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Record W4392385084 · doi:10.18280/rcma.340105

Influence of Date Palm Waste Aggregates on the Mechanical Strengths and Hygroscopicity Behavior of Earth-Based Composites

2024· article· fr· W4392385084 on OpenAlexvenueno aff
Ouarda Izemmouren, Bezaou Ferdous, Gadri Karima

Bibliographic record

VenueRevue des composites et des matériaux avancés · 2024
Typearticle
Languagefr
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsnot available
FundersDirection Générale de la Recherche Scientifique et du Développement Technologique
KeywordsComposite materialMaterials sciencePalmEarth (classical element)Mathematics

Abstract

fetched live from OpenAlex

The underutilization of natural waste from date palm plantation maintenance presents an opportunity for the production of sustainable building materials.This study investigates the mechanical properties and environmental sustainability of adobe bricks reinforced with date palm waste (DPW) and a small percentage of cement.Adobe bricks were stabilized using 7% cement by weight and varying proportions of DPW (0%, 0.5%, 1%, and 1.5% by weight), followed by curing under two distinct conditions: moist storage (MS) and open-air (AF).It was observed that bricks cured under MS conditions significantly outperformed those cured in AF, evidenced by a 47.05% reduction in capillary absorption coefficient compared to the reference brick.Despite a decrease in compressive strength due to DPW incorporation, the bricks exhibited increases in capillary and total absorption while still satisfying earth construction standards.Notably, flexural strength improved by 41.66% under MS curing.Enhanced erosion and abrasion resistance, as well as improved performance throughout wetting/drying cycles, were also recorded.These enhancements underscore the potential of DPW as a renewable additive in the formulation of adobe bricks for ecological and durable housing.The study not only proposes a novel use for date palm byproducts but also contributes to the advancement of environmentally-friendly construction methodologies.

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 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 score0.056
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.032
GPT teacher head0.295
Teacher spread0.263 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueRevue des composites et des matériaux avancésSame topicNatural Fiber Reinforced CompositesFrench-language works237,207