A Comprehensive Review of Sustainable Geopolymer Concrete Using Palm Oil Clinker: Environmental and Engineering Aspects
Bibliographic record
Abstract
ABSTRACT Amidst the dual challenges of aggregate scarcity and the environmental impact of carbon dioxide (CO2) emissions from cement production, this study investigates the viability of palm oil clinker (POC) as a sustainable aggregate in geopolymer concrete (GPC). The lack of appropriate alternative coarse and fine aggregates essential in concrete production is one of the critical issues faced by the construction industry. This review evaluates its environmental benefits, chemical and physical attributes, and influence on GPC's microstructure. Previous studies have shown that incorporating POC in GPC significantly reduces density from 2345 to 1821 kg/m3 while maintaining competitive compressive strength, thus proving its applicability in various structural and nonstructural contexts. Moreover, GPC with POC demonstrates enhanced resistance to aggressive environmental conditions such as water absorption and resistance against acid and sulfate environments. Geopolymer mortar (GPM) exposed to sulfate attack recorded the lowest decrease in strength than GPM containing POC fine aggregates by about 20%. The use of 100% POC aggregates in GPC mix has a 3.2% water absorption, which is lower than the limit for high‐performance concrete. The results advocate for the development of POC‐aggregate GPC as an environmentally friendly construction material, contributing to the sustainable advancement of the building industry.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".