Year 1 Pure · Chapter 11

Exponential Models

Specification: Edexcel Pure 6 — Exponentials and logarithms  ·  AQA section F

In this chapter
  1. 1. The number e and y = eˣ
  2. 2. The natural logarithm
  3. 3. Exponential growth and decay
  4. 4. Reduction to linear form
  5. Practice

Key facts — this chapter

  • e≈2.718e \approx 2.718 is the special base where y=exy = e^x has gradient equal to its own height at every point.
  • ln⁡x\ln x means log⁡ex\log_e x — the inverse of exe^x, so ln⁡(ex)=x\ln(e^x) = x and eln⁡x=xe^{\ln x} = x.
  • Growth/decay model: y=Aekty = A e^{kt} starts at AA (when t=0t = 0); k>0k > 0 grows, k<0k < 0 decays.
  • Doubling time is ln⁡2k\dfrac{\ln 2}{k}; half-life is ln⁡2∣k∣\dfrac{\ln 2}{|k|}.
  • Reduction to linear form: for y=abxy = ab^x, taking logs gives log⁡y=(log⁡b)x+log⁡a\log y = (\log b)x + \log a — a straight line when log⁡y\log y is plotted against xx.

Lots of real things grow or shrink at a rate proportional to their current size — populations, savings, radioactive decay, cooling drinks. They’re all modelled by the exponential function, and the natural base ee is what makes the maths clean.

1. The number e and y = eˣ

Among all the curves y=axy = a^x, exactly one has the elegant property that its gradient equals its height everywhere. That base is e≈2.718e \approx 2.718.

Key result

For y=exy = e^x, the gradient at any point equals the yy-value there:

dydx=ex=y\frac{dy}{dx} = e^x = y

This is exactly why ee shows up whenever a quantity changes at a rate proportional to its current amount.

The curves y = e to the x and y = ln x, reflections of each other in the line y = x
y = eˣ and its inverse y = ln x, mirror images in y = x.

2. The natural logarithm

The inverse of exe^x is the natural logarithm ln⁡x\ln x (that is, log⁡ex\log_e x). It obeys every log law from Chapter 10 — it just has base ee.

Key result

ln⁡(ex)=xandeln⁡x=x\ln(e^x) = x \qquad\text{and}\qquad e^{\ln x} = x

So to undo ee, take ln⁡\ln; to undo ln⁡\ln, raise ee to the power. This is the key to solving any equation with ee or ln⁡\ln in it.

Worked example 11.1 · Solving with e and ln

Solve e2x=7e^{2x} = 7, giving your answer to 3 significant figures.


  1. Take ln⁡\ln of both sides — it cancels the ee:

    ln⁡(e2x)=ln⁡7    ⟹    2x=ln⁡7\ln(e^{2x}) = \ln 7 \;\;\Longrightarrow\;\; 2x = \ln 7
  2. So

    x=ln⁡72=0.973   (3 s.f.)x = \frac{\ln 7}{2} = 0.973 \;\,(3\text{ s.f.})

3. Exponential growth and decay

The workhorse model is y=Aekty = A e^{kt}. Reading off its constants in context is a core exam skill.

Key result

In y=Aekty = A e^{kt}:

  • AA is the initial value (at t=0t = 0, since e0=1e^0 = 1);
  • kk is the growth rate — k>0k > 0 grows, k<0k < 0 decays;
  • the doubling time (growth) is ln⁡2k\dfrac{\ln 2}{k}, and the half-life (decay) is ln⁡2∣k∣\dfrac{\ln 2}{|k|}.
Two exponential curves from the same start A: one rising for k greater than 0, one falling for k less than 0
Same start A; positive k grows, negative k decays.

Build a model y = A e^(kt). A sets where it starts; k sets how fast it changes — positive grows, negative decays. The doubling time / half-life updates too.

t runs 0 to 10 · the vertical axis rescales to fit the curve

Worked example 11.2 · A population model

A population is modelled by P=8000 e0.05tP = 8000\,e^{0.05t}, where tt is in years. (a) Find the population after 1212 years. (b) Find, to the nearest year, when the population reaches 20 00020\,000.


