Lithium ion dynamics in synthetic quartz studied via the NMR of implanted <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mrow/> <mml:mn>8</mml:mn> </mml:msup> <mml:msup> <mml:mrow> <mml:mi>Li</mml:mi> </mml:mrow> <mml:mo>+</mml:mo> </mml:msup> </mml:math>
Bibliographic record
Abstract
We report $β$-detected nuclear magnetic resonance ($β$-NMR) measurements of implanted $^{8}$Li$^{+}$ in a synthetic single crystal of $α$-SiO$_2$ (quartz). At 6.55 Tesla, the spectrum is comprised of a large amplitude broad resonance and a quadrupolar multiplet that is only revealed by an RF comb excitation. The quadrupole splitting is surprisingly small, increases with temperature, and provides information on the implantation site. Supercell density functional theory calculations show that the small EFG is consistent with an in-channel interstitial site (Wyckoff 3$a$). The spin-lattice relaxation is unexpectedly fast and strongly temperature dependent with a diffusive peak above 200 K and a second more prominent relaxation peak at lower temperature. Analysis of the diffusive relaxation yields an activation barrier 178(43) meV for the isolated Li$^{+}$, in the range of other measurements and calculations. To account for many of the other features of the data, it is suggested that some of the implanted ions trap an electron forming the neutral Li$^{0}$, which is stable over a narrow range of temperatures.
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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 | 0.000 | 0.000 |
| 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".