Technical Report 292, c4e-Preprint Series, Cambridge

Authors: Aleksandar Kondinski, Angiras Menon, Daniel Nurkowski, Feroz Farazi, Sebastian Mosbach, Jethro Akroyd, and Markus Kraft*

Reference: Technical Report 292, c4e-Preprint Series, Cambridge, 2022

Associated Themes:
 

• Conceptualisation of metal-organic polyhedra (MOPs) by assembly models.
• Curation of MOPs and building unit data for knowledge graph development.
• Ontological representation of MOPs and their related concepts.
• Knowledge-based rational derivation of new MOP designs by a software agent.
• Mapping of the immediate MOP chemical space for future studies.

Metal-organic polyhedra (MOPs) are hybrid organic-inorganic nanomolecules, whose rational design depends on harmonious consideration of chemical complementarity and spatial compatibility between two or more types of chemical building units (CBUs). In this work, we apply knowledge engineering technology to automate the derivation of MOP formulations based on existing knowledge. For this purpose we have: i) curated relevant MOP and CBU data; ii) developed an assembly model concept that embeds rules in the MOP construction; iii) developed an OntoMOPs ontology that defines MOPs and their key properties; iv) input agents that populate The World Avatar (TWA) knowledge graph; and v) agents that, using information from TWA, derive a list of new constructible MOPs. Our result provides rapid and automated instantiation of MOPs in TWA and unveils the immediate chemical space of known MOPs, thus shedding light on new MOP targets for future investigations.

PDF (10.8 MB)