- What Makes a Strong Chemistry IA Topic?
- Chemistry IA Requirements (Guide First Assessed in 2025)
- Reaction Rate IA Ideas (Reactivity 2.2)
- Energetics and Thermodynamics IA Ideas (Reactivity 1)
- Equilibrium and Acid-Base IA Ideas (Reactivity 2.3, 3.1)
- Redox and Electrochemistry IA Ideas (Reactivity 3.2)
- Structure, Bonding and Materials IA Ideas (Structure 2, 3)
- Analytical, Database and Simulation IA Ideas
- Example Chemistry IA Research Questions
- How to Turn a Broad Idea Into a Good Research Question
- Data Analysis and Uncertainties in a Chemistry IA
- How the Four Chemistry IA Criteria Are Marked
- Safety and Feasibility Matter More Than Students Expect
- Common Chemistry IA Mistakes
Quick Answer
The best IB Chemistry IA topics are narrow, safe and quantitative: reaction rates, enthalpy changes, equilibrium by colorimetry, titrations, electrochemical cells and intermolecular forces all work well. The IA is a scientific investigation worth 20% at SL and HL, with a 3,000-word limit and four criteria worth 6 marks each: research design, data analysis, conclusion and evaluation.
What You'll Learn
- The Chemistry IA is a scientific investigation worth 20% at SL and HL, with a 3,000-word maximum and four criteria worth 6 marks each
- Choose a system where one variable changes continuously and the outcome can be measured precisely and repeated
- Plan uncertainties from the start: absolute, relative and percentage uncertainties, error bars and R squared are all in the guide
- HL students can push classic topics further with rate equations, the Arrhenius equation, equilibrium constants or pKa values
- Safety and school approval come first: a simple, well-controlled experiment beats an impressive one with messy data
What Makes a Strong Chemistry IA Topic?
A strong topic is safe, feasible in your school lab, quantitative and closely tied to chemistry you can explain. The best topics let you vary one factor across a continuous range, measure the outcome precisely, repeat trials, and process the results into something meaningful such as a rate constant, an enthalpy change or an equilibrium constant. Students often lose marks by choosing topics that sound impressive but produce weak or messy data.
Pro Tip
Before you commit, ask two questions: can I measure the outcome precisely enough to see a trend beyond my uncertainties, and can I explain the chemistry behind that trend in detail?
Chemistry IA Requirements (Guide First Assessed in 2025)
Chemistry, biology and physics share one IA model in the guides first assessed in May 2025, which apply to everyone sitting exams in November 2026, May 2027 and May 2028, including DP1 students who started in August 2026. The IA is the scientific investigation: an open-ended task in which you gather and analyse data to answer your own research question.
- Weighting: 20% of the final grade at both SL and HL, with the same criteria at both levels
- Length: a report of no more than 3,000 words; charts, diagrams, data tables, equations, calculations, citations, the bibliography and headers do not count
- Time: the guide recommends about 10 hours of teaching time for the IA
- Marking: research design, data analysis, conclusion and evaluation, each out of 6, for a total of 24; marked by your teacher and moderated by the IB
- Approaches: lab experiments, spreadsheet modelling, data from databases or simulations, alone or combined, as long as you collect and analyse quantitative data
- Group work: optional, in groups of up to three, with your own research question and your own report; you must not present the same raw data as another student
- Overlap: the same piece of work cannot count as both your IA and your extended essay
Watch Out
Advice that mentions personal engagement, exploration, analysis and communication criteria, a 6-12 page report or the group 4 project refers to the previous guide. The group 4 project has been replaced by the collaborative sciences project, which is separate from the IA.
Reaction Rate IA Ideas (Reactivity 2.2)
Rate experiments produce plenty of repeatable, quantitative data, which suits the data analysis criterion. Use sensors or colorimeters where you can, because judging an end point by eye adds large random error.
- Temperature and the thiosulfate-acid reaction (SL and HL): time the cloudiness with a light sensor or colorimeter rather than a disappearing cross, at 6-8 temperatures. HL can plot ln k against 1/T to find the activation energy with the Arrhenius equation.
