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Record W2007035587 · doi:10.1021/jf060441n

Solubilization of Chitosan by Bipolar Membrane Electroacidification

2006· article· en· W2007035587 on OpenAlex
Fabrice Lin Teng Shee, Joseph Arul, Serge Brunet, Andéa-Mircea Mateescu, Laurent Bazinet

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

VenueJournal of Agricultural and Food Chemistry · 2006
Typearticle
Languageen
FieldEngineering
TopicMembrane-based Ion Separation Techniques
Canadian institutionsUniversité LavalUniversité du Québec à Montréal
Fundersnot available
KeywordsSolubilizationChitosanChemistryMembraneChromatographyChemical engineeringOrganic chemistryBiochemistryEngineering

Abstract

fetched live from OpenAlex

Chitosan, a partially deacetylated derivative of chitin, was solubilized by bipolar membrane electroacidification (BMEA). Bipolar/monopolar (anionic or cationic) configuration and chitosan addition mode (single step or stepwise) were examined. Chitosan solubility and electroacidification parameters were monitored during the process to determine the optimal conditions. Bipolar/anionic configuration and stepwise feeding mode led to chitosan solubilization yield of 91% in 60 min at 20 mA/cm(2). In this configuration, chitosan solution had a pH of 2.5, a conductivity of 8.5 mS/cm, and an ash content of 0.2%. Relative energy consumption was 0.05 kWh/L of 1% chitosan solution prepared. Although some chitosan particles were aggregated in the electrodialysis stack, limiting chitosan solubilization, BMEA allowed complete solubilization of chitosan circulating in the system.

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 score0.003
Threshold uncertainty score0.256

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)0.0000.000

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 head0.004
GPT teacher head0.172
Teacher spread0.169 · 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