20 February 2026

A-Level Chemistry — Iodine and its Properties (the glamorous purple one)


A-Level Chemistry — Iodine and its Properties (the glamorous purple one)

If chlorine is the loud, attention-seeking halogen and bromine is the moody one, iodine is the dramatic artist: it sits there looking like a dull grey solid… then quietly produces a purple vapour that makes everyone in the lab suddenly pay attention.

This post is a tidy A-Level tour of iodine’s key physical and chemical properties, plus the bits exam questions love to poke.


1) Where iodine sits and what that tells you

Iodine is a Group 17 (halogen) element. Like the others, it exists as diatomic molecules: I₂.

Trends down Group 17 (F₂ → Cl₂ → Br₂ → I₂):

  • Melting/boiling points increase (bigger molecules → stronger intermolecular forces)

  • Colour gets darker

  • Reactivity decreases (harder to gain an electron as atoms get larger and shielding increases)

So iodine is less reactive than chlorine and bromine, but it still does plenty of chemistry.


2) Physical properties you can actually see

Appearance and state

  • Grey/black crystalline solid at room temperature

  • Produces a purple vapour when warmed

Sublimation (a favourite classroom moment)

Iodine can sublime: solid → gas without becoming a liquid first (under normal lab conditions).
That purple vapour is iodine gas (still I₂ molecules).

Why does iodine sublime easily?
Inside each I₂ molecule, the I–I covalent bond is strong. But between molecules the attractions are only London dispersion forces—and warming supplies enough energy to overcome those.


3) Solubility: iodine is fussy

Iodine is non-polar overall, so:

  • Low solubility in water

  • Much more soluble in non-polar solvents (e.g. cyclohexane / hexane)

Colour clue (classic practical / exam):

  • In water: brown/yellow-brown (a mixture of I₂ and some I₃⁻ if iodide is present)

  • In cyclohexane: vivid purple (I₂ really showing off)

If you add iodide ions (from KI), iodine forms triiodide:

I2(aq)+I(aq)I3(aq)\mathrm{I_2(aq) + I^-(aq) \rightleftharpoons I_3^-(aq)}

This helps “pull” iodine into aqueous solution.


4) Simple redox behaviour (the exam engine)

Iodine is an oxidising agent (it accepts electrons), but weaker than chlorine or bromine.

Reduction half-equation:

I2+2e2I\mathrm{I_2 + 2e^- \rightarrow 2I^-}

That’s the backbone of loads of questions: titrations, displacement, and redox calculations.


5) Displacement reactions: who can bully whom?

A more reactive halogen displaces a less reactive one from its halide.

So:

  • Chlorine displaces iodide:

Cl2+2I2Cl+I2\mathrm{Cl_2 + 2I^- \rightarrow 2Cl^- + I_2}

  • Bromine displaces iodide:

Br2+2I2Br+I2\mathrm{Br_2 + 2I^- \rightarrow 2Br^- + I_2}

  • But iodine does not displace bromide or chloride.

Observation: formation of iodine gives brown solution (or purple in organic layer).


6) Iodine as a test reagent (two big ones)

(A) Starch test (iconic)

Iodine forms a deep blue-black complex with starch (specifically amylose helices).
This is used to detect iodine, and also in clock reactions where iodine appears/disappears.

(B) Iodometry / iodimetry (A-Level titration territory)

  • Iodine can be titrated with thiosulfate:

I2+2S2O322I+S4O62\mathrm{I_2 + 2S_2O_3^{2-} \rightarrow 2I^- + S_4O_6^{2-}}

Starch indicator is added near the end point (when solution is pale) for a sharp finish.


7) A quick word on safety and good lab habits

  • Iodine vapour is irritant — use a fume cupboard for heating/sublimation demos.

  • Avoid skin contact (stains and irritates).

  • Use small quantities: iodine is “spectacular per gram”.


