As this was a short week due to the holiday, the SCIART chemistry group focused on training with three non-destructive analytical techniques using bones and antlers in preparation for our ivory tests.  We looked at Direct Sample Analysis (DSA), Raman spectroscopy and scanning electron microscopy (SEM). It is important, especially for our project to first explore non-destructive techniques before using destructive techniques due to the small size of samples available, as well as explore all avenues of analysis.  

Two techniques we looked at were DSA and Raman. DSA is an ambient mass spectrometry and Raman is an optical spectroscopy using a laser; both are helpful when determining the structure of the material. Under the supervision of Ian Shaffer from the Molecular Characterization and Analysis Complex (MCAC) at UMBC, we used DSA to analyze some of our bone and antler samples. As our samples are similar in composition, we hoped to find similar peaks in order to do a comparative analysis. We decided that, because DSA gave us only partial information, we are more inclined to use Raman: there is already literature discussing its use with ivory. As we already had read up on the peaks expected in similar samples, this gave us a good baseline to start from. 

During our visit to the New York Metropolitan Museum of Art last week, it was suggested we take a look at SEM. Dr. Takacs from the Physics department was able to assist us in analyzing a few of our samples. Using SEM we were able to look at the surface of the samples enabling us to look for patterns and structures of the cells. This would be beneficial in cross comparison when looking for differences or similarities between species, though only useful if we had access to a library to confirm our findings. 

To wrap up the week, we met with our supervisor, Daniel Rowlands, to discuss how we would like to proceed. Looking at the different non-destructive techniques so far, we are interested in exploring more with Raman spectroscopy, as it has been used prior. We are also intrigued by the use of DSA as it hasn’t been used before. We’re not opposed to using SEM, though we think it is not as applicable to our samples as particular features are more difficult to identify.