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HEAS Data Platform · 材料科学计算数据库

FeO

传统材料 TRA

MP-ID: mp-753682 · 空间群: P4_2/mmc (#131)

基础信息

化学式
FeO
MP-ID
mp-753682
元素数
2
位点数
8
密度
4.7067
g/cm³
体积
101.39
ų
晶胞参数 a
4.3075
Å
晶胞参数 b
4.3075
Å
晶胞参数 c
6.2561
Å
α 角
69.86
°
β 角
69.86
°
γ 角
90.00
°
空间群
P4_2/mmc
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
29.32 3.0459 12.5 (1,1,1)
29.32 3.0459 12.5 (1,-1,0)
32.78 2.7321 55.0 (0,0,2)
33.69 2.6606 100.0 (1,1,2)
33.69 2.6605 100.0 (1,-1,-1)
33.69 2.6605 100.0 (1,-1,1)
33.69 2.6604 100.0 (1,1,0)
41.95 2.1538 56.3 (2,0,1)
44.55 2.0339 3.1 (1,1,3)
44.55 2.0338 3.1 (1,-1,-2)
44.55 2.0338 3.1 (1,-1,2)
44.55 2.0337 3.1 (1,1,-1)
54.23 1.6915 36.2 (0,2,3)
54.23 1.6915 36.2 (2,0,3)
54.23 1.6914 72.3 (2,0,-1)
59.09 1.5633 17.5 (1,1,4)
59.10 1.5632 17.5 (1,-1,-3)
59.10 1.5632 17.5 (1,-1,3)
59.10 1.5632 17.5 (1,1,-2)
60.82 1.5230 24.3 (2,2,2)
60.82 1.5229 24.3 (2,-2,0)
68.71 1.3661 16.0 (0,0,4)
68.94 1.3622 1.1 (3,1,2)
68.94 1.3622 1.1 (3,-1,1)
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能量属性

形成能/原子
-1.39442
eV/atom
能量/原子
-8.10341
eV/atom
凸包距离
0.0871
eV/atom
未修正能量
-6.6319
eV/atom
体积/原子
12.67
ų
c/a 比
1.4524

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
AFM
磁性位点数
4
磁化强度/体积
0.000000
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
Fe · 0.500
元素家族
N/A
溶质分数
0.500
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
0.651
家族
Fe-rich Alloy
基质元素
Fe · 0.500

关联任务

引用参考

Materials Project 官方页面
https://materialsproject.org/materials/mp-753682
参考引用

The crystal structure and related material properties of FeO were obtained from the Materials Project database (MP-ID: mp-753682, 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_FeO
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   4.30754178
_cell_length_b   4.30754178
_cell_length_c   6.25608833
_cell_angle_alpha   69.85860741
_cell_angle_beta   69.85861979
_cell_angle_gamma   89.99879603
_symmetry_Int_Tables_number   1
_chemical_formula_structural   FeO
_chemical_formula_sum   'Fe4 O4'
_cell_volume   101.38798594
_cell_formula_units_Z   4
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
  Fe  Fe0  1  0.50000000  0.00000200  0.50000000  1.0
  Fe  Fe1  1  0.25000100  0.24999900  0.00000000  1.0
  Fe  Fe2  1  0.00000000  0.50000000  0.50000000  1.0
  Fe  Fe3  1  0.75000200  0.74999800  0.00000000  1.0
  O  O4  1  0.37499400  0.37499500  0.24999800  1.0
  O  O5  1  0.87499300  0.87499300  0.24999900  1.0
  O  O6  1  0.12500400  0.12500600  0.75000200  1.0
  O  O7  1  0.62500700  0.62500700  0.75000100  1.0
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