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Record W4241698551 · doi:10.1201/9780429332609-47

HFC-134a as a Coblowing Agent with Pentanes

2020· book-chapter· en· W4241698551 on OpenAlexaboutno aff
Jinhuang Wu, Doug Dillon

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldChemical Engineering
TopicCatalysis and Oxidation Reactions
Canadian institutionsnot available
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

The Montreal Protocol regulates the uses of ozone depletion substances (ODSs). In the developed countries, the phaseout of high ozone depletion potential (ODP) CFCs in rigid foam applications was made possible with the introduction of lower ODP HCFCs. HCFC-141b was chosen as an excellent replacement for CFC-11 in many rigid foam applications. HCFC-141b blown rigid foams offer excellent thermal insulation, fire resistance and dimensional stability. According to the Montreal Protocol, HCFC-141b will eventually be phased out. Lower ODP HCFCs (i.e., HCFC-142b and HCFC-22), zero ODP HFCs and hydrocarbons are considered to be alternatives. Unfortunately, neither HFCs nor pentanes can match performance and cost of HCFCs. An HFC and pentane(s) coblowing system can potentially offer some advantages over purely pentane blown foams including lower foam density (therefore lower cost), better thermal insulation and better fire performance than purely pentane(s) blown foams. The coblown foam has lower cost than HFC blown foams. In this study, we choose HFC-134a, a commercially available blowing agent, as a coblowing agent with pentane(s). We make polyisocyanurate (PIR) foams with HFC-134a as a coblowing agent with n-C5, i-C5, i-C5/c-C5, and the levels of HFC-134a are 10 and 20 mole%. We determine thermal conductivity (or k-factor) of foams from −8 to 40 °C. The results show that the effects of HFC-134a on the low temperature k-factors are different, depending on the pentane isomers. Furthermore, we screen a series of surfactants to determine their effects on the k-factors.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.967
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.002

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.

Opus teacher head0.016
GPT teacher head0.214
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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