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ErSF

弹性数据 ELA

MP-ID: mp-10932 · 空间群: P4/nmm (#129)

基础信息

化学式
ErSF
MP-ID
mp-10932
元素数
3
位点数
6
密度
7.7393
g/cm³
体积
93.69
ų
晶胞参数 a
3.7200
Å
晶胞参数 b
3.7200
Å
晶胞参数 c
6.7700
Å
α 角
90.00
°
β 角
90.00
°
γ 角
90.00
°
空间群
P4/nmm
点群
4/mmm
晶体系统
Tetragonal
布拉维格子
Tetragonal P
稳定性
否
堆积分数
0.6800

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
13.08 6.7700 3.8 (0,0,1)
26.33 3.3850 31.6 (0,0,2)
27.36 3.2603 100.0 (1,0,1)
34.08 2.6305 48.5 (1,1,0)
35.87 2.5036 16.6 (1,0,2)
43.57 2.0770 52.8 (1,1,2)
47.10 1.9294 32.7 (1,0,3)
48.97 1.8600 25.3 (2,0,0)
53.50 1.7127 3.0 (1,1,3)
54.19 1.6925 3.4 (0,0,4)
56.45 1.6301 16.1 (2,0,2)
57.00 1.6156 27.5 (2,1,1)
60.06 1.5405 6.6 (1,0,4)
62.17 1.4931 6.3 (2,1,2)
65.59 1.4233 4.3 (1,1,4)
69.41 1.3540 1.6 (0,0,5)
70.30 1.3391 19.8 (2,1,3)
71.77 1.3152 7.8 (2,2,0)
74.59 1.2723 7.5 (1,0,5)
76.03 1.2518 4.8 (2,0,4)
77.93 1.2259 6.5 (2,2,2)
78.40 1.2197 5.5 (3,0,1)
79.64 1.2039 2.7 (1,1,5)
81.05 1.1864 5.7 (2,1,4)
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能量属性

形成能/原子
-3.29840
eV/atom
能量/原子
-6.83830
eV/atom
凸包距离
0.0024
eV/atom
未修正能量
-18.3523
eV/atom
体积/原子
15.61
ų
c/a 比
1.8199

电子属性

金属性
非金属
带隙
1.326
eV
直接带隙
是
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
108.999
GPa
剪切模量 GVRH
58.212
GPa
杨氏模量 E
148.245
GPa
泊松比 ν
0.273
Pugh 比 K/G
1.872
维氏硬度估算
7.348
GPa
韧性
Brittle
各向异性
0.121
拉梅 λ
70.191
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
Er · 0.333
元素家族
Lanthanide
溶质分数
0.667
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
0.1210
均匀泊松比 ν
0.2730
Debye 温度
689.2
K
声速
3,053.3
m/s
均匀度
0.2730

关联任务

引用参考

Materials Project 官方页面
https://materialsproject.org/materials/mp-10932
参考引用

The crystal structure and related material properties of ErSF were obtained from the Materials Project database (MP-ID: mp-10932, 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_ErSF
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   3.72002033
_cell_length_b   3.72002033
_cell_length_c   6.76997952
_cell_angle_alpha   90.00000000
_cell_angle_beta   90.00000000
_cell_angle_gamma   90.00000000
_symmetry_Int_Tables_number   1
_chemical_formula_structural   ErSF
_chemical_formula_sum   'Er2 S2 F2'
_cell_volume   93.68670859
_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
  Er  Er0  1  0.75000000  0.75000000  0.77310122  1.0
  Er  Er1  1  0.25000000  0.25000000  0.22689878  1.0
  S  S2  1  0.25000000  0.25000000  0.64456238  1.0
  S  S3  1  0.75000000  0.75000000  0.35543762  1.0
  F  F4  1  0.25000000  0.75000000  0.00000000  1.0
  F  F5  1  0.75000000  0.25000000  0.00000000  1.0
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