Skip to main content
SpringerLink
Log in

Polymer Informatics

  • Chapter
  • First Online:
Polymer Libraries

Part of the book series: Advances in Polymer Science ((POLYMER,volume 225))

Abstract

Polymers are arguably the most important set of materials in common use. The increasing adoption of both combinatorial as well as high-throughput approaches, coupled with an increasing amount of interdisciplinarity, has wrought tremendous change in the field of polymer science. Yet the informatics tools required to support and further enhance these changes are almost completely absent. In the first part of the chapter, a critical analysis of the challenges facing modern polymer informatics is provided. It is argued, that most of the problems facing the field today are rooted in the current scholarly communication process and the way in which chemists and polymer scientists handle and publish data. Furthermore, the chapter reviews existing modes of representing and communicating polymer information and discusses the impact, which the emergence of semantic technologies will have on the way in which scientific and polymer data is published and transmitted. In the second part, a review of the use of informatics tools for the prediction of polymer properties and in silico design of polymers is offered.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Abbreviations

ACS:

American Chemical Society

ANN:

Artificial neural network

BPAC:

Bisphenol A Polycarbonate

CAS:

Chemical Abstracts Service

FTIR:

Fourier Transform Infrared Spectroscopy

GREMAS:

Genealogical Retrieval by Magnetic Tape Storage

HIM:

Hamiltonian Interaction Modeling

HTE:

High Throughput Experimentation

IUPAC:

International Union of Pure and Applied Chemistry

LCST:

Lower Critical Solution Temperature

LDPE:

Low Density Polyethylene

LLDPE:

Linear Low Density Polyethylene

OWL:

Web Ontology Language

PCA:

Principal Component Analysis

PCR:

Principal Component Regression

PDF:

Portable document format

PDI:

Polydispersity Index

PET:

Poly(ethylene terephthalate)

POLIDCASYR:

Polymer Documentation System of IDC with Inclusion of Analytical and Synthetic Concept Relations

PVA:

Poly(vinyl alcohol)

QSPR:

Quantitative Structure Property Relationship

R 2 :

Correlation coefficient

R cv 2 :

Cross-validated correlation coefficient

RBF:

Radial Basis Function

RDF:

Resource Description Framework

RMS:

Root Mean Square Error

STM:

Scientific, technical, medical

T g :

Glass transition temperature

ToF-SIMS:

Time-of-Flight Secondary Ion Mass Spectrometry

TOSAR:

Topological Representation of Synthetic and Analytical Relations of Concepts

UCST:

Upper Critical Solution Temperature

UV:

Ultraviolet

WWW:

World Wide Web

XML:

eXtensible Markup Language

References

  1. Yoshida M, Langer R, Lendlein A et al. (2006) From advanced biomedical coatings to multi-functionalized biomaterials. Polym Rev 46:347–375

    CAS  Google Scholar 

  2. Dewez JL, Lhoest JB, Detrait E et al. (1998) Adhesion of mammalian cells to polymer surfaces: from physical chemistry of surfaces to selective adhesion on defined patterns. Biomaterials 19:1441–1445

    Article  CAS  Google Scholar 

  3. Brocchini S, James K, Tangpasuthadol V et al. (1998) Structure-property coorrelations in a combinatorial library of degradable biomaterials. J Biomed Mat Res 42:66–75

    Article  CAS  Google Scholar 

  4. Cuchelkar V, Kopecek J (2006) Polymer-drug conjugates. In: Uchegbu IF and Schaetzlein AG (ed) Polym Drug Deliv, CRC Press, Boca Raton

    Google Scholar 

  5. Torchilin VP (2006) Polymorphic micelles as pharmaceutical carriers. Polym Drug Deliv 111–130

    Google Scholar 

  6. Haag R, Kratz F (2006) Polymer therapeutics: concepts and applications. Angew Chem Int Edn 45:1198–1215

    Article  CAS  Google Scholar 

  7. Khandare J, Minko T (2006) Polymer-drug conjugates: progress in polymeric prodrugs. Prog Polym Sci 31:359–397

    Article  CAS  Google Scholar 

  8. Way JL, Petrikovics I, Jiang J et al. (2001) Application of dendrimeric polymers as a drug carrier in pharmacology. Abstracts of Papers, 221st ACS National Meeting, San Diego, CA, United States, April 1–5, 2001 IEC-316

    Google Scholar 

  9. Kataoka K, Kwon GS, Yokoyama M et al. (1993) Block copolymer micelles as vehicles for drug delivery. J Contr Rel 24:119–132

    Article  CAS  Google Scholar 

  10. Malmsten M (2006) Soft drug delivery systems. Soft Matter 2:760–769

    Article  CAS  Google Scholar 

  11. Qiu LY, Bae YH (2006) Polymer architecture and drug delivery. Pharm Res 23:1–30

    Article  CAS  Google Scholar 

  12. Kang HC, Lee M, Bae YH (2007) Polymeric gene delivery vectors. In: Peppas NA, Hilt JZ, Thomas JB (ed) Nanotechnology in therapeutics Taylor and Francis, New York

