论文部分内容阅读
目的探讨抽球模型预测粉体最小取样量的可行性。方法将粉体粒子抽象为小球,建立抽球模型,推导出能够代表所测粉体的最小取样量;并以微晶纤维素(MCC)、淀粉2种不同粒径的药用辅料为模型粉体,测定取样量分别为5、10、100 mg时的粒径分布,用粒径分布的重合性判断取样的均匀性。结果根据抽球模型推算出MCC的最小取样量大于5 mg,淀粉的最小取样量小于5 mg,与实验结果一致;当取样量为100 mg时,MCC的样本也能代表总体。结论用抽球模型研究粉体的最小取样量可行,粉体粒径越小,最小取样量越小。
Objective To explore the feasibility of using the ball extraction model to predict the minimum sample size of powder. Methods The powder particles were abstracted into small balls, and the model of ball extraction was established. The minimum sampling volume that could represent the measured powder was deduced. The microcrystalline cellulose (MCC) and two kinds of pharmaceutical excipients with different particle sizes were used as models Powder, the determination of the sample size were 5,10,100 mg particle size distribution, particle size distribution of the coincidence to determine the uniformity of sampling. Results According to the bolting model, the minimum sampling amount of MCC was more than 5 mg and the minimum sampling amount of starch was less than 5 mg, which was consistent with the experimental results. When the sampling volume was 100 mg, the samples of MCC could also represent the whole population. Conclusion It is feasible to study the minimum sampling volume of powder by the ball-blow model. The smaller the particle size, the smaller the minimum sampling volume.