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Volumn 23, Issue 1, 2008, Pages 22-32

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

Author keywords

[No Author keywords available]

Indexed keywords

CORRELATION DATABASE; POLYMER OPTICAL FIBERS;

EID: 38149065289     PISSN: 08848173     EISSN: 1098111X     Source Type: Journal    
DOI: 10.1002/int.20256     Document Type: Article
Times cited : (35)

References (16)
  • 2
    • 38149016552 scopus 로고    scopus 로고
    • Van Krevelen DW Properties of polymers. New York: Elsevier Science; 1990.
    • Van Krevelen DW Properties of polymers. New York: Elsevier Science; 1990.
  • 3
    • 0041346137 scopus 로고    scopus 로고
    • A new group contribution scheme to estimate the glass transition temperature for polymers and diluents
    • Camacho-Zuniga C, Ruiz-Trevino FA. A new group contribution scheme to estimate the glass transition temperature for polymers and diluents. Ind Eng Chem Res 2003;42:1530-1534.
    • (2003) Ind Eng Chem Res , vol.42 , pp. 1530-1534
    • Camacho-Zuniga, C.1    Ruiz-Trevino, F.A.2
  • 4
    • 0035387458 scopus 로고    scopus 로고
    • Group-contribution based estimation of pure component properties
    • Marrero J, Gani R. Group-contribution based estimation of pure component properties. Fluid Phase Equilibria 2001;183:183-208.
    • (2001) Fluid Phase Equilibria , vol.183 , pp. 183-208
    • Marrero, J.1    Gani, R.2
  • 5
    • 0001379475 scopus 로고    scopus 로고
    • Prediction of polymer glass transition temperatures using a general quantitative structure-property relationship treatment
    • Katritzky AR, Rachwal P, Law KW, Karelson M, Lobanov VS. Prediction of polymer glass transition temperatures using a general quantitative structure-property relationship treatment. J Chem Inf Comput Sci 1996;36:879-884.
    • (1996) J Chem Inf Comput Sci , vol.36 , pp. 879-884
    • Katritzky, A.R.1    Rachwal, P.2    Law, K.W.3    Karelson, M.4    Lobanov, V.S.5
  • 6
    • 0032028350 scopus 로고    scopus 로고
    • Quantitative structure-property relationship (QSPR) correlation of glass transition temperatures of high molecular weight polymers
    • Katritzky AR, Sild S, Lobanov V, Karelson M. Quantitative structure-property relationship (QSPR) correlation of glass transition temperatures of high molecular weight polymers. J Chem Inf Model 1998;38:300-304.
    • (1998) J Chem Inf Model , vol.38 , pp. 300-304
    • Katritzky, A.R.1    Sild, S.2    Lobanov, V.3    Karelson, M.4
  • 7
    • 0036522801 scopus 로고    scopus 로고
    • Prediction of glass transition temperatures from monomer and repeat unit structure using computational neural networks
    • Mattioni BE, Jurs PC. Prediction of glass transition temperatures from monomer and repeat unit structure using computational neural networks. J Chem Inf Model 2002;42:232-240.
    • (2002) J Chem Inf Model , vol.42 , pp. 232-240
    • Mattioni, B.E.1    Jurs, P.C.2
  • 8
    • 23844539732 scopus 로고    scopus 로고
    • Interpreting computational neural network quantitative structure-activity relationship models: A detailed interpretation of the weights and biases
    • Guha R, Stanton DT, Jurs PC. Interpreting computational neural network quantitative structure-activity relationship models: A detailed interpretation of the weights and biases. J Chem Inf Model 2005;45:1109-1121.
    • (2005) J Chem Inf Model , vol.45 , pp. 1109-1121
    • Guha, R.1    Stanton, D.T.2    Jurs, P.C.3
  • 9
    • 20444409456 scopus 로고    scopus 로고
    • Interpreting computational neural network QSAR models: A measure of descriptor importance
    • Guha R, Jurs PC. Interpreting computational neural network QSAR models: A measure of descriptor importance. J Chem Inf Model 2005;45:800-806.
    • (2005) J Chem Inf Model , vol.45 , pp. 800-806
    • Guha, R.1    Jurs, P.C.2
  • 10
    • 0037365387 scopus 로고    scopus 로고
    • Correlation between the glass transition temperatures and repeating unit structure for high molecular weight polymers
    • Cao C, Lin Y. Correlation between the glass transition temperatures and repeating unit structure for high molecular weight polymers. J Chem Inf Model 2003;43:643-650.
    • (2003) J Chem Inf Model , vol.43 , pp. 643-650
    • Cao, C.1    Lin, Y.2
  • 12
    • 0030413236 scopus 로고    scopus 로고
    • Prediction of the glass transition temperature of multicyclic and bulky substituted acrylate and methacrylate polymers using the energy, volume, mass (EVM) QSPR model
    • Cypcar CC, Camelio P, Lazzeri V, Mathias LJ, Waegell B. Prediction of the glass transition temperature of multicyclic and bulky substituted acrylate and methacrylate polymers using the energy, volume, mass (EVM) QSPR model. Macromolecules 1996;29:8954-8959.
    • (1996) Macromolecules , vol.29 , pp. 8954-8959
    • Cypcar, C.C.1    Camelio, P.2    Lazzeri, V.3    Mathias, L.J.4    Waegell, B.5
  • 13
    • 0032492525 scopus 로고    scopus 로고
    • Glass transition temperature calculations for styrene derivatives using the energy, volume, and mass model
    • Camelio P, Lazzeri V, Waegell B, Cypcar C, Mathias LJ. Glass transition temperature calculations for styrene derivatives using the energy, volume, and mass model. Macromolecules 1998;31:2305-2311.
    • (1998) Macromolecules , vol.31 , pp. 2305-2311
    • Camelio, P.1    Lazzeri, V.2    Waegell, B.3    Cypcar, C.4    Mathias, L.J.5
  • 14
    • 0043286836 scopus 로고    scopus 로고
    • Artificial neural networks applied to polymer composites-A review
    • Zhang Z, Friedrich K. Artificial neural networks applied to polymer composites-A review. Compos Sci Technol 2003;63:2029-2044.
    • (2003) Compos Sci Technol , vol.63 , pp. 2029-2044
    • Zhang, Z.1    Friedrich, K.2
  • 15
    • 0041568265 scopus 로고    scopus 로고
    • Artificial neural network predictions on erosive wear of polymers
    • Zhang Z, Barkoula NM, Karger-Kocsis J, Friedrich K. Artificial neural network predictions on erosive wear of polymers. Wear 2003;255:708-713.
    • (2003) Wear , vol.255 , pp. 708-713
    • Zhang, Z.1    Barkoula, N.M.2    Karger-Kocsis, J.3    Friedrich, K.4
  • 16
    • 0024292833 scopus 로고
    • Aromatic rings act as hydrogen bond acceptors
    • Levitt M, Perutz MF. Aromatic rings act as hydrogen bond acceptors. J Mol Biol 1988;201:751.
    • (1988) J Mol Biol , vol.201 , pp. 751
    • Levitt, M.1    Perutz, M.F.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.