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Record W3080820544 · doi:10.1021/acsomega.0c02910

Sorption Study of Water Vapor and a Dye on Chitosan-Based Framework Materials

2020· article· en· W3080820544 on OpenAlexafffund
Mohammad H. Mahaninia

Bibliographic record

VenueACS Omega · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsUniversity of Saskatchewan
FundersUniversity of Saskatchewan
KeywordsChitosanSorptionAdsorptionDifferential scanning calorimetryAqueous solutionDesorptionContact angleChemical engineeringWater vaporTrimesic acidMaterials scienceSupramolecular chemistryChemistryPhysical chemistryOrganic chemistryMoleculeThermodynamics

Abstract

fetched live from OpenAlex

Abstract Two types of chitosan framework materials were functionalized with carboxyl groups via a supramolecular cross-linking process by citric acid (CA) and trimesic acid (TMA). The role of surface chemistry (i.e., functional groups) and textural properties (i.e., pore size and surface area) in adsorption properties of these chitosan frameworks toward water vapor and dye was investigated. Extensive characterizations using N2 adsorption–desorption, contact angle measurements, differential scanning calorimetry, atomic force microscopy, and confocal microscopy were carried out to understand structure–property relationships of these framework materials. The dynamic vapor sorption analyzer measured water vapor sorption percentage (R %) values of 46.7, 43.9, and 41.5 for TMA1, CA1 framework materials, and chitosan, respectively. The calculated adsorption percentage values of dyes in aqueous solution were 69.7, 39.2, and 18.8 (R %) for TMA1, CA1, and chitosan, respectively.

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 score0.010
Threshold uncertainty score0.020

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.233
Teacher spread0.215 · 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

Citations7
Published2020
Admission routes2
Has abstractyes

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