Bibliographic record
Abstract
A new technology is suggested for crystallizing arbitrary materials at temperatures of 3000-4000ºC and pressures of 20-100 thousand atmospheres. First experimental results were obtained in a foil-coated polycarbonate that comprised diffraction gratings. It was established that a laser beam reflected from the diffraction gratings is self-focused inside polycarbonate and becomes a seed, which changes the polycarbonate structure and leads to vitrification and growth of ordered structures from symmetrically arranged whiskers. This results in a light dispersion effect in composites. The results concerning whiskers formed with sharp tips are presented. We used data obtained in these experiments for developing a model of crystallization with the rates of 80-100 m/s. In this case, not only crystals grow, but nanowhiskers also. A new phenomenon of nanowhiskerography was discovered, which can be used for developing the defence against falsification that cannot be reproduced by polygraphic methods. A fundamental data, obtained in this article is allowed us to use technology for crystallisation any materials (glass, quartz, semiconductors, whisker graphite). The term “coherent nanowhiskerography” - is introduced for the first time by us, because the whisker crystallization occurs with a delay in reflection from two diffraction gratings, which are situated at the different depths. Thus, each whisker repeats in structure a retarded whisker during the crystalization. Due to this, unique optical and electrophysical properties arise. Since at the ends of whiskers there is only 1-2 atoms with dangling chemical bonds, therefore, the technology is extremely promising for the new direction of creating a new direction of terahertz technology and also up to date generations of the computing technology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".