Mini “exam-style” check questions (with answers)

  1. Why are iodine’s melting and boiling points higher than chlorine’s?
    Because iodine molecules are larger with more electrons, so London dispersion forces are stronger.

  2. Write the ionic equation for chlorine reacting with potassium iodide solution.

Cl2+2I2Cl+I2\mathrm{Cl_2 + 2I^- \rightarrow 2Cl^- + I_2}

  1. Why does iodine appear purple in cyclohexane but brown in water?
    Cyclohexane dissolves molecular I₂ well (purple). In water iodine is poorly soluble and can form I₃⁻ in the presence of I⁻, giving brown shades.

  2. State the half-equation for iodine being reduced.

I2+2e2I\mathrm{I_2 + 2e^- \rightarrow 2I^-}

19 February 2026

Experiments with a PASCO Light Sensor (and why light is never ‘just light’)

 


Experiments with a PASCO Light Sensor (and why light is never ‘just light’)

If you’ve ever said, “It’s brighter over there,” congratulations — you’ve made a scientific observation. If you’ve ever argued with someone about it, you’ve made a scientific dispute. The PASCO Light Sensor is the peace treaty: it turns “bright” into numbers you can graph, analyse, and (most importantly) use to win the argument politely.

In this post I’ll share a set of simple, reliable experiments you can run with a PASCO Light Sensor (in class or at home), plus what to measure, what to plot, and the usual “why do my results look odd?” troubleshooting.

What you’ll need

  • PASCO Light Sensor (any PASCO light/illuminance sensor)

  • PASCO interface / SPARKvue or Capstone (or whatever you’re using)

  • A lamp (desk lamp is fine) and/or torch

  • Metre rule or tape measure

  • A sheet of white paper or card (as a reflector)

  • Optional: coloured filters/cellophane, sunglasses, polarising sheets, diffraction grating, blinds/curtains

Tip: Try to keep room lighting constant. Daylight through a window is lovely… and also a chaos agent.


Experiment 1: The inverse square law (the “physics that actually works” one)

Question: How does light intensity change with distance from a point source?

Method

  1. Set the lamp at one end of a bench. Keep it still throughout.

  2. Place the sensor facing the lamp.

  3. Measure distance dd from the lamp to the sensor (start at, say, 10 cm, then 15, 20, 30, 40, 50 cm).

  4. Record light intensity at each distance (lux).

  5. Repeat each reading 2–3 times and average.

What to plot

  • Plot Intensity (lux) vs distance (m) → curve

  • Plot Intensity (lux) vs 1/d² → should be a straight line (ish!)

What you should find
If the lamp behaves like a point source, intensity 1/d2\propto 1/d^2.

Common problems

  • At small distances the lamp isn’t a point source.

  • If the sensor saturates, move further away or reduce brightness.

  • Reflections from walls and benches can lift the readings.


Experiment 2: Absorption and transmission (a.k.a. “how good are your sunglasses?”)

Question: How much light gets through different materials?

Method

  1. Fix the lamp and sensor positions (don’t change distance).

  2. Record baseline intensity I0I_0.

  3. Place a material between lamp and sensor (paper, tracing paper, plastic, sunglasses, tinted film, acetate).

  4. Record transmitted intensity II.

  5. Calculate percentage transmission:

%T=(I/I0)×100\%T = (I/I_0)\times 100

Extensions

  • Stack layers of the same material and see if transmission drops steadily.

  • Compare clear vs frosted plastic.

  • Compare different “SPF” sunglasses (if available).


Experiment 3: Reflection — colour, surface, and angle (the “why is it brighter off the white card?” one)

Question: What affects reflected light intensity?

Method

  1. Put a white card on the bench.

  2. Shine a lamp or torch at it at a fixed angle.

  3. Point the sensor towards the card to measure reflected light.

  4. Compare different surfaces: white paper, coloured paper, foil, matte card, glossy magazine.

Ideas to test

  • Colour: Which reflects more: white, yellow, red, black?

