The Electrodynamics of Quantum Materials: Quasicrystals, Semimetals, and Poor Metals
Bibliographic record
Abstract
In this thesis, I examine three very different solid-state systems that are all poor conductors when compared to elemental metals. The physics of canonical metals, such as the alkali and noble metals, is well known and is usually idealized in the free-or nearly free-electron picture. Their electron band structures are characterized by parabolic-like bands that cross the Fermi energy and possibly d-bands with flatter dispersions a few eV away. These well-behaved systems lend themselves to the use of simple analytic relations. Each of the three systems that I examine here differs significantly from the nearly-free parabolic band-picture of the electronic structure and require more complex analyses. In the first system of quasicrystals and approximants, we will discover that the electrons are undergoing anomalous diffusion depending on the size and symmetry of the lattices. Of course, as is well known, the details of these atomic lattice are what determine the nature of electronic band structures and how electrons may propagate in solids. In the second system, I find great agreement between my NbAs measurements and calculations on the closely related NbP compound. Incidental to this, I find that a reading of band structures shows that claims of measuring the linear band dispersion in Weyl/Dirac semimetals are not supported by the experimental and theoretical band structures. Finally, in the metallic regime of Nd_(1−x)TiO_3, we find that the Fermi liquid b coefficient is not within the bounds allowed by present models in samples with x = 0.2 and x = 0.15. It is suggested that the approximations used in current models may be why theory and experiment disagree.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".