Comparison of the Reaction of Li[sub x]Si or Li[sub 0.81]C[sub 6] with 1 M LiPF[sub 6] EC:DEC Electrolyte at High Temperature
Bibliographic record
Abstract
The reaction of lithiated silicon with ethylene carbonate–diethyl carbonate(EC:DEC) electrolyte was compared with that of and the same electrolyte using accelerating rate calorimetry (ARC). In the presence of -containing electrolyte, and showed similar ARC response in cases where the same number of moles of lithium atoms and the same amount of electrolyte were involved. X-ray diffraction results indicate that the major reaction product is comprised primarily of for both and . Apparently, the reaction product reduces the reactivity with electrolyte of both and . The self-heating rate of reacting with electrolyte was less than that of even though the specific surface area was about twice as large. This suggests composite electrodes using powdered Si-based electrode materials will be as safe as or safer than corresponding graphite electrodes in full-scale Li-ion cells. The reason that the lithiated silicon is safer than is because silicon stores more Li per unit volume than graphite, leading to thicker surface layers that slow the reaction with electrolyte.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".