5 November 2015
On Wednesday, November 4th Materialytics presented its latest diamond provenance results at the GSA 2015 convention in Baltimore, Maryland.
"The report is unique because all of the 330 test samples used are of gem quality, making this diamond provenance study relevant not only to geologists but also to consumers by providing a scientific verification in support of conflict-free trade," said McManus.
A set of 30 cut diamonds from each of ten controlled localities and one set of 30 synthetic diamonds were analyzed using Materialytics Analysis. The sample set (330 total diamonds) includes both kimberlite and placer diamonds from five countries and five different cratons. Materialytics Analysis determined the correct provenance with an average accuracy rate of 98%.
Unlike other testing processes, Materialytics Analysis determines provenance of cut diamonds from information in the stone itself. Other provenance determinations rely on: 1) gemological and mineralogical features of stones, such as spectroscopic measurements, geochemistry, and inclusions, and 2) certification and tracking of individual stones through the Kimberly Process Certificate Scheme. Unfortunately, during cutting and polishing, many gemological features are obliterated and tracking individual stones through the chain of custody can be difficult.
Materialytics uses Laser Induced Sectroscopy to acquire the atomic emission spectra released from a material during laser ablation. The spectra contain information from nearly every element in the periodic table, and thus are unique chemical, or quantagenetic, signatures of the material. Spectra are analyzed using a Bayesian statistical method that compares groups of samples defined by the reported locations of the stones to clusters of samples defined by spectral similarity. Ideally, each spectral cluster coincides with a group of stones. The spectrum of each sample is compared to a set of reference spectra from each group to determine the probable provenance of the sample.
In our diamond study the correlation between groups and clusters was excellent, with average accuracy of 98%, suggesting that diamonds from each location are spectrally similar to each other and distinct from those from other locations. This is true even for diamonds from kimberlites in close proximity to each other. Synthetic diamonds are easily distinguished from natural diamonds (100% success). Some groups of diamonds in the study are more heterogeneous than others. For instance, a placer group has five recognizable spectrally-defined sub-clusters. This work demonstrates that diamond provenance can be determined at a high level of confidence on individual cut gemstones.
For more information on this study or a copy of our presentation poster please email your request to Contact@Materialytics.com