Structure and Electrochemistry of SiO<sub>x</sub> Made By Reactive Gas Milling
Bibliographic record
Abstract
SiO x is a promising Li-ion battery negative electrode material because of its high capacity and unique microstructure that leads to good cycle life. However, SiO is typically made by high temperature methods that are expensive and difficult to realize, especially at lab scale. Here, SiO x negative electrode materials were synthesized by ball milling Si in air. This method allows efficient control of oxygen content, as shown in Figure 1a and results in a similar microstructure as a commercially purchased SiO. XRD and TEM results show that the SiOx prepared by ball milling in air are composed of nanocrystalline Si embedded in an amorphous silicon oxide matrix (Figure 1b). The very low initial coulombic efficiency (ICE) of conventionally made SiO (measured here to be ~55% for Aldrich SiO) is one of its major drawbacks. In contrast, reactive gas milled SiO x have much higher reversible capacities (>1500 mAh/g) and higher ICE values (>70%). Reactive gas milled SiO x has a number of attractive features: an inexpensive and simple synthesis process, high capacity, high ICE, high thermal stability (stable microstructure at 800 °C, Figure 1c), and a special microstructure that protects Si from reaction with electrolyte, resulting in excellent cycling performance (Figure 1d). Here a detailed study will be presented describing SiO x synthesis by reactive gas milling, thermal properties, and its electrochemical performance in relation to its composition and microstructure. 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) | 0.001 | 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".