| Sidney H. Young | |
|---|---|
| Analysis of the Vibrational Spectrum of a Linear Molecule
Richard W. Schwenz, University of Northern Colorado William F. Polik, Hope College Sidney H. Young, University of South Alabama |
This document provides a moderately interactive tutorial describing the analysis of vibrational frequencies obtained from the infrared spectrum of hydrogen chloride. |
| An Introduction to Mathcad
Theresa Julia Zielinski, Monmouth University Arthur Ferguson, Worcester State College Sidney H. Young, University of South Alabama |
This document provides a tutorial for Mathcad vs 8, 2001i, and 11. |
| A Summary of Statistical Thermodynamic Calculations
Theresa Julia Zielinski, Monmouth University Sidney H. Young, University of South Alabama |
In this document students can explore the full set of statistical thermodynamic calculations leading to the prediction of the heat capacity at constant volume from the translational, rotational, vibrational, and electronic partition functions. An extension of the calculation of the thermodynamic properties of a molecule is made to predict the equilibrium constant of the dissociation of N2. The document concludes with the study of the NO molecule which has a low lying electronic energy level. |
| Computing a Liquid-Vapor Phase Diagram
Sidney H. Young, University of South Alabama |
A Mathcad worksheet focused on determining vapor-liquid phase diagrams for ideal and non-ideal binary mixtures for learning about activity and activity coeeficients. |
| Linear Least Squares Regression
Sidney H. Young, University of South Alabama Andrzej Wierzbicki, University of South Alabama |
Linear least-squares regression is the workhorse mathematical tool of the physical chemistry laboratory. This Mathcad worksheet and its accompanying data files demonstrate various implicit and explicit methods for determination of slope and intercept of a regressed line. |
| Non-Linear Least Squares Regression
Sidney H. Young, University of South Alabama Andrzej Wierzbicki, University of South Alabama |
Nonlinear least-squares regression is often required in the physical chemistry laboratory. It is especially important for fitting functions that cannot be linearized. This template demonstrates various implicit and explicit methods for determining the parameters of the regressed curve obtained by nonlinear curve-fitting. |