  • Texture: Glossy vs matte

  • Angle: Rotate the card and see how reflections change

Bonus physics
Specular reflection (mirror-like) vs diffuse reflection (scattered). Foil behaves very differently from paper.


Experiment 4: Light intensity and shadow patterns (because shadows have structure)

Question: How does intensity change across a shadow?

Method

  1. Place a small object (ruler, pencil, hand) between lamp and sensor.

  2. Move the sensor slowly sideways across the shadow edge.

  3. Record intensity at each position.

What to plot

  • Intensity vs position → you’ll see a drop, then a rise.

  • With a small light source you get a sharp edge; with a bigger source you get a fuzzy “penumbra”.

Link to GCSE Physics
This is a brilliant way to measure umbra and penumbra rather than just draw them.


Experiment 5: Flicker and mains lighting (why 230 V lighting isn’t steady)

Question: Do lights actually stay constant?

Many LED lights and some fluorescents flicker at 100 Hz (UK mains is 50 Hz; brightness often varies twice per cycle).

Method

  1. Put the sensor under a mains-powered lamp (not daylight).

  2. Record intensity vs time at a high sample rate (if possible).

  3. Look for periodic variation.

What you’ll see
Some lights are smooth; others are “invisible strobe lights”. Great discussion for cameras, headaches, and why slow-motion video looks odd under certain lights.


Experiment 6: Polarisation (if you have polarising filters)

Question: How does light intensity change through crossed polarisers?

Method

  1. Place one polariser in front of the light source (or in front of sensor).

  2. Place a second polariser in front of it.

  3. Rotate one polariser and record intensity at angles 0° → 90°.

What to plot

  • Intensity vs angle (°)

Expected pattern
It follows Malus’ Law:

I=I0cos2(θ)I = I_0 \cos^2(\theta)

(And yes, it’s one of those rare laws that behaves beautifully in a school lab.)


Data handling (make it look like proper science)

  • Take repeats and average.

  • Control one variable at a time (distance OR filter OR angle — not all at once).

  • Use units carefully (lux, metres, degrees).

  • Try at least one linearised graph (e.g., intensity vs 1/d21/d^2).


Troubleshooting: the “why are my readings weird?” section

  • Sunlight changed → close curtains or work at night (science is glamorous).

  • Reflections → move away from white walls, use a dark cloth behind.

  • Sensor orientation → keep it facing the same way each reading.

  • Auto-ranging → if the sensor/interface changes range, it can look jumpy. Lock range if possible.


If you’re teaching this (or revising)

These experiments are brilliant for:

  • GCSE Physics: inverse square, reflection/absorption, shadows

  • A-Level Physics: Malus’ law, measurement uncertainty, data linearisation, practical write-ups

And they’re perfect for filmed demonstrations too — you can see the graph change live, which is exactly the kind of “Ohhh, I get it” moment students remember.

18 February 2026

Maths: Applying Maths to Spreadsheets (GCSE & A-Level)

 


Maths: Applying Maths to Spreadsheets (GCSE & A-Level)

In exams, students often treat maths and computing as separate subjects.

In real life? They work together all the time.

If you’re studying GCSE or A-Level Maths, Business, or Computing, learning how maths applies inside a spreadsheet like Microsoft Excel or Google Sheets is a genuine superpower.

Because spreadsheets don’t just store numbers — they apply mathematics at scale.


1️⃣ Percentages – Profit, Growth & Error

Common GCSE Applications:

  • Percentage increase/decrease

  • Profit margins

  • Reverse percentages

  • VAT calculations

Example: Percentage Increase

=(NewValue-OldValue)/OldValue*100

This directly links to GCSE percentage change questions.

In Business Studies, this becomes:

  • Revenue growth

  • Inflation rates

  • Cost increases

And suddenly maths has context.


2️⃣ Algebra – Turning Equations into Formulas

Spreadsheets are algebra machines.

