Chemistry IA · Structure 2 · Models of bonding and structure · topic 6 of 25

Bond length and strength by computer modelling · IB Chemistry IA idea: guide, sample graph and step-by-step plan

no wet lab, but the method is your lab

Let a computer 'measure' the bond, then ask how far you should trust it.

Difficulty●●○ Medium
KitBasic: computer, free molecular modelling software
TimeAbout 10 hours
FitsSL and HL
  • ✓ you like simulation more than wet lab
  • ✓ you are happy with a spreadsheet
  • ✓ you enjoy asking how far to trust a result

The big idea

← this is your RQ hook!

Down group 17 the halogen atoms get bigger, so the H–X bond gets longer, and longer bonds are usually weaker. Modelling software can calculate each bond length without a lab. The computer is not a measurement: its answer depends on the method and settings you choose. The strong version of this IA compares computed lengths and tabulated bond enthalpies with each other and with experiment, and judges the method as well as the chemistry. State the method precisely, change it deliberately, and see what happens.

Make it yours: pick one twist

Copying a classic won't show your choices. Pick one of these (or invent your own) and your IA becomes yours.

Swipe for more twists →

Compare two methods

Compute the same four molecules with a simple force field and with a quantum-chemistry method, or with two basis sets.

→ The method becomes your independent variable. You compare each with experimental lengths.
Go across a period

Model HF, H₂O, NH₃ and CH₄ instead.

→ A different trend, where electronegativity and bond polarity enter the explanation.
Vary bond order

Model ethane, ethene and ethyne and compare C–C lengths with tabulated enthalpies.

→ Same method, new variable. Links bond order, length and strength.
Add vibrational frequencies

Use software that reports a stretching frequency and compare with IR data.

→ A third quantity, linked to bond stiffness. Needs a method that calculates it.
Plot enthalpy against length

Put tabulated enthalpy against computed length for all four.

→ One graph for the whole trend. Use the spread between methods as your uncertainty.
Give it a purpose

Frame it around why hydrofluoric acid is weak but hydroiodic acid is strong.

→ A real context. Acid strength links to bond enthalpy and the stability of the anion.

Your Chemistry IA research question: run the check

Write your own question first. Then make sure it ticks every box:

  • Names the software, its version, the method and basis set (or force field), and keeps them the same for every molecule.
  • Names the quantities compared (computed length, tabulated enthalpy) and where the tabulated values come from, with conditions.
  • Says how you estimate an uncertainty on a computed value, for example from different methods or starting geometries.
  • Says which experimental bond lengths you compare with, and where they come from.
  • Says what you would count as good agreement, before you look at the result.

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The workflow

No apparatus here: the 'set-up' is the software, the settings and the tables you compare. Sketch yours with the details you choose.

HXd = ? pmXd / pmBE / kJ mol⁻¹same software, method andbasis set for all fourwrite down the methodand the software versiontabulated values: cite thetable and its conditionscomputed is not measured:compare it with the data

How your Chemistry IA could be laid out

The usual order for a topic like this, what each part needs to show, and roughly how much of your 3,000 words it takes. The words are all yours.

Research question and context~250
Your question; why bond length and strength are linked; what you predict down the group.
Background chemistry~450
Bond length and bond enthalpy; why they might trend with atomic size; what the computational method does and does not model; prediction.
Data source and method~450
Software, version, method and settings; how you built and optimised each molecule; where the tabulated and experimental values come from. Enough detail to repeat it.
Variablestable
Independent, dependent and controlled variables, each with how it is chosen or held constant.
Safety, ethics, environment~60
No lab hazards, so say so. Take screen breaks. Name the software and licence, report computed values as calculated, not measured, and keep every run.
Raw datatable
One clear table: molecule, computed length, method details and tabulated values, with units and sources.
Processing~250
Percentage difference from experiment for each molecule, and the uncertainty from your chosen estimate. One worked example.
Graphs and analysis~400
Your graphs with uncertainty bars; how well the trend holds; where computed and tabulated values disagree.
Conclusion~400
Answer with numbers: how length and enthalpy change down the group, and how well the method agrees with experiment, with sources.
Evaluation~650, the biggest part!
Limits of the method and basis set, treatment of iodine, only four molecules; weaknesses ranked, with improvements linked.
Referencesnot counted
Every source: software, method, tables and experimental values.

What your Chemistry IA graph could look like

say which method gave the length ✓

Made-up data, to show you the form of a strong graph, not the answer. Yours will look different. example only

8090100110120130140150160170180200250300350400450500550600650700Computed bond length d / pm (spread between methods ± 2 pm)Bond enthalpy / kJ mol⁻¹ (± 5)straight-line fit through the four pointsH–X molecules, with error barsonly four points:how will you judge the fit?ILLUSTRATIVE · MADE-UP DATA
  • Both axes carry units. The length is a computed value, so say which method gave it.
  • Use the spread between methods for the horizontal bars, not the decimals the software prints.
  • With four points, a line and a gentle curve both fit. Say what you can and cannot conclude.
  • Label each point with its molecule so the reader can follow the trend down the group.
  • Another graph to consider: percentage difference between computed and experimental length, for each molecule and each method.

Your game plan

re-run one molecule with a different start

Tick steps off as you go. We'll remember on this device.

0 of 11 done

  1. Read and predictRead about bond length, bond enthalpy and atomic size. Predict the trend in both down group 17, and say what would count as a surprise.
  2. Trial run (1 lesson)Build one molecule, optimise it and read the bond length. Change the method or starting geometry and run it again. How much does the answer move?
  3. Choose software and settingsPick the software, the method, and the basis set or force field. Check it can handle iodine. Write down why, and use the same settings for every molecule.
  4. Find tabulated and experimental valuesFind bond enthalpies and experimental lengths in cited sources. Note the conditions, and whether they are average or molecule-specific values.
  5. CollectRun each molecule, and record the settings and the output in your table. Keep a log of every run, including any that failed.
  6. Estimate uncertaintyDecide how you will estimate an uncertainty on a computed length, for example from a second method or different starting geometries.
  7. ProcessWork out the difference between computed and experimental lengths for each molecule. Decide how to report it.
  8. Graph and interpretPlot enthalpy against length with uncertainty bars. How well does the trend hold? Where does the method fail?
  9. EvaluateRank the weaknesses: method choice, basis set, four molecules. Make each improvement specific.
  10. Write, then cutWrite in the order of the layout above, within 3,000 words. Tables, calculations and graphs are not counted.
  11. Check before your teacher's draftRun the checklist, then get your RQ or draft checked. Your teacher reads one draft only.

Chemistry you'll need

Traps to avoid in this Chemistry IA

  • Treating a computed value as a measurement. It is a model result: compare it with experiment and discuss the gap.
  • Not saying which method, basis set or force field was used, or changing it between molecules.
  • A force-field optimiser returns lengths from stored parameters, not from electron calculations. Check what your software actually does, especially for iodine.
  • A basis set that does not cover iodine, so the result looks fine but is not comparable with the others.
  • Calling a relationship quantitative from only four points.
  • Mixing data tables that define bond enthalpy differently (average against molecule-specific).
  • Quoting a computed length to many decimal places with no uncertainty.

More Chemistry IA ideas like this

Make sure it's yours

This guide shows how a topic like this is usually approached. It is not an IA. Your question, choices, data, analysis and words must be your own: change something, tell your teacher where the idea came from, and follow your school's rules on outside help.

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