IB Chemistry Revision Guide

IB Chemistry Revision Guide

IB Chemistry Revision Guide

Ray Dexter

Anthem Press

An imprint of Wimbledon Publishing Company

www.anthempress.com

This edition first published in UK and USA 2019

by ANTHEM PRESS

75–76 Blackfriars Road, London SE1 8HA, UK

or PO Box 9779, London SW19 7ZG, UK

and

244 Madison Ave #116, New York, NY 10016, USA

Copyright © Ray Dexter 2019

The author asserts the moral right to be identified as the author of this work.

All rights reserved. Without limiting the rights under copyright reserved above, no part of this publication may be reproduced, stored or introduced into a retrieval system, or transmitted, in any form or by any means (electronic, mechanical, photocopying, recording or otherwise), without the prior written permission of both the copyright owner and the above publisher of this book.

British Library Cataloguing-in-Publication Data

A catalogue record for this book is available from the British Library.

ISBN-13: 978-1-78527-081-9 (Pbk)

ISBN-10: 1-78527-081-8 (Pbk)

This title is also available as an e-book.

For Áron and Maja, as always.

Thanks to Nadine for her constant support and love throughout the writing of this book. You had a lot more faith than I did!! Thanks to my colleagues at St Edmund’s College for their encouragement and comments, especially those in the chemistry and the history departments. Thanks to Emma Baxter for checking my medicinal chemistry and Elizabeth Hartley for her calculations’ summary design. Thanks also to Peter Capaldi and Richard Saunders for their usual contribution to my world. Thanks, as ever to Douglas Adams for the quote, I love deadlines, I love the whooshing sound they make as the go by. It made me hit my deadline!!

To Arch Overbury, my high school chemistry teacher, the greatest of them all. I still hear your voice when I teach. To Brian Orger and James Tearle from Stowe School, the legendary teachers who took me under their wing and taught me all I know when I first started out in this teaching game.

To all the past IB DP students I have ever taught and tried to teach chemistry. This book is the product of our work together. I thank you for being so inspiring; I hope this book can be equally inspiring.

About the Author

Ray Dexter is a University of London graduate who has been teaching chemistry since 1996 and has been an IB chemistry teacher since 2001. He was Head of Chemistry at Haileybury College in the UK for 10 years and has worked for OSC, one of the world’s leading providers of revision classes for IB DP students. He is an in-demand trainer of chemistry teachers in the UK and is currently IB Coordinator at St Edmund’s College, also in the UK.

Contents

1 Measurement and data processing

SPREAD 1: Uncertainties and errors in measurement and results

SPREAD 2: Applying uncertainty readings to a calculated number

SPREAD 3: What is the difference between accuracy and precision?

SPREAD 4: Graphical techniques

2 Stoichiometric relationships

SPREAD 1: Writing formulae

SPREAD 2: Avogadro’s number and the mole concept

SPREAD 3: Empirical and molecular formula

SPREAD 4: Calculations (a summary)

SPREAD 5: Limiting reagent, percentage yield

SPREAD 6: Gas calculations

3 Atomic structure

SPREAD 1: The nuclear atom

SPREAD 2: Working out RAM

SPREAD 3: Electronic configuration

SPREAD 4: Electrons in atoms

SPREAD 5: Orbital shapes

SPREAD 6: Electrons in atoms

4 Chemical bonding and structure

SPREAD 1: Structure, an overview and metallic bonds

SPREAD 2: Ionic bonding and structure

SPREAD 3: Writing formulae from ions

SPREAD 4: Covalent bonding

SPREAD 5: Giant covalent structures

SPREAD 6: Dative covalent bonding and a summary of bond types

SPREAD 7: Further covalent bonding

SPREAD 8: Shapes of molecules

SPREAD 9: How do lone pairs affect the shapes of molecules?

SPREAD 10: How to work out the shape of a molecule?

