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Li2PdO3

弹性数据 ELA

MP-ID: mp-760483 · 空间群: C2/m (#12)

基础信息

化学式
Li2PdO3
MP-ID
mp-760483
元素数
3
位点数
12
密度
5.2037
g/cm³
体积
107.41
ų
晶胞参数 a
5.1008
Å
晶胞参数 b
5.1008
Å
晶胞参数 c
5.0589
Å
α 角
80.32
°
β 角
99.68
°
γ 角
60.05
°
空间群
C2/m
点群
2/m
晶体系统
Monoclinic
布拉维格子
Monoclinic C
稳定性
是
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
18.62 4.7647 100.0 (0,0,1)
20.11 4.4164 20.9 (1,1,0)
21.04 4.2226 37.0 (1,0,0)
23.67 3.7584 27.2 (1,0,-1)
27.54 3.2390 18.0 (1,1,1)
32.21 2.7792 11.2 (1,0,1)
35.74 2.5123 17.0 (1,-1,-1)
35.76 2.5108 33.8 (2,1,0)
37.41 2.4038 7.0 (1,-1,0)
37.44 2.4019 14.0 (2,1,-1)
37.47 2.4001 7.0 (1,0,-2)
37.76 2.3824 6.9 (0,0,2)
40.87 2.2082 2.5 (2,2,0)
41.35 2.1837 4.9 (2,0,-1)
42.83 2.1113 4.7 (2,0,0)
43.14 2.0968 4.7 (1,1,2)
43.59 2.0766 25.2 (1,-1,-2)
43.60 2.0761 50.4 (2,1,1)
45.26 2.0035 4.3 (2,2,1)
47.76 1.9042 6.6 (1,-1,1)
47.80 1.9030 13.3 (2,1,-2)
48.44 1.8792 3.9 (2,0,-2)
49.14 1.8539 3.3 (1,0,2)
52.32 1.7486 3.2 (2,0,1)
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能量属性

形成能/原子
-1.63142
eV/atom
能量/原子
-5.60502
eV/atom
凸包距离
0.0000
eV/atom
未修正能量
-9.0915
eV/atom
体积/原子
8.95
ų
c/a 比
-

电子属性

金属性
非金属
带隙
1.864
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
103.120
GPa
剪切模量 GVRH
56.718
GPa
杨氏模量 E
143.791
GPa
泊松比 ν
0.268
Pugh 比 K/G
1.818
维氏硬度估算
7.549
GPa
韧性
Brittle
各向异性
0.350
拉梅 λ
65.308
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
O · 0.500
元素家族
Metalloid-Nonmetal
溶质分数
0.500
间隙分数
0.000

弹性数据特征

弹性模量对比 (GPa)
弹性特征
弹性各向异性 AU
0.3500
均匀泊松比 ν
0.2680
Debye 温度
588.9
K
声速
3,672.9
m/s
均匀度
0.2680

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-760483
参考引用

The crystal structure and related material properties of Li2PdO3 were obtained from the Materials Project database (MP-ID: mp-760483, 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_Li2PdO3
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   5.10082048
_cell_length_b   5.10082048
_cell_length_c   5.05887629
_cell_angle_alpha   80.32120580
_cell_angle_beta   99.67879420
_cell_angle_gamma   60.04555646
_symmetry_Int_Tables_number   1
_chemical_formula_structural   Li2PdO3
_chemical_formula_sum   'Li4 Pd2 O6'
_cell_volume   107.41088670
_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
  Li  Li0  1  0.50000000  0.50000000  0.50000000  1.0
  Li  Li1  1  0.16353201  0.16353201  0.50000000  1.0
  Li  Li2  1  0.83646799  0.83646799  0.50000000  1.0
  Li  Li3  1  -0.00000000  0.00000000  0.00000000  1.0
  Pd  Pd4  1  0.33330368  0.33330368  0.00000000  1.0
  Pd  Pd5  1  0.66669632  0.66669632  0.00000000  1.0
  O  O6  1  0.26766340  0.73233660  0.76236266  1.0
  O  O7  1  0.07799832  0.57501129  0.23521106  1.0
  O  O8  1  0.42498871  0.92200168  0.23521106  1.0
  O  O9  1  0.92200168  0.42498871  0.76478894  1.0
  O  O10  1  0.57501129  0.07799832  0.76478894  1.0
  O  O11  1  0.73233660  0.26766340  0.23763734  1.0
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