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Record W3084251202 · doi:10.1021/acssuschemeng.0c02260

Growth of Calcium Carbonate Induced by Accelerated Carbonation of Tricalcium Silicate

2020· article· en· W3084251202 on OpenAlexaff
Dan Wang, Cang Xiong, Wenzheng Li, Jun Chang

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsMcGill University
FundersNational Natural Science Foundation of China
KeywordsCarbonationCalciteChemical engineeringCalcium carbonateMaterials scienceMineralogyAmorphous calcium carbonateCarbonateDiagenesisChemistryMetallurgyComposite material

Abstract

fetched live from OpenAlex

Accelerated carbonation is expected to be a potential technique for sustainable development of cement-based materials, where the strength is significantly increased in several hours and greenhouse gas CO2 is stored permanently. Tricalcium silicate (C3S) is the most dominant composition in Portland cement, and the investigation regarding the gas–solid carbonation process of pure C3S is beneficial for further in-depth understanding of carbonation of complex C3S-containing systems. Besides, the vital roles of calcium carbonate in promoting mechanical properties during the diagenesis process are proposed in terms of the calcite growth process induced by carbonation. Multitechnique approaches, such as carbonation heat (via isothermal calorimetry), Rietveld refinement, etc., suggested that rhombic calcite was covered by spherical nanoparticles, formed from the transformation of amorphous calcium carbonate, and the rate of reaction was controlled by the solution environment. The particle size of calcite increased greatly in the leveled reaction stage (i.e., stage III). A combined effect of the strong mechanical bond and lamellar stack formed among calcite particles compacted the microstructure significantly. Changes in the crystallite size (from 43.9 to 107.9 nm), particle size (from 302.2 to 2077.6 nm), thermodynamic stability, lattice volume, and bond length were observed during the growth process of calcite. These findings provide a possibility to control the polymorphs, microstructures, or specific particle sizes of calcium carbonate for industrial applications and are beneficial for understanding and imitation of diagenesis paths in natural processes.

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 categoriesMeta-epidemiology (narrow)
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 score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.019
GPT teacher head0.229
Teacher spread0.210 · 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.

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

Citations112
Published2020
Admission routes1
Has abstractyes

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