SPREAD 11: Molecular polarity

SPREAD 12: Intermolecular forces

SPREAD 13: More on intermolecular forces

SPREAD 14: Resonance structures

SPREAD 15: Writing formulae

SPREAD 16: Formal charge and exceptions to the octet

SPREAD 17: Ozone

SPREAD 18: Hybridization

5 Periodicity

SPREAD 1: The periodic table

SPREAD 2: Periodic trends—physical properties

SPREAD 3: Chemical properties

SPREAD 4: More chemical trends

SPREAD 5: The first-row d-block elements

SPREAD 6: More transition metals

SPREAD 7: Colored compounds

6 Energetics and thermochemistry

SPREAD 1: Energy changes

SPREAD 2: Calculating the enthalpy change for a chemical reaction

SPREAD 3: Using a conducting calorimeter

SPREAD 4: Bond enthalpies

SPREAD 5: Potential energy diagrams and ozone

SPREAD 6: Hess’s Law

SPREAD 7: Using enthalpy of combustion data (ΔHθc)

SPREAD 8: Born–Haber cycles

SPREAD 9: Enthalpy of solution cycle

SPREAD 10: The magnitude of lattice enthalpy

SPREAD 11: Entropy and spontaneity

SPREAD 12: Gibbs free energy

7 Chemical kinetics

SPREAD 1: Collision theory and rates of reaction

SPREAD 2: How do temperature and catalysts affect rate of reaction?

SPREAD 3: The rate expression

SPREAD 4: Initial rates data

SPREAD 5: Mechanisms

SPREAD 6: Activation energy

8 Equilibrium

SPREAD 1: What is equilibrium?

SPREAD 2: Changing the position of equilibrium

SPREAD 3: The equilibrium constant, Kc

SPREAD 4: What does the value of Kc tell us?

SPREAD 5: The equilibrium law

SPREAD 6: Kc, free energy and entropy

9 Acids and bases

SPREAD 1: What is an acid?

SPREAD 2: Conjugate acid–base pairs and Lewis acids

SPREAD 3: Properties of acids and bases

SPREAD 4: Strong and weak acids and indicators

SPREAD 5: What is pH?

SPREAD 6: Acid deposition

SPREAD 7: Calculations involving acids and bases

SPREAD 8: Using the Ka expression to work out the pH of a weak acid

SPREAD 9: Working out pH of bases and temperature changes

SPREAD 10: pH curves

SPREAD 11: Buffer solutions and indicators

10 Redox processes

SPREAD 1: The three types of redox reaction

SPREAD 2: Oxidation numbers

SPREAD 3: Applications of redox, Winkler BOD, oxidation numbers

SPREAD 4: The BOD of water

SPREAD 5: Writing redox equations

SPREAD 6: The activity series

SPREAD 7: Electrochemical cells (1): Electrolytic cells

SPREAD 8: Higher level electrolytic cells

SPREAD 9: Voltaic cells

SPREAD 10: HL voltaic cells

11 Organic chemistry

SPREAD 1: Fundamentals of organic chemistry

SPREAD 2: More on the homologous series

SPREAD 3: The alkanes

SPREAD 4: The alkenes

SPREAD 5: The alcohols

SPREAD 6: The halogenoalkanes

SPREAD 7: Benzene reactions and its mechanism

SPREAD 8: Benzene reactions and its mechanism

SPREAD 9: Further electrophilic substitution

SPREAD 10: Further nucleophilic substitution

SPREAD 11: Reduction reactions

SPREAD 12: Synthetic routes

SPREAD 13: Isomerism

SPREAD 14: Optical isomerism

12 Measurement and data processing: Part 2

SPREAD 1: Index of hydrogen deficiency

SPREAD 2: Mass spectrometry

SPREAD 3: Infrared spectroscopy

SPREAD 4: Nuclear magnetic resonance spectroscopy

SPREAD 5: Further NMR

SPREAD 6: X-ray crystallography

13 Option A: Materials

SPREAD 1: An introduction to material science

SPREAD 2: More on classifying materials

SPREAD 3: Metal extraction 1 (reduction with carbon)