    Google Scholar 

  13. Alexis F, Zeng J, Wang S (2007) PEI nanoparticles for targeted gene delivery. Gene Transfer 473–478

    Google Scholar 

  14. Leong KW (2006) Polymer design for nonviral gene delivery. BioMEMS Biomed Nanotechnol 1:239–263

    Article  CAS  Google Scholar 

  15. Mahato RI (2005) Water insoluble and soluble lipids for gene delivery. Adv Drug Deliv Rev 57:699–712

    Article  CAS  Google Scholar 

  16. Mahato RI, Kim SW (2005) Water soluble lipopolymers for gene delivery. In: Ammiji MM (ed) Polym Gene Deliv, CRC Press, Boca Raton

    Google Scholar 

  17. Adams ML, Lavasanifar A, Kwon GS (2003) Amphiphilic block copolymers for drug delivery. J Pharm Sci 92:1343–1355

    Article  CAS  Google Scholar 

  18. Wagner E, Kloeckner J (2006) Gene delivery using polymer therapeutics. Adv Polym Sci 192:135–173

    Article  CAS  Google Scholar 

  19. Joester D, Losson M, Pugin R et al. (2003) Amphiphilic dendrimers: novel self-assembling vectors for efficient gene delivery. Angew Chem Int Ed 42:1486–1490

    Article  CAS  Google Scholar 

  20. Bjornerg HC, Derici L, Haggman BH et al. (2006) Hair care compositions comprising a dendritic polymer. 2005-EP7017 2006018064

    Google Scholar 

  21. Derici L, Harcup JP, Khoshdel E (2006) Hair care composition comprising a dendritic macromolecule. 2005-EP7016 2006018063

    Google Scholar 

  22. Goosey M (2007) An overview of polymers as key enablers in electronics assembly-a printed circuit board perspective. Polymers in Electronics 2007: Paper9/1-Paper9/5, Munich, Germany

    Google Scholar 

  23. Rost H (2007) Printed electronic circuits. Kunstst 97:97–101

    CAS  Google Scholar 

  24. Xing R-b, Ding Y, Han Y-c (2007) Patterning of polymer by inkjet printing and its application in the fabrication of organic electronic devices. Fenzi Kexue Xuebao 23:75–81

    Google Scholar 

  25. Liang Z, Wang Q (2007) Patterning of conjugated polymers for organic electronics and optoelectronics. In: Naiwa HS (ed) Polym Nanostruct Their Appl, American Scientific Publishers, Stevenson Ranch, California

    Google Scholar 

  26. Bock K (2005) Polytronics – electronics and systems on flexible substrates. IEEE VLSI-TSA International Symposium on VLSI Technology, Hsinchu, Taiwan, pp 53–56

    Google Scholar 

  27. Stafford N (2007) Large-scale biopolymer production. http://www.rsc.org/chemistryworld/ News/2007/May/14050701.asp, Accessed Dec 12 2008

  28. Zhang H, Hoogenboom R, Meier MAR et al. (2004) High-throughput experimentation in polymer chemistry. Trans Mater Res Soc Jpn 29:319–324

    CAS  Google Scholar 

  29. Zhang H, Hoogenboom R, Meier MAR et al. (2005) Combinatorial and high-throughput approaches in polymer science. Meas Sci Technol 16:203–211

    Article  CAS  Google Scholar 

  30. Hoogenboom R, Fijten MWM, Wijnans S et al. (2006) High-throughput synthesis and screening of a library of random and gradient copoly(2-oxazoline)s. J Comb Chem 8:145–148

    Article  CAS  Google Scholar 

  31. Hoogenboom R, Schubert US (2005) High-throughput synthesis equipment applied to polymer research. Review of Scientific Instruments 76:062202/062201–062202/062207

    Article  CAS  Google Scholar 

  32. Brocchini S, James K, Tangpasuthadol V et al. (1997) A combinatorial approach for polymer design. J Am Chem Soc 119:4553

    Article  CAS  Google Scholar 

  33. Wiesbrock F, Hoogenboom R, Leenen MAM et al. (2005) Investigation of the living cationic ring-opening polymerization of 2-methyl-, 2-ethyl-, 2-nonyl-, and 2-phenyl-2-oxazoline in a single-mode microwave reactor. Macromolecules 38:5025–5034

    Article  CAS  Google Scholar 

  34. Wiesbrock F, Hoogenboom R, Abeln CH et al. (2004) Single-mode microwave ovens as new reaction devices: accelerating the living polymerization of 2-ethyl-2-Oxazoline. Macromol Rapid Commun 25:1895–1899

