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Record W7030012992

Maximizing the biomethane yield from algal biomass by integrating hydrothermal posttreatment of the anaerobic solid digestate

2016· article· en· W7030012992 on OpenAlexvenueno aff

Bibliographic record

VenueNPARC · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNeurology and Historical Studies
Canadian institutionsnot available
FundersRoyal Golden Jubilee (RGJ) Ph.D. Programme
KeywordsDigestateHydrothermal carbonizationAnaerobic digestionBiogasHydrothermal circulationRaw materialBiomass (ecology)Hydrothermal liquefaction
DOInot available

Abstract

fetched live from OpenAlex

As an alternative to applying the hydrothermal treatment to the raw algal feedstock before the anaerobic digestion (i.e. pre-treatment), one considered a post- treatment scenario where anaerobic digestion is directly used as the primary treatment while the hydrothermal treatment is thereafter applied to the digestate. Hydrothermal treatments such as wet oxidation (WetOx) and hydrothermal carbonization (HTC) were compared at a temperature of 200°C, for initial pressure of 0.1 and 0.82 MPa, and no holding time after the process had reached the temperature setpoint. Both WetOx and HTC resulted in a substantial solids conversion (47% with HTC; 64-83% with WetOx) into soluble products, while some carbon loss was observed (20-33%). This generated high soluble products concentrations (from 6.2 to 10.9 g soluble chemical oxygen demand/L). Biomethane potential tests showed that these hydrothermal treatments allowed for a 4-fold improvement of the digestate anaerobic biodegradability, with a methane potential of about 200 LSTP CH4/kg volatile solids when based on the organic content of the untreated digestate.

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 score0.014
Threshold uncertainty score0.249

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 head0.028
GPT teacher head0.243
Teacher spread0.215 · 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
Published2016
Admission routes1
Has abstractyes

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