1. Laser light stimulates vibration, causing some energy to be absorbed and the rest to be scattered as a slightly red-shifted photon. Raman Microspectroscopic Imaging

2. Collect full Raman spectra at many points on a grid, with the goal of determining the distribution of all mineral components simultaneously.

3. The final dataset is an information-rich hyperspectral image cube. Every pixel has a corresponding spectrum, and every Raman shift has an intensity map.

4. The current situation: Most research only uses the intensity in a few discrete bands to map components, which fails to take advantage of the richness of the dataset (and doesn’t address the detection and identification of unknown components).

5. Decomposing with an “unfolded” dataset: 3520 grid points 1024 wavelengths X (centered/scaled) PCA 3520 grid points N significant components Scores 1024 wavelengths Loadings

6. N significant components 1024 wavelengths Loadings Varimax rotation N significant components 1024 wavelengths VM Loadings N significant components 1024 wavelengths VM Loadings 3520 grid points 1024 wavelengths Least Squares (X T X) -1 X T Y 3520 grid points N significant components VM Scores Varimax rotation:

7. 3520 grid points N significant components Scores 1024 wavelengths Loadings N significant components Set negative loading values to 0, Calculate scores by least squares Set negative scores to 0, Calculate loadings by least squares Multivariate curve resolution

8. PC-1 PC-2 Principle component analysis highlights the spatial paterns of variation but fails to provide meaningful loading spectra that can be interpreted/identified.

9. Varimax rotation helps acquire meaningful spectral components

10. The crucial question: how many components? -How many true chemical components exist? -How many components are needed to model the dataset?

11. VM-3 VM-4 VM-2 16 Varimax components: -Xenotime (YPO 4 ) -Barite -Hematite -Apatite -Eu 3+ luminescence in apatite -3 components of carbonaceous fluorescent spectrum -2 baseline subtraction artifacts -2 Hematite crystalinity effects -2 barite orientation effects -1 unknown minor component spatially associated with xenotime.

12. VM-7 components: Apatite with Eu luminescence Xenotime Barite Hematite Carbonaceous fluorescence 2 Eu3+ luminescence components MCR-7 components: Apatite with Eu luminescence Barite Apatite with Eu luminescence Carbonaceous fluorescence Xenotime Hematite

13. VM-7 Apatite/Eu 3+ luminescence spectraMCR-7 Apatite/Eu 3+ luminescence spectra

14. MCR-7VM-7 Mineral distribution maps inferred from scores are very similar with some differences in relative magnitude of normalized scores—the same geological conclusions would be drawn from the two maps.

15. Conclusions Varimax rotation elucidated the same general components as MCR. Varimax seemed less sensitive to the choice of the number of components (less likely to miss or fail to separate components). Varimax components were more noisy, were decomposed to a greater extent, and contained residual negative values. Each of these factors impacts the ability to identify unknowns. Varimax models had lower residuals (and less residual structure) than MCR models with the same number of components.