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Record W2550870777 · doi:10.1002/cjce.22737

Equilibrium condition and stabilization kinetics of lactic acid oligomers in aqueous solutions

2016· article· en· W2550870777 on OpenAlexvenueno aff
Sara Frattari, Fausto Gironi, Rocchina Sabia, Claudio Villani

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsnot available
Fundersnot available
KeywordsLactic acidAqueous solutionOligomerMonomerChemistryArrhenius equationKineticsRaw materialPolymerPolyesterChemical engineeringFermentationOrganic chemistryPolymer chemistryActivation energyBacteria

Abstract

fetched live from OpenAlex

Lactic acid is one of the most important compounds in the field of bio‐renewable chemicals. Lactic acid is present in nature but can also be produced by chemical synthesis or by fermentation of biomass. It can be used as raw material for the production of biodegradable and environmentally friendly polymers or copolymers, such as poly lactic acid (PLA). In this work, the equilibrium distribution of monomer and low molecular weight oligomers of lactic acid in aqueous solutions at different overall concentrations of lactic acid (from 0.09 g/g to 0.94 g/g) and temperatures (423 K and 453 K), was investigated. In addition, a kinetic study of monomer and oligomer esterification reactions, of a lactic acid aqueous solution at about 0.09 g/g, was carried out at 423, 433, 443, and 453 K. The values of the kinetic constants were successfully correlated through Arrhenius’ law.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.016
GPT teacher head0.191
Teacher spread0.175 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2016
Admission routes1
Has abstractyes

Explore more

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