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HEAS Data Platform · 材料科学计算数据库

Na3Pu

传统材料 TRA

MP-ID: mp-1186128 · 空间群: P6_3/mmc (#194)

基础信息

化学式
Na3Pu
MP-ID
mp-1186128
元素数
2
位点数
8
密度
3.4925
g/cm³
体积
297.60
ų
晶胞参数 a
7.8585
Å
晶胞参数 b
7.8585
Å
晶胞参数 c
5.5646
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
13.01 6.8056 42.3 (1,0,-1,0)
20.62 4.3079 100.0 (1,0,-1,1)
22.63 3.9292 52.7 (2,-1,-1,0)
26.19 3.4028 20.3 (2,0,-2,0)
30.80 2.9030 80.8 (2,0,-2,1)
32.17 2.7823 16.1 (0,0,0,2)
34.84 2.5754 8.5 (1,0,-1,2)
34.88 2.5723 10.2 (3,-1,-2,0)
38.56 2.3349 39.8 (3,-1,-2,1)
39.69 2.2707 25.6 (2,-1,-1,2)
39.73 2.2685 12.7 (3,0,-3,0)
41.94 2.1539 7.8 (2,0,-2,2)
41.94 2.1539 3.9 (2,-2,0,2)
46.21 1.9646 5.9 (2,2,-4,0)
46.21 1.9646 11.7 (4,-2,-2,0)
48.18 1.8888 8.4 (3,-1,-2,2)
48.21 1.8875 1.2 (3,1,-4,0)
48.21 1.8875 2.4 (4,-1,-3,0)
51.03 1.7896 9.8 (1,0,-1,3)
51.10 1.7875 19.7 (4,-1,-3,1)
52.01 1.7582 8.0 (3,0,-3,2)
52.01 1.7582 4.0 (3,-3,0,2)
53.89 1.7014 2.8 (4,0,-4,0)
56.51 1.6286 14.6 (2,0,-2,3)
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能量属性

形成能/原子
0.48438
eV/atom
能量/原子
-23.77784
eV/atom
凸包距离
0.4844
eV/atom
未修正能量
-4.0745
eV/atom
体积/原子
37.20
ų
c/a 比
0.7081

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
14.1064
μB
磁有序
FM
磁性位点数
2
磁化强度/体积
0.047400
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
Na · 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
0.441
家族
Binary Alloy
基质元素
Na · 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-1186128
参考引用

The crystal structure and related material properties of Na3Pu were obtained from the Materials Project database (MP-ID: mp-1186128, 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_Na3Pu
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   7.85846943
_cell_length_b   7.85846943
_cell_length_c   5.56458300
_cell_angle_alpha   90.00000000
_cell_angle_beta   90.00000000
_cell_angle_gamma   119.99999523
_symmetry_Int_Tables_number   1
_chemical_formula_structural   Na3Pu
_chemical_formula_sum   'Na6 Pu2'
_cell_volume   297.60430806
_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
  Na  Na0  1  0.16061100  0.32122100  0.25000000  1.0
  Na  Na1  1  0.67877900  0.83938900  0.25000000  1.0
  Na  Na2  1  0.16061100  0.83938900  0.25000000  1.0
  Na  Na3  1  0.83938900  0.67877900  0.75000000  1.0
  Na  Na4  1  0.32122100  0.16061100  0.75000000  1.0
  Na  Na5  1  0.83938900  0.16061100  0.75000000  1.0
  Pu  Pu6  1  0.33333300  0.66666700  0.75000000  1.0
  Pu  Pu7  1  0.66666700  0.33333300  0.25000000  1.0
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