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Record W4399765747 · doi:10.32920/26052481.v1

Effects of Sulfuric Acid on Geopolymer Composites

2024· preprint· en· W4399765747 on OpenAlexaff

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsGeopolymerSulfuric acidComposite materialMaterials scienceCompressive strengthMetallurgy

Abstract

fetched live from OpenAlex

This report investigates the effects of sulfuric acid attack on the High-Performance Concrete (HPC) and Engineered Geopolymer Composite (EGC) mixes. Specimens from a total of 28 EGC mixes and 10 HPC mixes were selected for this study. A sulfuric acid solution with concentration of 10% was used for examining the resistance of concrete specimens over a period of 45. The durability of concrete mixes was evaluated by measuring the weight loss, change in strength, thermal conductivity and UPV value. The results of the weight loss reveal that the EGC mixes were more resistant to sulfuric acid attack than HPC mixes. The mixes with ternary binders of class c fly ash, silica sand, and class f fly ash experienced the greater strength loss after exposure to high concentrations of sulfuric acid as opposed to the binary mix of class c fly ash and silica sand. A significant decline in compressive strength of HPC specimens was observed as compared to EGC specimens.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0020.000

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 source (direct Gemma or distilled Codex), 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
Published2024
Admission routes1
Has abstractyes

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