    Article  CAS  Google Scholar 

  35. Gilman JW, Bourbigot S, Shields JR et al. (2003) High throughput methods for polymer nanocomposites research: extrusion, NMR characterization and flammability property screening. J Mat Sci 38:4451

    CAS  Google Scholar 

  36. Davis RD, Bur AJ, McBearty M et al. (2004) Dielectric spectroscopy during extrusion processing of polymer nanocomposites: a high-throughput processing/characterization method to measure layered silicate content and exfoliation. Polymer 45:6487–6493

    Article  CAS  Google Scholar 

  37. Gilman JW, Davis RD, Bellayer S et al. (2005) Use of optical probes and laser scanning confocal fluorescence microscopy for high-throughput characterization of dispersion in polymer layered silicate nanocomposites. PMSE Prepr 92:168–169

    CAS  Google Scholar 

  38. Gilman JW, Davis RD, Shields JR et al. (2004) Development of high-throughput methods for polymer flammability property characterization. International SAMPE Symposium and Exhibition:460–469

    Google Scholar 

  39. Gilman JW, Maupin PH, Harris RH et al. (2004) High throughput methods for nanocomposite materials research. Extrusion and visible optical probes. PMSE Prepr. 90:717–718

    CAS  Google Scholar 

  40. Adams N, Moneke M, Gulmus SA et al. (2006) Combinatorial compounding. Mater Res Soc Symp Proc 894:171–179

    Google Scholar 

  41. Kranenburg JM, Tweedie CA, Hoogenboom R et al. (2007) Elastic moduli for a diblock copoly(2-oxazoline) library obtained by high-throughput screening. J Mater Chem 17:2713–2721

    Article  CAS  Google Scholar 

  42. Kranenburg JM, van Duin M, Schubert US (2007) Screening of EPDM cure states using depth-sensing indentation. Macromol Chem Phys 208:915–923

    Article  CAS  Google Scholar 

  43. Cheung K-H, Yip KY, Townsend JP et al. (2008) HCLS 2.0/3.0: health care and life sciences data mashup using Web 2.0/3.0. J Biomed Inform 41:694–705

    Article  Google Scholar 

  44. Walkingshaw AD, White TOH, Day NE et al. (2008) Representing, indexing and mining scientific data with XML and RDF: Golem and CrystalEye. XTech 2008: Dublin, Ireland

    Google Scholar 

  45. Ma H, Melillo G, Oliva L et al. (2005) Aluminum alkyl complexes supported by [OSSO] type bisphenolato ligands: synthesis, characterization and living polymerization of rac-lactide. Dalton Trans 721–727

    Google Scholar 

  46. Huggins ML (1969) Macromolecular nomenclature: general background and perspective. J Chem Doc 9:230–231

    Article  CAS  Google Scholar 

  47. Livingston HK, Fox RB (1969) Nomenclature of organic polymers. J Chem Doc 9:232–234

    Article  CAS  Google Scholar 

  48. Cohn WE (1969) Representation of macromolecules and polymers of biological importance. J Chem Doc 9:235–241

    Article  CAS  Google Scholar 

  49. Block BP, Thomas PM, Donovan KM (1969) Problems in the nomenclature of inorganic polymers. J Chem Doc 9:242–244

    Article  CAS  Google Scholar 

  50. Bikales NM (1969) Polymer nomenclature in industry. J Chem Doc 9:245–247

    Article  CAS  Google Scholar 

  51. Loening KL, Metanomski WV, Powell WH (1969) Indexing of polymers in Chemical Abstracts. J Chem Doc 9:248–251

    Article  CAS  Google Scholar 

  52. Metanomski WV (1979) Symposium on retrieval of polymer information: introductory remarks. J Chem Inf Comput Sci 19:59

    Article  CAS  Google Scholar 

  53. Langstaff EM, Ostrum K (1979) Access to polymer information in chemical abstracts. J Chem Inf Comput Sci 19:60–64

    Article  CAS  Google Scholar 

  54. Fugmann R (1979) POLIDCASYR: the polymer documentation system of IDC. J Chem Inf Comp Sci 19:64–68

    Article  CAS  Google Scholar 

  55. Donaruma LG (1979) Some problems encountered in interdisciplinary searches of the polymer literature. J Chem Inf Comp Sci 19:68–70

    Article  CAS  Google Scholar 

  56. Nardone J (1979) Computerized numeric data for polymers. J Chem Inf Comp Sci 19:71–73

    Article  CAS  Google Scholar 

  57. Roush PF, Seitz JT, Young LF (1979) An on-line system for storage and retrieval of polymer data. J Chem Inf Comp Sci 19:73–76

    Article  CAS  Google Scholar 

  58. Skolnik H (1979) A classification system for polymer literature in an industrial environment. J Chem Inf Comp Sci 19:76–79

