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B4C

弹性数据 ELA

MP-ID: mp-1238815 · 空间群: Cm (#8)

基础信息

化学式
B4C
MP-ID
mp-1238815
元素数
2
位点数
15
密度
2.5419
g/cm³
体积
108.29
ų
晶胞参数 a
5.0465
Å
晶胞参数 b
5.1948
Å
晶胞参数 c
5.1948
Å
α 角
65.15
°
β 角
66.05
°
γ 角
66.05
°
空间群
Cm
点群
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
19.64 4.5200 17.3 (0,1,0)
19.64 4.5200 17.3 (0,0,1)
20.08 4.4221 3.5 (1,0,0)
22.19 4.0067 63.8 (1,1,1)
23.19 3.8359 71.6 (0,1,1)
23.82 3.7351 46.8 (1,1,0)
23.82 3.7351 46.8 (1,0,1)
32.00 2.7970 13.9 (0,1,-1)
32.08 2.7898 18.9 (1,0,-1)
34.84 2.5752 60.6 (1,2,1)
34.84 2.5752 60.6 (1,1,2)
35.79 2.5087 64.4 (2,1,1)
37.73 2.3843 96.3 (1,-1,-1)
38.07 2.3638 100.0 (1,1,-1)
38.07 2.3638 100.0 (1,-1,1)
38.72 2.3258 1.2 (0,2,1)
38.72 2.3258 1.2 (0,1,2)
39.28 2.2935 2.7 (1,2,0)
39.28 2.2935 2.7 (1,0,2)
39.99 2.2548 3.6 (2,1,0)
39.99 2.2548 3.6 (2,0,1)
45.26 2.0033 1.3 (2,2,2)
50.28 1.8145 2.1 (1,-2,0)
50.28 1.8145 2.1 (1,0,-2)
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能量属性

形成能/原子
-0.13057
eV/atom
能量/原子
-7.99710
eV/atom
凸包距离
0.0000
eV/atom
未修正能量
-7.9971
eV/atom
体积/原子
7.22
ų
c/a 比
-

电子属性

金属性
非金属
带隙
3.242
eV
直接带隙
否
导带底 CBM
N/A
eV

磁性属性

磁性
否
总磁矩
0.0000
μB
磁有序
NM
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
238.023
GPa
剪切模量 GVRH
184.835
GPa
杨氏模量 E
440.486
GPa
泊松比 ν
0.192
Pugh 比 K/G
1.288
维氏硬度估算
28.520
GPa
韧性
Ductile
各向异性
0.501
拉梅 λ
114.800
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
B · 0.800
元素家族
Metalloid-Nonmetal
溶质分数
0.200
间隙分数
1.000

弹性数据特征

弹性模量对比 (GPa)
弹性特征
弹性各向异性 AU
0.5010
均匀泊松比 ν
0.1920
Debye 温度
1,448.5
K
声速
9,405.5
m/s
均匀度
0.1920

关联任务

关联的计算任务 ID(1 个)

引用参考

Materials Project 官方页面
https://materialsproject.org/materials/mp-1238815
参考引用

The crystal structure and related material properties of B4C were obtained from the Materials Project database (MP-ID: mp-1238815, 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_B4C
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   5.04646593
_cell_length_b   5.19479252
_cell_length_c   5.19477907
_cell_angle_alpha   65.15271732
_cell_angle_beta   66.04617268
_cell_angle_gamma   66.04606697
_symmetry_Int_Tables_number   1
_chemical_formula_structural   B4C
_chemical_formula_sum   'B12 C3'
_cell_volume   108.28781432
_cell_formula_units_Z   3
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
  B  B0  1  0.83739316  0.50818714  0.50832026  1.0
  B  B1  1  0.48467638  0.17578767  0.49794280  1.0
  B  B2  1  0.50469531  0.83109682  0.50613717  1.0
  B  B3  1  0.48467604  0.49781151  0.17591985  1.0
  B  B4  1  0.50469560  0.50600438  0.83122934  1.0
  B  B5  1  0.18075553  0.69337798  0.69350738  1.0
  B  B6  1  0.81175301  0.31002864  0.31016019  1.0
  B  B7  1  0.69481862  0.18808678  0.69702729  1.0
  B  B8  1  0.29914309  0.81754820  0.30396350  1.0
  B  B9  1  0.69481868  0.69689492  0.18821656  1.0
  B  B10  1  0.29914286  0.30383447  0.81767766  1.0
  B  B11  1  0.98897429  0.99947612  0.99960816  1.0
  C  C12  1  0.17505190  0.49695927  0.49709092  1.0
  C  C13  1  0.88191391  0.87574306  0.87587383  1.0
  C  C14  1  0.10357464  0.12051503  0.12064412  1.0
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