Virtual Photoelectric Lab
This activity has benefited from input through a review and suggestion process.
This activity has benefited from input from faculty educators beyond the author through a review and suggestion process as a part of an activity development workshop. Workshop participants were provided with a set of criteria against which they evaluated each others' activities. For information about the criteria used for this review, see http://serc.carleton.edu/sp/compadre/devactivities/reviewcriteria.html.
This page first made public: Oct 15, 2010
This material is replicated on a number of sites as part of the SERC Pedagogic Service Project
In this activity, students measure the relationship between kinetic energy of photoelectrons and the frequency of the incident light. The kinetic energy is measured in the usual way by determining the stopping potential for each frequency. In this version, a Java applet that simulates the experimental set-up is used. The simulation shows the behavior of an electron when struck by a photon. The stopping potential is determined by observing the behavior of the electron in response to a counter voltage applied across the emitter and collector in the phototube. The stopping potential is the voltage that allows the electron to cross the gap and just touch the collector before falling back.
Context for Use
Time required: approx 50 min
Special equipment: Computer with Internet access and browser that supports Java.
Pre-requisite knowledge: Students should be familiar with the problems inherent in the classical model of the photoelectric effect and the basic features of Einstein's quantum model.
Teaching Notes and Tips
If possible, instructors should demonstrate the simulation prior to doing the lab. This should include the method used to find the stopping potential (see "Quick Method for Finding Stopping Potential" in the instructions.
Data analysis is done graphically. Graphs can be done by hand, however, computer generated graphs (with slope and intercept determined by linear regression) should be the preferred method, particularly in a distance learning situation.
Standard spreadsheet software (e.g. Excel) is probably best for this; however, a link to a Java applet for this purpose is provided in the instructions. For the latter, students will need to do a screen capture to save the graph