Phonon-mediated stabilization and softening of 2D transition metal carbides: case studies of Ti<sub>2</sub>CO<sub>2</sub> and Mo<sub>2</sub>CO<sub>2</sub>
Bibliographic record
Abstract
Two-dimensional transition metal carbides (MXenes) exhibit excellent thermodynamic stability, mechanical strength and flexibility, which make them promising candidates in flexible devices and reinforcements in nanocomposites. However, the dynamic stability may intrinsically determine the preferred adsorption sites of functional groups in MXenes and lead to premature failure under finite strain before approaching the elastic limits. It is found interestingly that different adsorption sites of the functional groups correspond to the different phonon stabilities and adsorption energies of MXenes, which can be attributed to different hybridization characteristics between the metal-d and O-pz states and delocalized electron behaviors around the metal atoms. Although both Ti2CO2 and Mo2CO2 possess high ideal strengths and superior flexibility, the premature phonon instabilities appear unexpectedly in distinct manners before approaching their elastic limits. An in-depth exploration of the soft modes and deformed electronic structures reveals that a continuously decreasing gap-opening at the Γ point in Ti2CO2 increases after in-plane phonon instability due to the pseudo Jahn-Teller effect, differing from the out-of-plane phonon instability and semiconductor-metal transition under biaxial tension observed in MoS2. Although Mo2CO2 shows similar failure modes to graphene under uniaxial/biaxial tensions, the band crossings around the Fermi level are found to be responsible for its metallic character and elastic/phonon instabilities by modifying the elastic energy or electronic band energy, different from the gap opening appearing in graphene. Our results shed light onto the profound effect of the phonon instability on the preferable structure and strengths of MXenes, providing theoretical guidance on designing flexible MXene devices, raising a great challenge to the conventional strengthening theory by simply counting bonds.
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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) | 0.001 | 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".