Evidence map›Paper›PMID 39679764›Full record

ReviewChemistryOpen2025

Integration of Design of Experiments, Analysis of Variance and Response Surface Methodology in Assessing Heterogeneous Catalysts Processes: A Minireview.

Carlos Esteban Aristizábal-Alzate, Eva Castillejos-López, Ana Belén Dongil, Manuel Romero-Sáez

Abstract readReview
In one paragraph

Review in ChemistryOpen, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

4 authors.

Carlos Esteban Aristizábal-AlzateGrupo Química Básica, Aplicada y Ambiente-Alquimia, Facultad de Ciencias Exactas y Aplicadas, Instituto Tecnológico Metropolitano, Robledo, Medellín, 050034, Colombia.
Eva Castillejos-LópezDepartment of Inorganic and Technical Chemistry, Faculty of Sciences, UNED, Madrid, 28232, Spain.ORCID https://orcid.org/0000-0003-0913-1560
Ana Belén DongilGrupo de Química Verde y Catálisis, Instituto de Catálisis y Petroleoquímica CSIC, Cantoblanco, Madrid, 28049, España.
Manuel Romero-SáezGrupo Química Básica, Aplicada y Ambiente-Alquimia, Facultad de Ciencias Exactas y Aplicadas, Instituto Tecnológico Metropolitano, Robledo, Medellín, 050034, Colombia.

Funding

BIOALL 101008058European Commission H2020-MSCA-RISE-2020Instituto Tecnológico Metropolitano and Instituto de Catálisis y Petroleoquímica-CSIC
6 · The paper itself

Abstract

This work reviews the application of Analysis of Variance (ANOVA), Design of Experiments (DOE), and Response Surface Methodology (RSM) in heterogeneous catalysis, based on an analysis of recent scientific literature. Heterogeneous catalysis plays a key role in various industries, guiding chemical reactions, optimizing the performance of different processes and/or prioritizing products, and ANOVA, DOE and RSM are valuable tools to understand the intricate relationships between catalyst properties, process variables and reaction responses. This understanding facilitates improvements in catalysts performance and selectivity, thereby optimizing processes. Drawing insights from recent studies, this minireview highlights the different applications of ANOVA-based experimental designs and RSM optimization techniques in catalytic process evaluation. Therefore, this review provides valuable insights into these current statistical methodologies applied to heterogeneous catalysis research, informing the relevance and future directions of the research in the field.

Indexed as

ANOVACatalyst assessmentExperimental designHeterogeneous catalystResponse surface methodology

Identifiers

PMID39679764
PMCPMC11726655

What OpenQuestion holds

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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.