If you understand:

y=mx+cy = mx + c

You can model it directly:

= m*A2 + c

Applications:

  • Modelling taxi fares

  • Predicting future sales

  • Calculating depreciation

  • Physics motion equations

At A-Level, this becomes:

  • Iterative modelling

  • Recursive formulas

  • Financial modelling

You are effectively programming with maths.


3️⃣ Statistics – Mean, Standard Deviation & Correlation

Spreadsheets make statistics immediate.

Functions:

=AVERAGE() =STDEV.S() =CORREL()

GCSE:

  • Mean, median, range

  • Charts and data presentation

A-Level:

  • Standard deviation

  • Regression lines

  • Correlation coefficients

For my own sailing race analysis at Upper Thames Sailing Club, spreadsheets allow:

  • Personal handicap tracking

  • Improvement calculations

  • Race performance comparisons

That’s maths with purpose.


4️⃣ Financial Maths – Compound Growth

Compound interest appears constantly in exams.

In a spreadsheet:

=Initial*(1+rate)^years

Or use:

=FV()

This connects GCSE maths to:

  • Mortgages

  • Savings

  • Investment growth

  • Battery ROI calculations (something I’ve analysed in my own solar system modelling)

Real mathematics. Real consequences.


5️⃣ Logical Maths – IF Statements

This is where Maths meets Computing.

=IF(A2>50,"Pass","Resit")

You’re applying inequalities and logical reasoning.

In A-Level Computing this links directly to:

  • Boolean logic

  • Algorithms

  • Decision structures

Spreadsheets are the bridge between maths and code.


🎯 Why This Matters

Students often ask:

“When will I ever use this?”

If you can:

  • Build a working financial model

  • Analyse data properly

  • Model change

  • Test scenarios

You’re already thinking like:

  • An analyst

  • An engineer

  • A business owner

  • A scientist

Maths in spreadsheets turns abstract numbers into decisions.

And that’s powerful.


17 February 2026

A-Level Physics: AC Theory, RMS Voltages – and Why 230 V Isn’t 230 V at All


 A-Level Physics: AC Theory, RMS Voltages – and Why 230 V Isn’t 230 V at All

When students first meet alternating current in A-Level Physics, there’s a moment of quiet confusion:

“If the UK mains supply is 230 V… why does the graph go above 230 V?”

Excellent question.

Because 230 V isn’t the peak voltage. It isn’t even the average voltage. It’s something called the RMS voltage — and that changes everything.


1️⃣ What Is AC?

In the UK, our mains electricity is:

  • Alternating Current (AC)

  • Frequency = 50 Hz

  • Stated voltage = 230 V

Unlike DC (direct current), AC voltage:

  • Continuously changes direction

  • Follows a sine wave

  • Alternates between positive and negative values

Mathematically:

V=V0sin(ωt)V = V_0 \sin(\omega t)

Where:

  • V0V_0 = peak voltage

  • ω\omega = angular frequency

  • tt = time


2️⃣ Peak Voltage vs RMS Voltage

Here’s the key idea students must master:

VRMS=V02V_{RMS} = \frac{V_0}{\sqrt{2}}

So if the RMS voltage is 230 V:

V0=230×2V_0 = 230 \times \sqrt{2} V0325 VV_0 \approx 325 \text{ V}

🚨 That means the UK mains actually reaches +325 V and –325 V every cycle.

Not 230 V.


3️⃣ So What Does RMS Actually Mean?

RMS stands for:

Root Mean Square

It is the DC voltage that would produce the same heating effect in a resistor.

This is crucial.

Because power in a resistor is:

P=V2RP = \frac{V^2}{R}

If we simply averaged the AC voltage over a full cycle, we'd get zero (positive and negative cancel).

But heating depends on , which is always positive.

So we:

  1. Square the voltage

  2. Find the mean

  3. Take the square root

Hence: Root Mean Square.


