The materials we use are fundamental to our civilization - so much so that epochs of history have been named after them, like the “bronze age” or “iron age”. Over the last century, exotic technologies have been enabled by the discovery of new materials like shape-memory-alloys (ranging in use from medicine to automobiles) and thermoelectrics (ranging in use from wine coolers to spacecraft). Yet as many of these technologies mature, one might wonder what next? Where and how will we find the next game changer? What if you could state your purpose and have an ideal material found for you quickly and cheaply? What if you could take challenges such as finding lightweight but high strength building materials or finding efficient energy storage or generation materials and rather than testing one-at-a-time through thousands of different candidates - incurring the time and expense in fabricating, evaluating, and verifying each one’s properties - you could know what the right handful of materials are ahead of time and get the same results? Material discovery and optimization would cost far less and be much faster!
Material Mind (MM) has built a Discovery Engine using artificial intelligence and machine learning combined with fundamental physics understanding and modelling. It comes from the founders’ realization that certain physical properties can be predicted from correlations of patterns in the electronic, phononic, magnonic, and crystal structures of a material. Dr. Mazhar Ali laid the groundwork for this idea in his academic research, linking fundamental physics to certain key features in these structures, resulting in a new way to predict and identify materials for Spintronics. Since then, MM has gathered more than 90,000 structures for more than 60,000 materials into our database on which we carry out our analyses allowing us to find the right materials for a variety of applications. Every day we expand our database and add capability to solve technology problems.

Material Mind

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Material Mind

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