Formation and characterization of nano- and microstructures of twinned cubic boron nitride
Bibliographic record
Abstract
Nano- and microstructures of phase-pure cubic boron nitride (c-BN) are synthesized by employing nanosecond pulsed-laser annealing techniques at room temperature and atmospheric pressure. In a highly non-equilibrium synthesis process, nanocrystalline h-BN is directly converted into phase-pure twinned c-BN from a highly undercooled melt state of BN. By changing nucleation and growth rates, we have synthesized a wide range of sizes (90 nm to 25 μm) of c-BN. The electron diffraction patterns show the formation of twinned c-BN with [11[combining macron]1] as the twin axis. The twinning density in c-BN can be controlled by the degree of undercooling and quenching rates. The formation of twins predominantly occurs prior to the formation of amorphous quenched BN (Q-BN). Therefore, the defect density in nano c-BN formed under higher undercooling conditions is considerably larger than that in micro c-BN, which is formed under lower undercooling conditions. The temperature-dependent Raman studies show a considerable blue-shift of ∼6 cm-1 with a decrease in temperature from 300 to 78 K in nano c-BN as compared to micro c-BN. The size-effects of c-BN crystals in Raman spectra are modeled using spatial correlation theory, which can be used to calculate the correlation length and twin density in c-BN. It has also been found that the Raman blue-shift in nano c-BN is caused by anharmonic effects, and the decrease in Raman linewidth with decreasing temperature (300 to 78 K) is caused by three- and four-phonon decay processes. The bonding characteristics and crystalline nature of the synthesized c-BN are also demonstrated by using electron energy-loss spectroscopy and electron backscatter diffraction, respectively. We envisage that the controlled growth of phase-pure nano and microstructures of twinned c-BN and their temperature-dependent Raman-active vibrational mode studies will have a tremendous impact on low-temperature solid-state electrical and mechanical devices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".