Designing novel polymers with targeted properties using the signature molecular descriptor.
A method for solving the inverse quantitative structure-property relationship (QSPR) problem is presented which facilitates the design of novel polymers with targeted properties. Here, we demonstrate the efficacy of the approach using the targeted design of polymers exhibiting a desired glass transition temperature, heat capacity, and density. We present novel QSPRs based on the signature molecular descriptor capable of predicting glass transition temperature, heat capacity, density, molar volume, and cohesive energies of linear homopolymers with cross-validation squared correlation coefficients ranging between 0.81 and 0.95. Using these QSPRs, we show how the inverse problem can be solved to design poly(N-methyl hexamethylene sebacamide) despite the fact that the polymer was used not used in the training of this model.
Department of Computational Biology, Sandia National Laboratories, P.O. Box 5800, Albuquerque, New Mexico 87185-0310, USA. wmbrown@sandia.gov
W Michael
WM
Brown
Shawn
S
Martin
Mark D
MD
Rintoul
Jean-Loup
JL
Faulon
D000465:Algorithms; D015195:Drug Design; D008689:Methacrylates / Q000737:chemistry; D015394:Molecular Structure; D044367:Phase Transition; D011108:Polymers / Q000737:chemistry* / Q000494:pharmacology; D021281:Quantitative Structure-Activity Relationship; D013696:Temperature; D013816:Thermodynamics
D008689:Methacrylates; D011108:Polymers