Abstract

This study examines the roughness of mechanically cleaved edges in 2D crystals and glasses using molecular dynamics simulations with chemically accurate machine-learning force fields. Our results show that ultra-flat armchair and zigzag edges can be achieved in graphene by aligning the loading direction with specific lattice orientations. Deviations from these orientations create kinks between the atomically smooth armchair and zigzag segments, with increased irregularities when dynamic effects are considered. Fracture mechanics analysis highlights the kinetic and dynamic factors contributing to crack deflection and edge roughening. In three-atom-thick 2D silica crystals, the relationship between edge morphologies and cleavage conditions is modified by their bilayer structure and sublattice asymmetry. In 2D silica glasses, this correlation is further disrupted by topological disorder. These insights are crucial for minimizing edge roughness in 2D materials, which is essential for their performance in mechanical and electronic applications.

Abstract

This study examines the roughness of mechanically cleaved edges in 2D crystals and glasses using molecular dynamics simulations with chemically accurate machine-learning force fields. Our results show that ultra-flat armchair and zigzag edges can be achieved in graphene by aligning the loading direction with specific lattice orientations. Deviations from these orientations create kinks between the atomically smooth armchair and zigzag segments, with increased irregularities when dynamic effects are considered. Fracture mechanics analysis highlights the kinetic and dynamic factors contributing to crack deflection and edge roughening. In three-atom-thick 2D silica crystals, the relationship between edge morphologies and cleavage conditions is modified by their bilayer structure and sublattice asymmetry. In 2D silica glasses, this correlation is further disrupted by topological disorder. These insights are crucial for minimizing edge roughness in 2D materials, which is essential for their performance in mechanical and electronic applications.

Abstract

This study examines the roughness of mechanically cleaved edges in 2D crystals and glasses using molecular dynamics simulations with chemically accurate machine-learning force fields. Our results show that ultra-flat armchair and zigzag edges can be achieved in graphene by aligning the loading direction with specific lattice orientations. Deviations from these orientations create kinks between the atomically smooth armchair and zigzag segments, with increased irregularities when dynamic effects are considered. Fracture mechanics analysis highlights the kinetic and dynamic factors contributing to crack deflection and edge roughening. In three-atom-thick 2D silica crystals, the relationship between edge morphologies and cleavage conditions is modified by their bilayer structure and sublattice asymmetry. In 2D silica glasses, this correlation is further disrupted by topological disorder. These insights are crucial for minimizing edge roughness in 2D materials, which is essential for their performance in mechanical and electronic applications.

Abstract

This study examines the roughness of mechanically cleaved edges in 2D crystals and glasses using molecular dynamics simulations with chemically accurate machine-learning force fields. Our results show that ultra-flat armchair and zigzag edges can be achieved in graphene by aligning the loading direction with specific lattice orientations. Deviations from these orientations create kinks between the atomically smooth armchair and zigzag segments, with increased irregularities when dynamic effects are considered. Fracture mechanics analysis highlights the kinetic and dynamic factors contributing to crack deflection and edge roughening. In three-atom-thick 2D silica crystals, the relationship between edge morphologies and cleavage conditions is modified by their bilayer structure and sublattice asymmetry. In 2D silica glasses, this correlation is further disrupted by topological disorder. These insights are crucial for minimizing edge roughness in 2D materials, which is essential for their performance in mechanical and electronic applications.