Feasibility Studies of Micro Photosynthetic Power Cells as a Competitor of Photovoltaic Cells for Low and Ultra-Low Power IoT Applications
Bibliographic record
Abstract
In this work, we provide a cost comparison of micro-photosynthetic power cells (µPSC) with the well-established photovoltaic (PV) cells for ultra-low power and low power applications. We also suggest avenues for the performance improvement of µPSC. To perform cost comparison, we considered two case studies, which are development of energy systems for: (i) A typical mobile-phone battery charging (low power application) and (ii) powering a humidity sensor (ultra-low power application). For both the cases, we have elucidated the steps in designing energy systems based on PV and µPSC technologies. Based on the design, we have considered the components needed and their costs to obtain total cost for developing energy systems using both PV and µPSC technologies. Currently, µPSCs based energy systems are costlier compared to their PV counterparts. We have provided the avenues for improving µPSC performance, niche application areas, and aspects in which µPSCs are comparable to PV cells. With a huge potential to develop low-cost and high performing technologies, this emerging technology can share the demand on PV technologies for ultra-low power 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 | 0.000 |
| 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".