A dynamical model towards continuous single-cell cultivation using photobioreactors
Bibliographic record
Abstract
Phenomenological models for different stages of a photosynthetic system have helped predict experimental outcomes at the cell level. Similar models exist to predict process outcomes at the bioreactor scale. However, biological and process models are typically ontologically separate, as process models do not include explicit mappings of cellular processes. This work presents a model for the dynamics of photobioreactors with phenomenological reaction kinetics. The model allows for design and control integration, with insights into design parameters and operating conditions aiding both the growth of microalgae and the production of valuable lipids. The model also enables integration of process topology such that the reactor network connections yielding a complete process can be modelled alongside reaction kinetics. Therefore, we provide insights on nonlinear dependence of biomass and lipid production using microalgae cultivation, design parameters such as incident light intensity and photobioreactor radius, and process operating conditions such as flow rates. • A dynamical model for continuous single-cell cultivation is presented. • Dynamical model considers light and flow rate of species into the reactor as only inputs. • Dependence on radial design parameter is also studied to yield optimal conditions for growth and production. • Simplicity of the model could aid in control and monitoring applications.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".