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Record W1980278358 · doi:10.1063/1.1467631

Nuclear magnetic resonance monitoring of capillary imbibition and diffusion of water into hardened white cement paste

2002· article· en· W1980278358 on OpenAlexaff
J. S. Ceballos-Ruano, Teobald Kupka, D. W. Nicoll, John Benson, Marios A. Ioannidis, C.M. Hansson, M. M. Pintar

Bibliographic record

VenueJournal of Applied Physics · 2002
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsImbibitionCementDiffusionNuclear magnetic resonanceMaterials scienceSaturation (graph theory)Capillary actionAnalytical Chemistry (journal)ChemistryCountercurrent exchangeComposite materialThermodynamicsChromatography

Abstract

fetched live from OpenAlex

Nuclear magnetic resonance (NMR) experiments monitoring the imbibition (sorption) and diffusion of water into white cement paste are reported. The sample was a 1.3 cm long cylinder (6 mm o.d.) of hardened ordinary white cement paste, with a water/cement ratio of 0.42 containing 0.5% Ca(NO2)2 and 2% NaCl. Water proton magnetization and T2 values were obtained as functions of time. Imbibition of H2O and diffusion of H2O and D2O were monitored with H1 NMR at 26 and 30 MHz. The countercurrent water imbibition experiments revealed a two-stage process. A rapid uptake of water, involving about 85% of the total, took place in about 45 min. Maximum saturation was reached in about 2 days. Both stages of the process were well described by a nonlinear diffusion-like equation. Diffusion of both H2O and D2O was characterized by a single diffusion coefficient. The diffusion coefficient for H2O and D2O, derived by fitting the data to the diffusion equation, is well predicted by D0/(Fφ).

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 score0.012
Threshold uncertainty score0.269

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 head0.010
GPT teacher head0.199
Teacher spread0.188 · 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

Citations17
Published2002
Admission routes1
Has abstractyes

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