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Record W2980283579 · doi:10.1016/j.heliyon.2019.e02566

Pozzolanic properties of ultrafine sugar cane bagasse ash produced by controlled burning

2019· article· en· W2980283579 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHeliyon · 2019
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsnot available
FundersGlobal Affairs CanadaFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de JaneiroConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsPozzolanic activityPozzolanMaterials sciencePortlanditeCompressive strengthBagassePozzolanaPortland cementThermogravimetric analysisPozzolanic reactionComposite materialCementWaste managementPulp and paper industryChemistry

Abstract

fetched live from OpenAlex

This paper evaluated the feasibility of using residual sugar cane bagasse ash with a high carbon content (as-received SCBA) as raw material to produce a pozzolan after controlled recalcination and grinding. Initially, the as-received SCBA was re-burned using rotary (continuous) and muffle (batch) kilns, both at 600 °C for 1 h. Next, the resulting ash was ground in a closed-circuit ball mill with an air classifier system to obtain a product with 50% passing particle size of approximately 10 μm (SCBA600). SCBA600 was then characterized in terms of oxide composition, loss on ignition, density, specific surface area, and pozzolanic activity. A hydration study was carried out using isothermal calorimetry, thermogravimetric analysis and mercury intrusion porosimetry. Additionally, the performance of SCBA600 in mortars was evaluated by axial compression tests. The combination of recalcination at 600 °C, low-energy ultrafine grinding of the material and classification resulted in pozzolanic SCBA. The results also showed that including SCBA600 in cement mortars reduced total accumulated heat and portlandite content in cement-based pastes, in addition to refining pore structure and significantly increasing compressive strength after 3 days of curing.

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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.849

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)0.0010.000

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 head0.010
GPT teacher head0.208
Teacher spread0.198 · 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