    Article  CAS  Google Scholar 

  59. Zurbach Balent M, Lotz JW (1979) Polymers and patents don’t mix-easily. J Chem Inf Comp Sci 19:80–83

    Article  Google Scholar 

  60. Fugmann R (1974) Representation of concept relations using the TOSAR system of the IDC. J Am Soc Inf Sci 25:287–307

    Article  CAS  Google Scholar 

  61. Manola F, Miller E (2004) RDF Primer. http://www.w3.org/TR/rdf-primer/. Accessed Jul 10 2007

  62. Brickley D, Guha RV (2004) RDF vocabulary description language 1.0: RDF schema. http://www.w3.org/TR/rdf-schema/. Accessed Dec 30 2008

  63. McGuiness D, van Harmelen F (2004) OWL web ontology language overview. http://www.w3.org/TR/owl-features/.Accessed Dec 30 2008

  64. Ranganathan SR (1963) Colon classification. Asia Publishing House, Bombay, India

    Google Scholar 

  65. Metanomski WV (1991) Compendium of macromolecular nomenclature (the purple book). Blackwell Scientific Publications, Oxford

    Google Scholar 

  66. Kaback SM (1991) Polymer information: storage for retrieval, or hide and seek? Introduction. J Chem Inf Comput Sci 31:439–443

    Article  CAS  Google Scholar 

  67. Gushurst AJ, Nourse JG, Hounshell WD et al. (1991) The substance module: the representation, storage and searching of complex structures. J Chem Inf Comp Sci 31:447–454

    Article  CAS  Google Scholar 

  68. Kaback SM (1991) There’s more to a polymer than just its build. J Chem Inf Comput Sci 31:439–443

    Article  CAS  Google Scholar 

  69. Briggs JA, Ferns EA, Shenton KE (1991) Improvements in Derwent Plasdoc system. J Chem Inf Comput Sci 31:454–458

    Article  CAS  Google Scholar 

  70. Rieder MD (1991) The IFI polymer indexing system: its past, present and future. J Chem Inf Comput Sci 31:458–462

    Article  CAS  Google Scholar 

  71. Green C (1991) The Rapra abstracts rubber and plastics database. J Chem Inf Comput Sci 31:476–481

    Article  CAS  Google Scholar 

  72. Herz M (1991) Polymer searching in different databases. J Chem Inf Comput Sci 31:469–475

    Article  CAS  Google Scholar 

  73. Lambert N (1991) Online searching of polymer patents: precision and recall. J Chem Inf Comput Sci 31:443–446

    Article  CAS  Google Scholar 

  74. Wilke RN, Buntrock RE (1991) Condensation polymer information: problems and opportunities. J Chem Inf Comput Sci 31:463–468

    Article  CAS  Google Scholar 

  75. Berners-Lee T, Hendler J, Lassila O (2001) The semantic web. Sci Am 284:34–44

    Article  Google Scholar 

  76. Bray T, Paoli J, Sperberg-McQueen CM et al. (2006) Extensible markup language (XML) 1.1 (Second Edition). http://www.w3.org/TR/REC-xml/.Accessed Jul 10 2007

  77. W3C (2004) XML schema part 0: primer. Second edition http://www.w3.org/TR/xmlschema-0/. Accessed Dec 12 2008

  78. Holliday GL, Murray-Rust P, Rzepa HS (2006) Chemical markup, XML, and the world wide web. 6. CMLReact, an XML vocabulary for chemical reactions. J Chem Inf Model 46:145–157

    Article  CAS  Google Scholar 

  79. Murray-Rust P, Rzepa HS, Williamson MJ et al. (2004) Chemical markup, XML, and the world wide web. 5. Applications of chemical metadata in RSS aggregators. J Chem Inf Comput Sci 44:462–469

    Article  CAS  Google Scholar 

  80. Murray-Rust P, Rzepa HS (2003) Chemical markup, XML, and the world wide web. 4. CML schema. J Chem Inf Comput Sci 43:757–772

    Article  CAS  Google Scholar 

  81. Gkoutos GV, Murray-Rust P, Rzepa HS et al. (2001) Chemical markup, XML and the world-wide web. 3. Toward a signed semantic chemical web of trust. J Chem Inf Comput Sci 41:1124–1130

    Article  CAS  Google Scholar 

  82. Murray-Rust P, Rzepa HS (2001) Chemical markup, XML and the world-wide web. 2. Information objects and the CMLDOM. J Chem Inf Comput Sci 41:1113–1123

    Article  CAS  Google Scholar 

  83. Murray-Rust P, Rzepa H (1999) Chemical markup, XML, and the world-wide web. 1. Basic principles. J Chem Inf Comput Sci 39:928–942

    Article  CAS  Google Scholar 

  84. Frenkel M, Chiroco RD, Diky V et al. (2006) XML-based IUPAC standard for experimental, predicted, and critically evaluated thermodynamic property data storage and capture (ThermoML) (IUPAC Recommendations 2006). Pure Appl Chem 78:541–612

