Polymeric materials are integral components of nearly every aspect of modern life. Today, polymer scientists and engineers devote significant resources to the design and development of these materials to meet growing societal needs. However, developing cheminformatic solutions for polymers has been difficult since they are large stochastic molecules with hierarchical structures spanning multiple length scales from chemical bonds to large molecular assemblies. Here we present the design for a general material data model that underpins the Community Resource for Innovation in Polymer Technology (CRIPT) data ecosystem. Among the key challenges that the data model addresses are the high complexity in defining a polymer structure and the intricacies involved with characterizing material properties. The core design of the data model is graph-based which provides flexibility, robustness, and scalability to support the community-driven mission. This approach to structuring material data provides the key advancements that the community needs to bring cheminformatics to polymer science and accelerate the development of new materials.
main supporting information
Contains a detailed discussion for each node, sub-object, and additional examples.