arXiv subjects

Nicholas Taormina

Publications and source records attributed to Nicholas Taormina.

3 recordsLinked to original sources

arXiv2025

Machine-Learned Interatomic Potential for Predictive Simulation of MoS2 Epitaxy

A machine-learned interatomic potential (MLIP) for multilayer MoS2 was developed using the ultra-fast force field (UF3) framework. The UF3 MLIP reproduces key properties in strong agreement with DFT including lattice constants, interlayer binding energies, and phase-stability. Furthermore, the potential reasonably captures the phonon spectra and the highly anisotropic elastic tensor across monolayer (1H) and bulk (2H, 3R) MoS2 phases. Critically, defect and edge formation energies are captured with high fidelity, exhibiting a strong correlation with DFT (R^2 = 0.91) across ten defective monolayers and reproducing the relative difference between the free energies of zigzag and armchair edges within 5% of DFT. Non-equilibrium molecular dynamics simulations reveal layered homoepitaxial growth consistent with experimental observations, demonstrating the formation of van der Waals gaps between successive epilayers and triangular domains bounded by zigzag edges. The robust UF3 MLIP, which is only ~2X slower than the fastest empirical potentials, enables large-scale atomistic simulations of MoS2 epitaxial growth.

cond-mat.mtrl-sci↗

arXiv2025

Machine-learning interatomic potential for AlN for epitaxial simulation

A machine learned interatomic potential for AlN was developed using the ultra-fast force field (UF3) methodology. A strong agreement with density functional theory calculations in predicting key structural and mechanical properties, including lattice constants, elastic constants, cohesive energy, and surface energies has been demonstrated. The potential was also shown to accurately reproduce the experimentally observed atomic core structure of edge dislocations. Most significantly, it reproduced the experimentally observed wurtzite crystal structure in the overlayer during homoepitaxial growth of AlN on wurtzite AlN, something that prior potentials failed to achieve. Additionally, the potential reproduced the experimentally observed layer-by-layer growth mode in the epilayer. The combination of accuracy, transferability, and computational speed afforded by the UF3 framework thus makes large-scale, atomistic simulations of epitaxial growth of AlN feasible.

cond-mat.mtrl-sci↗

arXiv2025

Effect of Misfit and Threading Dislocations on Surface Energies of PbTe-PbSe Interfaces

This work quantifies the effect of misfit and threading dislocations on the surface energies of PbTe-PbSe interfaces, with the defect structures of the interfaces being obtained from atomistic and multiscale simulations of their manufacturing processes. Simulation results show that direct bonding produces semi-coherent interfaces with two-dimensional misfit dislocation networks, while heteroepitaxial processes produce complex three-dimensional dislocation structures with both misfit and threading dislocations. Surface energies at these interfaces were determined by computing the interaction energies across these interfaces. Compared with coherent interfaces, directly bonded interfaces exhibit up to ~23% lower surface energy, while the surface energies of epitaxially grown interfaces can be nearly 50% lower. The results demonstrate the significant effects of dislocations on interfacial energy.

cond-mat.mtrl-sci↗