Carbon under pressure

Autor: Bertil Sundqvist
Rok vydání: 2021
Předmět:
Zdroj: Physics Reports. 909:1-73
ISSN: 0370-1573
Popis: Carbon is an element with extremely versatile bonding properties and theoretical calculations have suggested the possible existence of several hundred structural allotropes. Many, or even most, of these are predicted to be formed under conditions of high pressure and temperature. On the other hand, experimental high pressure studies have identified surprisingly few structural allotropes. In this paper, physical properties and structural transformations observed in high pressure experiments, at and above room temperature, are reviewed for a large number of solid carbon allotropes. The materials discussed include bulk carbon such as graphite, diamond, glass-like and amorphous carbon, two-dimensional graphene, and molecular carbon in the form of one-dimensional carbon nanotubes and zero-dimensional fullerenes. Results from recent studies on twisted graphene, graphdiyne, graphyne, carbon dots and other interesting all-carbon allotropes are also briefly described. Observed similarities and differences between the high pressure behavior and evolution of carbon materials are discussed. In spite of the enormous volume of experimental work carried out on these materials, few new structural allotropes have been identified and most carbon materials studied convert into diamond at sufficiently high temperature and pressure. Further theoretical work thus seems to be needed to elucidate possible transformation processes and transition paths for the many undiscovered allotropes proposed from calculations. In particular, it is recommended that, for every new allotrope predicted by theory, suitable precursors and transformation conditions should also be investigated. Efficient creation of new structural allotropes or functional materials based on pure carbon by high pressure methods should ideally start from designed, preassembled precursor structures or composites for which transition paths can be theoretically predicted.
Databáze: OpenAIRE