
Numerous experiments showed that on cold compression graphite transforms into a new superhard and transparent allotrope. Several structures with different topologies have been proposed for this phase. While experimental data are consistent with these models, the only way to solve this puzzle is to find which structure is kinetically easiest to form. Using state-of-the-art molecular-dynamics transition path sampling simulations, we investigate kinetic pathways of the pressure-induced transformation of graphite to various superhard candidate structures. Unlike hitherto applied methods for elucidating nature of superhard graphite, transition path sampling realistically models nucleation events necessary for physically meaningful transformation kinetics. We demonstrate that nucleation mechanism and kinetics lead to $M$-carbon as the final product. $W$-carbon, initially competitor to $M$-carbon, is ruled out by phase growth. Bct-C$_4$ structure is not expected to be produced by cold compression due to less probable nucleation and higher barrier of formation.
Condensed Matter - Materials Science, Materials Science (cond-mat.mtrl-sci), FOS: Physical sciences, Computational Physics (physics.comp-ph), Physics - Computational Physics, Article
Condensed Matter - Materials Science, Materials Science (cond-mat.mtrl-sci), FOS: Physical sciences, Computational Physics (physics.comp-ph), Physics - Computational Physics, Article
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 88 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