SPREAD 4: Metal extraction: The production of aluminum by electrolysis

SPREAD 5: Stoichiometric problems using electrolysis

SPREAD 6: Alloys

SPREAD 7: Magnetism in metals

SPREAD 8: Inductively coupled plasma spectroscopy and optical emission spectroscopy

SPREAD 9: Catalysts

SPREAD 10: Transition metal catalysts and zeolites

SPREAD 11: Liquid crystals

SPREAD 12: Polymers

SPREAD 13: Nanotechnology

SPREAD 14: Environmental impact—plastics

SPREAD 15: Dioxins and plasticizers

SPREAD 16: Superconducting metals

SPREAD 17: X-ray crystallography

SPREAD 18: Condensation polymers

SPREAD 19: Environmental impact—heavy metals

SPREAD 20: Solubility product and removal methods with heavy metals

14 Option B: Biochemistry

SPREAD 1: Introduction to biochemistry

SPREAD 2: Amino acids

SPREAD 3: Proteins

SPREAD 4: Enzymes

SPREAD 5: Separating and identifying amino acids and proteins

SPREAD 6: Lipids

SPREAD 7: Lipids and health issues

SPREAD 8: Phospholipids and steroids

SPREAD 9: Carbohydrates

SPREAD 10: Vitamins

SPREAD 11: Biochemistry and the environment

SPREAD 12: Green chemistry

SPREAD 13: Advanced proteins

SPREAD 14: Buffer solutions

SPREAD 15: Nucleic acids

SPREAD 16: Biological pigments

SPREAD 17: Stereochemistry in biomolecules

15 Energy

SPREAD 1: Energy sources, an introduction

SPREAD 2: Fossil fuels

SPREAD 3: Nuclear energy, an introduction

SPREAD 4: Nuclear fusion

SPREAD 5: Nuclear fission

SPREAD 6: Solar energy

SPREAD 7: What is a semiconductor?

SPREAD 8: Environmental impact—global warming

SPREAD 9: Electrochemistry, rechargeable batteries and fuel cells

SPREAD 10: Proton exchange membrane fuel cells (PEMFC)

SPREAD 11: Rechargeable batteries

16 Medicinal chemistry

SPREAD 1: Pharmaceutical products and drug action

SPREAD 2: New drugs

SPREAD 3: Aspirin

SPREAD 4: Penicillin

SPREAD 5: Opiates

SPREAD 6: pH regulation of the stomach

SPREAD 7: Antiviral medications

SPREAD 8: Environmental impact of some medications`

SPREAD 9: More on green chemistry

SPREAD 10: Taxol—a chiral auxiliary case study

SPREAD 11: Nuclear medicine

SPREAD 12: Use of radioactive sources as medicine

SPREAD 13: Drug detection and analysis

Index

This chapter’s contents refer to the material covered in Topics 11.1 and 11.2 of the IB Chemistry Specification.

CORE

SPREAD 1: Uncertainties and errors in measurement and results

Qualitative data includes all non-numerical information obtained from observations not from measurement.

Quantitative data are obtained from measurements, and are always associated with random errors/uncertainties, determined by the apparatus, and by human limitations such as reaction times.

Propagation of random errors in data processing shows the impact of the uncertainties on the final result.

Introduction

All lab work in any science subject isn’t perfect. Mistakes will be made. Some will be human error; some will be related to the equipment used. No experimental result has true validity unless these errors are acknowledged and worked into any result. Remember, an error is something that prevents you from getting the true, correct result.

Before we look at the errors let’s clarify a few terms related to lab work:

Qualitative data: This is all information obtained from observations not from measurement. For example, a color change or the formation of a precipitate is a qualitative observation. There can be no mathematical content to such observations.

Quantitative data: This is where the numbers come in. This data is obtained from measurements and often requires mathematical processing.

In experiments we typically measure a variable. The independent variable is affected when another variable is changed (the dependent variable). For example, in an experiment to measure how temperature affects the speed of a reaction, the independent variable is the temperature and the dependent variable would be the measured time.

