Subproject 5: Theoretical and experimental description of heat transport
Table of contents
Motivation
SP 5 supports the multi-scale prediction of the thermomechanical behavior of fiber composite materials as well as the interaction between individual components on the molecular level by means of theoretical simulations and validating experimental investigations in order to generate data for meso- and macro-scale modeling. Hence, this subproject holds a key function for the simulative design of spatially deformable adaptive fiber rubber composites.
State of the art and preliminary research
Preliminary research of the 1st cohort includes the theoretical description of heat transport of basic polymers using molecular dynamics simulation (MD) (cf. Fig., right) and its validation by measurements. Investigations were focused on, for example, the dependency of mechanical behavior on ambient conditions (pressure, temperature), the various types and degrees of cross-linking and the composition of investigated polymers. The results achieved [1, 2] are comparable to those that can be found in the literature [3, 4] and offer considerably extended MD model parameters. Furthermore, two characterization methods for heat conductivity (see Fig., left) were established so that liquid as well as solid samples (new fiber composite materials and reference materials) could be investigated. Clear correlations between heat conductivity and degrees of cross-linking as well as polymer composition could be identified. The obtained results are the foundation for MD research using polymer combinations. The main research topic of the 2nd cohort will involve the prediction of 3D heat flow in previously unknown highly heterogeneous polymer fiber composites.
Scientific questions and project objectives
SP 5 will focus on the theoretical determination of thermal parameters of individual components (polymer, textile, fillers), complex highly heterogeneous composites (3D) under mechanical stress and the investigation of molecular interactions of the polmer matrix with various filler materials. In addition to empirical methods, initio processes will be employed as well. This will be supported and thus validated by experimental investigations. Based on existing test stands, innovative evaluation methods shall be developed by coupling with already available measurement and analysis devices. Experiments using real samples of subprojects will serve to validate theoretical approaches.
Another main research aspect of the 2nd cohort involves the extensive screening of various polymers and their combinations in close collaboration with SP 3, which will provide further variations in terms of the type of polymer, the degree and type of cross-linking and compositions. Screening will be supported by AI algorithms so that previously unknown material properties can be derived from already existing datasets using machine learning, which can then be compared with molecular dynamics simulations and experimental data, and even completely new combinations can be identified. Thus, areas that are inaccessible through experimental investigations can be considered for validation.
References
| [1] | Vasilev A., Lorenz T., Breitkopf C. Thermal conductivity of polyisoprene and polybutadiene from molecular dynamics simulations and transient measurements //Polymers. – 2020. – Т. 12. – №. 5. – С. 1081. |
| [2] | Vasilev A., Lorenz T., Breitkopf C. Thermal Conductivities of Crosslinked Polyisoprene and Polybutadiene from Molecular Dynamics Simulations //Polymers. – 2021. – Т. 13. – №. 3. – С. 315. |
| [3] | Chen J., Liu B., Gao X. Thermal properties of graphene-based polymer composite materials: A molecular dynamics study //Results in Physics. – 2020. – Т. 16. – С. 102974. |
| [4] | Wu S. et al. Machine-learning-assisted discovery of polymers with high thermal conductivity using a molecular design algorithm //Npj Computational Materials. – 2019. – Т. 5. – №. 1. – С. 1-11. |
Contact
Institute of Power Engineering (IET), Chair of Technical Thermodynamics, Faculty of Mechanical Science and Engineering
© Lutz Liebert/TUD
Leiterin der Professur
NameMs Prof. Dr. rer. nat. habil. Cornelia Breitkopf
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Visiting address:
Merkel-Bau, Zi. 106 Helmholtzstraße 14
01069 Dresden