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Record W4408746924 · doi:10.1021/acsomega.4c08250

Catalytic Hydrothermal Liquefaction of Grape Pomace Using Ni–ZrO<sub>2</sub>–MSS and Ni–HZSM5 in a Water–Crude Glycerol Cosolvent

2025· article· en· W4408746924 on OpenAlexafffund
Shahin Mazhkoo, Omid Norouzi, Omid Pourali, Maryam Ebrahimzadeh Sarvestani, Aneela Hayder, Francesco Di Maria, Animesh Dutta

Bibliographic record

VenueACS Omega · 2025
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPomaceHydrothermal liquefactionGlycerolLiquefactionHydrothermal circulationCatalysisChemistryChemical engineeringWaste managementPulp and paper industryMaterials scienceNuclear chemistryOrganic chemistryEngineeringFood science

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide This study focused on the catalytic hydrothermal liquefaction (HTL) of grape pomace using Ni–HZSM5 and Ni–ZrO 2 –modified steel slag (MSS) catalysts, employing a water-crude glycerol cosolvent. The research aimed to understand how temperature, solvent ratios, and crude glycerol composition affect biocrude yield and properties, and to evaluate the stability of regenerated catalysts. The results revealed that when fatty acids/glycerides-rich crude glycerol was used, the highest biocrude yield of 76 wt %, HHV of 41 MJ/kg, H/C ratio of 1.81, and energy recovery of 90.9% was achieved at 320 °C with 75% crude glycerol concentration in the cosolvent. Catalytic HTL with Ni–HZSM5 significantly reduced the acid content of the biocrude by 44%. Although Ni–ZrO 2 –MSS increased the biocrude yield from 44.07 to 49.97 wt %, it promoted the production of acids and reduced the esters in biocrude. TGA refinery cut results showed that both catalysts enhance diesel production, with Ni–HZSM5 yielding the highest diesel fraction (41.24%) compared to Ni–ZrO 2 –MSS (37.51%) and the noncatalytic process (33.56%). Moreover, both catalysts significantly reduced the production of heavier fractions, such as residual fuel oil and bitumen. While the modification significantly enhanced the BET surface area of raw steel slag from 4.04 to 49.61 m 2 /g in Ni–ZrO 2 –MSS, the surface area of the regenerated catalyst after HTL dropped to 15.88 m 2 /g, aligning with decreased H 2 uptake, indicating a loss of active sites. Similarly, the surface area of Ni–HZSM5 decreased from 522.25 to 387.37 m 2 /g after HTL, while the pore volume increased from 0.2095 to 0.3425 cm 3 /g. However, the spent Ni–HZSM5 catalyst displayed an increase in H 2 uptake (269.49 μmol/g) with a shift in the reduction peaks to higher temperatures, suggesting the creation of new active sites or changes in the dispersion of NiO species during the reaction. The TPO graphs confirm the presence of coke with an intermediate structure between amorphous and graphitic carbon.

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 score0.002
Threshold uncertainty score0.638

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 head0.210
Teacher spread0.204 · 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

Citations7
Published2025
Admission routes2
Has abstractyes

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