    Article  CAS  Google Scholar 

  85. Sankar P, Aghila G (2006) Design and development of chemical ontologies for reaction representation. J Chem Inf Model 46:2355–2368

    Article  CAS  Google Scholar 

  86. Sankar P, Aghila G (2007) Ontology aided modeling of organic reaction mechanisms with flexible and fragment based XML markup procedures. J Chem Inf Model 47:1747–1762

    Article  CAS  Google Scholar 

  87. Microsoft (2008) Chem4Word project. http://research.microsoft.com/projects/chem4word/. Accessed Dec 30 2008

  88. Adams N, Murray-Rust P (2008) Engineering polymer informatics: towards the computer-aided design of polymers. Macromol Rapid Commun 29:615–632

    Article  CAS  Google Scholar 

  89. Adams N, Murray-Rust P, Winter J et al. (2008) Chemical markup, XML and the world wide web. 8. Polymer Markup Language. J Chem Inf Model 48:2118–2128

    Article  CAS  Google Scholar 

  90. Clark J (1999) XSL Transformations (XSLT). http://www.w3.org/TR/xslt. Accessed Aug 04 2008

  91. de Matos P, Ennis M, Zbinden M et al. (2006) ChEBI – Chemical entities of biological interest. http://www3.oup.co.uk/nar/database/summary/646, Accessed Dec 12 2008

  92. Kanehisa M, Goto S, Kawashima S et al. (2004) The KEGG resource for decipering the genome. Nucleic Acids Res 32:D277–D280

    Article  CAS  Google Scholar 

  93. Fleischmann A, Darsow M, Degtyarenko K et al. (2004) IntEnz, the integrated relational enzyme database. Nucleic Acids Res 32:D434–D437

    Article  CAS  Google Scholar 

  94. Degtyarenko K (2007) The Rex ontology. http://obofoundry.org/cgi-bin/detail.cgi?id$=$rex, Accessed Dec 30 2008

  95. Degtyarenko K (2007) The FIX ontology. http://obofoundry.org/cgi-bin/detail.cgi?id$=$fix, Accessed Dec 30 2008

  96. Feldman HJ, Dumontier M, Lng S et al. (2005) CO: a chemical ontology for identification of functional groups and semantic comparison of small molecules. FEBS Lett 579:4685–4691

    Article  CAS  Google Scholar 

  97. Frey JG, Hughes GV, Mills HR et al. (2003) Less is more: lightweight ontologies and user interfaces for smart labs. UK e-Science All Hands Meeting:500–507, Nottingham, UK

    Google Scholar 

  98. Frey JG, de Roure D, Schraefel MC et al. (2003) Context slicing the chemical aether. First International Workshop on Hypermedia and the Semantic Web:9, Nottingham, UK

    Google Scholar 

  99. Taylor KR, Gledhill RJ, Essex JW et al. (2006) Bringing chemical data onto the semantic web. J Chem Inf Model 46:939–952

    Article  CAS  Google Scholar 

  100. Soldatova LN, Clare A, Sparkes A et al. (2006) An ontology for a robot scientist. Bioinformatics 22:e464–e471

    Article  CAS  Google Scholar 

  101. Niles I, Pease A (2001) Towards a standard upper ontology. Proceedings of the 2nd International Conference on Formal Ontology in Information Systems (FOIS-2001): Ogunquit, Maine, United States

    Google Scholar 

  102. Heller B, Herre H (2004) Ontological categories in GOL. Axiomathes 14:57–76

    Article  Google Scholar 

  103. Brandrup J, Immergut EH (1989) Polymer handbook. Wiley, New York

    Google Scholar 

  104. King J (2008) Text content in pdf files. http://blogs.adobe.com/insidepdf/2008/07/text_content _in_pdf_files.html. Accessed Dec 28 2008

  105. Fenniri H, Chun S, Terreau O et al. (2007) Preparation and infrared/Raman classification of 630 spectroscopically encoded styrene copolymers. J Comb Chem 10:31–36

    Article  CAS  Google Scholar 

  106. Hall SR, Allen FH, Brown ID (1991) The Crystallographic Information File (CIF): a new standard archive file for crystallography. Acta Cryst A 47:655–685

    Article  Google Scholar 

  107. CCDC (2008) The Cambridge Crystallographic Data Centre. http://www.ccdc.cam.ac.uk/. Accessed Dec 12 2008

  108. Day NE (2008) CrystalEye. http://wwmm.ch.cam.ac.uk/crystaleye/index.html. Accessed Dec 12 2008

  109. Corbett P, Murray-Rust P (2006) High-throughput identification of chemistry in life science texts. Computational Life Sciences II. Lecture Notes in Computer Science, vol 4216, pp 107–118

    Google Scholar 

  110. Atkinson D (1992) The evolution of medical research writing from 1735 to 1985: the case of the Edinburgh Medical Journal. Appl Linguist 13:337–374