Although errors can be made in recording qualitative data, the majority of errors are associated with quantitative data.

What sort of errors are there?

Essentially three types of error exist:

Systematic error: These are errors that are due to the procedure or equipment you have used. For example, an experiment to measure the quantity of gas produced (see Chapter 7) will have to overcome the gap between mixing the reagents and the gas hitting a gas syringe. Some gas will be lost. As this would be a fault of the procedure the error should be the same each time.

Random errors: These, as the name suggests, are harder to quantify. They are the result of human error, failure to carry out the procedure properly and other factors that can go wrong. They can include the parallax errors of misreading a burette by looking from the wrong angle and simple reaction times of the person carrying out the experiment.

The uncertainty of the apparatus: All pieces of quantitative apparatus have a tolerance. This is the preciseness of the result. For example, the pipette in the picture below is designed to measure 25 ml, but the tolerance is ±0.06 ml. This means that if the pipette is used correctly the actual amount measured from this pipette will be between 24.94 ml and 25.06 ml. You cannot know the actual figure with any greater certainty.

A pipette showing the tolerance at 20°C.

Repeating results

Repetition of results is important for the removal of random errors, but it will have no effect on systematic errors, or the uncertainty of the apparatus.

CORE

SPREAD 2: Applying uncertainty readings to a calculated number

Experimental design and procedure usually lead to systematic errors in measurement, which cause a deviation in a particular direction.

Repeat trials and measurements will reduce random errors but not systematic errors.

The uncertainty involved with all numerical readings on apparatus needs to be factored in to any calculation made. It is known as the percentage uncertainty. It is easy to calculate:

For example, using the pipette above which measures 15 ml with an uncertainty of ±0.03 ml is

0.03/15 × 100 = 0.2%

The calculation can get more complicated when the required reading needs two measurements, for example on a burette reading, or recording a temperature change, starting and end temperature. Here BOTH readings have the uncertainty quoted, and so the uncertainty is doubled.

For example, with these burette readings:

So the percentage uncertainty here is 0.05 × 2/24.65 × 100 = ±0.41%.

In an experiment where many readings are made the uncertainty of all measurements needs to be calculated and then added together to give a total percentage uncertainty for the experiment.

Example from thermochemistry

The heat capacity of a copper can is 25 JK−1 ± 1. Using it to carry out a calorimetric experiment a temperature rise of 8°C is recorded on a thermometer with an uncertainty of ±1°C. What is the total uncertainty?

Calorimeter uncertainty = 1/25 × 100 = 4%

Thermometer uncertainty (0.1 + 0.1)/8 × 100 = 2.5%

Total uncertainty = 6.5%

What can be done to reduce systematic error?

There are two ways to approach reducing systematic errors and uncertainty errors. This mainly involves reviewing either the procedure itself, or to use apparatus that will reduce the potential for error.

Let’s take the example of gas collection with upturned measuring cylinder and gas syringe. Discuss the variables and the problems.

There are many problems with this setup. The potential for gas to escape, or to dissolve in the water: the inaccuracy of the measuring scale on the gas jar.

When it comes to reducing percentage uncertainty often the quantities used can cause the problem. See the example below:

A student weighs out 0.5 g on a balance with an uncertainty of 0.1 g and again on a balance with an uncertainty of 0.01 g (20% and 2%).

The student then weighs out 5 g on the 0.1 balance and the 0.01 balance (2%) and 0.2, so the percentage uncertainty of the apparatus also depends on the measured quantity. As a rule of thumb a good way of reducing percentage uncertainty is to increase the quantity measured.

CORE

SPREAD 3: What is the difference between accuracy and precision?

This is a concept that can cause confusion, as the two words are used in the real world interchangeably, but in science they have very specific meanings:

Accuracy means how close the answer is to the true answer.

Precision means how reproducible is the result, or the resolution of the result (the number of decimal places).

In IB chemistry often target diagrams are used to illustrate the point.

