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Record W2258497300 · doi:10.1038/ncomms9318

Covalency of hydrogen bonds in liquid water can be probed by proton nuclear magnetic resonance experiments

2015· article· en· W2258497300 on OpenAlexaff
Hossam Elgabarty, Rustam Z. Khaliullin, Thomas D. Kühne

Bibliographic record

VenueNature Communications · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsMcGill University
FundersGauss Centre for SupercomputingSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsIntermolecular forceHydrogen bondChemical physicsAnisotropyMoleculeProtonElectromagnetic shieldingChemical bondCovalent bondMaterials scienceChemistryPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

The concept of covalency is widely used to describe the nature of intermolecular bonds, to explain their spectroscopic features and to rationalize their chemical behaviour. Unfortunately, the degree of covalency of an intermolecular bond cannot be directly measured in an experiment. Here we established a simple quantitative relationship between the calculated covalency of hydrogen bonds in liquid water and the anisotropy of the proton magnetic shielding tensor that can be measured experimentally. This relationship enabled us to quantify the degree of covalency of hydrogen bonds in liquid water using the experimentally measured anisotropy. We estimated that the amount of electron density transferred between molecules is on the order of 10 m while the stabilization energy due to this charge transfer is ∼15 kJ mol(-1). The physical insight into the fundamental nature of hydrogen bonding provided in this work will facilitate new studies of intermolecular bonding in a variety of molecular systems.

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 score0.256
Threshold uncertainty score0.331

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 science0.0010.000
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 head0.022
GPT teacher head0.301
Teacher spread0.279 · 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

Citations74
Published2015
Admission routes1
Has abstractyes

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