Sn  Sn6  1  0.33333300  0.66666700  0.75000000  1.0
  Sn  Sn7  1  0.66666700  0.33333300  0.25000000  1.0
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