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Record W2536274993 · doi:10.1002/anie.201607745

Mediating Order and Modulating Porosity by Controlled Hydrolysis in a Phosphonate Monoester Metal–Organic Framework

2016· article· en· W2536274993 on OpenAlexafffund
Benjamin S. Gelfand, Racheal P. S. Huynh, Roger K. Mah, George K. H. Shimizu

Bibliographic record

VenueAngewandte Chemie International Edition · 2016
Typearticle
Languageen
FieldChemistry
TopicMetal-Organic Frameworks: Synthesis and Applications
Canadian institutionsUniversity of Calgary
FundersCarbon Management Canada
KeywordsPhosphonateSelectivityAdsorptionChemistryLinkerSorptionMetal-organic frameworkPorosityHydrolysisMetalInorganic chemistryCopperChemical engineeringOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

Abstract A crystalline and permanently porous copper phosphonate monoester framework has been synthesized from a tetraaryl trigonal phosphonate monoester linker. This material has a surface area over 1000 m2 g−1, as measured by N2 sorption, the highest reported for a phosphonate‐based metal–organic framework (MOF). The monoesters result in hydrophobic pore surfaces that give a low heat of adsorption for CO2 and low calculated selectivity for CO2 over N2 and CH4 in binary mixtures. By careful manipulation of synthetic conditions, it is possible to selectively remove some of the monoesters lining the pore to form a hydrogen phosphonate while giving an isomorphous structure. This increases the affinity of the framework for CO2 giving higher ambient uptake, higher heat of adsorption, and much higher calculated selectivity for CO2 over both N2 and CH4. Formation of the acid groups is noteworthy as complexation with the parent acid gives a different structure.

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 score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.008
GPT teacher head0.232
Teacher spread0.224 · 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

Citations55
Published2016
Admission routes2
Has abstractyes

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