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Cu3N

Elasticity Data ELA

MP-ID: mp-1933 · Space group: Pm-3m (#221)

Basic Information

Formula
Cu3N
MP-ID
mp-1933
Elements
2
Sites
4
Density
6.1216
g/cm³
Volume
55.51
ų
Cell a
3.8147
Å
Cell b
3.8147
Å
Cell c
3.8147
Å
α Angle
90.00
°
β Angle
90.00
°
γ Angle
90.00
°
Space Group
Pm-3m
Point Group
m-3m
Crystal System
Cubic
Bravais Lattice
Cubic P
Stability
No
Packing Fraction
0.5240

X-ray Diffraction

Diffraction Pattern
X-axis: 2θ (°); Y-axis: relative intensity; CuKa ; λ=1.5406 Å
Diffraction Peaks (Top 11)
2θd (Å)Ihkl
23.32 3.8147 63.2 (1,0,0)
33.21 2.6974 22.0 (1,1,0)
40.98 2.2024 100.0 (1,1,1)
47.68 1.9074 60.0 (2,0,0)
53.73 1.7060 22.0 (2,1,0)
59.34 1.5574 8.3 (2,1,1)
69.72 1.3487 34.3 (2,2,0)
74.64 1.2716 9.2 (2,2,1)
79.45 1.2063 3.4 (3,1,0)
84.17 1.1502 32.5 (3,1,1)
88.86 1.1012 11.5 (2,2,2)
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Energy Properties

Formation Energy/atom
0.19208
eV/atom
Energy/atom
-10.22520
eV/atom
Energy above Hull
0.1921
eV/atom
Uncorrected Energy
-4.8762
eV/atom
Volume/atom
13.88
ų
c/a Ratio
-

Electronic Properties

Metallic
Non-metal
Band Gap
0.195
eV
Direct Gap
No
CBM
N/A
eV

Magnetic Properties

Magnetic
No
Total Mag. Moment
0.0000
μB
Mag. Ordering
NM
Mag. Sites
0
Magnetization/Volume
0.000000
μB/ų

Elastic Properties

KVRH
116.742
GPa
GVRH
38.179
GPa
Young's Modulus E
103.278
GPa
Poisson Ratio ν
0.353
Pugh Ratio K/G
3.058
Vickers Hardness Est.
1.555
GPa
Ductility
Brittle
Anisotropy
3.768
Lame λ
91.289
GPa

Feature Analysis

Composition Overview

Element Composition (atomic fraction)
Composition Info
Major / Matrix Element
Cu · 0.750
Element Family
3d-TM
Solute Fraction
0.250
Interstitial Fraction
0.250

Elasticity Features

Elastic Modulus Comparison (GPa)
Elastic Features
Elastic Anisotropy AU
3.7680
Homogeneous Poisson ν
0.3530
Debye Temperature
347.9
K
Sound Velocity
2,808.8
m/s
Homogeneity
0.3530

Related Tasks

Citation & References

Materials Project Page
https://materialsproject.org/materials/mp-1933
Reference Citation

The crystal structure and related material properties of Cu3N were obtained from the Materials Project database (MP-ID: mp-1933, database version v2026.04.13).

Literature Citation

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.}
}

3D Crystal Structure Rendering

Loading 3D structure…

Style: Ball & Stick
Raw CIF Data
# generated using pymatgen
data_Cu3N
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   3.81470600
_cell_length_b   3.81470600
_cell_length_c   3.81470600
_cell_angle_alpha   90.00000000
_cell_angle_beta   90.00000000
_cell_angle_gamma   90.00000000
_symmetry_Int_Tables_number   1
_chemical_formula_structural   Cu3N
_chemical_formula_sum   'Cu3 N1'
_cell_volume   55.51153254
_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
  Cu  Cu0  1  0.00000000  0.00000000  0.50000000  1.0
  Cu  Cu1  1  0.00000000  0.50000000  0.00000000  1.0
  Cu  Cu2  1  0.50000000  0.00000000  0.00000000  1.0
  N  N3  1  0.00000000  0.00000000  0.00000000  1.0
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