Valorization of Agricultural Ashes from Cold and Temperate Regions as Alternative Supplementary Cementitious Materials: A Review
Bibliographic record
Abstract
The pursuit of sustainable alternatives to portland cement has become a global imperative within the construction sector, driven by the need to reduce carbon dioxide emissions and energy consumption. Among the promising alternatives, agricultural ashes have garnered attention for their potential as alternative supplementary cementitious materials (ASCMs), owing to their inherent pozzolanic properties when appropriately processed. However, the availability and utilization of these ashes have predominantly been concentrated in tropical and subtropical regions, where such biomass is more abundant. This review offers a comprehensive bibliometric analysis to identify and assess agricultural ashes (specifically switchgrass, barley, sunflower, and oat husks) that are cultivated in temperate and cold climates and exhibit potential for SCM application. The analysis aims to bridge the knowledge gap by systematically mapping the existing research landscape and highlighting underexplored resources suitable for cold-region implementation. Key processing parameters, including incineration temperature, retention duration, and post-combustion grinding techniques, are critically examined for their influence on the resulting ash’s physicochemical characteristics and pozzolanic reactivity. In addition, the effect on fresh, hardened, and durability properties was evaluated. Findings reveal that several crops grown in colder regions may produce ashes rich in reactive silica, thereby qualifying them as viable ASCM candidates and bioenergy sources. Notably, the ashes derived from switchgrass, barley, oats, and sunflowers demonstrate significant reactive silica content, reinforcing their potential in sustainable construction practices. Hence, this study underscores the multifaceted benefits of contributing to the decarbonization of the cement industry and circular economy, while addressing environmental challenges associated with biomass waste disposal and uncontrolled open-air combustion.
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 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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".