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Record W4417199516 · doi:10.1021/acs.cgd.5c00721

Enhanced Morphology Control and Hydrolytic Stability of HKUST-1 by Incorporation of Poly(acrylic acid)

2025· article· en· W4417199516 on OpenAlexafffund
Stacy M. Kenyon, Justin Van Houten, Wendy Y. Wu, Maciej Damian Korzyński, Alana F. Ogata

Bibliographic record

VenueCrystal Growth & Design · 2025
Typearticle
Languageen
FieldChemistry
TopicMetal-Organic Frameworks: Synthesis and Applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCatalysisHydrolysisAdsorptionChemical stabilityPolymerPorosityParticle (ecology)Degradation (telecommunications)Particle sizePhase (matter)

Abstract

fetched live from OpenAlex

HKUST-1 is a copper-based metal–organic framework (MOF) that exhibits desirable properties including high porosity, catalytic activity, and the ability to encapsulate biomolecules. However, pristine HKUST-1 demonstrates poor hydrolytic stability, which results in the degradation of its porous framework upon exposure to water and poses challenges for broader applications as a catalyst or adsorbent. Polymers can be incorporated into MOFs for enhanced chemical stability due to their hydrophobic nature, coordination capacity, and modulating ability. Here, we report the synthesis of octahedral HKUST-1 particles using poly(acrylic acid) (PAA) both as an acid catalyst to mediate a phase transformation and as a modulator to control particle growth. The structural identity and stability of HKUST-1 were confirmed by powder X-ray diffraction, scanning electron microscopy, and N 2 adsorption measurements. PAA incorporation was confirmed by nuclear magnetic resonance spectroscopy and pore size distribution analysis. Notably, our synthetic route produced a PAA–HKUST-1 composite with enhanced stability against air humidity for 14 days and biological buffer submersion for 7 days.

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 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 score0.469
Threshold uncertainty score0.686

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 head0.012
GPT teacher head0.225
Teacher spread0.214 · 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 teacher head, 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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

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