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Record W2594332600 · doi:10.1002/cjce.22828

Ethylene production from diluted bioethanol solutions

2017· article· en· W2594332600 on OpenAlexvenueno aff
Ilenia Rossetti, Matteo Compagnoni, Giorgia De Guido, Laura A. Pellegrini, Gianguido Ramis, Stanisław Dźwigaj

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2017
Typearticle
Languageen
FieldChemistry
TopicZeolite Catalysis and Synthesis
Canadian institutionsnot available
Fundersnot available
KeywordsBiofuelEthyleneRaw materialCatalysisDehydrationChemistryLimitingChemical engineeringEthanolMaterials sciencePulp and paper industryWaste managementOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Ethylene production by ethanol dehydration has been investigated over a set of zeolites with BEA structure in acidic form (HAlBEA). The effect on Ni addition (up to 0.03 g/g (3 mass%)) is explored as a means to improve ethylene selectivity limiting the formation of heavier byproducts. The reaction temperature has been varied between 300 and 500 °C and the effect of cofeeding water has been also explored. Both an increase of the operating temperature and of the water/ethanol ratio can improve stability of coking and thus catalyst life. The use of diluted bioethanol solutions was shown to be beneficial for catalyst stability. The effect of possible impurities present in less purified raw materials was also checked by testing two diluted second generation bioethanol solutions (0.5 and 0.9 g/g (50 and 90 mass%)). A first reactor layout and the integration with the bioethanol purification strategy are also proposed, including two purification options which are much less energy demanding than traditional rectification.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
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 head0.022
GPT teacher head0.208
Teacher spread0.186 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations27
Published2017
Admission routes1
Has abstractyes

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