Investigation on the physicochemical properties of blended algae-diesel fuel with nanoparticles additive using mixture design method / Hazim Sharudin ... [et al.]

• Main Authors: Sharudin, Hazim, Ismail, Noor Iswadi, Che Mat, Sharzali, Khairul Salleh, Nurul Nabilah, Abdol Rahim, Abdul Hadi
• Format: Article
• Language: English
• Published: Universiti Teknologi MARA, Pulau Pinang 2023
• Subjects: Universiti Teknologi MARA; Fuel; Biodiesel fuels
• Online Access: https://ir.uitm.edu.my/id/eprint/76555/1/76555.pdf; https://ir.uitm.edu.my/id/eprint/76555/; https://uppp.uitm.edu.my/

Biodiesel from algae sources is one of the most promising alternative fuels to substitute fossil fuels in the future as it has relatively high oil content, besides rapid biomass production. However, in terms of exhaust emissions, the nitrogen (NOx) emission stemming from algae-diesel blends is higher due to the presence of oxygen content. As a solution, one of the approaches is by using the addition of fuel additives, such as nanoparticles as it plays a major role in increasing biodiesel performance and improving the properties of the biodiesel blends. Therefore, this study directly focuses on improving algae-diesel blends by adding cerium oxide as the fuel additive. The main phases involved in this research are the extraction of algae oil, blending process of algae-diesel with cerium oxide and data collection of dynamic viscosity with calorific value. Then, the data collected were used as an input for Design of Expert (DOE) software to obtain the optimum blends for algae-diesel blends with cerium oxide addition. Analysis of variance (ANOVA) was applied to evaluate the properties of the blends and provides equations for the model, wherein the equations involved in this research were dynamic viscosity and calorific value. The equations generated through the software were used to obtain the theoretical value of dynamic viscosity and calorific value. Finally, the theoretical value was further validated by comparing it with the experimental data for each of the blends. The results of experimental and theoretical (predicted) for each blend model showed the percentage errors between the experimental and the calculated values was between 0.19% and 9.51%. Hence, numerically derived equations are considered valid and reliable. In conclusion, the results showed that the optimum blend obtained by the software was significant and complied with the biodiesel standard of EN14213.