Integrated Computational Materials, Process and Product Engineering – IC-MPPE 2022

Machine learning (ML) has become a standard tool for accelerating innovation in the materials industry. A particularly well-suited ML application is materials design, wherein a user specifies a number of target properties and constraints (e.g., cost, manufacturability, etc.), and then uses ML to identify materials candidates most likely to meet those requirements. However, a number of key challenges must be overcome in order to realize the benefits of ML in materials design. In this talk, I will describe Citrine’s platform approach to these challenges, and some materials-specific ML method development results.