Polymer informatics for QSPR prediction of tensile mechanical properties. Case study: Strength at break
The artificial intelligence-based prediction of the mechanical properties derived from the
tensile test plays a key role in assessing the application profile of new polymeric materials …
tensile test plays a key role in assessing the application profile of new polymeric materials …
Molecular simulation of thermoplastic polyurethanes under large tensile deformation
Thermoplastic polyurethanes (TPUs) are useful materials for numerous applications due in
part to their outstanding resilience and ability to dissipate energy under large mechanical …
part to their outstanding resilience and ability to dissipate energy under large mechanical …
A quantitative relationship between Tgs and chain segment structures of polystyrenes
X Yu, X Huang - Polímeros, 2017 - SciELO Brasil
The glass transition temperature (T g) is a fundamental characteristic of an amorphous
polymer. A quantitative structure-property relationship (QSPR) based on error back …
polymer. A quantitative structure-property relationship (QSPR) based on error back …
Thermal analysis of the structure of segmented polyurethane elastomers: relation to mechanical properties
K Bagdi, K Molnár, B Pukánszky… - Journal of thermal analysis …, 2009 - Springer
Abstract Polyurethanes were prepared from 4, 4′-methylenebis (phenyl isocyanate)(MDI),
1, 4-butanediol (BD), and poly (tetrahydrofurane) polyether polyol (PTHF) by melt …
1, 4-butanediol (BD), and poly (tetrahydrofurane) polyether polyol (PTHF) by melt …
Linking the morphology of a high hard segment content polyurethane to its thermal behaviour and mechanical properties
Understanding and controlling the morphology of thermoplastic polyurethane (TPU) is
crucial, as it is closely linked with its thermal and mechanical properties. The morphology of …
crucial, as it is closely linked with its thermal and mechanical properties. The morphology of …
Polymer genome: a data-powered polymer informatics platform for property predictions
The recent successes of the Materials Genome Initiative have opened up new opportunities
for data-centric informatics approaches in several subfields of materials research, including …
for data-centric informatics approaches in several subfields of materials research, including …
Designing temperature-memory effects in semicrystalline polyurethane
N Mirtschin, T Pretsch - Rsc Advances, 2015 - pubs.rsc.org
Temperature-memory polymers are able to generate a substantial mechanical response
when heated above the temperature, at which a preceding deformation was carried out …
when heated above the temperature, at which a preceding deformation was carried out …
Multitask Neural Network for Mapping the Glass Transition and Melting Temperature Space of Homo- and Co-Polyhydroxyalkanoates Using σProfiles Molecular …
Polyhydroxyalkanoates (PHAs) are an emerging type of bioplastic that have the potential to
replace petroleum-based plastics. They are biosynthetizable, biodegradable, and …
replace petroleum-based plastics. They are biosynthetizable, biodegradable, and …
Modeling the temperature dependence of dynamic mechanical properties and visco-elastic behavior of thermoplastic polyurethane using artificial neural network
This paper presents one of the soft computing methods, specifically the artificial neural
network technique, that has been used to model the temperature dependence of dynamic …
network technique, that has been used to model the temperature dependence of dynamic …
Predicting phase behavior of linear polymers in solution using machine learning
JG Ethier, RK Casukhela, JJ Latimer… - …, 2022 - ACS Publications
The phase behavior of polymers in solution is crucial to many applications in polymer
processing, synthesis, self-assembly, and purification. Quantitative prediction of polymer …
processing, synthesis, self-assembly, and purification. Quantitative prediction of polymer …