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Record W4411222023 · doi:10.3389/fenve.2025.1597684

Retrospective of DIET process for enhanced biogas production during anaerobic digestion of thermal/chemically pretreated waste activated sludge

2025· article· en· W4411222023 on OpenAlexaff
Abdulaziz Mohammed Almegbl, Ali Mohammad Rahmani, Kamaluddin Kamal, Faris Mohammad A. Munshi, Abbas Khursheed, Muntjeer Ali, Anwar Khursheed

Bibliographic record

VenueFrontiers in Environmental Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicAnaerobic Digestion and Biogas Production
Canadian institutionsCarleton University
Fundersnot available
KeywordsAnaerobic digestionBiogas productionBiogasActivated sludgeWaste managementPulp and paper industryChemistryDigestion (alchemy)Production (economics)Thermal hydrolysisFood scienceSewage sludge treatmentSewage treatmentMethaneOrganic chemistryEngineeringChromatography

Abstract

fetched live from OpenAlex

Hydrolysis of recalcitrant organic waste such as lignocellulosic biomass and waste-activated sludge (WAS) is a rate-limited step in anaerobic digestion (AD) due to the chemical and physical barriers that can be diminished by pretreatment of the waste. However, for readily biodegradable, soluble organics or already hydrolyzed organics, acetogenesis and methanogenesis become the rate-limiting steps owing to the discrepancy in the syntrophic relationship of the inter-microbial matrix. Enhancing the syntrophic relation of VFA oxidizing bacteria and hydrogenotrophic methanogens via direct interspecies electron transfer (DIET) is vital for enhanced and efficient bio-methanation. DIET changes the metabolic pathways, which can be evidenced by microbial diversity, abundance, and associated enzymes. The stimulation of DIET can enhance biogas production and methane content and enhance VFA and ammonia-stressed digesters. The conductive materials for DIET in AD should be non-hazardous, chemically stable, cheap, recyclable, non-reactive, porous, conductive, microbe-friendly, and provide a large surface area. DIET stimulation and optimization via sustainable materials for high organic wastes are the future research areas that need comprehensive exploration.

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 score0.216
Threshold uncertainty score0.887

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 head0.003
GPT teacher head0.178
Teacher spread0.175 · 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

Citations6
Published2025
Admission routes1
Has abstractyes

Explore more

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