Nanoscale Lithium Quantification in LiXNiyCowMnZO2 as Cathode for Rechargeable Batteries
Bibliographic record
Abstract
Time-of-flight secondary ion mass spectrometry (TOF-SIMS) using a focused ion-beam scanning electron microscope (FIB-SEM) is a promising and economical technique for lithium detection and quantification in battery materials because it overcomes the limitations with detecting low Li content by energy dispersive spectroscopy (EDS). In this work, an experimental calibration curve was produced, which to our best knowledge allowed for the first time, the quantification of lithium in standard nickel manganese cobalt oxide (NMC-532) cathodes using 20 nm resolution. The technique overcomes matrix effects and edges effects that makes quantification complex. This work shows the high potential of TOF-SIMS tool for analytical characterization of battery materials, and demonstrates its tremendous capabilities towards identification of various chemical or electrochemical phenomena in the cathodes via high-resolution ion distributions. Various phenomena in the ion distributions are also assessed, such as edge effects or measurement artifacts from real signal variations.
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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 | 0.001 | 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".