KIT | KIT-Bibliothek | Impressum | Datenschutz

A Social Network-Guided Approach to Machine Learning for Metal-Organic Framework Property Prediction

Jalali, Mehrdad ORCID iD icon 1; Wonanke, A. D. Dinga 1; Woll, Christof 1
1 Institut für Funktionelle Grenzflächen (IFG), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

The number of new materials and applications of these materials is experiencing rapid growth. ‎Today, increased computational power and the established use of automated machine learning ‎approaches make data science tools available, which provide an overview of the chemical space, ‎support the choice of appropriate materials, and predict specific properties of materials for the ‎desired application. Among the different data science tools, graph theory approaches, where data ‎generated from numerous real-world applications are represented as a graph (network) of ‎connected objects, has been widely used in a variety of scientific fields such as social sciences, ‎health informatics, biological sciences, agricultural sciences, and economics. In this work, we ‎describe applying a particular graph theory approach, social network analysis (SNA), to the metal-organic framework (MOF). To demonstrate MOF materials, we construct a social network called ‎MOFSocialNet from geometrical MOFs descriptors in the CoRE-MOFs database. The MOFSocialNet ‎is an undirected, weighted, and heterogeneous social network; following the construction of this ‎graph, a set of social network analysis processes is conducted to extract valuable knowledge from ‎the MOFs data using graph machine learning algorithms. ... mehr


Volltext §
DOI: 10.5445/IR/1000162803
Veröffentlicht am 05.10.2023
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Funktionelle Grenzflächen (IFG)
Publikationstyp Poster
Publikationsdatum 25.09.2023
Sprache Englisch
Identifikator KITopen-ID: 1000162803
HGF-Programm 43.33.11 (POF IV, LK 01) Adaptive and Bioinstructive Materials Systems
Veranstaltung 5th European Conference on Metal Organic Frameworks and Porous Polymers (EuroMOF 2023), Granada, Spanien, 24.09.2023 – 27.09.2023
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
KITopen Landing Page