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Record W4404578397 · doi:10.1016/j.nxener.2024.100213

Influence of phenol-formaldehyde and melamine-formaldehyde resins on the gasification of high-pressure laminate waste materials

2024· article· en· W4404578397 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNext Energy · 2024
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaUniversité de Sherbrooke
KeywordsFormaldehydePhenolMelaminePhenol formaldehyde resinMaterials scienceMelamine resinComposite materialWaste managementOrganic chemistryChemistryEngineering

Abstract

fetched live from OpenAlex

The repurposing of industrial solid wastes for sustainable energy production figures as a convenient alternative to decrease the carbon footprint of industrial processes by increasing circularity and reducing the utilization of fossil-based energy vectors. The furniture industry generates significant amounts of carbon-based waste materials, including high-pressure laminates (HPL) that comprise cellulose-based materials treated with thermosetting phenol-formaldehyde and melamine-formaldehyde resins. There are currently no energy recovery studies for this type of waste, especially concerning thermochemical conversion. In this work, we proposed to evaluate the potential of HPL wastes for the generation of energy relevant gaseous products (syngas) by gasification, using air and steam as gasifying agents in a downdraft gasifier. The influence of temperature (600–900 °C), equivalence ratio (ER, 0.20–0.30) and the presence of the thermosetting formaldehyde-based resins were evaluated in the composition (H 2 content, H 2 /CO ratio) and lower heating value (LHV) of the obtained syngas. The increase in temperature positively influenced the H 2 content in the final gas product, contrarily to the increase in ER. High temperature (900 °C) and low ER (0.20) were found to favor H 2 production (43.8%vol), increase syngas fraction (58.0%vol) and LHV (7.4 MJ/Nm 3 ) of the gas products. The presence of the thermosetting resins contributed to the production of a larger syngas fraction with high H 2 content (62.3%vol, H 2 /CO = 2.4). Overall, gasification of HPL wastes was shown to be a promising alternative to the production of hydrogen-rich syngas with potential industrial applications. • H 2 -rich syngas rich was produced from the gasification of HPL wastes. • The use of steam in has a positive influence on the H 2 content. • The gasification of HPL wastes produced high fraction syngas streams. • Thermosetting resins increased H 2 content and syngas fraction. • Grain and random pore kinetic models best described the gasification process.

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 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 score0.029
Threshold uncertainty score0.409

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 head0.181
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