Manama, March 21 (BNA): MIT and the Bahrain Institute for Pearls and Gems (Danat) have established a research collaboration to develop advanced characterization tools to analyze pearl properties and explore techniques to assign unique identifiers to individual pearls.
The three-year project will be led by Associate Professor of Civil and Environmental Engineering Admir Mašić, in collaboration with Fariborz Maseeh Chair of Emerging Technology, Electrical Engineering and Computer Science Professor Vladimir Polović.
The project will develop new material characterization tools and techniques to assign unique identifiers to individual pearls.
“Pearls are very complex and fascinating, wonderfully arranged hierarchical biological materials made up of a wide variety of different species,” says Mašić.
“Working with DANAT provides us with a unique opportunity to apply our lab’s multiscale material characterization tools to identify species-specific pearl fingerprints, while also addressing scientific research questions related to key biomineralization processes that can aid advances in sustainable building materials.”
Like many other gemstones, pearls have been created through scientific experimentation, says Noura Jamsheer, CEO of DANAT.
Gemological laboratories devise scientific testing methods to distinguish natural pearls from all other pearls that exist due to direct or indirect human intervention.
Entitled “Exploring the Nanoworld of Vital Gemstones,” the project will aim to improve the testing and identification process for pearls by identifying precise morphological, structural, optical, and chemical features sufficient to distinguish a pearl’s region of origin, mode of growth, or both.
MIT.nano, MIT’s Open Access Center for Nanoscience and Nanoengineering, will be the organizational home for the project, where Macic and his team will use the facility’s state-of-the-art characterization tools.
In addition to discovering new methodologies for determining the origin of pearls, the project aims to take advantage of machine learning (ML) to automate pearl grading. Furthermore, the researchers will investigate techniques for creating a unique identifier associated with the individual pearl.
The supported initial research project is expected to last three years, with the possibility of continued collaboration based on key findings or building on the success of the project to open up new avenues of research into the structure, properties and growth of pearls.
ZHB