Operando μ-Beam Diffraction Following the Decomposition of Individual Li<sub>2</sub>O<sub>2</sub> Grains in a Non-Aqueous Li-O<sub>2</sub> Battery
Bibliographic record
Abstract
Fundamental research into the Li-O2 battery system has gone into high gear, gaining momentum due its very high theoretical specific energy. The electrochemical processes that drive this battery are represented by the total chemical reaction:. We report for the first time the technique of operando micro beam X-ray diffraction applied to monitor the decomposition of individual grains of Li2O2 in a working non-aqueous Li-O2 battery. Due to the extremely small beam size and bright X-rays, the diffraction rings break up into spots, each spot representing a grain of Li2O2 having nanometer dimensions. We have studied two kinds of Li2O2; the first, electrochemically generated toroids of Li2O2 comprising of Li2O2 platelets formed at a low discharge current density of (E-Li2O2) and the second, chemically prepared Li2O2 incorporated into a carbon electrode (C-Li2O2). The most obvious difference the two is the shape and size of the primary crystallites. Using this technique, we have time-resolved information on the individual transformation of a number of grains of both E-Li2O2 and C-Li2O2, following their complete decomposition. Figure 1 Voltage curve corresponding to the Oxygen Evolution Reaction (OER) using a current density of 100 mA/cm2, and the corresponding evolution of a 2D (100) reflection of Li2O2 following its decomposition. Figure 1
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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) | 0.002 | 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".