(218c) Cript: A Scalable Polymer Material Data Structure

Having accessible well-structured data is the foundation of cheminformatics. The complexity of polymer structures poses significant challenges in the formation of databases as there is no single representation that can capture the full molecular detail of a polymer material. More specifically, polymers are large stochastic molecules with distributions in chain length, composition, and topology. Additionally, data collection methods are highly variable, typically provide relative structural information (ex. molecular weight relative to a polystyrene standard), and/or use models which require expert knowledge to put into context. In some cases, experimentally obtaining structural information is impossible, and information from prior processing steps is needed. To complicate matters further, polymers can assemble into a wide range of morphologies through phenomena like phase segregation and crystallization. The formation of these morphologies can be highly influenced by the processing condition under which the material was made. Ultimately, data sets that do not completely capture all the relevant polymer, process, and characterization information pose challenges for advancing data-driven research in the polymer field.

Here, we discuss the development and deployment of CRIPT to the community. CRIPT is an open-source community driven digital polymer data ecosystem. At the core of CRIPT is universal data model that provides a unique graph-based representation which enables the full scope of polymer data to be captured and organized in an intuitive manner. This includes experimental data such as synthesis, material processing, chemical characterization, and physical characterization, as well as atomistic simulation data. To support the data model, we have launched a website and python API to enable everyone, from chemists to data scientists, to add and retrieve data in an efficient manner. This seamless access to polymer data will enable solutions which otherwise go unseen to be a simple search away which will lead to the ability to develop better materials faster. Overall, CRIPT seeks to accelerate the development of new innovations and enable the rapid sharing of data across research teams.