Kinetics of the dehydration of lithium dihydrogenphosphate
Bibliographic record
Abstract
Phosphate‐based lithium materials, such as lithium iron phosphate (known as lithium ferrophosphate, LiFePO4, LFP), are among the safest materials for large‐scale lithium‐ion batteries due to the stability of the phosphate‐bound oxygen at elevated temperatures. LFP can be melt‐synthesized where the kinetics is faster, allowing for coarser and lower cost reactants. The most common lithium‐ and phosphate‐bearing reactants can react violently upon heat‐up and release a large volume of gaseous by‐product. Lithium metaphosphate (LiPO3, LPO) can improve the processability and safety of the operation. In this work, we investigate the thermal decomposition of lithium dihydrogenphosphate (LiH2PO4, LHP) to LPO up to 400 °C. The decomposition was analyzed by isothermal and constant rate differential thermogravimetric (DTG) experiments. Activation energy profiles were estimated by an isoconversional model‐free approach and kinetic model fitting. Li5H4P5O17 (L2.5) was determined to be the most stable reaction intermediate and can be isolated at temperatures between 200 and 240 °C. The resulting reaction is comprised of 6 reactions, where the LHP is progressively polymerized by condensation reactions leading successively to L2.5, Li3H2P3O10 (L3), Li4H2P4O13 (L4), and LPO. The first reaction step (LHP → L2.5) was fitted with 3 reactions series/parallel describing the solid surface reaction, the viscous/liquid surface reaction, and the bulk reaction. Limiting the reaction temperature to 400 °C results in a solid product that can be advantageous if LPO is to be prepared in advance and dosed for LFP synthesis.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".