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HEAS Data Platform · 材料科学计算数据库

Te4Pt3

传统材料 TRA

MP-ID: mp-1077948 · 空间群: C2/m (#12)

基础信息

化学式
Te4Pt3
MP-ID
mp-1077948
元素数
2
位点数
7
密度
6.5986
g/cm³
体积
275.72
ų
晶胞参数 a
8.3305
Å
晶胞参数 b
8.3305
Å
晶胞参数 c
7.4259
Å
α 角
83.24
°
β 角
83.24
°
γ 角
32.62
°
空间群
C2/m
点群
2/m
晶体系统
Monoclinic
布拉维格子
Monoclinic C
稳定性
否
堆积分数
0.5240

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
11.15 7.9348 100.0 (1,1,0)
12.01 7.3698 5.1 (0,0,1)
15.37 5.7639 63.4 (1,1,1)
17.40 5.0972 17.1 (1,1,-1)
19.78 4.4884 63.3 (1,0,0)
22.84 3.8939 9.5 (1,0,1)
23.56 3.7757 7.2 (1,0,-1)
24.14 3.6872 6.8 (2,2,1)
25.37 3.5106 2.6 (1,1,2)
25.41 3.5049 15.6 (2,1,0)
26.79 3.3272 7.2 (2,2,-1)
27.27 3.2699 9.4 (2,1,1)
27.92 3.1957 6.2 (1,1,-2)
29.09 3.0699 4.3 (2,1,-1)
30.86 2.8978 1.2 (1,0,2)
31.03 2.8820 11.7 (2,2,2)
31.95 2.8008 12.0 (1,0,-2)
33.83 2.6494 2.1 (2,1,2)
33.89 2.6449 3.0 (3,3,0)
34.13 2.6267 23.4 (3,2,0)
34.60 2.5926 3.8 (3,3,1)
35.08 2.5577 3.4 (3,2,1)
35.21 2.5486 4.2 (2,2,-2)
36.58 2.4566 27.2 (0,0,3)
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能量属性

形成能/原子
0.18837
eV/atom
能量/原子
-36.40193
eV/atom
凸包距离
0.6214
eV/atom
未修正能量
-4.1559
eV/atom
体积/原子
39.39
ų
c/a 比
-

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
0.0001
μB
磁有序
NM
磁性位点数
0
磁化强度/体积
0.000000
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
Te · 0.571
元素家族
N/A
溶质分数
0.429
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
0.453
家族
Binary Alloy
基质元素
Te · 0.571

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-1077948
参考引用

The crystal structure and related material properties of Te4Pt3 were obtained from the Materials Project database (MP-ID: mp-1077948, 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_Te4Pt3
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   8.33044900
_cell_length_b   8.33044900
_cell_length_c   7.42585692
_cell_angle_alpha   83.24000632
_cell_angle_beta   83.24000632
_cell_angle_gamma   32.62332279
_symmetry_Int_Tables_number   1
_chemical_formula_structural   Te4Pt3
_chemical_formula_sum   'Te4 Pt3'
_cell_volume   275.72269286
_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
  Te  Te0  1  0.15751900  0.15751900  0.03685000  1.0
  Te  Te1  1  0.84248100  0.84248100  0.96315000  1.0
  Te  Te2  1  0.39123900  0.39123900  0.67213100  1.0
  Te  Te3  1  0.60876100  0.60876100  0.32786900  1.0
  Pt  Pt4  1  0.00000000  0.00000000  0.00000000  1.0
  Pt  Pt5  1  0.04022200  0.04022200  0.33889600  1.0
  Pt  Pt6  1  0.95977800  0.95977800  0.66110400  1.0
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