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Record W2788289539 · doi:10.1021/acs.chemmater.7b04800

Biotemplated Lightweight γ-Alumina Aerogels

2018· article· en· W2788289539 on OpenAlex

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.

Bibliographic record

VenueChemistry of Materials · 2018
Typearticle
Languageen
FieldChemistry
TopicAerogels and thermal insulation
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAerogelChitosanMaterials scienceAqueous solutionNanofiberSelf-healing hydrogelsChemical engineeringDissolutionComposite materialPolymer chemistryChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

We present the biotemplating of γ-Al2O3 aerogels with chitosan nanofibrils. Aluminum–chitosan interactions cause the swelling of iridescent chitosan structures into helicoidal hydrogels and the subsequent aqueous dissolution of swollen fibrils to form Al–chitosan solutions. Viscous aqueous solutions of Al3+–chitosan hybrid nanofibers were freeze-dried to give lightweight cotton-like aerogels. Homogeneous incorporation of Al3+ ions into chitosan yields water-soluble nanofibrils that can serve as polymeric templates to support Al3+ ions in the aerogel composites. We investigated thermal removal of chitosan in the composites to obtain lightweight γ-Al2O3 nanocrystal aerogels that retain the weblike fiber networks of the chitosan template. These biotemplated alumina aerogel materials are promising candidates for catalyst supports and thermal insulation.

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 categoriesInsufficient payload (model declined to judge)
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 score0.032
Threshold uncertainty score0.981

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)0.0200.000

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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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