| Issue |
E3S Web Conf.
Volume 714, 2026
2026 4th International Forum on Clean Energy Engineering (FCEE2026)
|
|
|---|---|---|
| Article Number | 02001 | |
| Number of page(s) | 17 | |
| Section | Biomass Valorization: Fuel Conversion and Biobased Products | |
| DOI | https://doi.org/10.1051/e3sconf/202671402001 | |
| Published online | 08 June 2026 | |
Statistical Optimization of Crude Palm Oil Biodiesel Purification via Solvent-Aided Crystallization
1 HICoE-Centre for Biofuel and Biochemical Research (CBBR), Institute of Sustainable Energy and Resources (ISER), Universiti Teknologi PETRONAS (UTP), Seri Iskandar 32610, Perak, Malaysia
2 Chemical Engineering Department, Faculty of Engineering, Universiti Teknologi PETRONAS (UTP), Seri Iskandar 32610, Perak, Malaysia
Abstract
Purification remains a major challenge in biodiesel production, particularly when handling impurity-rich feedstocks such as crude palm oil (CPO). Conventional separation techniques are often less effective under these conditions, leading to lower purity. Therefore, this study introduces solvent-aided crystallization (SAC) system as advanced method compared to conventional where shaking is integrated to facilitate efficient solution movement, enabling improved purification of CPO-based biodiesel. In this study, four key variables such as coolant temperature, crystallization time, shaking speed, and solvent addition were optimized by using response surface methodology (RSM). The system achieved high-purity biodiesel, with optimal conditions yielding up to 95% purity. These results demonstrate that SAC offers a low-energy, scalable, and sustainable alternative to conventional purification techniques, reducing the need for intensive pre-treatment and supporting decentralized biodiesel production. Overall, this work provides a practical pathway for upgrading unrefined oils into high-quality biofuels, contributing to cleaner energy systems and the broader transition toward sustainable liquid fuels.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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