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Record W4416745414 · doi:10.1080/21650373.2025.2588314

Optimizing nutmeg shell biochar production temperature for enhanced cement composite performance

2025· article· en· W4416745414 on OpenAlexaff
Bhavya, Balasubramanya Manjunath, Claudiane Ouellet‐Plamondon, Bibhuti B. Das, Chandrasekhar Bhojaraju

Bibliographic record

VenueJournal of Sustainable Cement-Based Materials · 2025
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsBiocharComposite numberShell (structure)Production (economics)Nutmeg

Abstract

fetched live from OpenAlex

The growing focus on sustainability has driven research into converting agricultural waste into biochar (BC) for concrete applications. As cement manufacturing contributes significantly to global CO2 emissions, BC offers a promising replacement solution. This study investigates nutmeg shell BC as a sustainable cement alternative produced through pyrolysis at temperatures of 400 °C, 500 °C, and 600 °C, and incorporates it at concentrations of 1%, 2%, and 3% by weight. The main findings reveal that 2% BC prepared at 500 °C achieved optimal performance, with 23% and 27.57% increase in compressive strength and electrical resistivity, respectively, at 28 days. Additional benefits included enhanced water absorption resistance, reduced chloride permeability. Hydration analysis confirms BC’s porous structure provides nucleation sites for cluster formation during early hydration, representing a novel mechanism for accelerated strength development. This research demonstrates BC as a sustainable alternative to cement, offering environmental benefits through CO2 reduction and the valorization of agricultural waste.

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 score0.016
Threshold uncertainty score0.973

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 head0.008
GPT teacher head0.240
Teacher spread0.232 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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