Authors :
Joseph Nifu Barnabas; Noela Chinyelu Igwemmar
Volume/Issue :
Volume 11 - 2026, Issue 10 - October
DOI :
https://doi.org/10.38124/ijisrt/26Oct607
Note : A published paper may take 4-5
working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and
ResearchGate.
Abstract :
This study develops a study-aware, data-driven framework for comparing biodiesel catalyst families and identifying favourable yield–time performance profiles, with particular emphasis on biomass-derived catalysts. A literaturederived database comprising 302 catalyst observations from 166 studies was assembled, of which 198 observations met the biodiesel-yield eligibility criteria (149 FAME and 49 FAEE). Catalyst systems were classified into 12 families and evaluated using descriptive statistics, non-parametric tests, correlation analysis, clustered regression, yield–time productivity (YTP), Pareto analysis and study-level sensitivity analyses.
Keywords :
Biodiesel; Heterogeneous Catalysts; Biomass-Derived Catalysts; FAME; FAE.
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This study develops a study-aware, data-driven framework for comparing biodiesel catalyst families and identifying favourable yield–time performance profiles, with particular emphasis on biomass-derived catalysts. A literaturederived database comprising 302 catalyst observations from 166 studies was assembled, of which 198 observations met the biodiesel-yield eligibility criteria (149 FAME and 49 FAEE). Catalyst systems were classified into 12 families and evaluated using descriptive statistics, non-parametric tests, correlation analysis, clustered regression, yield–time productivity (YTP), Pareto analysis and study-level sensitivity analyses.
Keywords :
Biodiesel; Heterogeneous Catalysts; Biomass-Derived Catalysts; FAME; FAE.