Production of sustainable biocrude from Canadian agricultural biomass: Process optimization and product characterization
Bibliographic record
Abstract
The world's energy requirement is rising continuously due to an increase in the global population and demand for better quality of life. Fossil fuels are non-renewable, and their consumption poses global warming. Biomass-derived fuels are sustainable alternatives to fossil fuels as they are originated from renewable feedstocks. The present study investigates the production of biocrude from hydrothermal liquefaction of Canadian agricultural straws at identical conditions. Further, barley straw is found to be promising; therefore, hydrothermal liquefaction process parameters are varied for barley straw to maximize the biocrude yield with lower oxygen content. At optimum reaction conditions, the existence of carboxylic acids, phenols, aldehydes, and ketones is identified in the produced biocrude. Further, the recyclability study of the aqueous phase is attempted to explore the possibility of reusing this phase. The physicochemical characteristics of the biocrude (main product) and by-products (hydrochar, non-condensable gases, and aqueous phase) are also studied to identify the suitable areas of applications. The present experimental study demonstrates a detailed understanding of the liquefaction behavior of Canadian barley straw for biocrude production with an immense potential to co-refine in the existing petroleum refineries. • Various Canadian agricultural biomass are screened for biocrude production. • Focus is on characterization of biomass and biocrude produced. • HTL process parameters are studied to maximize biocrude production. • Biocrude and byproducts detailed characterizations are completed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".