*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
Georgia Tech - MRSEC | Posted: July 1, 2013
Summary Sentence:
A method is proposed to extract pure Raman spectrum of epitaxial graphene on SiC by using a Non-negative Matrix Factorization
Full Summary:
A method is proposed to extract pure Raman spectrum of epitaxial graphene on SiC by using a Non-negative Matrix Factorization. It overcomes problems of negative spectral intensity and poorly resolved spectra resulting from a simple subtraction of a SiC background from the experimental data. We also show that the method is similar to deconvolution, for spectra composed of multiple sub- micrometer areas, with the advantage that no prior information on the impulse response functions is needed. We have used this property to characterize the Raman laser beam. The method capability in efficient data smoothing is also demonstrated
A method to extract pure Raman spectrum of epitaxial graphene on SiCAuthors: Jan Kunc, Yike Hu, James Palmer, Claire Berger, Walter A. de Heer
A method is proposed to extract pure Raman spectrum of epitaxial graphene on SiC by using a Non-negative Matrix Factorization. It overcomes problems of negative spectral intensity and poorly resolved spectra resulting from a simple subtraction of a SiC background from the experimental data. We also show that the method is similar to deconvolution, for spectra composed of multiple sub- micrometer areas, with the advantage that no prior information on the impulse response functions is needed. We have used this property to characterize the Raman laser beam. The method capability in efficient data smoothing is also demonstrated