- Acid concentration and magnesium (SL and HL): measure hydrogen production with a gas syringe or by mass loss at different hydrochloric acid concentrations. HL can find the order of reaction with respect to the acid.
- Catalysing hydrogen peroxide decomposition (SL and HL): vary the mass of manganese(IV) oxide or the concentration of potassium iodide and measure oxygen volume or pressure with a sensor.
- The iodine clock reaction (HL): vary each reactant concentration in turn to find the orders and the rate equation, then the rate constant at several temperatures.
- Particle size and marble chips (SL and HL): sieve calcium carbonate into size ranges, estimate the surface area, and measure the rate of mass loss with acid. Discuss the uncertainty in estimating surface area.
- Temperature and vitamin C breakdown (SL and HL): measure the ascorbic acid left in solution over time by redox titration at different temperatures. HL can test whether the breakdown is first order.
- Crystal violet and sodium hydroxide (HL): follow the fading colour with a colorimeter to find the order and rate constant under pseudo-first-order conditions. Only with teacher approval, as crystal violet is hazardous.
Energetics and Thermodynamics IA Ideas (Reactivity 1)
Calorimetry is in the guide's list of techniques, but heat loss makes raw results inaccurate. Strong energetics IAs correct for heat loss, for example by extrapolating a cooling curve, and compare the result with literature values.
- Chain length and enthalpy of combustion (SL and HL): burn a series of primary alcohols in spirit burners and compare with data booklet values. A classic, so add value by correcting for heat loss or comparing isomers.
- Acid strength and enthalpy of neutralisation (SL and HL): use calorimetry with extrapolated temperature curves on several acids of different strength, and explain the differences through the energy needed to ionise weak acids.
- Hess's law for an unmeasurable reaction (SL and HL): find the enthalpy change for hydrating anhydrous magnesium sulfate, or decomposing calcium carbonate, from two reactions you can measure.
- Enthalpy of solution of salts (SL and HL): measure the temperature change as a series of group 1 or group 2 salts dissolve and relate the trend to ion size and charge.
- Energy from fuels (SL and HL): compare energy released per gram for ethanol and other liquid fuels under identical heating conditions, and discuss incomplete combustion, which links to Reactivity 1.3.
- Solubility, enthalpy and entropy (HL): measure the solubility of potassium nitrate at several temperatures and use the temperature dependence to estimate the enthalpy and entropy of dissolving. Links to entropy and Gibbs energy, which are additional higher level.
Equilibrium and Acid-Base IA Ideas (Reactivity 2.3, 3.1)
Colorimetry and pH probes turn equilibrium and acid-base chemistry into precise, continuous data. Several of these ideas use additional higher level content, but SL students can run the experiments and explain them qualitatively.
- Iron(III) thiocyanate equilibrium (SL and HL): use colorimetry to measure how the equilibrium position shifts with the concentration of one reactant. HL can calculate the equilibrium constant from absorbance data.
- Temperature and the equilibrium constant (HL): measure Kc for the iron(III) thiocyanate system at several temperatures and use the trend to deduce the sign of the enthalpy change.
- pKa of weak acids (HL): find pKa from the half-equivalence point of pH curves for a series of carboxylic acids and relate the trend to molecular structure.
- Buffer capacity (HL): measure how much acid or alkali a buffer absorbs before its pH changes by one unit, at different buffer concentrations or acid-to-salt ratios.
- Antacid tablets (SL and HL): measure neutralising capacity by back titration. Comparing brands gives categorical data, so consider varying the mass of tablet or the stated dose instead.
- Fruit juice acidity during storage (SL and HL): titrate the acid content of fruit juice after different storage times or temperatures.
- Calcium hydroxide solubility and temperature (SL and HL): titrate saturated solutions at different temperatures to find solubility; HL can discuss the equilibrium constant for dissolving.