    Article  Google Scholar 

  111. Zaye DF, Metanomski WV (1986) Scientific communication pathways: an overview and introduction to a symposium. J Chem Inf Comput Sci 26:43–44

    Article  CAS  Google Scholar 

  112. Suh C, Rajagopalan A, Li X et al. (2002) The application of principal component analysis to materials science data. Data Sci J 1:19

    Article  CAS  Google Scholar 

  113. Bajorath J (2001) Selected concepts and investigations in compound classification, molecular descriptor analysis and virtual screening. J Chem Inf Comput Sci 41:233

    Article  CAS  Google Scholar 

  114. Wold S, Esbensen K, Geladi P (1987) Principal component analysis. Chemom Intell Lab Syst 2:37

    Article  CAS  Google Scholar 

  115. Vanden Eynde X, Bertrand P (1997) ToF-SIMS quantification of polystyrene spectra based on principal component analysis (PCA). Surf Interface Anal 25:878

    Article  Google Scholar 

  116. Coullerez G, Lundmark S, Malmstroem E et al. (2003) ToF-SIMS for the characterization of hyperbranched aliphatic polyesters: probing their molecular weight on surfaces based on principal component analysis (PCA). Surf Interface Anal 35:693–708

    Article  CAS  Google Scholar 

  117. Batur C, Vhora MH, Cakmak M et al. (1999) On-line crystallinity measurement using laser Raman spectrometer and neural network. ISA Trans 38:139–148

    Article  CAS  Google Scholar 

  118. Miranda TMR, Goncalves AR, Amorim MTP (2001) Ultraviolet-induced crosslinking of poly(vinyl alcohol) evaluated by principal component analysis of FTIR spectra. Polym Int 50:1068–1072

    Article  CAS  Google Scholar 

  119. Vazquez C, Boeykens S, Bonadeo H (2002) Total reflection X-ray fluorescence polymer spectra: classification by taxonomy statistic tools. Talanta 57:1113–1117

    Article  CAS  Google Scholar 

  120. Tuchbreiter A, Marquardt J, Zimmermann J et al. (2001) High-throughput evaluation of olefin copolymer composition by means of attenuated total reflection fourier transform infrared spectroscopy. J Comb Chem 3:598–603

    Article  CAS  Google Scholar 

  121. Lukasiak BM, Faria R, Zomer S et al. (2006) Pattern recognition for the analysis of polymeric materials. Analyst 131:73–80

    Article  CAS  Google Scholar 

  122. van Krevelen DW (1990) Properties of polymers: their correlation with chemical structure, their numerical estimation and prediction from additive group contributions. Elsevier, Amsterdam

    Google Scholar 

  123. Bicerano J (2002) Prediction of polymer properties. Marcel Dekker Ltd, New York

    Book  Google Scholar 

  124. Stevens MP (1990) Polymer chemistry. An introduction. Oxford University Press, Oxford

    Google Scholar 

  125. Koehler MG, Hopfinger AJ (1989) Molecular modelling of polymers: 5. Inclusion of intermolecular energetics in estimating glass and crystal-melt transition temperatures. Polymer 30:116–126

    CAS  Google Scholar 

  126. Hopfinger AJ, Koehler MG, Pearlstein RA (1988) Molecular modling of polymers. IV. Estimation of glass transition temperatures. J Polym Sci Part B 26:2007–2028

    Article  CAS  Google Scholar 

  127. Katritzky AR, Rachwal P, Law KW et al. (1996) Prediction of polymer glass transition temperatures using a general quantitative structure-property relationship treatment. J Chem Inf Comput Sci 36:879–884

    Article  CAS  Google Scholar 

  128. Ivanciuc O (1997) CODESSA version 2.13 for Windows. J Chem Inf Comput Sci 37:405–406

    Article  CAS  Google Scholar 

  129. Katritzky AR, Sild S, Lobanov V et al. (1998) Quantitative structure-property relationship (QSPR) correlation of glass transition temperatures of high molecular weight polymers. J Chem Inf Comput Sci 38:300–304

    Article  CAS  Google Scholar 

  130. Cao C, Lin Y (2003) Correlation between the glass transition temperatures and repeating unit structure for high molecular weight polymers. J Chem Inf Comput Sci 43:643–650

    Article  CAS  Google Scholar 

  131. Reynolds CH (1999) Designing diverse and focused combinatorial libraries of synthetic polymers. J Comb Chem 1:297–306

    Article  CAS  Google Scholar 

  132. Brown WM, Martin S, Rintoul MD et al. (2006) Designing novel polymers with targeted properties using the signature molecular descriptor. J Chem Inf Model 46:826–835

    Article  CAS  Google Scholar 

  133. Gurney K (1997) An introduction to neural networks. Routledge, London

    Book  Google Scholar 

  134. Sumpter BG, Getino C, Noid DI (1994) Theory and applications of neural computing in chemical science. Annu Rev Phys Chem 45:439–481