In diagram 1 there is low accuracy and low precision because none of the points are in the inner ring (low accuracy) and the points are far apart (low precision).

Diagram 2 is also low accuracy because no points hit the inner ring, but the results are precise because they are all close together.

Diagram 3 shows a high accuracy because all the points are in the inner ring, but the precision is poor.

Diagram 4 has high accuracy and high precision.

Repetition can increase the precision of results but is unlikely to affect the accuracy; often a redesign of the experiment is required there.

Calculation of percentage error

The technique for working out how ACCURATE you’ve been is the percentage error. Here you will have to look up the true value from a reliable source (and reference it).

Then you simply divide your answer by the correct answer and multiply by 100 and quote this value. If your answers are enthalpy changes and have negative numbers it is OK to work this out by ignoring the sign. All we care about is how far apart the numbers are from each other.

Any experimental work that is to be assessed needs to have percentage error and percentage uncertainty calculated. If your answer’s percentage uncertainty brings it close to the true answer, that is, they overlap, you can argue in an evaluation that the limitations of your apparatus might be a factor. If they are way out you may have to look for other reasons.

CORE

SPREAD 4: Graphical techniques

Graphical techniques are an effective means of communicating the effect of an independent variable on a dependent variable, and can lead to determination of physical quantities.

Sketched graphs have labelled but unscaled axes, and are used to show qualitative trends, such as variables that are proportional or inversely proportional.

Drawn graphs have labelled and scaled axes, and are used in quantitative measurements.

Many of the quantitative relationships you meet on a chemistry course can be more easily interpreted with a graph. There are many types of graphs, but the most common type encountered in chemistry is some kind of plot with a line or curve of best fit. Graphs are only of use if the correct choice of axes is chosen and the scale is sensible. As a general rule the bigger you can make the plot the more useful the graph is. Typically the dependent variable is plotted on the y axis, and the independent variable is measured on the x axis. So the x should represent the change you make, and the y is the result of that change.

Sometimes it is acceptable to sketch a graph and not worry about the preciseness of the plotting, and the detail of the axes. This is when you are merely showing a positive correlation or proportionality in the results.

Using graphs to predict unknown values

Plotting graphs is a skill you will also have to master in other aspects of your IB diploma. I do not intend to go into detail here. However, there are a few skills you should be aware of:

Plotting best fit lines and curves is essential for all graphs that you attempt to plot a best fit line or curve. A common mistake for the physicists out there is to assume all plots should have a best fit line. In chemistry a best fit curve is also common, so watch out for them.

Graphs can also be used to predict results where no experiment has been performed.

Interpolation is when a value is worked out from within the parameters of known results.

In this graph we would be able to predict the rate for any temperature recorded between the minimum and maximum.

Extrapolation is when the best fit line is extended beyond the experimental line to give results outside the range of the performed experiment. In calorimetry experiments because of the time lag on the thermometer the true temperature rise is often calculated using extrapolation from the straight line plot.

Gradients and intercepts

Measuring gradients is an important aspect of graph plotting, especially in the kinetics section. The gradient is dy/dx, not forgetting to use the correct units and scale to use on the axis. Here activation energy can be calculated by use of the gradient. See Chapter 7.

Intercepts are also useful. This is where the trend line is extrapolated until it crosses the axis. This is useful for calculating the steric factor in kinetics and working out pKa of a weak acid from a pH curve using the Henderson–Hasselbach technique.

This chapter’s contents refer to the material covered in Topic 1 of the IB Chemistry Specification.

SPREAD 1: Writing formulae

• Atoms of different elements combine in fixed ratios to form compounds, which have different properties from their component elements.

• Mixtures contain more than one element and/or compound that are not chemically bonded together and so retain their individual properties.

• Mixtures are either homogeneous or heterogeneous.

• Calculating relative molecular mass (RMM). Molar mass (M r ) has the units g mol −1 .

You can’t begin a chemistry course until you have these basic ideas sorted out. Simplistically there are three types of substance: element, compound and mixture.

