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Record W4405549487 · doi:10.1007/s44290-024-00151-2

Exploring the impact of CO2 sequestration on plastic properties, mechanical performance, and microstructure of concrete

2024· article· en· W4405549487 on OpenAlexafffund
Clinton Pereira, Rishi Gupta

Bibliographic record

VenueDiscover Civil Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversity of Victoria
FundersUniversity of Victoria
KeywordsMicrostructureMaterials scienceComposite material

Abstract

fetched live from OpenAlex

In view of global warming, carbon sequestration techniques are being employed across the globe to minimize the damaging effects of greenhouse gases on the environment. Studies have revealed that adding CO 2 during the mixing or curing stage of concrete enhances its mechanical properties and long-term durability. This study aims to examine the effect of CO 2 addition during the mixing stage on the plastic, mechanical and microstructural properties of concrete. Various CO 2 dosages, ranging from 0.1 to 1%, were injected during mixing to analyze the plastic and hardened properties of concrete. CO 2 primarily reacts with calcium hydroxide in concrete to form calcium carbonate (CaCO 3 ), thereby densifying its microstructure and improving its compressive strength by 10–20%. An optimum strength of up to 20% was achieved with 0.75% dosage. Additionally, the results show a 5–10% improvement in flexural and split tensile strength with CO 2 addition over the control mix, with 0.75% dosage yielding optimal strength. Semi-adiabatic calorimetry test on early hydrating concrete shows a 14% peak temperature rise at 0.75% CO 2 dosage compared to control concrete, indicating enhanced early-age strength development. Thermal Pyrolysis tests, microscopy and infrared spectroscopy indicated the presence of CaCO 3 , thereby confirming the carbonation process. However, CO 2 dosages above 0.5% by weight of cement resulted in a drop in the workability of concrete in the plastic stage. This research attempts to create a simplified CO 2 sequestration process in concrete, develop a predictive model to estimate the compressive strength and utilize material characterization techniques to identify the mineralization process. Highlights Injecting CO 2 into fresh concrete improves its strength and lowers its environmental impact. A multiple linear regression model predicts the compressive strength of CO 2 -injected concrete. Semi-adiabatic calorimetry shows that CO 2 injection speeds up early hydration. Thermal Pyrolysis detects mass loss stages linked to dehydration and calcite breakdown. Microscopy and spectroscopy indicate CaCO 3 crystal formation in CO 2 -sequestered concrete.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score0.338

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 head0.029
GPT teacher head0.229
Teacher spread0.199 · 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

Citations5
Published2024
Admission routes2
Has abstractyes

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