Experimental and thermodynamic study of Li‐O and Li<sub>2</sub>O‐P<sub>2</sub>O<sub>5</sub> systems
Bibliographic record
Abstract
Abstract LiFePO4 (LFP) as a promising cathode material has been extensively studied. However, the high cost of current batch production technology limits its application, especially in automotive industries. To develop the new melting synthesis of LFP, the process conditions have to be strictly controlled, such as temperature, composition, and the partial pressure of oxygen. Reliable and accurate thermodynamic information about Li‐Fe‐P‐O systems could serve as a useful guide for designing operating conditions. As part of ongoing efforts, the Li‐O and Li2O‐P2O5 binary systems have been first studied following the CALPHAD method using FactSage thermodynamic software. The data on thermodynamic properties (Cp, enthalpy of formation, and vapor pressure) and phase diagrams (liquidus/solidus temperature, phase transition, and solid solubility) available in the literature were carefully reviewed and evaluated for the above‐mentioned systems. The modified quasichemical model (MQM) with quadruplet approximation was used for the liquid phase in the present studies. This model simultaneously takes into account the short‐range ordering of first‐nearest‐neighbours (FNN) and second‐nearest‐neighbours (SNN), which improves the thermodynamic description of the Gibbs energy of the liquid. The thermodynamic model parameters of the Gibbs energy have been obtained for all of the phases considered in the Li‐O and Li2O‐P2O5 binary systems. DSC‐TGA experiments on the selected four compositions were carried out to validate the liquidus and phase transition temperature reported in the literature. Overall, the self‐consistent thermodynamic description using the model parameters obtained in this work can successfully reproduce the evaluated experimental data.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".