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Record W7117146419 · doi:10.1504/ijep.2025.150812

Synthesis of activated carbon from coffee husks and its effect on CO<SUB align="right">2 capture and CH<SUB align="right">4 and H<SUB align="right">2 storage

2025· article· en· W7117146419 on OpenAlex
Cristian Toncón Leal, Kiara Montiel Centeno, Cristian Díaz, Deicy Barrera, Jhonny Villarroel Rocha, Liliana Trevani, Laura Conde, Karim Sapag

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Environment and Pollution · 2025
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsActivated carbonHuskAdsorptionFourier transform infrared spectroscopyScanning electron microscopePorosity

Abstract

fetched live from OpenAlex

This work presents the synthesis of activated carbons from coffee husk pre- treated with steam explosion. The influence of the impregnation ratio (H3PO4/precursor) and impregnation time was evaluated. The synthesised materials were characterised by N2 adsorption-desorption isotherms at 77 K and CO2 adsorption at 273 K, scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and Raman spectroscopy. These techniques confirmed the success of activated carbons from the coffee industry waste. Two selected activated carbons were further evaluated for their CO2, CH4, and H2 adsorption capacities at 308 K, 298 K, and 77 K, respectively, under pressures of up to 10 bar. CA-1 and CA-5 exhibited promising H2adsorption capacities, comparable to values reported. These findings open up new possibilities for developing porous carbon- based activated materials for advanced gas separation applications.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.004
GPT teacher head0.192
Teacher spread0.188 · 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