Isochoric, isobaric, and ultrafast conductivities of aluminum, lithium, and carbon in the warm dense matter regime
Bibliographic record
Abstract
We study the conductivities $\ensuremath{\sigma}$ of (i) the equilibrium isochoric state ${\ensuremath{\sigma}}_{\mathrm{is}}$, (ii) the equilibrium isobaric state ${\ensuremath{\sigma}}_{\mathrm{ib}}$, and also the (iii) nonequilibrium ultrafast matter state ${\ensuremath{\sigma}}_{\mathrm{uf}}$ with the ion temperature ${T}_{i}$ less than the electron temperature ${T}_{e}$. Aluminum, lithium, and carbon are considered, being increasingly complex warm dense matter systems, with carbon having transient covalent bonds. First-principles calculations, i.e., neutral-pseudoatom (NPA) calculations and density-functional theory (DFT) with molecular-dynamics (MD) simulations, are compared where possible with experimental data to characterize ${\ensuremath{\sigma}}_{\mathrm{ic}}$, ${\ensuremath{\sigma}}_{\mathrm{ib}}$, and ${\ensuremath{\sigma}}_{\mathrm{uf}}$. The NPA ${\ensuremath{\sigma}}_{\mathrm{ib}}$ is closest to the available experimental data when compared to results from DFT with MD simulations, where simulations of about 64--125 atoms are typically used. The published conductivities for Li are reviewed and the value at a temperature of 4.5 eV is examined using supporting x-ray Thomson-scattering calculations. A physical picture of the variations of $\ensuremath{\sigma}$ with temperature and density applicable to these materials is given. The insensitivity of $\ensuremath{\sigma}$ to ${T}_{e}$ below 10 eV for carbon, compared to Al and Li, is clarified.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".