Curve Fitting, Linear Algebra, and Solver in an Analytical Chemistry Course: A Facile and Safe Activity Suitable for the Classroom Setting

Abstract

Undergraduate analytical chemistry courses emphasize fundamental stoichiometric and physicochemical analytical techniques with statistical analysis and linear calibrations. Higher-level data analysis techniques may not be included in the college junior-level curriculum, but widely available software enables more complex analysis to be accessible. In this work, activities to train students in multicomponent spectral curve fitting (using Microsoft Excel’s Solver) and utilizing matrix algebra were incorporated within a large-enrollment undergraduate analytical chemistry lecture setting. When analyzing multiple compounds in solutions without separation pretreatment, both curve-fitting and classical matrix approaches are valuable techniques for students to understand and execute using commercially available software. When hands-on activities, multimedia screencasts, and in-class data collection and analysis were implemented, students were trained to employ these advanced analysis methods. The efficacy of the in-class practical activities was assessed with pre- and post-test instruments that quantified gains in learning outcomes. Inclusion of such activities will empower students with an expanded repertoire of these important analytical methods and their applications with a real world, portable, active-learning approach that can be completed in a lecture setting with nonhazardous samples.

Rate Equations for Reversible Disproportionation Reactions and Fitting to Time-Course Data

“…14 UV−vis spectra are then acquired periodically and concentrations of TEMPO and TEMPO + are extracted by deconvolution of the spectra into contributions from these species based on reference spectra (TEMPOH 2 + does not absorb at relevant wavelengths, so its concentration was inferred based on mass balance). 15 Experiments were conducted at pH 1, 2, and 3, where the approach to equilibrium is observable under the latter two conditions. A typical stack plot of spectra is shown in Figure 1.…”

“…At t = 0, a stock solution of TEMPO and a solution of a buffer at the desired pH are mixed to give the desired initial conditions . UV–vis spectra are then acquired periodically and concentrations of TEMPO and TEMPO + are extracted by deconvolution of the spectra into contributions from these species based on reference spectra (TEMPOH 2 + does not absorb at relevant wavelengths, so its concentration was inferred based on mass balance) …”

Exploring the pH Dependent Aqueous Speciation of Metal Complexes through UV–Vis Spectroscopy

“…This holistic, active-learning activity is designed to be integrated into the undergraduate inorganic chemistry course lecture series in the classroom setting 17 to provide the necessary contextualization of aqueous speciation in coordination chemistry and of its significance to real-world applications. The lecture component will be coupled with a hands-on experimental session that demonstrates the pH dependent speciation of Fe(III) DHNS interactions to enable students to visualize how much a complex can change in solution (Figures 1a and 2).…”

Rate Equations for Reversible Disproportionation Reactions and Fitting to Timecourse Data

“…13 UV-Vis spectra are then acquired periodically and concentrations of TEMPO and TEMPO + are extracted by deconvolution of the spectra into contributions from these species based on reference spectra (TEMPOH 2 + does not absorb at relevant wavelengths, so its concentration was inferred based on mass balance). 14 Experiments were conducted at pH 1, 2, and 3, where the approach to equilibrium is observable at the latter two conditions. A typical stack plot of spectra is shown in Fig.…”