    Article  CAS  Google Scholar 

  135. Joyce SJ, Osguthorpe DJ, Padgett JA et al. (1995) Neural network prediction of glass-transition temperatures from monomer structure. J Chem Soc Faraday Trans 91:2491–2496

    Article  CAS  Google Scholar 

  136. Mattioni BE, Jurs PC (2002) Prediction of glass transition temperatures from monomer and repeat unit structure using computational neural networks. J Chem Inf Comput Sci 42:232–240

    Article  CAS  Google Scholar 

  137. Ulmer II CW, Smith DA, Sumpter BG et al. (1998) Computational neural networks and the rational design of polymeric materials: the next generation polycarbonates. Comput Theor Polym Sci 8:311–321

    Article  CAS  Google Scholar 

  138. Schweizer KS, Curro JG (1994) PRISM theory of the structure, thermodynamics, and phase transitions of polymer liquids and alloys. Adv Polym Sci 116:319–377

    Article  CAS  Google Scholar 

  139. Porter D (1995) Group interaction modeling of polymer properties. Marcel Dekker, New York

    Google Scholar 

  140. Afantitis A, Melagraki G, Makridima K et al. (2005) Prediction of high weight polymers glass transition temperature using RBF neural networks. J Mol Struct: THEOCHEM 716:192–198

    Article  CAS  Google Scholar 

  141. Yu X, Yi B, Wang X et al. (2007) Correlation between the glass transition temperatures and multipole moments for polymers. Chem Phys 332:115–118

    Article  CAS  Google Scholar 

  142. Gao J, Wang X, Li X et al. (2006) Prediction of polyamide properties using quantum-chemical methods and BP artificial neural networks. J Mol Model 12:513–520

    Article  CAS  Google Scholar 

  143. Liu W, Yi P, Tang Z (2006) QSPR Models for various proeprties of polymethacrylates based on quantum chemical descriptors. QSAR Comb Sci 25:936–943

    Article  CAS  Google Scholar 

  144. Liu A, Wang X, Wang L et al. (2007) Prediction of dielectric constants and glass transition temperatures of polymers by quantitative structure-property relationships. Eur Polym J 43:989–995

    Article  CAS  Google Scholar 

  145. Duce C, Michell A, Starita A et al. (2006) Prediction of polymer properties from their structure by recursive neural networks. Macromol Rapid Commun 27:711–715

    Article  CAS  Google Scholar 

  146. Katritzky AR, Sild S, Karelson M (1998) Correlation and prediction of the refractive indices of polymers by QSPR. J Chem Inf Comput Sci 38:1171–1176

    Article  CAS  Google Scholar 

  147. Xu J, Chen B, Zhang Q et al. (2004) Prediction of refractive indices of linear polymers by a four descriptor QSPR model. Polymer 45:8651–8659

    Article  CAS  Google Scholar 

  148. Yu X, Yi B, Wang X (2007) Prediction of the refractive index of vinyl polymers by using density functional theory. J Comp Chem 28:2336–2341

    Article  CAS  Google Scholar 

  149. Xu J, Liang H, Chen B et al. (2008) Linear and nonlinear QSPR models to predict refractive indices of polymers from cyclic dimer structures. Chemom Intell Lab Syst 92:152–156

    Article  CAS  Google Scholar 

  150. Gao J, Xu J, Chen B et al. (2007) A quantitative structure-property relationship study for refractive indices of conjugated polymers. J Mol Model 13:573–578

    Article  CAS  Google Scholar 

  151. Liu H, Zhong C (2005) Modeling of the theta (lower critical solution temperature) in polymer solutions using molecular connectivity indices. Eur Polym J 41:139–147

    Article  CAS  Google Scholar 

  152. Liu H, Zhong C (2005) General correlation for the prediction of theta (lower critical solution temperature) in polymer solutions. Ind Eng Chem Res 44:634–638

    Article  CAS  Google Scholar 

  153. Melagraki G, Afantitis A, Sarimveis H et al. (2007) A novel QSPR model for predicting theta (lower critical solution temperature) in polymer solutions using molecular descriptors. J Mol Model 15:55–64

    Google Scholar 

  154. Xu J, Liu L, Xu W et al. (2007) A general QSPR model for the prediction of theta (lower critical solution temperature) in polymer solutions with topological indices. J Mol Graph Model 26:352–359

    Article  CAS  Google Scholar 

  155. Xu J, Chen B, Liang H (2008) Accurate prediction of theta (lower critical solution temperature) in polymer solutions based in 3D descriptors and artificial neural networks. Macromol Theory Simul 17:109–120

    Article  CAS  Google Scholar 

  156. Rushing TS, Hester RD (2004) Semi-empirical model for polyelectrolyte intrinsic viscosity as a function of ionic strength and polymer molecular weight. Polymer 45:6587–6594

