Describe 2 methods using graphical analysis to determine the half-life of a radioactive isotope; basis ?
Answers
Answer:
How do you read a decay graph?
If a scientist comes across a funky new radioactive rock while exploring an excavation site, she can identify what radioactive isotope is present in it by measuring the the decay constant of the isotopes inside the rock.
An exponential decay graph like the one shown above can be generated by taking a sample of an unknown radioactive isotope and repeatedly measuring the total mass of radioactive material within it. At the start of the experiment, a piece of the sample is run through a mass spectrometer or similar device that can identify the relative mass of various isotopes currently present. Then, at several later times, the procedure is repeated and the new fraction of various isotopes is recorded.
One sample of rock is shown decaying and the level of decay is corresponded to points on a decay graph.
What is a half-life?
Half-life is defined as the amount of time it takes for half of an isotope to change into another isotope.
Like the decay constant, the half-life tells us everything we need to know to guess what kind of isotope we might have. It even turns out that the two numbers are equivalent if you correctly solve the radioactive decay equation. This means that, like the decay constant, the half-life gives an estimate of the stability of a particular radioactive substance, and it can thus be used to identify unknown isotopes. The primary reason that scientists use half-lives instead of decay constants is because half-lives have a more intuitive immediate meaning: if a scientist collects 20 kg of a radioactive isotope with a half-life of 30 min, and she leaves her lab to meet with a grad student for 30 minutes, when she comes back she will have 10 kg of the isotope remaining. If she then goes to check on another experiment for 30 minutes, when she gets back she will have 5 kg remaining… in other words, for every 30 minutes that passes, she’ll lose half of her sample!
