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Record W1250677884

Ethanol dehydration system by SiftekTM polymeric membrane.

2010· article· en· W1250677884 on OpenAlexaboutno aff
José Luiz Oliverio, H. Gabardo Filho, Fernando C. Boscariol, Pierre Côté

Bibliographic record

VenueInternational sugar journal · 2010
Typearticle
Languageen
FieldEngineering
TopicCatalysis for Biomass Conversion
Canadian institutionsnot available
Fundersnot available
KeywordsEthanolEthanol fuelDehydrationRenewable energyPulp and paper industryChemistryBiofuelMembraneWaste managementFood scienceBiotechnologyEnvironmental scienceEngineeringBiochemistryBiology
DOInot available

Abstract

fetched live from OpenAlex

ETHANOL is very important renewable energy to Brazil and several companies are improving their technologies by developing processes to increase the benefits of ethanol compared to fossil sources. The Siftek TM polymeric membrane is a technology that can save between 35 and 70% of energy when compared with conventional processes. The first pilot plant (Tiverton, Canada) operated dehydrating grain-based ethanol from 80– 90 wt% ethanol to 99.2 wt%, showing the good performance of the membrane system. With the goal of testing the system in a commercial capacity, a second plant (Chatham, Canada) was built and operated with success, drying grain-based ethanol from 40–60 wt% ethanol to 99.5 wt%. To demonstrate this technology to Brazilian ethanol producers, a third demonstration unit was built and operated in ethanol plants from sugarcane. The results confirmed the excellent selectivity of the membrane system to water, dehydrating ethanol from 85–93 wt% to higher then 99.5 wt%, with lower energy consumption and preserving product quality.

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 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 score0.201
Threshold uncertainty score0.651

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)0.0010.000

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 head0.003
GPT teacher head0.184
Teacher spread0.182 · 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

Citations3
Published2010
Admission routes1
Has abstractyes

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