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Effect of Synthetic Wastewater by Electrochemical Pretreatment on <i>Chlorella vulgaris</i> Growth and Nutrients Removal

2013· article· en· W2013132139 on OpenAlexaff
Meng Zi Wang, Zhiwei Zhu, Wei Cao, H. Zhou, Yu Wu, Baoming Li, Yuan Hui Zhang

Bibliographic record

VenueAdvanced materials research · 2013
Typearticle
Languageen
FieldEnergy
TopicAlgal biology and biofuel production
Canadian institutionsUniversity of Guelph
FundersFundamental Research Funds for the Central UniversitiesChinese Universities Scientific Fund
KeywordsChlorella vulgarisWastewaterElectrolysisBiomass (ecology)NutrientSewage treatmentChemistryChlorellaPulp and paper industryFood scienceBiologyBotanyAlgaeEnvironmental engineeringEnvironmental scienceAgronomyOrganic chemistryElectrode

Abstract

fetched live from OpenAlex

Electrochemical processing combined with the system of microalgae Chlorella vulgaris was used to treat the synthetic organic wastewater in this paper. The effect of wastewater concentration on the biomass growth and nutrients removal was investigated. Three levels of the wastewater concentrations were ranked as Low, Mid and High, respectively. After 2 h of electrolysis pretreatment and 10 d of microalgae cultivation, TOC, NH 4 -N, and TP concentrations in the group Low were reduced by 83.7%, 99.3% and 95.0%, respectively. The Chlorella vulgaris in the groups Mid and High without electrolysis pretreatment did not survive longer than 24 h, whereas it grown well in the wastewater pretreated by electrolysis. The dry weight (DW) of Chlorella vulgaris in the group Low with electrolysis pretreatment was increased from 0.048 g/l to 1.087 g/l by 10 d cultivation. Results indicate that electrolysis pretreatment for wastewater can provide appropriate conditions for the subsequent biological treatment and efficiently promote the biomass growth of Chlorella vulgaris .

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)0.001
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 score0.003
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.272
Teacher spread0.263 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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