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Simulation of Recovery of Aroma Compound from Aqueous Solutions by Batch Pervaporation Coupled with Permeate Decantation and Water Phase Recycle

2017· article· en· W2586486792 on OpenAlex
Muhammad Mujiburohman, Xianshe Feng

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.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueJournal of Membrane and Separation Technology · 2017
Typearticle
Languageen
FieldEngineering
TopicMembrane Separation and Gas Transport
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPervaporationAromaDecantationChemistryChromatographyPermeationSolubilityMembraneAqueous solutionChemical engineeringMass transferAqueous two-phase systemOrganic chemistryFood scienceBiochemistry

Abstract

fetched live from OpenAlex

In this work, the dynamic (batch) models of recovery of low soluble aroma compounds from aqueous solutions by pervaporation coupled with permeate decantation and water phase recycle was derived and simulated. The model was run to simulate the pervaporation of propyl propionate-water separation using PEBA membrane. The effect of two parametric models (i.e. ratio of feed mass over membrane area (F0/Am) and the aroma solubility in water) on the aroma compound recovery was studied. As compared to the conventional pervaporation, the application of water phase recycle was known to be able to enhance the recovery of aroma compounds in various extents, depending on the operating time and aroma solubility. The larger membrane area used (or smaller (F0/Am)) did not affect the maximum aroma compound recovery, but only shortened the operating time. For the aroma solubility of 0.56, 1, and 5 wt.%, referring to the optimum operating time in the conventional mode, the extent of improvement in recovery can be around 7, 10 and 16%, respectively. The modified pervaporation process also offered another advantage that the process would not be strictly restricted by the operating time due to permanent increase in cumulative mass of aroma compound recovered in the product.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score0.383

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 communication0.0000.001
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 head0.014
GPT teacher head0.271
Teacher spread0.256 · 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