The Challenge
Democratizing Computational Exploration of Crystal Growth
Investigating the crystal growth, stability, and properties of nanoparticles is experimentally slow, expensive, and limited to materials already synthesized. The Crystallography Open Database contains over 50,000 crystal structures, yet no computational tool existed to systematically explore their potential behavior as nanoparticles.
NanoConstruct addresses this gap by extending ASCOT's capabilities to any material and ellipsoidal geometries. Users can upload crystal structure files (CIF) from public databases, perform hypothetical element substitutions, and computationally investigate crystal growth, stability, and atomistic properties — accelerating Safe and Sustainable by Design innovation without requiring programming expertise.
Our Approach
A generic computational workflow to explore crystal growth of any material at the nanoscale
Load CIF and visualize unit cell
Upload any material's crystallographic information file (CIF) directly from the Crystallography Open Database. The tool validates the structure and provides immediate 3D visualization of the unit cell, making it accessible to non-experts.
Optional element substitution
Perform in silico element substitutions using same-group neighbors or adjacent rows of the periodic table to explore hypothetical material variants without requiring synthesis. This enables rapid screening of structural stability and property changes.
Define NP geometry
Specify nanoparticle geometry as spherical or ellipsoidal with custom axes and rotation angles. Replicate the unit cell into a bounding box and remove atoms outside the target shape while enforcing stoichiometric correctness via iterative shell removal (4 Å surface thickness).
Energy minimization
Apply molecular dynamics energy minimization using LAMMPS with conjugate gradient method and appropriate force fields from the OpenKIM database. Reactive force fields enable bond breaking and formation at NP surfaces for realistic crystal structures.
Calculate atomistic descriptors
Automatically compute geometrical (surface area, volume, ellipsoid axes) and atomistic (potential energy, coordination numbers, common neighbour parameters, hexatic order) descriptors. Results are separated into core and shell regions for detailed analysis of crystal growth patterns.