Redox and Electrochemistry IA Ideas (Reactivity 3.2)
Electrochemical cells are in the guide's list of techniques and give direct numerical readings. Control temperature and electrode condition carefully, because both shift voltages.
- Electrolyte concentration and cell voltage (SL and HL): measure the voltage of a copper-zinc cell as you change one electrolyte's concentration and compare the trend with predictions. HL can relate it to standard electrode potentials.
- Electroplating and charge (SL and HL): vary the current or time when plating copper and test whether the mass deposited is proportional to the charge passed.
- Fruit and vegetable cells (SL and HL): vary electrode separation or electrode area in a lemon or potato cell and measure the voltage or current through a fixed resistor.
- Salt concentration and rusting (SL and HL): measure the mass change of iron nails in different salt concentrations over a week. Needs time and careful drying to constant mass.
- Metal pairs and cell potential (HL): measure the potential of cells made from different metal pairs and compare with values calculated from standard electrode potentials, explaining the gap.
- Temperature and dissolved oxygen (SL and HL): measure dissolved oxygen in water with a probe at different temperatures and explain the trend in gas solubility.
Structure, Bonding and Materials IA Ideas (Structure 2, 3)
These ideas link a measurable property to intermolecular forces or structure. They work best with a homologous series or a continuous change in composition.
- Evaporation and intermolecular forces (SL and HL): record the temperature drop as different alcohols evaporate from a temperature probe, and relate it to chain length and hydrogen bonding.
- Viscosity and temperature (SL and HL): time a ball falling through glycerol or an oil at different temperatures and explain the trend in terms of intermolecular forces.
- Surface tension and detergent concentration (SL and HL): measure drop mass or count drops from a burette at different detergent concentrations.
- Bioplastic strength (SL and HL): vary the glycerol plasticiser in a starch-based film and measure tensile strength or stretch with hanging masses.
- Cross-linking in PVA slime (SL and HL): vary borax concentration and measure how viscosity changes using flow rate through a funnel.
- Recrystallisation yield (SL and HL): recrystallise a low-hazard solid such as benzoic acid, vary the final cooling temperature, and measure percentage yield and melting point to judge purity.
- Chain length and boiling point (SL and HL): measure or compile boiling points across a homologous series and model the trend, explaining it with London dispersion forces.
Analytical, Database and Simulation IA Ideas
Analytical techniques such as colorimetry and chromatography are listed in the guide, and database and simulation investigations are allowed. With secondary data, your method marks come from how you select and process the data.
- Iron in spinach or iron tablets (SL and HL): use colorimetry with thiocyanate and a calibration curve, then vary cooking time for spinach to create a continuous variable.
- Water hardness and boiling (SL and HL): measure calcium ion concentration by titration after boiling hard water for different times.
- Chromatography and solvent polarity (SL and HL): measure Rf values of food dyes in ethanol-water mixtures of different ratios and relate them to polarity.
- Absorbance and concentration (SL and HL): test how closely absorbance follows concentration for copper(II) sulfate solutions at different wavelengths, and find where the relationship breaks down.
- Periodic trends from data (SL and HL): use published data for melting point or ionisation energy across a period or down a group, model the trend and explain anomalies with electron configuration.
- Bond length and bond enthalpy (SL and HL): compile published values for carbon-halogen bonds and test the relationship, explaining it with atomic radius and orbital overlap.
- Real gases in a simulation (SL and HL): use a gas simulation or published data to measure how far a real gas departs from ideal behaviour as pressure or temperature changes, linking to Structure 1.5.
Example Chemistry IA Research Questions
A good research question names the system, the independent variable with its range, and the dependent variable with how it is measured. These illustrative examples show the level of detail to aim for.
- How does temperature (20-60 °C) affect the rate constant of the reaction between sodium thiosulfate and hydrochloric acid, measured by the time for a fixed fall in light transmission?
- How does the number of carbon atoms in a primary alcohol (one to five) affect its enthalpy of combustion, measured by calorimetry with heat-loss correction?
