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Record W2120409841 · doi:10.1039/c0cs00022a

Mastering fundamentals of supramolecular design with carboxylic acids. Common lessons from X-ray crystallography and scanning tunneling microscopy

2010· review· en· W2120409841 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

VenueChemical Society Reviews · 2010
Typereview
Languageen
FieldEngineering
TopicSurface Chemistry and Catalysis
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSupramolecular chemistryCatenaneHydrogen bondNanotechnologyCrystal engineeringChemistrySoft materialsScanning tunneling microscopeMaterials scienceMoleculeCrystallographyCrystal structureOrganic chemistry

Abstract

fetched live from OpenAlex

Hydrogen bonding is one of the most important non-covalent interactions in both biological (DNA, peptides, saccharides etc.) and artificial systems (various soft materials, host-guest architectures, molecular networks, etc.). Carboxylic acids are some of the most simple yet powerful hydrogen-bonding building blocks, that possess a particularly rich supramolecular chemistry. This tutorial review focuses on the structural diversity of supramolecular architectures accessible via hydrogen bonding of carboxylic acids, as observed both in single crystals using X-ray analysis and in monolayers on surfaces using scanning probe techniques. It provides a concise overview of the key concepts and principles of modern supramolecular design and is given in the form of case studies of finely selected literature examples, covering formation of macrocycles, chains, ladders, rotaxanes, catenanes, various 2D and 3D nets, host-guest systems and some applications thereof.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.860
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.041
GPT teacher head0.294
Teacher spread0.254 · 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