arXiv Open Access 2022

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

Yuan An Jane Greenberg Xintong Zhao Xiaohua Hu Scott McCLellan +7 lainnya

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Abstrak

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.

Topik & Kata Kunci

cs.AI

Penulis (12)

Yuan An

Jane Greenberg

Xintong Zhao

Xiaohua Hu

Scott McCLellan

Alex Kalinowski

Fernando J. Uribe-Romo

Kyle Langlois

Jacob Furst

Diego A. Gómez-Gualdrón

Fernando Fajardo-Rojas

Katherine Ardila

Format Sitasi

APA MLA BibTeX

An, Y., Greenberg, J., Zhao, X., Hu, X., McCLellan, S., Kalinowski, A. et al. (2022). Building Open Knowledge Graph for Metal-Organic Frameworks (MOF-KG): Challenges and Case Studies. https://arxiv.org/abs/2207.04502

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Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