  1. (a) Substitute t=12t = 12:

    P=8000 e0.05×12=8000 e0.6=14 600   (3 s.f.)P = 8000\,e^{0.05 \times 12} = 8000\,e^{0.6} = 14\,600 \;\,(3\text{ s.f.})
  2. (b) Set P=20 000P = 20\,000 and solve for tt:

    8000 e0.05t=20 000    ⟹    e0.05t=2.58000\,e^{0.05t} = 20\,000 \;\;\Longrightarrow\;\; e^{0.05t} = 2.5
  3. Take ln⁡\ln:

    0.05t=ln⁡2.5    ⟹    t=ln⁡2.50.05=18.3…0.05t = \ln 2.5 \;\;\Longrightarrow\;\; t = \frac{\ln 2.5}{0.05} = 18.3\ldots

So the population reaches 20 00020\,000 after about 1818 years.

Worked example 11.3 · Half-life of a decay

A radioactive sample has mass m=50 e−0.2tm = 50\,e^{-0.2t} grams, with tt in days. Find its half-life.


  1. The half-life is when the mass halves, from 5050 to 2525:

    50 e−0.2t=25    ⟹    e−0.2t=1250\,e^{-0.2t} = 25 \;\;\Longrightarrow\;\; e^{-0.2t} = \tfrac{1}{2}
  2. Take ln⁡\ln:

    −0.2t=ln⁡12=−ln⁡2    ⟹    t=ln⁡20.2=3.47  days   (3 s.f.)-0.2t = \ln\tfrac{1}{2} = -\ln 2 \;\;\Longrightarrow\;\; t = \frac{\ln 2}{0.2} = 3.47 \;\text{days} \;\,(3\text{ s.f.})

Common mistake

The starting amount AA is the value at t=0t = 0, not the coefficient of tt. In P=8000 e0.05tP = 8000\,e^{0.05t} the population starts at 80008000 (because e0=1e^0 = 1), and grows at rate 0.050.05 — don’t read 0.050.05 as a population.

4. Reduction to linear form

Raw exponential data looks like a curve, which is hard to fit by eye. Taking logs straightens it into a line — and a line you can find the equation of.

Key result

For a model y=abxy = ab^x, take logs of both sides:

log⁡y=log⁡a+xlog⁡b\log y = \log a + x\log b

Plotting log⁡y\log y (vertical) against xx (horizontal) gives a straight line with gradient log⁡b\log b and vertical intercept log⁡a\log a.

Why it works

The relationship y=abxy = ab^x is curved, but applying log⁡\log turns the product into a sum and brings the power down: log⁡(abx)=log⁡a+log⁡(bx)=log⁡a+xlog⁡b\log(ab^x) = \log a + \log(b^x) = \log a + x\log b. That has the form Y=mX+cY = mX + c with Y=log⁡yY = \log y, so the transformed data is linear — and a ruler can fit a line where it couldn’t fit a curve.

Left: data on an exponential curve. Right: the same data as a straight line when log y is plotted against x.
log y against x is straight, with gradient log b and intercept log a.

Worked example 11.4 · Finding the model from a straight line

Data fits a model y=abxy = ab^x. When log⁡10y\log_{10} y is plotted against xx, the line has gradient 0.30.3 and vertical intercept 0.60.6. Find aa and bb.


  1. Compare with log⁡y=(log⁡b)x+log⁡a\log y = (\log b)x + \log a:

    • intercept: log⁡10a=0.6  ⟹  a=100.6=3.98   (3 s.f.)\log_{10} a = 0.6 \;\Longrightarrow\; a = 10^{0.6} = 3.98 \;\,(3\text{ s.f.})
    • gradient: log⁡10b=0.3  ⟹  b=100.3=2.00   (3 s.f.)\log_{10} b = 0.3 \;\Longrightarrow\; b = 10^{0.3} = 2.00 \;\,(3\text{ s.f.})

So the model is approximately y=3.98×2.00 xy = 3.98 \times 2.00^{\,x}.

Common mistake

The gradient and intercept give log⁡a\log a and log⁡b\log b, not aa and bb themselves. You must raise the base to those values (a=10intercepta = 10^{\text{intercept}}, b=10gradientb = 10^{\text{gradient}}) to recover the constants.

Practice

Twelve questions in three tiers. Try each one properly before opening the solution — the solutions show full method, not just answers. Give non-exact answers to 3 s.f.

