Wavelength-selective plasmonics for enhanced cultivation of microalgae
Bibliographic record
Abstract
Optimal photon management is a key challenge for photobioreactor design, since light gradients and varying spectral sensitivities between organisms result in uneven illumination and unused photons. This paper demonstrates wavelength specific scattering from plasmonic nano-patterned surfaces as a means of addressing the challenge of photon management in photobioreactors. Modular photobioreactors were constructed with different reflective substrates including arrays of plasmonic nanodisks, broadband reflectors, and untreated glass. It was found that the growth rate of cyanobacterium S. elongatus in photobioreactors equipped with a plasmonic substrate (R623 nm ∼ 35%) was enhanced by 6.5% compared to photobioreactors equipped with untreated glass. Furthermore, plasmonic reflectors showed a normalized power efficiency improvement of 52% over broadband reflectors. Wavelength-specific reflection from plasmonic reflectors increases the flux of useful light to cultures without sacrificing the full spectrum.
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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 | 0.000 |
| 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".