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Record W2808348982 · doi:10.1002/cjce.23256

A simple power management circuit for microbial fuel cell operation with intermittent electrical load connection

2018· article· en· W2808348982 on OpenAlexaffvenue
L. A. Woodward, B. Tartakovsky

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Fuel Cells and Bioremediation
Canadian institutionsNational Research Council CanadaÉcole de Technologie Supérieure
Fundersnot available
KeywordsMicrobial fuel cellInternal resistanceRobustness (evolution)VoltageVoltage sourceComputer scienceMaximum power principlePower (physics)Energy sourceElectricity generationAutomotive engineeringMaterials scienceEnvironmental scienceElectrical engineeringEngineeringChemistry

Abstract

fetched live from OpenAlex

Abstract Practical implementation of microbial fuel cell (MFC)‐based power sources requires stable MFC performance regardless of the variations in the composition and quantity of a carbon source (fuel). This study describes a simple power management circuit (PMC) utilizing low and high voltage boundaries for intermittent MFC connection and disconnection to the electrical load. The PMC performance is demonstrated during MFC operation at carbon source‐replete and carbon source‐deplete conditions. In spite of MFC operation at external resistance values significantly below the estimated internal MFC resistance (e.g., 5.5 versus 24.5 Ω, respectively), the proposed PMC optimized MFC performance at all tested influent acetate concentrations, resulting in a volumetric power output of up to 56 mW · L −1 . Furthermore, MFC operation with an up‐converter is tested and approaches for optimizing the voltage boundaries are discussed. The robustness and simplicity of the proposed PMC algorithm allows for its implementation in a standalone microprocessor with ultralow energy consumption, which enables MFC application as an autonomous power source.

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: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.277

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 head0.005
GPT teacher head0.165
Teacher spread0.160 · 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

Citations4
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicMicrobial Fuel Cells and BioremediationFrench-language works237,207