    Article  CAS  Google Scholar 

  157. Afantitis A, Melagraki G, Sarimveis H et al. (2006) Prediction of intrinsic viscosity in polymer-solvent combinations using a QSPR model. Polymer 47:3240–3248

    Article  CAS  Google Scholar 

  158. Duncan R (2006) Polymer conjugates as anticancer nanomedicines. Nat Rev Cancer 6:688–701

    Article  CAS  Google Scholar 

  159. Duncan R, Ringsdorf H, Satchi-Fainaro R (2006) Polymer therapeutics: polymers as drugs, drug and protein conjugates and gene delivery systems: past, present and future opportunities. Adv Polym Sci 192:1–8

    Article  CAS  Google Scholar 

  160. G.S. Kwon, K. Kataoka (1995) Block copolymer micelles as long-circulating drug vehicles. Adv Drug Delivery Rev 16:295

    Article  CAS  Google Scholar 

  161. Hoffman AS, Stayton PS (2004) Bioconjugates of smart polymers and proteins: synthesis and applications. Macromol Symp 207:139–151

    Article  CAS  Google Scholar 

  162. Putnam D (2006) Polymers for gene delivery across length scales. Nat Mater 5:439–451

    Article  CAS  Google Scholar 

  163. Godbey WT, Wu KK, Mikos AG (1999) Poly(ethylenimine) and its role in gene delivery. J Controlled Release 60:149–160

    Article  CAS  Google Scholar 

  164. Hunter R, Strickland F, Kezdy F (1981) The adjuvant activity of nonionic block polymer surfactants. J Immunol 127:1244–1250

    CAS  Google Scholar 

  165. Hunter RL, Bennett B (1984) The adjuvant activity of nonionic block polymer surfactants. II. Antibody formation and inflammation related to the structure of the triblock and octablock copolymer. J Immunol 133:3167–3175

    CAS  Google Scholar 

  166. Brocchini S (2001) Combinatorial chemistry and biomedical polymer development. Adv Drug Delivery Rev 53:123–130

    Article  CAS  Google Scholar 

  167. Kholodovych V, Gubskaya A, Bohrer M et al. (2008) Prediction of biological response for large combinatorial libraris of biodegradable polymers: polymethacrylates as a test case. Polymer 49:2435–2439

    Article  CAS  Google Scholar 

  168. Yu X, Yi B, Liu F et al. (2008) Prediction of the dielectric dissipation factor tan delta of polymers with an ANN model based on DFT calculation. React Funct Polym 68:1557–1562

    Article  CAS  Google Scholar 

  169. Yu X, Wang X, Wang H et al. (2006) Prediction of solubility parameters for polymers by a QSPR model. QSAR Comb Sci 25:156–161

    Article  CAS  Google Scholar 

  170. Yu X, Xie Z, Yi B et al. (2007) Prediction of the thermal decomposition property of polymers using quantum chemical descriptors. Eur Polym J 818–823

    Google Scholar 

  171. Toropov AA, Nurgaliev IN, Balakhonenko OI et al. (2004) QSPR modeling of vitrification temperatures for polyarylene oxides. J Struct Chem 45:706–712

    Article  CAS  Google Scholar 

  172. Nantasenamat C, Isarankura-Na-Ayudhya I, Naenna T et al. (2007) Quantitative structure-imprinting factor relationship of molecularly imprinted polymers. Biosens Bioelectron 2007:3309–3317

    Article  CAS  Google Scholar 

  173. Si HZ, Zhang KJ, Hu ZD et al. (2007) QSAR model for prediction capacity factor of molecular imprinting polymer based on gene expression programming. QSAR Comb Sci 26:41–50

    Article  CAS  Google Scholar 

  174. Hamoudeh M, Faraj AA, Canet-Soulas E et al. (2007) Elaboration of PLLA-based superparamagnetic nanoparticles: characterization, magnetic behaviour study and in vitro relaxivity evaluation. Int J Pharm 338:248–257

    Article  CAS  Google Scholar 

  175. Service CA (1997) Chemical Abstracts Index Guide 1997. Columbus

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Unilever Centre for Molecular Science Informatics, University Chemical Laboratory, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK

    Nico Adams

Authors
  1. Nico Adams
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nico Adams .

Editor information

Editors and Affiliations

  1. FB Technik (T1116), FH Oldenburg, Constantiaplatz 4, Emden, 26723, Germany

    Michael A. R. Meier

  2. Dept. Coatings & Polymeric Materials, North Dakota State University, Fargo, 58105, USA

    Dean C. Webster

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer

About this chapter

Cite this chapter

Adams, N. (2010). Polymer Informatics. In: Meier, M., Webster, D. (eds) Polymer Libraries. Advances in Polymer Science, vol 225. Springer, Berlin, Heidelberg. https://doi.org/10.1007/12_2009_18

Download citation

Publish with us

Policies and ethics

Search

Navigation