4.5 Article

Quantitative Analysis Using a Flatbed Scanner: Aspirin Quantification in Pharmaceutical Tablets

期刊

JOURNAL OF CHEMICAL EDUCATION
卷 96, 期 7, 页码 1519-1526

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.jchemed.8b00620

关键词

First-Year Undergraduate/General; Second-Year Undergraduate; Analytical Chemistry; Chemoinformatics; Hands-On Learning/Manipulatives; UV-Vis Spectroscopy

资金

  1. FAPESC (Fundacao de Amparo a Pesquisa do Estado de Santa Catarina)
  2. CNPq (Conselho Nacional de Desenvolvimento Cientifico e Tecnologico) [402226/2016-0]
  3. CAPES (Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior)

向作者/读者索取更多资源

Here, students determine aspirin (acetylsalicylic acid) mass in pharmaceutical tablets using a colorimetric method. Aspirin, salicylate, and salicylic acid do not absorb visible light. Thus, in alkaline medium, acetylsalicylic acid was hydrolyzed to salicylate; then, it was reacted with an acidic Fe(III) solution, and a violet complex was formed. Quantitative analysis was carried out using absorbance measured at 535 nm (standard method) and digital images obtained with a flatbed scanner (proposed method). Results obtained with both methods were compared using an F-test and a t-test; both methods had shown equivalent accuracy and precision at the 95% confidence level. In addition, one-way ANOVA showed that aspirin masses found by five student groups using both methods are equivalent at the 95% confidence level. In the proposed method, samples were placed in a 96 microwell plate, and RGB values were extracted automatically from all wells in less than 5 min using ImageJ's plugin ReadPlate; data obtained were organized using a spreadsheet to determine aspirin mass in pharmaceutical tablets, recovery, and percent error. Our goal was to design a portable, cost-effective, and user-friendly platform and to develop an experimental methodology that can easily be applied to any research and education laboratory using just a flatbed scanner.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据