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Record W3093176503 · doi:10.1007/s12274-020-3123-z

Applying reticular synthesis to the design of Cu-based MOFs with mechanically interlocked linkers

2020· article· en· W3093176503 on OpenAlexaff
Alexander J. Stirk, Benjamin H. Wilson, Christopher A. O’Keefe, Hazem Amarne, Kelong Zhu, Robert W. Schurko, Stephen J. Loeb

Bibliographic record

VenueNano Research · 2020
Typearticle
Languageen
FieldChemistry
TopicMetal-Organic Frameworks: Synthesis and Applications
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRotaxaneLinkerCrystallographyMaterials scienceMoleculeTriphenyleneMetal-organic frameworkSolid-stateTopology (electrical circuits)ChemistryNanotechnologyCrystal structurePhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The concept of “robust dynamics” describes the incorporation of mechanically interlocked molecules (MIMs) into metal-organic framework (MOF) materials such that large amplitude motions (e.g., rotation or translation of a macrocycle) can occur inside the free volume pore of the MOF. To aid in the preparation of such materials, reticular synthesis was used herein to design rigid molecular building blocks with predetermined ordered structures starting from the well-known MOF NOTT-101. New linkers were synthesized that have a T-shape, based on a triphenylene tetra-carboxylate strut, and their incorporation into Cu(II)-based MOFs was investigated. The single-crystal structures of three new MOFs, UWCM-12 (fof), β-UWCM-13 (loz), UWCM-14 (lil), with naked T-shaped linkers were determined; β-UWCM-13 is the first reported example of the loz topology. A fourth MOF, UWDM-14 (lil) is analogous to UWCM-14 (lil) but contains a [2]rotaxane linker. Variable-temperature, 2H solid-state NMR was used to probe the dynamics of a 24-membered macrocycle threaded onto the MOF skeleton.

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 score0.004

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 head0.089
GPT teacher head0.319
Teacher spread0.230 · 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

Citations18
Published2020
Admission routes1
Has abstractyes

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