Warm-up

1 [3 marks]

Solve, giving exact answers:

  1. ex=5e^x = 5
  2. ln⁡x=3\ln x = 3
Show solution

(a) Take ln⁡\ln: x=ln⁡5x = \ln 5.

(b) Raise ee to both sides: x=e3x = e^3.

2 [3 marks]

Solve e3x=12e^{3x} = 12, giving your answer to 3 significant figures.

Show solution
3x=ln⁡12    ⟹    x=ln⁡123=0.828   (3 s.f.)3x = \ln 12 \;\;\Longrightarrow\;\; x = \frac{\ln 12}{3} = 0.828 \;\,(3\text{ s.f.})
3 [2 marks]

The value of a car is modelled by V=12000 e−0.15tV = 12000\,e^{-0.15t} pounds, tt years after purchase. State (a) the purchase value, (b) whether the model is growth or decay.

Show solution

(a) At t=0t = 0: V=12000 e0=£12000V = 12000\,e^0 = \pounds 12000.

(b) k=−0.15<0k = -0.15 < 0, so the value decays.

4 [2 marks]

Simplify (a) ln⁡(e4)\ln(e^4), (b) eln⁡9e^{\ln 9}.

Show solution

(a) ln⁡\ln and ee are inverses: ln⁡(e4)=4\ln(e^4) = 4.

(b) Likewise eln⁡9=9e^{\ln 9} = 9.

Standard

5 [4 marks]

A population of bacteria is modelled by N=400 e0.08tN = 400\,e^{0.08t}, where tt is in hours.

  1. Find NN when t=10t = 10. [2]
  2. Find, to 3 s.f., the time taken for the population to reach 10001000. [2]
Show solution

(a) N=400 e0.8=890N = 400\,e^{0.8} = 890 (3 s.f.).

(b) 400 e0.08t=1000⇒e0.08t=2.5400\,e^{0.08t} = 1000 \Rightarrow e^{0.08t} = 2.5, so

0.08t=ln⁡2.5    ⟹    t=ln⁡2.50.08=11.5   (3 s.f.)0.08t = \ln 2.5 \;\;\Longrightarrow\;\; t = \frac{\ln 2.5}{0.08} = 11.5 \;\,(3\text{ s.f.})
6 [4 marks]

A cup of coffee cools according to T=20+60 e−0.04tT = 20 + 60\,e^{-0.04t}, where TT is in ∘^\circC and tt in minutes.

  1. State the initial temperature. [1]
  2. Find the temperature after 3030 minutes. [1]
  3. Find, to the nearest minute, when the coffee reaches 50∘50^\circC. [2]
Show solution

(a) At t=0t = 0: T=20+60=80∘T = 20 + 60 = 80^\circC.

(b) T=20+60 e−1.2=38.1∘T = 20 + 60\,e^{-1.2} = 38.1^\circC (3 s.f.).

(c) 20+60 e−0.04t=50⇒e−0.04t=3060=1220 + 60\,e^{-0.04t} = 50 \Rightarrow e^{-0.04t} = \tfrac{30}{60} = \tfrac12, so

−0.04t=ln⁡12=−ln⁡2    ⟹    t=ln⁡20.04=17.3…≈17 min-0.04t = \ln\tfrac12 = -\ln 2 \;\;\Longrightarrow\;\; t = \frac{\ln 2}{0.04} = 17.3\ldots \approx 17 \text{ min}
7 [4 marks]

A radioactive isotope decays as m=m0 e−0.05tm = m_0\,e^{-0.05t} (tt in years). Find its half-life, to 3 significant figures.

Show solution

Half-life is when m=12m0m = \tfrac12 m_0:

e−0.05t=12    ⟹    −0.05t=−ln⁡2    ⟹    t=ln⁡20.05=13.9 yearse^{-0.05t} = \tfrac12 \;\;\Longrightarrow\;\; -0.05t = -\ln 2 \;\;\Longrightarrow\;\; t = \frac{\ln 2}{0.05} = 13.9 \text{ years}
8 [4 marks]

Data fits the model y=abxy = ab^x. When log⁡10y\log_{10} y is plotted against xx, a straight line of gradient 0.50.5 and vertical intercept 11 is obtained. Find aa and bb.

