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Record W4414302390 · doi:10.5539/ijc.v18n1p12

An Exploration of Ionic Buswell’s Equation for Biomethane

2025· article· en· W4414302390 on OpenAlexvenueno aff
Pong Kau Yuen, Kuok In Gabriel Yuen

Bibliographic record

VenueInternational Journal of Chemistry · 2025
Typearticle
Languageen
FieldEngineering
TopicMembrane Separation and Gas Transport
Canadian institutionsnot available
Fundersnot available
KeywordsIonic bondingDigestateIonic liquidAnaerobic digestionBiogasStoichiometry

Abstract

fetched live from OpenAlex

Anaerobic digestion is a sustainable process that occurs under anaerobic microorganism-mediated conditions. In this process, organic matters generate biogas and digestate in the gas-aqueous solution-solid multiphases system. Molecular Buswell’s equation has been widely applied for neutral organic matter. In contrast, ionic Buswell’s equation has been given little attention. This article uses the proton method to develop a stoichiometric ionic Buswell’s equation for neutral and ionic organic matters. When an empirical formula of organic matter is given, its stoichiometric ionic Buswell’s equation can be balanced and deduced. Conversely, when a structural formula is given, it must go through either the fragmentation method to identify the designated products or the carbon-atom method to identify the organic fragmented formula. The designated products or the organic fragmented formula can then be input into the proton method to balance the ionic Buswell’s equation. Based on any given organic matter, regardless of its electrical charge and nature of formula, the mean oxidation number of organic carbons, parameters of organic matter, parameters of Buswell’s equation, and ionic Buswell’s equation can be determined. Compared to molecular Buswell’s equation, the established ionic Buswell’s equation is an extended model for understanding physical, chemical, and biochemical processes among water molecules, ionic species, and neutral species in the multiphases anaerobic digestion system.

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: none
Teacher disagreement score0.592
Threshold uncertainty score0.232

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.030
GPT teacher head0.317
Teacher spread0.287 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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