Optofluidics for Energy: Fuel and Electricity From Plasmonically-Excited Photosynthetic Bacteria
Bibliographic record
Abstract
Microalgae have been demonstrated to be the only viable major biofuel avenue due to globally finite cropland[1]. Traditional photobioreactors used to cultivate microalgae and cyanobacteria for biofuel production are plagued by low cell density due to limited light penetration depth [2]. An optofluidic approach to cultivation of cyanobacteria provides an opportunity to overcome these difficulties by leveraging the inherent density advantages of biofilm growth [3]. A biophotovoltaic cell (BPV) is presented that is capable of high-density cultivation of cyanobacteria using surface plasmon resonance (SPR) enhanced evanescent fields as well as producing electrical power. This device, a photosynthetic-plasmonic-voltaic cell (PPV), demonstrated significant power output under direct illumination and plasmonic excitation and demonstrates for the first time the dual use of a gold film for photosystem excitation and electron harvesting. The techniques used in this device are amenable to scale up of an ultra-high density photobioreactor that is capable of coproducing electrical power and biofuel.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".