The synergy of sorbitan monooleate (SMO) and γ-Al₂O₃ nanoparticles, which was prepared via ultrasonic sonochemistry, as cold-flow improvers (CFI) in B30 biodiesel blend is presented in this work. Response surface methodology (RSM) was employed to study the influence of both CFIs on biodiesel's cold-flow properties, i.e., cloud point (CP), cold-filter plugging point (CFPP), filter blocking tendency (FBT), and precipitate. Based on the result, the relationship between CFI and CP's concentration was best expressed with a quadratic model. Meanwhile, two-factor interaction (2FI) models were more suitable for CFPP, FBT, and precipitate. Based on the result, the most optimum concentration of SMO and γ-Al₂O₃ nanoparticles were achieved at 0.1% w/v and 50 ppm, respectively. At this condition, the predicted values of CP, CFPP, FBT, and precipitate of the sample were 8.52 °C, 6.056 °C, 7.208, and 564 mg/L, respectively. It is believed that SMO's surface-activity and the ability of γ-Al₂O₃ nanoparticles to form Pickering emulsion were responsible for the inhibition of excessive crystallization of saturated FAME but also enhancing their colloidal stability at low temperature.

山梨醇单油酸酯的（SMO）的协同作用和在γ-Al ₂ ö _3个纳米颗粒，其通过超声波声化学制备，如B30生物柴油掺合冷流改进剂（CFI），提出了这项工作。响应面方法（RSM）被用来研究两种CFIs对生物柴油的冷流特性的影响，即浊点（CP），冷滤塞点（CFPP），过滤器阻塞趋势（FBT）和沉淀物。根据结果​​，用二次模型可以最好地表达CFI和CP浓度之间的关系。同时，两因素相互作用（2FI）模型更适合CFPP，FBT和沉淀。基于该结果，SMO和最适宜浓度的γ-Al ₂ ö ₃分别以0.1％w / v和 50ppm获得纳米颗粒。在这种情况下，CP的预测值，CFPP，FBT，和样品的沉淀物分别为8.52  ℃，6.056  ℃，7.208，和564 毫克/升，分别。据信，SMO的表面活性和γ-Al的能力_2个ø ₃纳米颗粒以形成皮克林乳液负责饱和FAME的过度结晶，而且在低温下提高它们的胶体稳定性的抑制。