摘要
研究物质的取样属性与取样误差之间的关系是分析化学取样学的重要内容.从微观角度探讨了物质的理化性质及其对取样误差的影响.以碳化硅为例,考察了粒度分布、组分随粒度的变化以及均匀度因子等,分析了取样误差的来源.首次通过粒度分级成功地对碳化硅进行了分层,并对分层取样和随机取样的误差进行了分析和讨论,为制定合理的取样方案提供了有利的依据.本文的研究方法可适用于所有粒状物质的取样,同时也为分析化学取样学的深入研究拓宽了方向.
The relationship between the sampling error and the sampling attributes of the material is an important content of sampling in analytical chemistry. Taking silicon carbide material as an example in this paper, we studied the grain size distribution, the homogeneity factors and the relationship between the concentrations of the components and the grain size, and analyzed the sources of sampling errors. Using t-test method, we successfully stratified the silicon carbide material by the grain size classification, and compared the stratified sampling variances with the randon sampling variances. The results of this study provided a basic reference for a design of suitable sampling protocols. The new methods used in this paper may be applied to any particulate material.
出处
《分析化学》
SCIE
EI
CAS
CSCD
北大核心
1999年第4期373-377,共5页
Chinese Journal of Analytical Chemistry
基金
国家自然科学基金
博士点基金资助课题