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Record W1992939062 · doi:10.2118/139570-pa

Diffusivity of Citric Acid During its Reaction With Calcite

2010· article· en· W1992939062 on OpenAlexfundno aff
M. H. Al-Khaldi, Hemanta Sarma, H. A. Nasr‐El‐Din

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2010
Typearticle
Languageen
FieldChemical Engineering
TopicChemical and Physical Properties in Aqueous Solutions
Canadian institutionsnot available
FundersSaudi AramcoUniversity of Ottawa
KeywordsCitric acidChemistryCalciumPrecipitationDiffusionThermal diffusivityInorganic chemistryCalciteNuclear chemistryMineralogyThermodynamicsBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Summary The mass transfer process during the reaction of citric acid with calcite was investigated using a rotating disk apparatus. The effects of disk rotational speed, initial citric acid concentration and temperature on the effective diffusion coefficient of citric acid were examined. Using various citric acid concentrations (1 wt%, 2 wt%, 5 wt% and 7.5 wt%), the diffusion coefficient of citric acid was calculated at 25°C, 40°C and 50°C. The effective diffusion coefficient of citric acid was found to be a function of the interplay between the calcium citrate precipitation and the presence of the counter-calcium ions. At high-initial acid concentration (5 wt% and 7.5 wt%), the effects of calcium citrate precipitation and counter-calcium ions were significant and the calculated citric acid diffusion coefficients were not comparable with those obtained using the rotating disk. However, the effects of both the calcium citrate precipitation and the counter-calcium ions on the citric acid diffusivity were minimal at low-initial citric acid concentrations. The effect of temperature on the diffusion coefficient of citric acid at a constant citric acid concentration was found to follow Arrhenius law, and the activation energy was 37.9 kJ/mol.

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 score0.011
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.186
Teacher spread0.180 · 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

Citations16
Published2010
Admission routes1
Has abstractyes

Explore more

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