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Record W2314659295 · doi:10.1021/ic202049t

Role of Entropy and Autosolvation in Dimerization and Complexation of C<sub>60</sub>by Zn<sub>7</sub>Metallocavitands

2012· article· en· W2314659295 on OpenAlexaff
Peter D. Frischmann, S. Hessam M. Mehr, Brian O. Patrick, Francesco Lelj, Mark J. MacLachlan

Bibliographic record

VenueInorganic Chemistry · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsChemistryEnthalpySolventMoleculeEntropy (arrow of time)MonomerSupramolecular chemistryThermodynamicsToluenePhysical chemistryBenzenePolymerOrganic chemistry

Abstract

fetched live from OpenAlex

The supramolecular chemistry of bowl-shaped heptazinc metallocavitands templated by Schiff base macrocycles has been investigated. Dimerization thermodynamics were probed by (1)H NMR spectroscopy in benzene-d(6), toluene-d(8), and p-xylene-d(10) and revealed the process to be entropy-driven and enthalpy-opposed in each solvent. Trends in the experimentally determined enthalpy and entropy values are related to the thermodynamics of solvent autosolvation, solvent molecules being released from the monomeric metallocavitand cavity into the bulk solvent upon dimerization. The relationship established between experimentally measured dimerization thermodynamics and autosolvation data successfully predicts the absence of dimerization in CH(2)Cl(2) and CHCl(3) and was used to estimate the number of solvent molecules interacting with the monomeric metallocavitand in solution. Host-guest interactions between heptazinc metallocavitands and fullerene C(60) have also been investigated. Interestingly, metallocavitand-C(60) interactions are only observed in solvents that facilitate entropy-driven dimerization suggesting entropy and solvent autosolvation may be important in explaining concave-convex interactions.

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 score0.030
Threshold uncertainty score0.638

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 head0.004
GPT teacher head0.198
Teacher spread0.194 · 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

Citations21
Published2012
Admission routes1
Has abstractyes

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