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Record W4293226488 · doi:10.1016/j.isci.2022.104903

Insights on production mechanism and industrial applications of renewable propylene glycol

2022· review· en· W4293226488 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueiScience · 2022
Typereview
Languageen
FieldEngineering
TopicCatalysis for Biomass Conversion
Canadian institutionsSt. Peter's Hospital
Fundersnot available
KeywordsHydrogenolysisPropylene oxideCatalysisGlycerolGreen chemistryChemistryPolyvinyl alcoholOrganic chemistryRenewable energyReaction mechanismPolymerEngineeringCopolymer

Abstract

fetched live from OpenAlex

Propylene glycol is a ubiquitous sustainable chemical that have several industrial applications. It can be used as a non-toxic antifreeze, moisturizers, and in cosmetics products. Commercial production of propylene glycol uses petroleum-based propylene oxide. Therefore, there is a need to develop alternative and renewable propylene glycol production routes. Renewable propylene glycol can be produced from catalytic hydrogenolysis of glycerol. This study reviews different catalyst for glycerol hydrogenolysis, the reaction mechanism, and process challenges. Additionally, previous studies related to the economic and environmental assessment of propylene glycol production are presented in detail. The technology readiness level of different production pathways were outlined as well as the challenges and future direction of propylene glycol production from glycerol and other renewable feedstocks. Catalytic transfer hydrogenolysis, a process that uses renewable H-donors in liquid medium for hydrogenolysis reaction is also discussed and compared with conventional hydrogenolysis.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.046
GPT teacher head0.258
Teacher spread0.212 · 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