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ScNiP

Elasticity Data ELA

MP-ID: mp-961675 · Space group: F-43m (#216)

Basic Information

Formula
ScNiP
MP-ID
mp-961675
Elements
3
Sites
3
Density
4.8949
g/cm³
Volume
45.67
ų
Cell a
4.0122
Å
Cell b
4.0122
Å
Cell c
4.0122
Å
α Angle
60.00
°
β Angle
60.00
°
γ Angle
60.00
°
Space Group
F-43m
Point Group
-43m
Crystal System
Cubic
Bravais Lattice
Cubic F
Stability
No
Packing Fraction
0.7400

X-ray Diffraction

Diffraction Pattern
X-axis: 2θ (°); Y-axis: relative intensity; CuKa ; λ=1.5406 Å
Diffraction Peaks (Top 7)
2θd (Å)Ihkl
27.22 3.2759 63.7 (1,1,1)
45.20 2.0061 100.0 (2,1,1)
53.57 1.7108 26.9 (2,2,1)
65.84 1.4185 14.9 (2,2,0)
72.63 1.3017 9.9 (3,2,2)
83.46 1.1582 29.9 (3,3,2)
89.82 1.0920 7.4 (3,3,3)
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Energy Properties

Formation Energy/atom
-1.03395
eV/atom
Energy/atom
-6.87665
eV/atom
Energy above Hull
0.1688
eV/atom
Uncorrected Energy
-6.8767
eV/atom
Volume/atom
15.22
ų
c/a Ratio
-

Electronic Properties

Metallic
Non-metal
Band Gap
0.596
eV
Direct Gap
No
CBM
N/A
eV

Magnetic Properties

Magnetic
No
Total Mag. Moment
0.0011
μB
Mag. Ordering
NM
Mag. Sites
0
Magnetization/Volume
0.000020
μB/ų

Elastic Properties

KVRH
129.129
GPa
GVRH
70.695
GPa
Young's Modulus E
179.354
GPa
Poisson Ratio ν
0.269
Pugh Ratio K/G
1.827
Vickers Hardness Est.
8.935
GPa
Ductility
Brittle
Anisotropy
0.027
Lame λ
81.999
GPa

Feature Analysis

Composition Overview

Element Composition (atomic fraction)
Composition Info
Major / Matrix Element
Sc · 0.333
Element Family
3d-TM
Solute Fraction
0.667
Interstitial Fraction
0.333

Elasticity Features

Elastic Modulus Comparison (GPa)
Elastic Features
Elastic Anisotropy AU
0.0270
Homogeneous Poisson ν
0.2690
Debye Temperature
507.8
K
Sound Velocity
4,228.4
m/s
Homogeneity
0.2690

Related Tasks

Citation & References

Materials Project Page
https://materialsproject.org/materials/mp-961675
Reference Citation

The crystal structure and related material properties of ScNiP were obtained from the Materials Project database (MP-ID: mp-961675, 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_ScNiP
_symmetry_space_group_name_H-M   'P 1'
_cell_length_a   4.01217479
_cell_length_b   4.01217479
_cell_length_c   4.01217479
_cell_angle_alpha   60.00000000
_cell_angle_beta   60.00000000
_cell_angle_gamma   60.00000000
_symmetry_Int_Tables_number   1
_chemical_formula_structural   ScNiP
_chemical_formula_sum   'Sc1 Ni1 P1'
_cell_volume   45.66931902
_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
  Sc  Sc0  1  0.50000000  0.50000000  0.50000000  1.0
  Ni  Ni1  1  0.25000000  0.25000000  0.25000000  1.0
  P  P2  1  0.00000000  0.00000000  0.00000000  1.0
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