NOMAD is driving a new way of understanding data in materials science, as NOMAD Coordinator Matthias Scheffler told key representatives at BASF, the largest chemical company in the world with a global presence in more than 80 countries worldwide.
Matthias was invited by Ansgar Schäfer of our Industry Advisory Committee to talk about how NOMAD is rethinking the pursuit of understanding through data-driven materials science. In new and exciting ways, high-performance computing is being applied to the discovery of:
Such discoveries are immensely exciting and hugely important economically for industry, but are challenging due to the immense amount of data available. In a presentation highlighting the work of NOMAD, Matthias described how compressed sensing and machine learning can be used to spot yet unseen patterns or structures in massive collections of data by identifying the key atomic and collective physical actuators. The results of this Big-Data analysis are maps of materials, where different regions correspond to materials with different properties.
Concrete, industrially relevant examples were presented, including methods to describe and predict 2D topological insulators, classify metals/insulators classification, model catalytic CO2 activation, and more.
Check out the NOMAD Success Stories on Uncovering Structure-Property Relationships of Materials by Subgroup Discovery, CO2 Conversion to Fuels and Other Useful Chemicals and many more to learn more about the work of NOMAD in this exciting domain.
NOMAD - modelling catalytic CO2 activation