MétaCan
Menu
Back to cohort

Building molecular frameworks with tailored pore structures

2000· article· en· W2102770744 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Physical Organic Chemistry · 2000
Typearticle
Languageen
FieldChemistry
TopicMetal-Organic Frameworks: Synthesis and Applications
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of MinnesotaNational Science Foundation
KeywordsSupramolecular chemistryNanotechnologyChemistryMolecular recognitionLamellar structureHydrogen bondMoleculeMaterials scienceCrystallography

Abstract

fetched live from OpenAlex

Interest in materials made from molecular components, driven by the promise of new systems with precisely tailored properties, is accelerating at a rapid pace. The last decade has witnessed tremendous advances in the sophistication of molecular materials based on supramolecular building blocks that can be interchanged at will to generate materials with properties and function that can be finely tuned in a systematic manner. This is exemplified here by examples that illustrate the role of hydrogen bonding in generating low-density ‘porous’ frameworks capable of forming lamellar host–guest inclusion compounds with tunable inclusion cavities and solid-state architectures, topologically related tube-like structures and two-dimensional porous molecular monolayers with structures mimicking layered motifs in molecular crystals. These systems demonstrate that low-density molecular frameworks can be systematically engineered to generate rather predictable and robust structures, particularly if they possess an intrinsic softness that enables the frameworks to self-optimize the non-covalent interactions governing their supramolecular architectures. Copyright © 2000 John Wiley & Sons, Ltd.

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 score0.021
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0210.000

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 head0.004
GPT teacher head0.226
Teacher spread0.222 · 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