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Record W2909261647 · doi:10.3390/en12020284

Liquid-Phase Hydrogenation of Maleic Acid over Pd/Al2O3 Catalysts Prepared via Deposition–Precipitation Method

2019· article· en· W2909261647 on OpenAlexaff
Mi Yeon Byun, Ji Sun Kim, Jae Ho Baek, Dae‐Won Park, Man Sig Lee

Bibliographic record

VenueEnergies · 2019
Typearticle
Languageen
FieldEngineering
TopicCatalysis for Biomass Conversion
Canadian institutionsUniversity of British Columbia
FundersKorea Institute of Industrial Technology
KeywordsCatalysisSelectivityDispersion (optics)Maleic acidChemistryFumaric acidSuccinic acidPhase (matter)PrecipitationHydrogenMaleic anhydrideInorganic chemistrySuccinic anhydrideChemical engineeringMaterials scienceOrganic chemistryPolymerCopolymer

Abstract

fetched live from OpenAlex

Succinic acid (SA) is a valuable raw material obtained by hydrogenation of maleic acid (MA). The product selectivity of this reaction is highly dependent on the reaction conditions. This study therefore investigated the effect of the reaction temperature, hydrogen pressure, and reaction time on the liquid-phase hydrogenation of MA by a Pd/Al2O3 catalyst. Complete conversion of MA and 100% selectivity for SA were achieved at a temperature of 90 °C, H2 pressure of 5 bar, and reaction time of 90 min. Fumaric acid (FA) was formed as an intermediate material by hydrogenation of MA under nonoptimal conditions. The impact of the percentage of Pd dispersion and phase of the Al2O3 support (γ, θ + α, and α) was also examined. The Pd/Al2O3 catalyst with 29.8% dispersion of Pd and γ phase of Al2O3 exhibited the best catalytic performance. Thus, catalytic activity depends not only on the amount of Pd dispersion but also on the physicochemical properties of Al2O3.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.004
GPT teacher head0.242
Teacher spread0.238 · 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 source (direct Gemma or distilled Codex), 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

Citations24
Published2019
Admission routes1
Has abstractyes

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