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HEAS Data Platform · 材料科学计算数据库

UP3

传统材料 TRA 弹性数据 ELA

MP-ID: mp-865428 · 空间群: P6_3/mmc (#194)

基础信息

化学式
UP3
MP-ID
mp-865428
元素数
2
位点数
8
密度
8.1950
g/cm³
体积
134.12
ų
晶胞参数 a
5.4212
Å
晶胞参数 b
5.4212
Å
晶胞参数 c
5.2696
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
18.90 4.6949 23.8 (0,1,-1,0)
18.90 4.6949 47.7 (1,0,-1,0)
25.41 3.5054 50.0 (0,1,-1,1)
25.41 3.5054 100.0 (1,0,-1,1)
33.05 2.7106 40.6 (1,1,-2,0)
33.05 2.7106 20.3 (2,-1,-1,0)
34.03 2.6348 47.9 (0,0,0,2)
38.34 2.3474 8.4 (0,2,-2,0)
38.34 2.3474 16.7 (2,0,-2,0)
39.21 2.2977 7.9 (0,1,-1,2)
39.21 2.2977 15.8 (1,0,-1,2)
42.14 2.1443 38.1 (0,2,-2,1)
42.14 2.1443 76.3 (2,0,-2,1)
48.16 1.8893 29.6 (1,1,-2,2)
48.16 1.8893 14.8 (2,-1,-1,2)
51.50 1.7745 1.8 (1,2,-3,0)
51.50 1.7745 1.8 (2,1,-3,0)
51.50 1.7745 1.8 (3,-1,-2,0)
52.19 1.7527 6.9 (0,2,-2,2)
52.19 1.7527 13.7 (2,0,-2,2)
54.57 1.6817 17.7 (1,2,-3,1)
54.57 1.6817 17.7 (2,1,-3,1)
54.57 1.6817 17.7 (3,-1,-2,1)
55.89 1.6452 19.2 (1,0,-1,3)
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能量属性

形成能/原子
-0.61212
eV/atom
能量/原子
-27.34919
eV/atom
凸包距离
0.1125
eV/atom
未修正能量
-27.3492
eV/atom
体积/原子
16.77
ų
c/a 比
0.9720

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
104.325
GPa
剪切模量 GVRH
79.737
GPa
杨氏模量 E
190.641
GPa
泊松比 ν
0.195
Pugh 比 K/G
1.308
维氏硬度估算
15.920
GPa
韧性
Ductile
各向异性
0.533
拉梅 λ
51.167
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
P · 0.750
元素家族
N/A
溶质分数
0.250
间隙分数
0.750

传统材料特征

ROM 混合特征雷达
评级与分类
评级 Tier
A
评分
0.566
家族
Binary Alloy
基质元素
P · 0.750

弹性数据特征

弹性模量对比 (GPa)
弹性特征
弹性各向异性 AU
0.5330
均匀泊松比 ν
0.1950
Debye 温度
611.3
K
声速
3,442.0
m/s
均匀度
0.1950

关联任务

引用参考

Materials Project 官方页面
https://materialsproject.org/materials/mp-865428
参考引用

The crystal structure and related material properties of UP3 were obtained from the Materials Project database (MP-ID: mp-865428, 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_UP3
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   5.42118207
_cell_length_b   5.42118754
_cell_length_c   5.26956768
_cell_angle_alpha   89.99999807
_cell_angle_beta   90.00000225
_cell_angle_gamma   119.99996680
_symmetry_Int_Tables_number   1
_chemical_formula_structural   UP3
_chemical_formula_sum   'U2 P6'
_cell_volume   134.12019883
_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
  U  U0  1  0.33333300  0.66666697  0.74999850  1.0
  U  U1  1  0.66666588  0.33333245  0.25000019  1.0
  P  P2  1  0.18604411  0.37208883  0.24999973  1.0
  P  P3  1  0.62791042  0.81395475  0.24999970  1.0
  P  P4  1  0.18604370  0.81395475  0.24999972  1.0
  P  P5  1  0.81393984  0.62788049  0.74999936  1.0
  P  P6  1  0.37211889  0.18605994  0.74999940  1.0
  P  P7  1  0.81394016  0.18605982  0.74999939  1.0
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