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Volumn 113, Issue 52, 2009, Pages 21721-21725

Identifying zeolite frameworks with a machine learning approach

Author keywords

[No Author keywords available]

Indexed keywords

COORDINATION SEQUENCE; CRYSTALLOGRAPHIC STRUCTURE; FEATURE VECTORS; FRAMEWORK STRUCTURES; KNOWLEDGE-BASED APPROACH; MACHINE-LEARNING; MICROPOROUS; PHYSICAL AND CHEMICAL PROPERTIES; TOPOLOGICAL DESCRIPTORS; VERTEX SYMBOL; ZEOLITE CRYSTALS;

EID: 73849134872     PISSN: 19327447     EISSN: 19327455     Source Type: Journal    
DOI: 10.1021/jp907017u     Document Type: Article
Times cited : (41)

References (34)
  • 4
    • 73849133337 scopus 로고    scopus 로고
    • IZA-SC database of ideal zeolite structures
    • IZA-SC database of ideal zeolite structures. http://www.iza-structure. org/databases, 2009.
    • (2009)
  • 16
  • 24
    • 73849152185 scopus 로고    scopus 로고
    • Lach-hab, M.; Yang, S.; Vaisman, I. I.; Blaisten-Barojas, E. Assignment of Framework Types to the Zeolite Crystals in the Inorganic Crystal Structure Database. arXiv:0904.2597V1. http://arxiv.org/0904.2597 (2009).
    • Lach-hab, M.; Yang, S.; Vaisman, I. I.; Blaisten-Barojas, E. Assignment of Framework Types to the Zeolite Crystals in the Inorganic Crystal Structure Database. arXiv:0904.2597V1. http://arxiv.org/0904.2597 (2009).
  • 29
    • 73849145124 scopus 로고    scopus 로고
    • The R project for statistical computing version 2.5.0, 2007
    • The R project for statistical computing version 2.5.0, http://www.r-project.org (2007).


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.