Mathematics for Chemists

Overview

Summary of Lecture Content:
 Lecture 1: Numbers, units, and scientific notation
 Lecture 2: Algebra and rearranging equations
 Lecture 3: Functions and graphing in Chemistry
 Lecture 4: Logarithms and exponentials in Chemistry
 Lecture 5: Differentiation: rates of change in Chemistry
 Lecture 6: Applications of differentiation in Chemistry
 Lecture 7: Integration: accumulation and area
 Lecture 8: Introduction to differential equations
 Lecture 9: Vectors and matrices in Chemistry
 Lecture 10: Complex numbers and their chemical applications
 Lecture 11: Statistics and error analysis
 Lecture 12: Revision and problem-solving strategies

Summary of Workshop Content:
 Workshop 1: Algebra, functions, and graphing
 Workshop 2: Calculus in Chemistry
 Workshop 3: Matrices, vectors and statistics
 Workshop 4: Applied problem solving

Learning Objectives

On completion of this module students should be able to:
 Apply numerical, algebraic, and graphical techniques to solve chemical problems, including
unit conversions, scientific notation, and equation manipulation.
 Use logarithms, exponentials, and calculus to describe chemical processes such as pH,
reaction kinetics, and thermodynamics.
 Differentiate and integrate functions to determine rates of change, accumulation, and reaction
progress in chemistry.
 Solve basic differential equations relevant to chemical kinetics and equilibrium.
 Apply vectors, matrices, and complex numbers in quantum chemistry, molecular symmetry, and
spectroscopy.
 Use statistical methods and error analysis to interpret experimental data, including regression
and uncertainty calculations.

Skills

Students are expected to demonstrate the following on completion of the module:
 Ability to apply numerical, algebraic, and graphical methods to solve chemical problems.
 Ability to use calculus and differential equations in chemical kinetics, thermodynamics, and
equilibria.
 Ability to apply vectors, matrices, and complex numbers in chemistry.
 Ability to analyse experimental data using statistical methods and error propagation.

Assessment

Assessment Profile
Element type Element weight (%)
Coursework submission 100%

Course Requirements:
 Coursework submission: 80%
 Coursework must be passed at: 40%