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HEAS Data Platform · 材料科学计算数据库

Al3Pd2

传统材料 TRA 弹性数据 ELA

MP-ID: mp-10901 · 空间群: P-3m1 (#164)

基础信息

化学式
Al3Pd2
MP-ID
mp-10901
元素数
2
位点数
5
密度
6.1383
g/cm³
体积
79.47
ų
晶胞参数 a
4.2122
Å
晶胞参数 b
4.2122
Å
晶胞参数 c
5.1724
Å
α 角
90.00
°
β 角
90.00
°
γ 角
120.00
°
空间群
P-3m1
点群
-3m
晶体系统
Trigonal
布拉维格子
Trigonal 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
17.14 5.1724 77.9 (0,0,0,1)
24.40 3.6478 61.2 (1,0,-1,0)
24.40 3.6478 30.6 (1,-1,0,0)
29.97 2.9811 16.4 (0,1,-1,1)
29.97 2.9811 100.0 (1,0,-1,1)
29.97 2.9811 16.4 (1,-1,0,1)
34.69 2.5862 5.2 (0,0,0,2)
42.87 2.1098 97.9 (1,0,-1,-2)
42.87 2.1098 22.9 (1,0,-1,2)
42.87 2.1098 11.5 (0,1,-1,-2)
42.87 2.1098 49.0 (1,-1,0,2)
42.94 2.1061 49.9 (1,1,-2,0)
42.94 2.1061 99.8 (2,-1,-1,0)
46.56 1.9506 11.5 (1,1,-2,1)
46.56 1.9506 5.8 (1,-2,1,-1)
46.56 1.9506 5.8 (2,-1,-1,-1)
46.56 1.9506 11.5 (2,-1,-1,1)
50.01 1.8239 4.2 (0,2,-2,0)
50.01 1.8239 4.2 (2,0,-2,0)
50.01 1.8239 4.2 (2,-2,0,0)
53.12 1.7241 5.6 (0,0,0,3)
53.25 1.7201 11.1 (2,0,-2,-1)
53.25 1.7201 6.3 (2,0,-2,1)
53.25 1.7201 3.2 (2,-2,0,-1)
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能量属性

形成能/原子
-0.81234
eV/atom
能量/原子
-14.03578
eV/atom
凸包距离
0.0000
eV/atom
未修正能量
-14.0358
eV/atom
体积/原子
15.89
ų
c/a 比
1.2280

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
127.891
GPa
剪切模量 GVRH
63.127
GPa
杨氏模量 E
162.624
GPa
泊松比 ν
0.288
Pugh 比 K/G
2.026
维氏硬度估算
6.895
GPa
韧性
Brittle
各向异性
0.261
拉梅 λ
85.806
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
Al · 0.600
元素家族
N/A
溶质分数
0.400
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
0.832
家族
Al-based Alloy
基质元素
Al · 0.600

弹性数据特征

弹性模量对比 (GPa)
弹性特征
弹性各向异性 AU
0.2610
均匀泊松比 ν
0.2880
Debye 温度
423.4
K
声速
3,576.7
m/s
均匀度
0.2880

关联任务

引用参考

Materials Project 官方页面
https://materialsproject.org/materials/mp-10901
参考引用

The crystal structure and related material properties of Al3Pd2 were obtained from the Materials Project database (MP-ID: mp-10901, database version v2026.09.28).

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_Al3Pd2
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   4.21215347
_cell_length_b   4.21215360
_cell_length_c   5.17238445
_cell_angle_alpha   89.99997111
_cell_angle_beta   90.00002479
_cell_angle_gamma   119.99995553
_symmetry_Int_Tables_number   1
_chemical_formula_structural   Al3Pd2
_chemical_formula_sum   'Al3 Pd2'
_cell_volume   79.47490367
_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
  Al  Al0  1  -0.00000000  0.00000000  -0.00000000  1.0
  Al  Al1  1  0.33333300  0.66666700  0.64492892  1.0
  Al  Al2  1  0.66666700  0.33333300  0.35507108  1.0
  Pd  Pd3  1  0.33333300  0.66666700  0.15687250  1.0
  Pd  Pd4  1  0.66666700  0.33333300  0.84312750  1.0
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