Lithium diffusion in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>Li</mml:mi><mml:mi>Mn</mml:mi><mml:mi mathvariant="normal">P</mml:mi><mml:msub><mml:mrow><mml:mi mathvariant="normal">O</mml:mi></mml:mrow><mml:mn>4</mml:mn></mml:msub></mml:math> detected with <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mi>μ</mml:mi><mml:mo>±</mml:mo></mml:msup><mml:mi>SR</mml:mi></mml:math>
Bibliographic record
Abstract
Positive-and negative-muon spin rotation and relaxation ( SR) was first used to investigate fluctuations of nuclear magnetic fields in an olivine-type battery material, LiMnPO 4 , in order to clarify the diffusive species, namely, to distinguish between a + hopping among interstitial sites and Li + ions diffusing in the LiMnPO 4 lattice. Muon diffusion can only occur in + SR, because the implanted -forms a stable muonic atom at the lattice site, and therefore any change in linewidth measured with -SR must be due to Li + diffusion. Since the two measurements exhibit a similar increase in the field fluctuation rate with temperature above 100 K, it is confirmed that Li + ions are in fact diffusing. The diffusion coefficient of Li + at 300 K and its activation energy were estimated to be 1.4(3) 10 -10 cm 2 /s and 0.19(3) eV, respectively. Such combined SR measurements are thus shown to be a suitable tool for detecting ion diffusion in solid-state energy materials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.004 | 0.006 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.009 | 0.010 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.270 | 0.014 |
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; both teacher heads agree on what is shown here.
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".