Building Open Knowledge Graph for Metal-Organic Frameworks (MOF-KG): Challenges and Case Studies

• URL: http://arxiv.org/abs/2207.04502v2
• Date: Wed, 29 Nov 2023 17:20:33 GMT
• Title: Building Open Knowledge Graph for Metal-Organic Frameworks (MOF-KG): Challenges and Case Studies
• Authors: Yuan An, Jane Greenberg, Xintong Zhao, Xiaohua Hu, Scott McCLellan, Alex Kalinowski, Fernando J. Uribe-Romo, Kyle Langlois, Jacob Furst, Diego A. G\'omez-Gualdr\'on, Fernando Fajardo-Rojas, Katherine Ardila
• Abstract summary: Metal-Organic Frameworks (MOFs) have great potential to revolutionize applications such as gas storage, molecular separations, chemical sensing, crystalline and drug delivery. The Cambridge Structural Database (CSD) reports 10,636 synthesized MOF crystals which in addition contains ca. 114,373 MOF-like structures. In this demo paper, we describe our effort on leveraging knowledge graph methods to facilitate MOF prediction, discovery, and synthesis.
• Score: 63.61566811532431
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Metal-Organic Frameworks (MOFs) are a class of modular, porous crystalline materials that have great potential to revolutionize applications such as gas storage, molecular separations, chemical sensing, catalysis, and drug delivery. The Cambridge Structural Database (CSD) reports 10,636 synthesized MOF crystals which in addition contains ca. 114,373 MOF-like structures. The sheer number of synthesized (plus potentially synthesizable) MOF structures requires researchers pursue computational techniques to screen and isolate MOF candidates. In this demo paper, we describe our effort on leveraging knowledge graph methods to facilitate MOF prediction, discovery, and synthesis. We present challenges and case studies about (1) construction of a MOF knowledge graph (MOF-KG) from structured and unstructured sources and (2) leveraging the MOF-KG for discovery of new or missing knowledge.

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