4️⃣ Why Engineers Use RMS

Imagine a 230 V electric heater.

If we replaced AC with DC, the DC voltage that would produce the same heating effect is:

230 V DC230\text{ V DC}

That’s why appliances are rated using RMS values.

It allows fair comparison between AC and DC power delivery.


5️⃣ Common Exam Mistakes

From years of teaching A-Level Physics, these errors appear again and again:

❌ Confusing peak and RMS
❌ Forgetting the √2 factor
❌ Using 230 V as peak in power calculations
❌ Forgetting RMS current obeys the same rule:

IRMS=I02I_{RMS} = \frac{I_0}{\sqrt{2}}

6️⃣ Why This Matters Beyond the Exam

Understanding RMS is vital for:

  • Designing power supplies

  • Understanding transformers

  • Working with oscilloscopes

  • Safety calculations

  • Interpreting energy transfer

It also explains why touching a “230 V” supply is far more dangerous than students imagine — because the peaks are significantly higher.


7️⃣ A Quick Exam-Style Question

The UK mains supply is 230 V RMS.

a) Calculate the peak voltage.
b) Calculate the peak current if a 2 kW heater is connected.

(Hint: Start with P=VIP = VI using RMS values.)


Final Thought

AC theory is one of those topics that feels abstract — until you realise your entire house is powered by a sine wave swinging between +325 V and –325 V fifty times every second.

Suddenly it feels rather more real.

16 February 2026

Making and Using a Point Quadrat (The Easy PVC Version)

 


Making and Using a Point Quadrat (The Easy PVC Version)

Point quadrats are one of those bits of ecology kit that sound simple… but are surprisingly awkward (and expensive) to buy.

So I made one.

Using ½-inch PVC tubing, a drill, and some metal rods.

And honestly? It works just as well as a photographic quadrat — and in some cases, better.

Combining them gives a powerful tool.


Building the Frame

What you need:

  • For the base

  • ½-inch PVC tubing (7 × 1 metre lengths)

  • 8 elbow joints

  • 8 T-Pieces

  • Drill + small drill bit (just wider than your metal rods)

  • Tape measure

  • Permanent marker

  • 20 Thin metal rods (or long nails/wire)

Construction:

  1. Build a 1 m × 1 m square using the PVC and elbows.

  2. Using t-pieces make two verticals slightly shorter than the rods.

  3. Using the pieces and elbow joints makes two short right-angle supports.

  4. Using elbow joints make a horizontal rod.

  5. Experience has shown that two horizontals are stronger and keep the rods vertical.

  6. Mark every 5 cm along this rod.

  7. Drill vertical holes at each 5 cm mark.


How It Works

Instead of estimating cover visually (like a photographic quadrat), you:

  • Insert a metal rod vertically through a drilled hole.

  • Let it drop straight down.

  • Record the first plant species it touches.

  • Move to the next hole.

  • Repeat.

If you sample all 20 positions across the frame and repeat along several transects, you quickly build a strong quantitative dataset.

Because the rod falls vertically, this method:

  • Reduces observer bias

  • Gives objective “point hits”

  • Works very well for slightly taller plants

  • Samples structure as well as surface cover


Example Calculation

Suppose you sample 100 points in total:

  • 55 hits on grass

  • 25 hits on clover

  • 10 hits on moss

  • 10 hits on bare ground

Percentage cover =

number of hitstotal points×100\frac{\text{number of hits}}{\text{total points}} \times 100

Grass = 55%

Clear. Quantitative. Exam-friendly.


Photographic Quadrat vs Point Quadrat

I often use both.

Photographic QuadratPoint Quadrat
Quick visual record    Objective contact data
Good for digital analysis    Excellent for statistics
Slightly subjective                Less observer bias
Best for small/low plants    Better for larger plants

The PVC point quadrat is just as easy to deploy as my photographic version, but it samples taller plants, so it handles larger vegetation more reliably.


