AI3SD Video: Automated Rational Design of Metal-Organic Polyhedra
AI3SD Video: Automated Rational Design of Metal-Organic Polyhedra
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) software tools that populate the knowledge graph; and v) algorithm that using information from the knowledge graph derive a list of new constructible MOPs. Our result provides rapid and automated instantiation of MOPs in the knowledge graph, unveils the immediate chemical space of known MOPs, and sheds light on new MOP targets for future investigations.
Kondinkski, Aleksandar
1267748f-6bd5-467b-a19f-533832f67607
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
2 March 2022
Kondinkski, Aleksandar
1267748f-6bd5-467b-a19f-533832f67607
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Kondinkski, Aleksandar
(2022)
AI3SD Video: Automated Rational Design of Metal-Organic Polyhedra.
Frey, Jeremy G., Kanza, Samantha and Niranjan, Mahesan
(eds.)
AI4SD Network+ Conference, Chilworth Manor , Southampton, United Kingdom.
01 - 03 Mar 2022.
(doi:10.5258/SOTON/AI3SD0197).
Record type:
Conference or Workshop Item
(Other)
Abstract
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) software tools that populate the knowledge graph; and v) algorithm that using information from the knowledge graph derive a list of new constructible MOPs. Our result provides rapid and automated instantiation of MOPs in the knowledge graph, unveils the immediate chemical space of known MOPs, and sheds light on new MOP targets for future investigations.
Video
ai4sd_march_2022_day_2_AleksandarKondinski
- Version of Record
More information
Published date: 2 March 2022
Additional Information:
Aleksandar Kondinski is a Feodor Lynen Fellow at the University of Cambridge. As a member of the CoMo Group (Prof. Markus Kraft), he is developing knowledge engineering tools that emulate the decision-making process of the inorganic chemist. Aleksandar studied chemistry at Jacobs University Bremen. During his graduate studies at the same university, he worked at the interface of experimental and theoretical polyoxometalate chemistry. Following his graduation in 2016, he has completed two postdoctoral fellowships at RWTH Aachen and KU Leuven dealing with magnetic and biofunctional inorganics respectively.
Venue - Dates:
AI4SD Network+ Conference, Chilworth Manor , Southampton, United Kingdom, 2022-03-01 - 2022-03-03
Identifiers
Local EPrints ID: 468644
URI: http://eprints.soton.ac.uk/id/eprint/468644
PURE UUID: 85636ef8-c070-40b0-b20a-628846eff852
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Date deposited: 19 Aug 2022 16:36
Last modified: 17 Mar 2024 03:51
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Author:
Aleksandar Kondinkski
Editor:
Mahesan Niranjan
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