Melting of a<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mtext>−</mml:mtext><mml:msub><mml:mi mathvariant="normal">H</mml:mi><mml:mn>2</mml:mn></mml:msub></mml:mrow></mml:math>monolayer on a lithium substrate
Bibliographic record
Abstract
Adsorption of $p\text{\ensuremath{-}}{\mathrm{H}}_{2}$ films on alkali metals substrates at low temperature is studied theoretically by means of path integral Monte Carlo simulations. Realistic potentials are utilized to model the interaction between two $p\text{\ensuremath{-}}{\mathrm{H}}_{2}$ molecules, as well as between a $p\text{\ensuremath{-}}{\mathrm{H}}_{2}$ molecule and the substrate, assumed smooth. Results show that adsorption of $p\text{\ensuremath{-}}{\mathrm{H}}_{2}$ on a lithium substrate, the most attractive among the alkali, occurs through completion of successive solid adlayers. Each layer has a two-dimensional density ${\ensuremath{\theta}}_{e}\ensuremath{\approx}0.070\phantom{\rule{0.3em}{0ex}}{\mathrm{\AA{}}}^{\ensuremath{-}2}$. A solid $p\text{\ensuremath{-}}{\mathrm{H}}_{2}$ monolayer displays a higher degree of confinement, in the direction perpendicular to the substrate, than a monolayer helium film, and has a melting temperature of about $6.5\phantom{\rule{0.3em}{0ex}}\mathrm{K}$. The other alkali substrates are not attractive enough to be wetted by ${\mathrm{H}}_{2}$ at low temperature. No evidence of a possible superfluid phase of $p\text{\ensuremath{-}}{\mathrm{H}}_{2}$ is seen in these systems.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.090 | 0.006 |
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; both teacher heads agree on what is shown here.
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".