Pc-C10: An innovative carbon allotrope with concurrent metallic conductivity and exceptional mechanical property
Bibliographic record
Abstract
Carbon, renowned for its versatility in bonding and structural diversity, has long been a focal point of materials research. Despite extensive studies on carbon allotropes, a significant challenge remains: the development of carbon materials that combine both exceptional mechanical properties and electrical conductivity. Here, we propose a novel sp 2 - sp 3 hybridized tetragonal carbon allotrope Pc -C 10 via first-principle calculations. This structure is more energetically favorable than graphite at pressures above 55 GPa, suggesting the potential for synthesis via high-pressure phase transitions. Our results show that Pc -C 10 not only exhibits metallic conductivity through a quasi-one-dimensional conducting channels but also demonstrates superconductivity with a critical temperature of 0.25 K. This new carbon structure displays remarkable mechanical properties, including a hardness of 26 GPa, tensile and shear strengths over 80 GPa for outstanding resistance to deformation and fracture. In particular, a unique damage-self-repair-strengthening behavior is displayed during shear. The combination of these distinctive properties makes this novel carbon material a promising candidate for future applications in electronics, superconductivity, and structural materials technology. • Pc -C 10 demonstrates enhanced thermodynamic stability over fullerene C 60 . • Pc -C 10 exhibits unique quasi-one-dimensional conductive channel and superconductivity with a critical temperature of 0.25 K. • The maximum tensile strength of Pc -C 10 along the [110] direction will reach 159 GPa, with the tensile strains being 39 %. • Pc -C 10 exhibits the distinctive damage-triggered adaptive strength enhancement behavior during shear.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".