Summer Undergraduate Research Fellowships

Department of Physics

University of Toronto

SURF: Spectra

Coordinator: David Bailey

Spectrometers are one of the most common and useful scientific instruments. This project is to set-up a new optical spectrometer, improve an existing X-Ray fluorescence spectrometer, create and document methods and procedures, and to develop improved offline Python software for spectrum analysis.

Specific Safety Issues

• Rigorous X-Ray safety procedures must be followed for the XRF spectrometer.
• Care must be taken to ensure the eye-safety of all light sources used (e.g. lasers, UV lamps).
• Optical spectrometer is heavy and delicate.

Optical Spectrometer

The spectrometer may be used for our Helium-Neon Laser and Raman Scattering experiments, and will be helpful for student projects and other experiments such as Fourier-Transform spectroscopy. Spectrum analysis software is useful for many experiments, in addition to the three already mentioned, these potentially include X-Ray Fluorescence, Germanium Gamma Ray Spectrometer, Sonoluminescence, Mossbauer Effect, and Mass Spectrometer.

1. Set up new LEOI-101 Optical Spectrometer on cart with computer.
2. With calibration lamps, test that spectrometer and accompanying software work in both grating and CCD mode. Check wavelength range, wavelength resolution, and sensitivity.
3. Compare new spectrometer with existing, but ancient, spectrometers currently in use.
4. Test capabilities for both emission and absorption spectrum.
5. May need (with help of technologists) to develop methods for getting light from source into spectrometer.

X-Ray Fluorescence

1. Become familiar with existing experiment.
2. Determine optimum settings for X-ray source, detector, software.
3. Devise method for using gold wire as calibration during measurement of unknown samples.
4. Develop Python software for quantitative analysis of elemental composition of samples, correcting for factors such as differential absorption in the sample, air, and detector.

Python Analysis Software

1. Spectral fitting is very common, so first investigate methods and existing open source python software, e.g. PyMCA, PySpecKit.
2. Existing proprietary XRF software provides a benchmark for comparison.
3. Software must work easily on Windows, Mac, and Linux.
4. First goal is offline fitting,e.g. with MatPlotLib graphics.
5. Would be nice to have a Tkinter interface for user selection of Regions of Interest.

Last updated on 28 February 2012