Postsynthetic Route for Modifying the Metal—Insulator Transition of VO<sub>2</sub> by Interstitial Dopant Incorporation
Bibliographic record
Abstract
The thermally driven orders-of-magnitude modulation of resistance and optical transmittance observed in VO 2 makes it an archetypal first-order phase transition material and underpins functional applications in logic and memory circuitry, electromagnetic cloaking, ballistic modulation, and thermochromic glazing to provide just a few representative examples. VO 2 can be reversibly switched from an insulating to a metallic state at an equilibrium transition temperature of 67 °C. Tuning the phase diagram of VO 2 to bring the transition temperature closer to room temperature has been a longstanding objective and one that has tremendous practical relevance. Substitutional incorporation of dopants has been the most common strategy for modulating the metal—insulator transition temperature but requires that the dopants be incorporated during synthesis. Here we demonstrate a novel postsynthetic diffusive annealing approach for incorporating interstitial B dopants within VO 2 . The postsynthetic method allows for the transition temperature to be programmed after synthesis and furthermore represents an entirely distinctive mode of modulating the phase diagram of VO 2 . Local structure studies in conjunction with density functional theory calculations point to the strong preference of B atoms for tetrahedral coordination within interstitial sites of VO 2; these tetrahedrally coordinated dopant atoms hinder the rutile → monoclinic transition by impeding the dimerization of V–V chains and decreasing the covalency of the lattice. The results suggest that interstitial dopant incorporation is a powerful method for modulating the transition temperature and electronic instabilities of VO 2 and provides a facile approach for postsynthetic dopant incorporation to reach a switching temperature required for a specific application.
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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 | 0.001 |
| 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".