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Record W4230919914 · doi:10.33263/proceedings22.017017

Active Roles of Water in Aqueous Assembly of Macromolecules

2020· article· en· W4230919914 on OpenAlexfundno aff

Bibliographic record

VenueProceedings International · 2020
Typearticle
Languageen
FieldMaterials Science
TopicSupramolecular Self-Assembly in Materials
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAqueous solutionChemistryIonic bondingSupramolecular chemistryMicelleMacromoleculeHydrophobic effectPhosphoniumMoleculeIonCrystallographyPolymer chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Aqueous self-assembly customarily focuses on the molecular interactions of assembling building blocks; the role of water is barely studied. The hydration of hydrophobic P+X- (P+: macromolecular phosphonium cation, X-: anion) is dependent on the ionic end groups, which is responsible for the consequent assembling behavior. The water interaction with the backbone was analyzed by FT-IR, and the dynamics were measured by low field-NMR spectroscopy. The combination of these two techniques reveals the effect of X- on hydration. When X- is I-, the ionic end group ordered water molecules that exerted a detectable long-range effect de-hydrating the backbone. The consequent hydrophobic interaction drove the aqueous assembly of P+I- into micelle-like aggregates with the ionic group exposed to water. In contrast, the ion pair with a hydrophobic anion of [BPh4]- was not able to hold water and did not deplete the hydration water. The hydrated backbone of P+[BPh4]- assembled into vesicles that were driven by hydration interactions. This elucidation at the molecular level is craved to progress aqueous supramolecular chemistry.

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 score0.002

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.255
Teacher spread0.242 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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Same venueProceedings InternationalSame topicSupramolecular Self-Assembly in MaterialsFrench-language works237,207