Bibliographic record
Abstract
Monovalent non-transition metals are robust Fermi liquids. They defy superconductivity even at lowest temperatures (Li is a minor exception:Tc $\approx$ 0.4 mK). However, Thapa and Pandey \cite{ThapaPandey} have recently reported signals for ambient temperature granular superconductivity in Ag nanoparticle embedded in Au matrix. We develop a theory, where competing superconducing, CDW and SDW orders lose and get confined (go off-shell). They leave behind a robust Fermi liquid on-shell. \textit{A single half filled band crossing the Fermi level} provides a number of special k-space regions for \textit{singlet stabilizing umklapp pair scattering and superconductivity stabilizing repulsive pair scattering}. Carefully designed perturbations could deconfine a confined superconductivity. We suggest that electron transfer (doping) from Ag nanoparticles to Au matrix (with a higher electronegativity), quasi 2d structural reconstructions (e.g., 9R structure) at Ag-Au interfaces etc., bring out confined superconductivity. Beneath a calm Fermi sea, strong supercurrents may exist in several metals.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| 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".