Theory of complex fluids in the warm-dense-matter regime, and application to an unusual phase-transitions in liquid carbon
Bibliographic record
Abstract
Data from recent laser-shock experiments, density-functional theory (DFT) with molecular-dynamics (MD), and path-integral Monte Carlo (PIMC) simulations on carbon are compared with predictions from the neutral-pseudo-atom (NPA)+ hyper-netted-chain (HNC) approach for carbon, a complex liquid in the warm-dense matter regime. The NPA results are in good agreement, not only with high-density regimes that have been studies via PIMC, but even at low densities and low temperatures where transient covalent bonding dominates ionic correlations. Thus the `pre-peak' due to the C-C bond at $\sim$1.4-1.6 Å$\,$ and other features found in the pair-distribution function from DFT+MD simulations at 0.86 eV and 3.7 g/cm$^3$ etc., are recovered accurately in the NPA+HNC calculations. Such C-C bonding peaks have not been captured via average-atom ion-sphere (IS) models. Evidence for an unusual liquid $\to$ vapor and metal$\to$ semi-metal transition occurring simultaneously is presented. Here a strongly correlated metallic-liquid with transient C-C bonds, i.e., carbon at density $\sim$ 1.0 g/cm$^3$ and mean ionization $Z=4$ transits abruptly to a disordered mono-atomic vapour at 7 eV, with $Z\simeq$ 3. Other cases where $Z$ drops abruptly are also noted. The nature of $Z$, its discontinuities, and the role of exchange correlation, are reviewed. The limitations of IS models in capturing the physics of transient covalent bonding in warm dense matter are discussed.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".