Bioreactor Operating Strategies for Improved Polyhydroxyalkanoate (PHA) Productivity
Bibliographic record
Abstract
Microbial polyhydroxyalkanoates (PHAs) are promising biodegradable polymers that may alleviate some of the environmental burden of petroleum-derived polymers. The requirements for carbon substrates and energy for bioreactor operations are major factors contributing to the high production costs and environmental impact of PHAs. Improving the process productivity is an important aspect of cost reduction, which has been attempted using a variety of fed-batch, continuous, and semi-continuous bioreactor systems, with variable results. The purpose of this review is to summarize the bioreactor operations targeting high PHA productivity using pure cultures. The highest volumetric PHA productivity was reported more than 20 years ago for poly(3-hydroxybutryate) (PHB) production from sucrose (5.1 g L−1 h−1). In the time since, similar results have not been achieved on a scale of more than 100 L. More recently, a number fed-batch and semi-continuous (cyclic) bioreactor operation strategies have reported reasonably high productivities (1 g L−1 h−1 to 2 g L−1 h−1) under more realistic conditions for pilot or industrial-scale production, including the utilization of lower-cost waste carbon substrates and atmospheric air as the aeration medium, as well as cultivation under non-sterile conditions. Little development has occurred in the area of fully continuously fed bioreactor systems over the last eight years.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.002 | 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".