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Record W4392380442 · doi:10.1016/j.catcom.2024.106894

Effects of alloying palladium with gold in furfural hydrogenation:An in situ ATR-IR spectroscopy and density functional theory study

2024· article· en· W4392380442 on OpenAlexfundno aff
Sebastiano Campisi, Silvio Bellomi, Lidia E. Chinchilla, M. Stucchi, Laura Prati, Alberto Roldán, Davide Ferri, Alberto Villa

Bibliographic record

VenueCatalysis Communications · 2024
Typearticle
Languageen
FieldEngineering
TopicCatalysis for Biomass Conversion
Canadian institutionsnot available
FundersLlywodraeth CymruEuropean Regional Development FundPaul Scherrer InstitutMcMaster University
KeywordsFurfuralDecarbonylationSelectivityCatalysisDensity functional theoryPalladiumChemistryIn situPhotochemistrySpectroscopyNanoparticleInorganic chemistryOrganic chemistryMaterials scienceNanotechnologyComputational chemistry

Abstract

fetched live from OpenAlex

Furfural is a versatile platform molecule and a model compound to explore the key factors influencing activity and selectivity in heterogeneous catalysis. In this study, Pd and AuPd nanoparticles (average size 3.5–4 nm) were deposited on TiO2 by sol immobilization method and were evaluated for liquid-phase furfural hydrogenation. Alloying Au and Pd caused a decrease in activity, an enhancement in stability, and a change in selectivity, favouring the complete hydrogenation of furfural over the decarbonylation reaction. These variations in catalytic performance were elucidated by combining in situ attenuated total reflectance infrared spectroscopy and density functional theory studies.

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 score0.003

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 head0.009
GPT teacher head0.224
Teacher spread0.216 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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