Department of Mechanical Engineering · Bilkent University

Atomistic Mechanics & Materials Modeling Laboratory

A3ML is dedicated to advancing the understanding of the structure, mechanics and deformation physics of materials across scales, from the quantum level to the mesoscale. The research efforts are directed towards:

  • development of predictive models that will guide the design of high-performance materials;
  • multiscale modeling of plastic deformation mechanics in metallic materials, including pure metals, alloys and high-entropy alloys;
  • first-principles modeling of crystal defects — point and line defects such as vacancies and dislocations, and twin boundaries.

Methods

First-principles calculations

Density functional theory is used to obtain the energetic quantities that govern defect behaviour in metals — generalized stacking fault energies, elastic constants, and solute–defect interaction energies — which then serve as input to larger-scale models.

Atomistic simulation

Molecular statics and molecular dynamics are employed to resolve dislocation core structures and their evolution, connecting electronic-structure quantities to the lattice resistance that governs slip.

Machine learning and physics-informed models

Neural-network surrogates and physics-informed neural networks are used to extract structure–property relations in materials, so that properties can be screened across composition space and inverse-design problems can be posed.

Multiscale modeling of plasticity

Quantities determined at the atomic scale are carried into continuum descriptions of plastic deformation, linking defect-level physics to the mechanical response of pure metals, alloys and high-entropy alloys.


Selected publications

Evolving dislocation cores at twin boundaries
Evolving dislocation cores at twin boundariesInternational Journal of Plasticity, 2022
Critical stress prediction upon accurate dislocation core description
Critical stress prediction upon accurate dislocation core descriptionActa Materialia, 2022
Effect of dislocation character on the CRSS
Effect of dislocation character on the CRSSActa Materialia, 2023
CRSS determination combining ab-initio framework and surrogate neural networks
CRSS determination combining ab-initio framework and surrogate neural networksInternational Journal of Plasticity, 2023
Distorted dislocation cores and asymmetric glide resistances in titanium
Distorted dislocation cores and asymmetric glide resistances in titaniumActa Materialia, 2024
Inverse design of short-range order arrangement via neural network
Inverse design of short-range order arrangement via neural networkInternational Journal of Solids and Structures, 2025

All publications →


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