A synergetic stabilization and strengthening strategy for two-dimensional ordered hybrid transition metal carbides
Bibliographic record
Abstract
Two-dimensional (2D) transition metal carbides (MXenes) exhibit excellent thermodynamic stability and remarkable mechanical strength and flexibility, as well as rich functionality, which attract considerable interest due to their potential application for high-performance flexible and stretchable devices. However, premature phonon instability of some non-hybrid MXenes was recently found to intrinsically limit their strength and flexibility, evoking passionate curiosity in pursuing an effective solution for more impressive mechanical properties. In this work, on the basis of an alloying strengthening mechanism, a combinational strategy is proposed to build ordered hybrid M2''M'C2O2 (M'' = Mo, W; M' = Ti, Zr, Hf) with remarkable dynamic stability and superior mechanical properties by hindering the premature phonon instability originating from the outer transition metals. By means of comprehensive screening, symmetrical-Mo2TiC2O2 is interestingly found to possess excellent stability at equilibrium and outstanding tolerance to phonon instability during straining compared to its Ti counterpart, being attributed to the character of the robust Mo-dz2 and O-pz hybridization. Although similar optical phonon soft modes appear in Ti3C2O2 and Mo2TiC2O2 under multiple loadings, the latter is much stiffer during straining. An in-depth analysis of deformed electronic structures reveals that a strain-induced increasing density of states in the vicinity of the Fermi level mainly composed of Mo-dz2 states facilitates the fatal phonon softening in Mo2TiC2O2 under biaxial tension, while differing from the mechanical instability in Ti3C2O2 triggered by a Peierls transition. Our findings provide a novel stabilization and strengthening strategy for 2D materials, and pave a new way for searching for 2D material candidates in designing flexible devices.
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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".