Why This Is Brilliant for GCSE & A-Level

This practical links directly to:

  • Random sampling

  • Systematic sampling

  • Reliability

  • Validity

  • Reducing bias

  • Increasing sample size

  • Calculating percentage cover

It’s also ideal for:

  • A-Level succession studies

  • Comparing mown vs unmown grass

  • Studying trampling effects

  • Investigating microhabitats

And because it’s PVC — muddy fieldwork is not a problem. Just rinse it off.


Teaching Tip

Ask students:

  • Why must the rod be vertical?

  • What happens if you push it at an angle?

  • Why might you repeat sampling along a transect?

  • How many points are “enough”?

Suddenly this becomes more than a practical — it becomes a discussion about experimental design.

15 February 2026

A-Level Sociology Positivism, Interpretivism & the Nature of Social Facts

 


A-Level Sociology

Positivism, Interpretivism & the Nature of Social Facts

One of the most important debates in A-Level Sociology Research Methods is this:

Is society something we can measure objectively like a science…
or is it something we must interpret through human meaning?

At the centre of this debate are three key ideas:

  • Positivism

  • Interpretivism

  • Social Facts

If students understand how these link together, essays become far easier to structure and evaluate.


1️⃣ Positivism – Sociology as a Science

Positivists argue that sociology should operate like the natural sciences.

Key thinkers:

  • Auguste Comte

  • Émile Durkheim

Core Beliefs:

  • Society exists outside individuals.

  • Social behaviour follows patterns and laws.

  • We should use:

    • Statistics

    • Large-scale surveys

    • Official data

    • Experiments

Durkheim’s study of suicide is the classic example. He argued that suicide rates are social facts — measurable external forces influencing individuals.


2️⃣ What Are Social Facts?

Durkheim defined social facts as:

Ways of acting, thinking and feeling that exist outside the individual and exert control over them.

Examples:

  • Laws

  • Religion

  • Education systems

  • Marriage patterns

  • Crime rates

These are:

  • External

  • Measurable

  • Constraining

Positivists therefore favour quantitative data because it allows generalisation and reliability.


3️⃣ Interpretivism – Understanding Meaning

Interpretivists disagree.

Key thinker:

  • Max Weber

They argue:

  • Society is created through human interaction.

  • People act based on meanings.

  • We must understand behaviour through Verstehen (empathetic understanding).

Preferred Methods:

  • Unstructured interviews

  • Participant observation

  • Case studies

  • Qualitative research

Interpretivists argue that statistics don’t tell us why people act — only that they do.


4️⃣ The Core Exam Debate

Examiners love questions like:

“Assess the view that sociology should be a science.”

To access top marks:

  • Explain positivism clearly

  • Link to social facts

  • Contrast with interpretivism

  • Evaluate strengths and weaknesses


5️⃣ Evaluation Structure (PEEL Ready)

Positivism Strengths

  • High reliability

  • Representative samples

  • Policy usefulness

Positivism Weaknesses

  • Lacks depth

  • Ignores human meaning

  • May oversimplify behaviour

Interpretivism Strengths

  • Rich, detailed data

  • High validity

  • Captures meaning

Interpretivism Weaknesses

  • Hard to generalise

  • Researcher bias

  • Smaller samples


Why This Matters for Students

If you're studying A-Level Sociology in Hemel Hempstead or online:

Understanding this debate helps you:

  • Analyse any research methods question

  • Structure 20-mark essays

  • Link theory to method

  • Impress examiners with evaluation

In my 1:1 tuition sessions at Hemel Private Tuition, we practise:

  • Turning theory into PEEL paragraphs

  • Writing model introductions

  • Building balanced evaluations

  • Applying theory to unseen questions

Phosphorescence & Fluorescence (and why one “stops showing off” the moment you turn the lights on)

  Phosphorescence & Fluorescence (and why one “stops showing off” the moment you turn the lights on) If you’ve ever waved a highlighter...