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Alkali-activated fly ash cured with pulsed microwave and thermal oven: A comparison of reaction products, microstructure and compressive strength

2023· article· en· W4319723449 on OpenAlexfundno aff
Shi Shi, Hui Li, Qizhi Zhou, Hongzhou Zhang, Muhammed Basheer, Yun Bai

Bibliographic record

VenueCement and Concrete Research · 2023
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilEducation Department of Shaanxi ProvinceChina Scholarship CouncilQueen's UniversityQueen's University Belfast
KeywordsMicrostructureFly ashCuring (chemistry)Materials scienceCompressive strengthMicrowave ovenComposite materialMicrowaveDissolutionAlkali metalThermalChemical engineeringChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The reaction products and microstructure of an 8 M NaOH-activated fly ash (AAFA) cured with microwave and thermal oven curing were comparatively investigated. The results show that the formation of an Al-rich N-A-S-H gel with a flaky morphology and crystalline chabazite-Na between fly ash particles were favoured under the microwave curing, whilst a Si-rich N-A-S-H gel with a fibrilllar morphology and crystalline hydroxysodalite on the surface of fly ash particles were dominant under the thermal oven curing. The formation of these unique reaction products and microstructure under the microwave curing is attributed not only to the thermal effect of microwaves which can increase the temperature of AAFA volumetrically, but also to the non-thermal effects of microwaves which can promote the dissolution and diffusion of silica and alumina during the AAFA reaction process. This explains why AAFA can achieve a high early strength within a short period of microwave 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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.641

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 head0.041
GPT teacher head0.311
Teacher spread0.270 · 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

Citations61
Published2023
Admission routes1
Has abstractyes

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