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  • Use the exponential growth model in applications, including population growth and compound interest.
  • Explain the concept of doubling time.
  • Use the exponential decay model in applications, including radioactive decay and Newton’s law of cooling.
  • Explain the concept of half-life.

One of the most prevalent applications of exponential functions involves growth and decay models. Exponential growth and decay show up in a host of natural applications. From population growth and continuously compounded interest to radioactive decay and Newton’s law of cooling, exponential functions are ubiquitous in nature. In this section, we examine exponential growth and decay in the context of some of these applications.

Exponential growth model

Many systems exhibit exponential growth. These systems follow a model of the form y = y 0 e k t , where y 0 represents the initial state of the system and k is a positive constant, called the growth constant . Notice that in an exponential growth model, we have

y = k y 0 e k t = k y .

That is, the rate of growth is proportional to the current function value. This is a key feature of exponential growth. [link] involves derivatives and is called a differential equation. We learn more about differential equations in Introduction to Differential Equations .

Rule: exponential growth model

Systems that exhibit exponential growth    increase according to the mathematical model

y = y 0 e k t ,

where y 0 represents the initial state of the system and k > 0 is a constant, called the growth constant .

Population growth is a common example of exponential growth. Consider a population of bacteria, for instance. It seems plausible that the rate of population growth would be proportional to the size of the population. After all, the more bacteria there are to reproduce, the faster the population grows. [link] and [link] represent the growth of a population of bacteria with an initial population of 200 bacteria and a growth constant of 0.02 . Notice that after only 2 hours ( 120 minutes), the population is 10 times its original size!

This figure is a graph. It is the exponential curve for y=200e^0.02t. It is in the first quadrant and an increasing function. It begins on the y-axis.
An example of exponential growth for bacteria.
Exponential growth of a bacterial population
Time (min) Population Size (no. of bacteria)
10 244
20 298
30 364
40 445
50 544
60 664
70 811
80 991
90 1210
100 1478
110 1805
120 2205

Note that we are using a continuous function to model what is inherently discrete behavior. At any given time, the real-world population contains a whole number of bacteria, although the model takes on noninteger values. When using exponential growth models, we must always be careful to interpret the function values in the context of the phenomenon we are modeling.

Population growth

Consider the population of bacteria described earlier. This population grows according to the function f ( t ) = 200 e 0.02 t , where t is measured in minutes. How many bacteria are present in the population after 5 hours ( 300 minutes)? When does the population reach 100,000 bacteria?

We have f ( t ) = 200 e 0.02 t . Then

f ( 300 ) = 200 e 0.02 ( 300 ) 80,686 .

There are 80,686 bacteria in the population after 5 hours.

To find when the population reaches 100,000 bacteria, we solve the equation

100,000 = 200 e 0.02 t 500 = e 0.02 t ln 500 = 0.02 t t = ln 500 0.02 310.73.

The population reaches 100,000 bacteria after 310.73 minutes.

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Source:  OpenStax, Calculus volume 1. OpenStax CNX. Feb 05, 2016 Download for free at http://cnx.org/content/col11964/1.2
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