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Record W2507580486 · doi:10.1021/acs.cgd.6b00126

Mineral Precipitation Kinetics: Assessing the Effect of Hydrostatic Pressure and Its Implication on the Nucleation Mechanism

2016· article· en· W2507580486 on OpenAlexfundno aff
Narayan Bhandari, Amy T. Kan, Fangfu Zhang, Zhaoyi Dai, Fei Yan, Gedeng Ruan, Zhang Zhang, Ya Liu, Rudi van Eldik, Mason B. Tomson

Bibliographic record

VenueCrystal Growth & Design · 2016
Typearticle
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsnot available
FundersTotalStatoilBaker HughesHess CorporationConocoPhillipsPetrobrasCenovus EnergyShellChevronDow Chemical Company
KeywordsNucleationSupersaturationChemistryAnhydriteKineticsHydrostatic pressureVolume (thermodynamics)PrecipitationThermodynamicsMineralogyInorganic chemistryChemical engineeringMaterials scienceGypsumMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

Sulfate minerals (barite, anhydrite, and celestite) can be a technological hindrance as a result of scale formation especially for operations where seawater injection is involved. The effect of pH, temperature, and saturation index (SI) on sulfate mineral nucleation and growth are fairly well-known, but the influence of pressure on the nucleation kinetics has attracted no attention. Here we show that nucleation kinetics of barite, anhydrite, and celestite is highly dependent on hydrostatic pressure applied even under constant thermodynamic driving force, that is, at the same supersaturation level. Activation parameters of barite nucleation kinetics were calculated, and measured values are in agreement with literature. The negative activation volume measured suggests that barite nucleation from hydrated Ba 2+ and SO 4 2– ions is coupled to an overall volume decrease, albeit a large volume increase due to dehydration is expected. The results indicate that nucleation is not controlled by desolvation of solvated precursor Ba 2+ and SO 4 2– ions but rather by an intrinsic volume collapse in the rate-determining step of the nucleation and crystal growth processes. The activation parameters measured in this study indirectly support previous findings of formation of hydrated barite precursor before formation of crystalline barite particles.

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)0.001
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 score0.090
Threshold uncertainty score0.274

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.016
GPT teacher head0.249
Teacher spread0.233 · 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
Published2016
Admission routes1
Has abstractyes

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