A Modern Twist on an Old Measurement: Using Laboratory Automation and Data Science to Determine the Solubility Product of Lead Iodide

被引：1

作者：

Norquist, Alexander J. ^{[1
]}

Jones-Thompson, Gabriel ^{[1
]}

He, Keqing ^{[1
]}

Egg, Thomas ^{[2
]}

Schrier, Joshua ^{[2
]}

机构：

[1] Haverford Coll, Dept Chem, Haverford, PA 19041 USA

[2] Fordham Univ, Dept Chem, Bronx, NY 10458 USA

来源：

JOURNAL OF CHEMICAL EDUCATION | 2023年 / 100卷 / 09期

基金：

美国国家科学基金会;

关键词：

Solubility Product; Equilibria; Automation; Randomized Experimentation; Logistic Regression; HIGH-THROUGHPUT-EXPERIMENTATION; CHEMISTRY; VISUALIZATION; TITRATION; CONSTANT;

D O I：

10.1021/acs.jchemed.3c00445

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

Laboratory automation and data science are valuable newskillsfor all chemists, but most pedagogical activities involving automationto date have focused on upper-level coursework. Herein, we describea combined computational and experimental lab suitable for a first-yearundergraduate general chemistry course, in which these topics areintroduced in the context of determination of the solubility equilibriumconstant of lead iodide. Students analyze their data using logisticregression analysis, which has a physical interpretation in termsof the solubility equilibrium expression and its stoichiometric coefficients.In addition to laboratory automation, data visualization, and datafitting skills, students also practice core laboratory skills suchas the preparation of stock solutions using a volumetric flask andthe use of micropipets. To keep the lab affordable, we demonstratethe use of a low-cost 3D-printed liquid dispensing robot to performthe automated experiment in addition to a commercial liquid-handlingrobot. Example pre- and post-lab computational notebooks are providedin both Mathematica and Python programming languages.

引用

页码：3445 / 3453

页数：9