Tracking Chemical Processing Pathways in Combinatorial Polymer Libraries via Data Mining

被引:23
作者
Broderick, Scott R. [1 ,2 ]
Nowers, Joseph R. [3 ,4 ]
Narasimhan, Balaji [2 ,3 ]
Rajan, Krishna [1 ,2 ]
机构
[1] Iowa State Univ, Dept Mat Sci & Engn, Ames, IA 50011 USA
[2] Iowa State Univ, Inst Combinatoria Discovery, Ames, IA 50011 USA
[3] Iowa State Univ, Dept Chem & Biol Engn, Ames, IA 50011 USA
[4] 3M Corp, Ames, IA 50010 USA
来源
JOURNAL OF COMBINATORIAL CHEMISTRY | 2010年 / 12卷 / 02期
基金
美国国家科学基金会;
关键词
STRUCTURE-PROPERTY RELATIONSHIPS; PRINCIPAL COMPONENT ANALYSIS; MULTIVARIATE; NETWORKS; INFORMATICS; KINETICS; SEQUENCE; DESIGN; MODELS;
D O I
10.1021/cc900145d
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
Changes in the molecular structure and composition of interpenetrating polymer networks (IPNs) call be used to tailor their properties. While the properties of IPNs are typically different than polymer blends, a clear understanding of the impact of changing polymerization sequence on the physical properties and the corresponding molecular bonding is needed. To address this issue, a data mining approach is used to identify the change with polymerization sequence of tensile and rheological properties of acrylate-epoxy IPNs. The experimental approach Used to Study the molecular structure is high throughput Fourier transform infrared (FTIR) spectroscopy. Analysis of the FTIR spectra of IPNs synthesized with different polymerization sequences leads to all understanding of the molecular bonding responsible for the tensile and rheological properties. Front the interpretation of the wavenumber bands and associated molecular bonds, we find that the polymerization sequence most affects hydrogen bonding and aromatic ring bond energies. This work defines the relationships between chemistry, structure, processing. and properties of the IPN samples.
引用
收藏
页码:270 / 277
页数:8
相关论文
共 32 条
[1]   Improving the interpretation of multivariate and rule induction models by using a peak parameter representation [J].
Alsberg, BK ;
Winson, MK ;
Kell, DB .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 1997, 36 (02) :95-109
[2]  
[Anonymous], 2001, MULTI MEGAVARIATE DA
[3]  
[Anonymous], 2009, STAT ANAL DATA MIN
[4]  
[Anonymous], 1999, SPECTROSCOPY POLYM
[5]  
[Anonymous], 1994, INTERPENETRATING POL
[6]   Principal component analysis for characterising homogeneity in powder mixing using image processing techniques [J].
Berthiaux, H ;
Mosorov, V ;
Tomczak, L ;
Gatumel, C ;
Demeyre, U .
CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION, 2006, 45 (05) :397-403
[7]   Informatics for combinatorial materials science [J].
Broderick, S. ;
Suh, C. ;
Nowers, J. ;
Vogel, B. ;
Mallapragada, S. ;
Narasimhan, B. ;
Rajan, K. .
JOM, 2008, 60 (03) :56-59
[8]   Investigation of protein retention in hydrophobic interaction chromatographic (HIC) systems using the preferential interaction theory and quantitative structure property relationship models [J].
Chen, Jie ;
Yang, Ting ;
Luo, Qiong ;
Breneman, Curt M. ;
Cramer, Steven M. .
REACTIVE & FUNCTIONAL POLYMERS, 2007, 67 (12) :1561-1569
[9]   PCA in studying coordination and variability: a tutorial [J].
Daffertshofer, A ;
Lamoth, CJC ;
Meijer, OG ;
Beek, PJ .
CLINICAL BIOMECHANICS, 2004, 19 (04) :415-428
[10]   Effect of curing sequence on the photopolymerization and thermal curing kinetics of dimethacrylate/epoxy interpenetrating polymer networks [J].
Dean, K ;
Cook, WD .
MACROMOLECULES, 2002, 35 (21) :7942-7954