Evidence map›Paper›PMID 37834493›Full record

ReviewMaterials (Basel, Switzerland)2023

Supported Gold Catalysts for Base-Free Furfural Oxidation: The State of the Art and Machine-Learning-Enabled Optimization.

Joëlle Thuriot-Roukos, Camila Palombo Ferraz, Hisham K Al Rawas, Svetlana Heyte, Sébastien Paul, Ivaldo Itabaiana, Mariusz Pietrowski, Michal Zieliński, Mohammed N Ghazzal, Franck Dumeignil and 1 more

Abstract readReview
In one paragraph

Review in Materials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Joëlle Thuriot-RoukosUniversité de Lille, CNRS, Centrale Lille, Université d'Artois, UMR 8181-UCCS-Unité de Catalyse et Chimie du Solide, 59000 Lille, France.ORCID 0000-0003-0490-718X
Camila Palombo FerrazDepartment of Inorganic Chemistry, Institute of Chemistry, Federal University of Rio de Janeiro, Rio de Janeiro 221941-910, Brazil.
Hisham K Al RawasUniversité de Lille, CNRS, Centrale Lille, Université d'Artois, UMR 8181-UCCS-Unité de Catalyse et Chimie du Solide, 59000 Lille, France.
Svetlana HeyteUniversité de Lille, CNRS, Centrale Lille, Université d'Artois, UMR 8181-UCCS-Unité de Catalyse et Chimie du Solide, 59000 Lille, France.ORCID 0000-0002-6599-4929
Sébastien PaulUniversité de Lille, CNRS, Centrale Lille, Université d'Artois, UMR 8181-UCCS-Unité de Catalyse et Chimie du Solide, 59000 Lille, France.ORCID 0000-0001-9877-9902
Ivaldo ItabaianaDepartment of Biochemical Engineering, School of Chemistry, Federal University of Rio de Janeiro, Rio de Janeiro 21941-910, Brazil.ORCID 0000-0003-0725-0881
Mariusz PietrowskiFaculty of Chemistry, Adam Mickiewicz University, 61-614 Poznań, Poland.ORCID 0000-0003-1004-8115
Michal ZielińskiFaculty of Chemistry, Adam Mickiewicz University, 61-614 Poznań, Poland.ORCID 0000-0002-6989-5039
Mohammed N GhazzalInstitut de Chimie Physique (ICP), UMR 8000 CNRS, Université Paris-Saclay, 91400 Orsay, France.
Franck DumeignilUniversité de Lille, CNRS, Centrale Lille, Université d'Artois, UMR 8181-UCCS-Unité de Catalyse et Chimie du Solide, 59000 Lille, France.ORCID 0000-0001-9727-8196
Robert WojcieszakUniversité de Lille, CNRS, Centrale Lille, Université d'Artois, UMR 8181-UCCS-Unité de Catalyse et Chimie du Solide, 59000 Lille, France.ORCID 0000-0002-8956-5846

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Supported gold nanoparticles have proven to be highly effective catalysts for the base-free oxidation of furfural, a compound derived from biomass. Their small size enables a high surface-area-to-volume ratio, providing abundant active sites for the reaction to take place. These gold nanoparticles serve as catalysts by providing surfaces for furfural molecules to adsorb onto and facilitating electron transfer between the substrate and the oxidizing agent. The role of the support in this reaction has been widely studied, and gold-support interactions have been found to be beneficial. However, the exact mechanism of furfural oxidation under base-free conditions remains an active area of research and is not yet fully understood. In this review, we delve into the essential factors that influence the selectivity of furfural oxidation. We present an optimization process that highlights the significant role of machine learning in identifying the best catalyst for this reaction. The principal objective of this study is to provide a comprehensive review of research conducted over the past five years concerning the catalytic oxidation of furfural under base-free conditions. By conducting tree decision making on experimental data from recent articles, a total of 93 gold-based catalysts are compared. The relative variable importance chart analysis reveals that the support preparation method and the pH of the solution are the most crucial factors determining the yield of furoic acid in this oxidation process.

Indexed as

base-freedecision treefurfuralgoldmachine learningoxidation

Identifiers

PMID37834493
PMCPMC10573714

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.