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Record W2528450474 · doi:10.2495/sdp-v11-n5-700-707

Biocrude production by hydrothermal liquefaction of olive residue

2016· article· en· W2528450474 on OpenAlexvenueno aff
Paolo De Filippis, Benedetta de Caprariis, Marco Scarsella, A. Petrullo, Nicola Verdone

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2016
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsnot available
Fundersnot available
KeywordsHydrothermal liquefactionLiquefactionResidue (chemistry)Hydrothermal circulationEnvironmental scienceWaste managementPulp and paper industryChemistryBiofuelEngineeringChemical engineering

Abstract

fetched live from OpenAlex

Hydrothermal liquefaction (HTL) converts biomass into a crude bio-oil by thermally and hydrolytically decomposing the biomacromolecules into smaller compounds. The crude bio-oil, or biocrude, is an energy dense product that can potentially be used as a substitute for petroleum crudes. Liquefaction also produces gases, solids, and water-soluble compounds that can be converted to obtain valuable chemical species or can be used as energy vectors. The process is usually performed in water at 250C-370C and under pressures of 4-22 MPa: depending on the adopted pressure and temperature the process can be carried out in sub-critical or super-critical conditions. In the conditions reached in hydrothermal reactors, water changes its properties and acts as a catalyst for the biomass decomposition reactions. One of the main advantages of this process is that the energy expensive biomass-drying step, required in all the thermochemical processes, is not necessary, allowing the use of biomass with high moisture content such as microalgae or olive residue and grape mark.

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 score0.032
Threshold uncertainty score0.214

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 head0.006
GPT teacher head0.212
Teacher spread0.206 · 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

Citations11
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Sustainable Development and PlanningSame topicThermochemical Biomass Conversion ProcessesFrench-language works237,207