Third-generation biomass for bioplastics: a comprehensive review of microalgae-driven polyhydroxyalkanoate production
Bibliographic record
Abstract
Bio-based plastics, primarily polyhydroxyalkanoates (PHAs), offer a hopeful alternative to petroleum-derived plastics. Third-generation (3G; microalgae/cyanobacteria) biomass has gained significant importance due to its rapid biomass productivity and metabolic versatility. Microalgae can produce PHAs by utilizing CO2 and wastewater, establishing them as highly promising and eco-friendly systems for bioplastic production. This comprehensive review presents comprehensive insights into microalgae-PHA production, from optimization of physicochemical and cultural conditions to effective PHA purification processes. The critical review also examines the latest advancements in cultivation strategies, metabolic engineering, and bioreactor developments, which may lead to more sustainable and progressive microalgal-based bioplastic accumulation. The effectiveness of algae biomass generation for PHA accumulation through integrated wastewater treatment has been addressed. This review examines the role of mathematical modeling and emerging artificial intelligence in advancing algae-based PHA production processes. Finally, the review concludes with a discussion of the economic and social challenges, life cycle analysis, and prospects for research and development of advanced microalgal-derived bioplastics production and predictions of potential solutions for economically feasible and sustainable microalgae-based PHA production at the industrial scale.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".