Show solution

Comparing with log⁡y=(log⁡b)x+log⁡a\log y = (\log b)x + \log a:

  • log⁡10a=1⇒a=101=10\log_{10} a = 1 \Rightarrow a = 10^1 = 10;
  • log⁡10b=0.5⇒b=100.5=3.16\log_{10} b = 0.5 \Rightarrow b = 10^{0.5} = 3.16 (3 s.f.).

Exam style

9 [5 marks]

The mass of a culture is M=5 e0.6tM = 5\,e^{0.6t} grams, tt hours after the start.

  1. Find the doubling time, to 3 s.f. [3]
  2. Explain why the doubling time does not depend on the starting mass. [2]
Show solution

(a) Doubling means M=2×5=10M = 2 \times 5 = 10:

5 e0.6t=10⇒e0.6t=2⇒t=ln⁡20.6=1.16 hours5\,e^{0.6t} = 10 \Rightarrow e^{0.6t} = 2 \Rightarrow t = \frac{\ln 2}{0.6} = 1.16 \text{ hours}

(b) Setting M=2M0M = 2M_0 gives ekt=2e^{kt} = 2 whatever M0M_0 is — the M0M_0 cancels. So the doubling time ln⁡2k\dfrac{\ln 2}{k} depends only on the rate kk, not the start.

10 [6 marks]

The temperature of a liquid is modelled by θ=75 e−kt+18\theta = 75\,e^{-kt} + 18, where tt is in minutes. After 55 minutes the temperature is 60∘60^\circC.

  1. Find the value of kk, to 3 s.f. [4]
  2. Find the temperature after 1515 minutes. [2]
Show solution

(a) At t=5t = 5, θ=60\theta = 60:

75 e−5k+18=60    ⟹    75 e−5k=42    ⟹    e−5k=0.5675\,e^{-5k} + 18 = 60 \;\;\Longrightarrow\;\; 75\,e^{-5k} = 42 \;\;\Longrightarrow\;\; e^{-5k} = 0.56

Take ln⁡\ln: −5k=ln⁡0.56-5k = \ln 0.56, so

k=−ln⁡0.565=0.116   (3 s.f.)k = -\frac{\ln 0.56}{5} = 0.116 \;\,(3\text{ s.f.})

(b) θ=75 e−0.116×15+18=75 e−1.74+18=31.2∘\theta = 75\,e^{-0.116 \times 15} + 18 = 75\,e^{-1.74} + 18 = 31.2^\circC (3 s.f.).

11 [5 marks]

The table shows values fitting y=abxy = ab^x:

xx112233
yy121224244848
  1. Explain how the table shows b=2b = 2. [2]
  2. Find aa. [3]
Show solution

(a) Each time xx increases by 11, yy multiplies by 22 (12→24→4812 \to 24 \to 48). For y=abxy = ab^x, a unit increase in xx multiplies yy by bb, so b=2b = 2.

(b) Use any data point, say x=1x = 1, y=12y = 12, with b=2b = 2:

12=a×21    ⟹    a=612 = a \times 2^1 \;\;\Longrightarrow\;\; a = 6

So y=6×2xy = 6 \times 2^x.

12 [6 marks]

A quantity is modelled by y=200 ekty = 200\,e^{kt}. It is known that y=260y = 260 when t=4t = 4.

  1. Find kk, to 3 s.f. [3]
  2. Find yy when t=10t = 10, to 3 s.f. [2]
  3. Find, to 3 s.f., the value of tt for which y=500y = 500. [1]
Show solution

(a) 200 e4k=260⇒e4k=1.3200\,e^{4k} = 260 \Rightarrow e^{4k} = 1.3, so

k=ln⁡1.34=0.0656   (3 s.f.)k = \frac{\ln 1.3}{4} = 0.0656 \;\,(3\text{ s.f.})

(b) y=200 e0.0656×10=200 e0.656=385y = 200\,e^{0.0656 \times 10} = 200\,e^{0.656} = 385 (3 s.f.).

(c) 200 ekt=500⇒ekt=2.5200\,e^{kt} = 500 \Rightarrow e^{kt} = 2.5, so t=ln⁡2.50.0656=14.0t = \dfrac{\ln 2.5}{0.0656} = 14.0 (3 s.f.).