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Record W2061912503 · doi:10.1109/tpel.2014.2317675

Advanced Fabrication, Modeling, and Testing of a Microphotosynthetic Electrochemical Cell for Energy Harvesting Applications

2014· article· en· W2061912503 on OpenAlexaff
Arvind Vyas Ramanan, Muthukumaran Pakirisamy, Sheldon S. Williamson

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsConcordia University
Fundersnot available
KeywordsEmulationComputer scienceEnergy harvestingElectrical engineeringPower densityPower (physics)PhysicsEngineeringThermodynamics

Abstract

fetched live from OpenAlex

Unconventional renewable energy sources are scarce and have not been explored thoroughly or exploited. The photosynthetic power cell (PSC) is one among them. Though there are few prototypes fabricated earlier, there has not been a comprehensive electrical equivalent model developed. This paper proposes an electrical equivalent model for a microphotosynthetic power cell (μPSC), which is tested and authenticated with experimental verification on a fabricated prototype. The developed model is further used for testing emulation behavior, to efficiently and accurately design an energy harvesting power electronic converter. The principle of the operation of the device is based on “photosynthesis.” Photosynthesis and respiration both involve an electron transfer chain. The electrons are extracted with the help of electrodes and a redox agent, and a power electronic converter is designed to harvest the energy. The fabricated cell is capable of producing an open-circuit voltage of 0.9 V and about 200 μW of peak power. The μPSC has an active area of 4.84 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , which approximately translates to a power density of 400 mW/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . This makes it as one of the best-performing μPSC. The other top-performing μPSC devices report power densities of between 100 and 250 mW/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . The PSC produces energy under both dark and light conditions.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.926
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.223
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2014
Admission routes1
Has abstractyes

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