The Stability and Electronic Structure of Anti-MXenes
Bibliographic record
Abstract
Anti-MXenes are a new class of 2D materials with the formula M n X n +1, and they have recently been attracting attention. The successful synthesis of Mo 5 N 6 and the identification of its atomic arrangements (labeled as α and γ), along with the resolved structure of TiC 2, raise an important question: What are the possible atomic structures of M n X n +1 layers across different transition metals M and values of n? In this work, we identify a new structural prototype, denoted as β, through a combination of density functional theory (DFT) calculations and evolutionary optimization. By systematically exploring the stable polymorphs of 32 anti-MXenes structures with the formula M n X n +1 (M = Ti, V, Cr, Mn, Nb, Mo, Ta, and W; n = 2, 3, 4, 5), we find that the β structure is more favorable in thinner compositions ( n = 2) and tends to appear at the outermost layers of thicker structures ( n = 5), leading to hybrid structures that are mixtures of α/γ and β configurations. We identify a range of nontrivial electronic states in these materials: semimetals, flat bands, a semiconductor, and materials with high electronic density at the Fermi level. Further analysis of M 2 X 3 β structures using supercell models reveals that Mo 2 X 3 relaxes into a different lower-energy configuration. Our findings unveil the rich and complex structural and electronic landscape of anti-MXenes, which warrants further exploration of this class of materials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".