Research Progress on Alternative Refrigerants and Their Development Trend
Bibliographic record
Abstract
The new agreement about “accelerate the phase-out of production and consumption of hydro-chlorofluorocarbons (HCFCs)” on the 19th meeting of the Parties to the Montreal Protocol put much more pressure on Chinese refrigeration industry. On the basis of message gotten from the conferences organized by UNIDO in Vienna in 2008 and UNEP in Cairo in 2010, the author summarized the research progress in the HCFCs replacement in recent years in the world. EU have been developing natural refrigerants, such corporations as Dupont are researching and propagating the good performances of HFO-1234yf, DR-2, etc., while the countries in Africa and south-east Asia put more attention to where to get the refrigerant replacement technology and the fund. As for China, besides R32 being considered as a interim refrigerant suitable for China's actual conditions, more works should be done on the development of such natural refrigerants as CO2, R290 as well as the alternative refrigerants with low GWP and thermodynamic properties similar to HCFCs. In addition, special attention should be paid to the standards for the replacement of HCFCs, which is the motivation for the development of refrigeration industry.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".