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A neural network approach to prediction of glass transition temperature of polymers

Abstract:

Polymeric materials are finding increasing application in commercial optical communication systems. Taking advantage of techniques from the field of artificial intelligence, the goal of our research is to construct systems that can computationally design polymer formulations, including polymer optical fibers, with specified desirable consumer characteristics. Through the use of an extensive structure-property correlation database, properties of polymers can be predicted by an artificial netwo...

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Publication status:
Published

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Publisher copy:
10.1002/int.20256

Authors


Sztandera, L More by this author
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Institution:
University of Oxford
Department:
Oxford, MPLS, Chemistry, Physical and Theoretical Chem
Journal:
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
Volume:
23
Issue:
1
Pages:
22-32
Publication date:
2008-01-05
DOI:
EISSN:
1098-111X
ISSN:
0884-8173
URN:
uuid:5f3b9a0c-9c3a-444e-83f6-b59c3d3a9ea9
Source identifiers:
40560
Local pid:
pubs:40560
Language:
English

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