title: Novel Approach for Clustering Zeolite Crystal Structures.
abstract: Informatics approaches play an increasingly important role in the design of new materials. In this work we apply unsupervised statistical learning for identifying four framework-type attractors of zeolite crystals in which several of the zeolite framework types are grouped together. Zeolites belonging to these super-classes manifest important topological, chemical and physical similarities. The zeolites form clusters located around four core framework types: LTA, FAU, MFI and the combination of EDI, HEU, LTL and LAU. Clustering is performed in a 9-dimensional space of attributes that reflect topological, chemical and physical properties for each individual zeolite crystalline structure. The implemented machine learning approach relies on hierarchical top-down clustering approach and the expectation maximization method. The model is trained and tested on ten partially independent data sets from the FIZ/NIST Inorganic Crystal Structure Database.
authors.affiliation: Computational Materials Science Center, George Mason University, MSN 6A2, Fairfax, VA 22030, USA phone: 011-703-9931988 fax /011-703-9939330.
authors.forename: M
authors.initials: M
authors.lastname: Lach-Hab
authors.affiliation: Computational Materials Science Center, George Mason University, MSN 6A2, Fairfax, VA 22030, USA phone: 011-703-9931988 fax /011-703-9939330.
authors.forename: S
authors.initials: S
authors.lastname: Yang
authors.affiliation: Computational Materials Science Center, George Mason University, MSN 6A2, Fairfax, VA 22030, USA phone: 011-703-9931988 fax /011-703-9939330.|Department of Bioinformatics and Computational Biology George Mason University, MSN 5B3, Manassas, VA 20110, USA.
authors.forename: I I
authors.initials: II
authors.lastname: Vaisman
authors.affiliation: Computational Materials Science Center, George Mason University, MSN 6A2, Fairfax, VA 22030, USA phone: 011-703-9931988 fax /011-703-9939330. blaisten@gmu.edu.|Department of Computational and Data Sciences, George Mason University, MSN 6A2, Fairfax, VA 22030, USA. blaisten@gmu.edu.
authors.forename: E
authors.initials: E
authors.lastname: Blaisten-Barojas
keywords: Clustering; Computational chemistry; Crystal structure; Framework type; Unsupervised learning; Zeolites