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HEAS Data Platform · 材料科学计算数据库

Pu3Au

传统材料 TRA

MP-ID: mp-1186840 · 空间群: P6_3/mmc (#194)

基础信息

化学式
Pu3Au
MP-ID
mp-1186840
元素数
2
位点数
8
密度
15.3975
g/cm³
体积
200.37
ų
晶胞参数 a
6.5949
Å
晶胞参数 b
6.5911
Å
晶胞参数 c
5.3264
Å
α 角
90.01
°
β 角
90.00
°
γ 角
120.07
°
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
31.32 2.8558 29.8 (2,-2,0,0)
31.35 2.8537 29.8 (2,0,-2,0)
31.36 2.8521 29.8 (0,2,-2,0)
33.65 2.6632 100.0 (0,0,0,2)
35.67 2.5169 63.9 (2,-2,0,1)
35.67 2.5169 63.9 (2,-2,0,-1)
35.69 2.5156 63.7 (2,0,-2,-1)
35.70 2.5153 63.7 (2,0,-2,1)
35.71 2.5145 63.7 (0,2,-2,-1)
35.71 2.5141 63.6 (0,2,-2,1)
46.63 1.9477 10.2 (2,-2,0,2)
46.63 1.9477 10.2 (2,-2,0,-2)
46.65 1.9472 10.2 (2,0,-2,-2)
46.65 1.9469 10.2 (2,0,-2,2)
46.66 1.9467 10.2 (0,2,-2,-2)
46.67 1.9463 10.2 (0,2,-2,2)
55.76 1.6487 24.0 (4,-2,-2,0)
55.79 1.6478 23.9 (2,-4,2,0)
55.84 1.6465 23.8 (2,2,-4,0)
61.50 1.5078 13.7 (2,-2,0,3)
61.50 1.5078 13.7 (2,-2,0,-3)
61.51 1.5076 13.7 (2,0,-2,-3)
61.52 1.5074 13.7 (2,0,-2,3)
61.52 1.5074 13.6 (0,2,-2,-3)
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能量属性

形成能/原子
-0.15447
eV/atom
能量/原子
-77.56797
eV/atom
凸包距离
0.0332
eV/atom
未修正能量
-11.6091
eV/atom
体积/原子
25.05
ų
c/a 比
0.8076

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
36.1499
μB
磁有序
FM
磁性位点数
6
磁化强度/体积
0.180420
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
Pu · 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
0.699
家族
Binary Alloy
基质元素
Pu · 0.750

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-1186840
参考引用

The crystal structure and related material properties of Pu3Au were obtained from the Materials Project database (MP-ID: mp-1186840, 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_Pu3Au
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   6.59494061
_cell_length_b   6.59107596
_cell_length_c   5.32638302
_cell_angle_alpha   90.00614247
_cell_angle_beta   90.00407475
_cell_angle_gamma   120.06856439
_symmetry_Int_Tables_number   1
_chemical_formula_structural   Pu3Au
_chemical_formula_sum   'Pu6 Au2'
_cell_volume   200.36864193
_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
  Pu  Pu0  1  0.17237300  0.34459200  0.25001300  1.0
  Pu  Pu1  1  0.65537400  0.82762500  0.25000300  1.0
  Pu  Pu2  1  0.17230200  0.82771800  0.24999400  1.0
  Pu  Pu3  1  0.82760000  0.65520000  0.74998400  1.0
  Pu  Pu4  1  0.34474600  0.17243600  0.74999600  1.0
  Pu  Pu5  1  0.82770600  0.17245300  0.75000700  1.0
  Au  Au6  1  0.33329100  0.66667700  0.75003600  1.0
  Au  Au7  1  0.66660400  0.33329600  0.24996300  1.0
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