- How does the concentration of copper(II) sulfate (0.10-1.00 mol dm-3) affect the potential of a copper-zinc voltaic cell at 25 °C?
- How does the mass of glycerol (0-4 g per 10 g of starch) affect the tensile strength of a starch-based bioplastic film?
- How does temperature (20-50 °C) affect the equilibrium constant for the formation of iron(III) thiocyanate, determined by colorimetry?
- How does storage temperature affect the ascorbic acid concentration in orange juice over 48 hours, determined by redox titration?
Watch Out
Do not copy a question directly. Your final question must fit your equipment, your teacher's guidance and your own pilot results.
How to Turn a Broad Idea Into a Good Research Question
Many weak Chemistry IAs start with a topic that is too broad. The guide says a research question with context should refer to the independent and dependent variables, describe the system and include directly relevant background theory.
- 1Start with an area of chemistry you understand reasonably well
- 2Choose one independent variable you can vary precisely over a continuous range
- 3Choose one dependent variable you can measure consistently, with a known uncertainty
- 4Define the exact chemicals, concentrations, apparatus and ranges
- 5Check that the results can be processed into something meaningful, such as a rate constant or enthalpy change
- 6Pilot the method, then finalise the wording
Data Analysis and Uncertainties in a Chemistry IA
The data analysis criterion rewards clear, precise recording and processing with appropriate consideration of uncertainties. The chemistry guide's maths skills set out what that involves.
- Record every measurement with its uncertainty and a consistent number of decimal places or significant figures
- Propagate uncertainties: add absolute uncertainties when adding or subtracting, and add relative or percentage uncertainties when multiplying or dividing (HL also covers exponents)
- Calculate percentage error against a literature value and compare it with your percentage uncertainty to discuss random and systematic error
- Draw uncertainty bars and use R squared to judge how well a trend line or curve fits
- Process data towards the research question, such as a rate constant, enthalpy change or equilibrium constant, rather than stopping at averages
Pro Tip
Plan the final graph before you collect data. If theory predicts a straight line only after a transformation, such as ln k against 1/T, choose your range and intervals so that graph will be convincing.
How the Four Chemistry IA Criteria Are Marked
Each criterion is out of 6 and worth 25% of the IA mark. These points paraphrase what the guide describes for the top band of 5-6 marks.
- Research design: the research question is described in a specific and appropriate context, methodological considerations are explained, and the method could be reproduced
- Data analysis: recording and processing are clear and precise, uncertainties are appropriately considered, and processing is appropriate and accurate
- Conclusion: the conclusion is justified, fully consistent with your processed data and its uncertainties, and compared with the accepted scientific context, such as literature values
- Evaluation: you explain the relative impact of specific methodological weaknesses or limitations and explain realistic improvements that address them
Safety and Feasibility Matter More Than Students Expect
Chemistry IAs often fail because students choose experiments their school cannot safely approve or supervise. The guide requires safety, ethical and environmental factors to be considered before practical work starts, and recognising them is part of research design. A simpler experiment with strong data usually makes the stronger IA.
- Check that the chemicals are available at the concentrations you need
- Avoid highly hazardous reagents unless your teacher explicitly approves them
- Think about disposal, ventilation, heating and measurement limits early
- Choose a method you can repeat many times in the time available
Common Chemistry IA Mistakes
These mistakes appear again and again in weaker Chemistry IAs and usually limit marks before the experiment begins. If you are stuck between topics, an IB Chemistry tutor can help you test which one will give you reliable, analysable data.
- A research question too broad to investigate properly in 3,000 words
- A method with poor measurement precision, such as judging colour changes by eye
- Too few data points or repeats for meaningful processing
- Ignoring heat loss in calorimetry or temperature drift in rate experiments
- Stopping at a trend instead of processing to a rate constant, enthalpy change or equilibrium constant
- Generic evaluation, such as human error, instead of specific weaknesses and their effect on the result
Watch Out
A visually impressive experiment is not automatically a high-scoring IA. Clear data and strong analysis matter more than novelty.