Elements are substances made of only one type of atom. Elements cannot be broken down into anything simpler that will have a form of chemical existence. They behave differently from their constituent elements. For example, table salt (sodium chloride) is a relatively benign white solid that isn’t toxic, whereas the elements sodium and chlorine are both very dangerous, as we will see.

Compounds are substances made of two or more elements chemically bonded together (see Chapter 4). Compounds can be written in the form of chemical formulae. This shows the fixed ratio of elements in the compound. For example, in magnesium carbonate, the formula is MgCO3—one magnesium, one carbon and three oxygens.

What is the difference between copper sulfide and copper sulfate?

In simple terms ide can be taken to mean combined in a compound, so copper sulfide is just copper and sulfur CuS. Ate can be taken to mean with oxygen as well, so copper sulfate is CuSO4. The exact nature of ate will be discussed further in the chapter on bonding.

Mixtures are elements or compounds (or both) chemically uncombined. Mixtures that contain chemicals in the same chemical state are called HOMOGENEOUS (from the Greek homo—the same, genous—combining from). A good example is air. HETEROGENOUS mixtures contain chemicals in different states (hetero—different). An example would be sea water. As the components in a mixture are not chemically combined they retain their individual characteristics.

Substances can occur in three states: solid (s), liquid (l) and gas (g). If you have a solution (a mixture of a substance dissolved in water) then it is called aqueous (aq) (from the Latin via French for water). These bracketed signs should appear next to any chemical formulae in equations.

A chemical reaction is one where chemistry occurs. Chemical reactions can be represented by chemical equations. Chemical equations are stoichiometrically correct (which means the proportions of each chemical are shown correctly). One of the skills needed on the IB DP course is to be able to balance chemical equations so that the stoichiometry is correct.

Balancing equations

NOTE: BEFORE WE START: WE NEVER WRITE 1 IN CHEMICAL EQUATIONS. It’s implied because it’s there, so it’s H2O not H2O1

Easy example

H2 + O2 ⇒ H2O

Atoms can’t simply disappear. The same number must be on the left as on the right. Here there are two hydrogens on both sides, two oxygens on the left, but only one on the right. The equation is not balanced.

You cannot change the formulae, so all you can do is change the quantities, by putting a large number in front of the equation’s components.

So a good place to start is to double the thing that is lacking, the right hand side (RHS):

H2 + O2 ⇒ 2H2O

This helps the oxygen; there are two on either side. But of course there are now four hydrogens on the RHS, so we need to fiddle with the left hand side.

2H2 + O2 ⇒ 2H2O

Harder example

C3H8 + O2 ⇒ CO2 + H2O

With questions involving hydrocarbons the rhythm is easier to find. How many carbons on the left? Three. So there MUST be three CO2 molecules.

C3H8 + O2 ⇒ 3CO2 + H2O

Eight hydrogens mean eight hydrogens on the RHS

C3H8 + O2 ⇒ 3CO2 + 4H2O

Now we just balance for oxygen. There are ten oxygens on the RHS, so make O2 = 10

C3H8 + 5O2 ⇒ 3CO2 + 4H2O

Plenty of practice on this will go a long way in helping you become more confident. Balancing problems will usually occur in the first three or four questions of a multiple choice paper. Practice a few below.

Working out the RMM

The periodic table contains all the information you need for the masses of atoms. It is given as the relative atomic mass. The mass of a compound is simply the sum of all the elements in the compound.

So copper sulfate CuSO4 = 63.5 + 32 + (16 × 4) = 159.5 g mol−1

SPREAD 2: Avogadro’s number and the mole concept

The mole is a fixed number of particles and refers to the amount, n, of a substance.

Masses of atoms are compared on a scale relative to ¹²C and are expressed as relative atomic mass (Ar) and relative formula/molecular mass (Mr).

Chemistry calculations: The basics

All chemistry calculations revolve around the concept of the mole. The problem with any calculation is that there is a difference between quantities that we understand as humans (mass, volume) and the quantities at an atomic level, where simply the number of