Thermophysical Property Measurements of Tetrabutylphosphonium Oxalate (TBPOx) Ionic Semiclathrate Hydrate as a Media for the Thermal Energy Storage System
Bibliographic record
Abstract
With increasing global power demand, thermal energy storage technology could play a role ensuring a sustainable energy supply in power generation from renewable energy sources and power demand concentration. Hydrates have high potential as phase change materials (PCMs) for the use as a thermal energy storage medium. To develop thermal energy storage technology using a hydrate-based material, further investigation of thermophysical properties and the selection of a suitable hydrate are required. Tetrabutylphosphonium oxalate (TBPOx) ionic semiclathrate hydrate contains oxalic acid in salt form, as a guest compound, which is classified as carboxylic acid group with low environmental impact. In the present study, the phase equilibrium temperature and the dissociation heat of TBPOx hydrate were measured. The highest equilibrium temperature of the solid hydrate formed was 9.4 °C at the mass fraction 0.35 of TBPOx in aqueous solution. The largest dissociation heat was 186.0 ± 0.5 kJ·kg-1 at the mass fraction of 0.35. Comparing with other PCMs with close phase equilibrium temperatures, TBPOx hydrate is superior in safety and sustainability. These results indicate that TBPOx hydrate would be suitable as the thermal storage medium for the general air conditioning systems.
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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".