TRI Authors: Muratahan Aykol, Joseph Montoya, Jens Hummelshøj
All Authors: Roni Choudhury, Muratahan Aykol, Samuel Gratzl, Joseph Montoya, Jens Hummelshøj
Materials science research deals primarily with understanding the relationship between the structure and properties of materials. With recent advances in computational power and automation of simulation techniques, material structure and property databases have emerged (Curtarolo et al., 2012; Jain et al., 2013; Kirklin et al., 2015), allowing a more data-driven approach to carrying out materials research. Recent studies have demonstrated that representing these databases as material networks can enable extraction of new materials knowledge (Hegde, Aykol, Kirklin, & Wolverton, 2018; Isayev et al., 2015) or help tackle challenges like predictive synthesis (Aykol, Hegde, et al., 2019) that require relational information between materials. Materials databases have become very popular because they enable their users to do rapid prototyping by searching near globally for figures of merit for their target application. However, both scientists and engineers have little in the way of visualization of aggregates from these databases, that is, intuitive layouts that help understand which materials are related and how they are related. The need for a tool that does this is particularly crucial in materials science because properties like phase stability and crystal structure similarity are themselves functions of a material dataset, rather than of individual materials. Read More
Citation: Choudhury, Roni, Muratahan Aykol, Samuel Gratzl, Joseph Montoya, and Jens Hummelshøj. "MaterialNet: A web-based graph explorer for materials science data." Journal of Open Source Software 5, no. 47 (2020): 2105.