# UC Berkeley Physics 111 Semiconductor Circuits Lab Experiments

Publish Date: Jul 31, 2017 | 5 Ratings | 3.40 out of 5 | Print

## Overview

The Basic Semiconductor Circuits Labs developed at UC Berkeley contain an introduction to signal measurement, processing, and graphical programming in the LabVIEW environment. Concepts including data acquisition, noise reduction, and control systems are also covered with an emphasis on virtual instrumentation. Throughout the labs, interactive LabVIEW applications (VIs) allow the reader to experimentally gain familiarity with key concepts.

Link to the Full Physics 111 Laboratory Manual by Dr. Joel Fajans, Dr. James L Siegrist, & Donald Orlando

### 1. LabVIEW Programming

For many decades, it was sufficient to read the signal on a meter, or display the signal on an oscilloscope. Sometimes hybrid methods were used; for my Ph.D. thesis, I took about ten thousand photographs of oscilloscope screens, and analyzed the information on the photos with calipers. Nowadays, most data is collected by computer. Computers have become astonishingly powerful, and data acquisition hardware has become cheap, fast and accurate.

### 2. Analog to Digital and Digital to Analog Conversion

Our world is largely analog and continuous; quantities vary smoothly. There are, of course, intrinsically discrete exceptions to this rule, like the quantization of charge or the quantum hall effect. But even measurements of discrete phenomena tend to be confounded by noise and produce continuous data. Internally, however, modern computers deal only with discrete quantities; specifically, they deal only with quantities that take on only two values: on or off.

This so-called digital representation of information has many advantages over analog representations, most importantly that digital information is relatively immune to noise. If a 0, or off state, is represented by a voltage near 0, and a 1, or on state is represented by a voltage near 4 (a scheme used by a common family of digital devices called TTL logic), then noise is unlikely to cause a fluctuation great enough to confuse the two.

### 3. Signal Processing and Control

Most real world signals are contaminated by noise. A frequently used figure-of-merit is the signal-to-noise ratio, or Sn. The Sn value for clean signals is much larger than one; as Sn approaches one the signal fades into the noise. Fortunately, we can often extract the signal from the noise. There are three primary techniques for recovering the signal:

1. Bandwidth narrowing
2. Averaging
3. Pattern matching

There are many ways to implement each of these techniques; we will explore the most important.

### 4. Final Project

In this last lab, you will design and build a final project of your choice. Several suggested projects are outlined, but you may also dream up your own project. Suggestions for building projects using LabVIEW and electronic circuits learned:

1. For the digitally minded: Measure the acceleration of gravity with LabVIEW as an interface Panel.
2. For the analog minded: Build a circuit which transmits an audio signal over a light beam and then controlled by LabVIEW display Panel.

Look on the Internet for ideas about your final project, but DO NOT copy the circuits. Get ideas from them, not complete diagrams. Very little of the circuits on the Internet work properly if at all and you’ll waste your time trouble shooting these circuits. However, you will need some time to trouble shoot your circuits and program. You should use LabVIEW, ADC, DAC, and electronics you have learned in the BSC Lab.

Acknowledgment and Disclaimer

This material is based upon work supported by the National Science Foundation under Grant No. 0411367. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).

### Ratings

Rate this document