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Record W3215229892 · doi:10.3390/polym13234160

Research on Compressive and Flexural Properties of Coal Gangue-Slag Geopolymer under Wetting-Drying Cycles and Analysis of Micro-Mechanism

2021· article· en· W3215229892 on OpenAlexaff
Xiaoyun Yang, Yan Zhang, Zhuhan Li, Minglei Wang

Bibliographic record

VenuePolymers · 2021
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversity of WaterlooUniversity of Victoria
FundersChina Scholarship CouncilNational Natural Science Foundation of China
KeywordsGeopolymerCompressive strengthMaterials scienceFlexural strengthComposite materialGangueCorrosionMetallurgy

Abstract

fetched live from OpenAlex

Coal gangue-slag geopolymer is a kind of environment-friendly material with excellent engineering performance and is formed from coal gangue and slag after excitation by an alkaline activator. In this study, three kinds of coal gangue-slag geopolymer were activated by different activators, and the compressive and flexural strengths of water and sulphate solutions in the wetting-drying (W-D) cycles were compared. The microscopic mechanism was analyzed by the XRD, the FTIR and the SEM. The following conclusions are drawn: The influence of W-D cycles on flexural strength was greater than compressive strength. The water migration and the recombination of geopolymers lead to the change of colour, as well as the reduction of flexural strength and compressive strength of geopolymers. The SH geopolymer had excellent anti-erosion ability in terms of flexural strength, and the reason for this was the recombination and polymerization reaction of geopolymer being weaker than the SS and the SSG. The corrosion resistance of the SS was reflected in the compressive strength, because its geopolymerization reaction was fierce, which produced more Na-rich C-N-A-S-H, N-A-S-H and C-A-S-H gels. Therefore, the compressive strength could still reach more than 39 MPa after 150 cycles. Sulfate solution could effectively control the reduction of compressive strength of the SH and the SS geopolymers during W-D cycles. The SSG had the worst corrosion resistance.

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 score0.007
Threshold uncertainty score0.421

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 head0.052
GPT teacher head0.305
Teacher spread0.253 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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