Both my curriculum vitae (PDF) and resume (TXT,PDF) are available for downloading.
|I'm designing several Matlab-based programs with graphical user interfaces (GUIs) that simulate possible spectra in frequency-scanned multi-dimensional vibrational spectroscopy. |
These programs feature the ability to simulate spectra while including the effects of:
Created using one of these programs, example images here show changes that two nearby peaks make with each other based on a change in sign of a molecular parameter. The first is a typical fit, the second changes the sign of the product of transition dipoles of one of the peaks, the third changes the sign of the correlation factor of the top peak, and the fourth changes the correlation factor sign of the bottom peak (the diagonal is a reference line...the two peaks are best noticed in the last of the four images).
Two technical problems are currently preventing it from completion. First is in the proper treatment of the final discrete Fourier transform along a monochromator axis (whether to take the left hand side or right hand side of the final transform, or something else entirely). Second involves whether there is a "good enough" reason to include the imaginary terms to fluctuation correlation functions for this room-temperature, typical liquid solvent simulation code.
Ultimately, I intend to make this page be the repository of these programs (rather than to submit them to Matlab) as well as provide some help in getting them running. If you are interested, please feel free to contact me to find out the current state of the program.
There is a great deal in commone with multi-dimensional optical spectroscopies and more well known NMR methods. However (in my opinion), there always seems to be just enough difference not to make it possible for conversions between them.
The two major purposes these modeling programs serve in the interest of multi-dimensional spectroscopy is in verifying the peaks are real (not an artifact of other interfering phenomena) and in understanding how nearby peaks interact with one another to see if the multi-dimensional methods can determine certain factors that the standard methods cannot.
The MEYER Home Page, ©2010. Updated: June 25, 2010.