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Record W3024907020 · doi:10.1149/09707.0565ecst

In-situ Electrodeposition of Nickel on a Biocathode to Enhance Methane Production from Carbon Dioxide in a Microbial Electrosynthesis System

2020· article· en· W3024907020 on OpenAlexaff
Abraham Gomez Vidales, Sasha Omanovic, B. Tartakovsky

Bibliographic record

VenueECS Transactions · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Fuel Cells and Bioremediation
Canadian institutionsMcGill UniversityNational Research Council Canada
Fundersnot available
KeywordsElectrosynthesisNickelCathodeSalt (chemistry)MethaneCarbon dioxideCarbon fibersCatalysisChemistryDeposition (geology)In situInorganic chemistryChemical engineeringMaterials scienceElectrodeElectrochemistryOrganic chemistryGeology

Abstract

fetched live from OpenAlex

This study demonstrates the continuous conversion of CO 2 to CH 4 in a laboratory-scale Microbial Electrosynthesis System (MES). The introduction of a Ni salt at 0.2 g L -1 into the cathode influent stream improved the CO 2 conversion. After the introduction of the Ni salt at an applied voltage of 2.8 V, the MES with the carbon-felt cathode reached a CH 4 production of 422 ± 36 mL d -1 (0.81 L L c -1 d -1 ), which was 39 ± 12% higher than that of this system before the Ni salt was introduced. Additionally, when the dissolved Ni salt was removed from the influent solution, the MES performance remained unchanged, thus confirming the in-situ deposition of Ni on the carbon-felt cathode and its catalytic effect.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.007
GPT teacher head0.208
Teacher spread0.202 · 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
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

Citations12
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueECS TransactionsSame topicMicrobial Fuel Cells and BioremediationFrench-language works237,207