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Record W4319072690 · doi:10.24214/jcbps.d.13.1.04150

Removal of Hydrogen Sulphide from Biogas by Activated Carbon Based on Borassus Aethiopum (Ivory Coast)

2023· article· en· W4319072690 on OpenAlexfundno aff
Ahissan Donatien Ehouman, Konan Affoué, Tindo Sylvie, Adjoumani Rodrigue Kouakou, Taniky Ouattara, Adou Kouakou, Konan Gbangbo Rémis, K. Horo, Lynda Ekou, Tchirioua Ekou

Bibliographic record

VenueJournal of Chemical Biological and Physical Sciences · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicPhosphorus and nutrient management
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsBiogasActivated carbonEnvironmental scienceRenewable energyWaste managementRaw materialPulp and paper industryCarbon fibersAdsorptionChemistryMaterials scienceEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Biogas is one of the most attractive renewable resources because of its ability to convert waste into energy.Biogas is composed mainly of CH4, CO2, and some trace gases such as hydrogen sulphide (H2S) which is a very toxic, deadly and corrosive gas.Therefore, raw biogas needs to be cleaned of hydrogen sulphide before it can be used in many applications.The overall objective of this work was to investigate the removal efficiency of hydrogen sulphide (H2S) by activated carbon based on borassus aethiopum.Borassus aethiopum, also known as roast tree, is an abundant agricultural resource in the rural areas of western, central and northern Cte d'Ivoire.Physico-chemical parameters such as iodine value, ash content, pH at zero load point, tapped density were determined to characterize the synthesized activated carbon.The tests for the elimination of H2S by adsorption on activated carbons were carried out at the BRIN FOUNDATION poultry farm, located in the village of YAOKOKOROKO, sub-prefecture of TABAGNE in the GONTOUGO region.This farm has a methaniser with a capacity of 15 m 3 for the treatment of the chicken Removal of

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 score0.017
Threshold uncertainty score0.302

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.017
GPT teacher head0.235
Teacher spread0.218 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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