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Record W4200340982 · doi:10.1002/cpz1.322

Simple, Economical Methods for the Culture of Green Algae for Energy Harvesting from Photosynthesis in a Microfluidic Environment

2021· article· en· W4200340982 on OpenAlexaff
Kiran Kuruvinashetti, Soroush Rahimi, Shanmugasundaram Pakkiriswami, Muthukumaran Packirisamy

Bibliographic record

VenueCurrent Protocols · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Fuel Cells and Bioremediation
Canadian institutionsSaint John Regional HospitalDalhousie UniversityConcordia University
Fundersnot available
KeywordsChlamydomonas reinhardtiiComputer sciencePhotosynthesisBiochemical engineeringProtocol (science)Process engineeringNanotechnologyEnvironmental scienceChemistryMaterials scienceEngineeringBiochemistry

Abstract

fetched live from OpenAlex

Abstract Ongoing technological advancements continually increase the demand for energy. Among various types of energy harvesting systems, biologically based systems have been an area of increasing interest for the past couple of decades. Such systems provide clean, safe power solutions, mainly for low‐ and ultra‐low‐power applications. The microphotosynthetic power cell (μPSC) is one such system that make use of photosynthetic living cells or organisms to generate power. For strong performance, μPSC technology, because of its interdisciplinary nature, requires optimal engineering of both electrochemical cell design and the culture conditions of the photosynthetic microorganisms. We present here a simple, economical culture method for the photosynthetic microorganism Chlamydomonas reinhardtii suitable for the application of this biologically based power system in any geographical location. This article provides a series of protocols for preparing materials and culture medium designed to facilitate the culture of a suitable C. reinhardtii strain even in a non‐biological laboratory. Possible challenges and methods to overcome them are also discussed. Cultured C. reinhardtii perform sufficiently well that they have already been successfully utilized to generate power from a μPSC, generating a peak power of 200 μW from just 2 ml of exponential‐phase algal culture in a μPSC with an active electrode surface area of 4.84 cm2. The μPSC thus has potentially broad applications in low‐ and ultra‐low‐power devices and sensors. © 2021 Wiley Periodicals LLC. This article was corrected on 26 July 2022. See the end of the full text for details. Basic Protocol 1: Algal growth conditions and algal growth chamber fabrication Basic Protocol 2: Preparation of Tris‐acetate‐phosphate (TAP) nutrient medium Basic Protocol 3: Preparation of suspension algal culture from algal strain Basic Protocol 4: Preparation of stock culture plates (algal strain) from suspension algal culture

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.045
GPT teacher head0.339
Teacher spread0.294 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations2
Published2021
Admission routes1
Has abstractyes

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