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Record W3203562598 · doi:10.3390/constrmater1030010

Clay as a Sustainable Binder for Concrete—A Review

2021· article· en· W3203562598 on OpenAlexaff
Seyed Sina Mousavi, Chandrasekhar Bhojaraju, Claudiane Ouellet‐Plamondon

Bibliographic record

VenueConstruction Materials · 2021
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsShrinkageCompressive strengthCementRaw materialThixotropyMaterials scienceGeotechnical engineeringPortland cementCalcinationComposite materialEnvironmental scienceGeology

Abstract

fetched live from OpenAlex

The negative environmental impacts of Portland cement as a binder in the construction industry have created a growing impetus to develop sustainable alternative binders. Various types of clay have been considered as potential cement replacements. The impact of clays as cement replacement depends on the dosage and treatment methods. This paper presents a comprehensive review to determine the effects of different types of clay on the fresh and hardened properties of concrete mixtures by analyzing the experimental database reported by the literature, including raw, calcined, modified, nano, and organo. This study intends to show the process of optimizing the use of clay in concrete, the reason behind converting raw clay to modified types, and research gaps through a comparison study between different types of clays. The present review study shows that clay-based concrete mixtures have higher thixotropy and yield stress values, improving shape stability. This results in lower early-age shrinkage of the concrete. However, the high floc strength of clay-based concrete causes a reduction in flowability. Treatment methods of raw clay, such as calcination and nano-sized clay particles, improve concrete compressive strength. General results of the previous studies highlight that all types of clay investigated positively affect the resistance of concrete to environmental attack.

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 categoriesInsufficient payload (model declined to judge)
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 score0.159
Threshold uncertainty score0.992

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)0.0090.000

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 head0.276
Teacher spread0.260 · 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

Citations43
Published2021
Admission routes1
Has abstractyes

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