Chemical fingerprinting and cluster-based evaluation of vegetable oils for biodiesel applications - Hüseyin Söyler; Mustafa Kemal Balki (Case Studies in Thermal Engineering)
This study evaluates the biodiesel potential of five vegetable oils—safflower, flaxseed, rapeseed, niger seed, and perilla through detailed analysis of their fatty acid composition and key fuel properties. Gas chromatography mass spectrometry (GC-MS/MS) was used to characterize the oils and quantify their saturated, monounsaturated, and polyunsaturated fatty acid contents. The impact of fatty acid profiles on cetane number, oxidative stability, viscosity, and cold-flow behavior was assessed. Hierarchical and K-Means clustering techniques identified chemical similarities and guided the development of optimized blending strategies. Results showed that rapeseed and safflower oils, with high monounsaturated fatty acid content, provided superior oxidative stability and combustion performance. In contrast, flaxseed and perilla oils offered improved cold-flow properties but required stabilization to enhance storage life. Based on these findings, nine biodiesel blend formulations were proposed to balance fuel quality and adapt to different operational conditions. This research demonstrates that integrating chemical fingerprinting and clustering analysis can effectively support feedstock selection and biodiesel optimization.