@article{JiangZhuangRabczuk, author = {Jiang, Jin-Wu and Zhuang, Xiaoying and Rabczuk, Timon}, title = {Orientation dependent thermal conductance in single-layer MoS 2}, series = {Scientific Reports}, journal = {Scientific Reports}, doi = {10.1038/srep02209}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170418-31417}, abstract = {We investigate the thermal conductivity in the armchair and zigzag MoS2 nanoribbons, by combining the non-equilibrium Green's function approach and the first-principles method. A strong orientation dependence is observed in the thermal conductivity. Particularly, the thermal conductivity for the armchair MoS2 nanoribbon is about 673.6 Wm-1 K-1 in the armchair nanoribbon, and 841.1 Wm-1 K-1 in the zigzag nanoribbon at room temperature. By calculating the Caroli transmission, we disclose the underlying mechanism for this strong orientation dependence to be the fewer phonon transport channels in the armchair MoS2 nanoribbon in the frequency range of [150, 200] cm-1. Through the scaling of the phonon dispersion, we further illustrate that the thermal conductivity calculated for the MoS2 nanoribbon is esentially in consistent with the superior thermal conductivity found for graphene.}, subject = {Mechanische Eigenschaft}, language = {en} } @article{MortazaviPereiraJiangetal., author = {Mortazavi, Bohayra and Pereira, Luiz Felipe C. and Jiang, Jin-Wu and Rabczuk, Timon}, title = {Modelling heat conduction in polycrystalline hexagonal boron-nitride films}, series = {Scientific Reports}, journal = {Scientific Reports}, doi = {10.1038/srep13228}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170425-31534}, abstract = {We conducted extensive molecular dynamics simulations to investigate the thermal conductivity of polycrystalline hexagonal boron-nitride (h-BN) films. To this aim, we constructed large atomistic models of polycrystalline h-BN sheets with random and uniform grain configuration. By performing equilibrium molecular dynamics (EMD) simulations, we investigated the influence of the average grain size on the thermal conductivity of polycrystalline h-BN films at various temperatures. Using the EMD results, we constructed finite element models of polycrystalline h-BN sheets to probe the thermal conductivity of samples with larger grain sizes. Our multiscale investigations not only provide a general viewpoint regarding the heat conduction in h-BN films but also propose that polycrystalline h-BN sheets present high thermal conductivity comparable to monocrystalline sheets.}, subject = {W{\"a}rmeleitf{\"a}higkeit}, language = {en} } @article{ShiraziMohebbiAzadiKakavandetal., author = {Shirazi, A. H. N. and Mohebbi, Farzad and Azadi Kakavand, M. R. and He, B. and Rabczuk, Timon}, title = {Paraffin Nanocomposites for Heat Management of Lithium-Ion Batteries: A Computational Investigation}, series = {JOURNAL OF NANOMATERIALS}, journal = {JOURNAL OF NANOMATERIALS}, doi = {10.1155/2016/2131946}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170411-31141}, abstract = {Lithium-ion (Li-ion) batteries are currently considered as vital components for advances in mobile technologies such as those in communications and transport. Nonetheless, Li-ion batteries suffer from temperature rises which sometimes lead to operational damages or may even cause fire. An appropriate solution to control the temperature changes during the operation of Li-ion batteries is to embed batteries inside a paraffin matrix to absorb and dissipate heat. In the present work, we aimed to investigate the possibility of making paraffin nanocomposites for better heat management of a Li-ion battery pack. To fulfill this aim, heat generation during a battery charging/discharging cycles was simulated using Newman's well established electrochemical pseudo-2D model. We couple this model to a 3D heat transfer model to predict the temperature evolution during the battery operation. In the later model, we considered different paraffin nanocomposites structures made by the addition of graphene, carbon nanotubes, and fullerene by assuming the same thermal conductivity for all fillers. This way, our results mainly correlate with the geometry of the fillers. Our results assess the degree of enhancement in heat dissipation of Li-ion batteries through the use of paraffin nanocomposites. Our results may be used as a guide for experimental set-ups to improve the heat management of Li-ion batteries.}, subject = {Batterie}, language = {en} } @article{ZhangHaoWangetal., author = {Zhang, Chao and Hao, Xiao-Li and Wang, Cuixia and Wei, Ning and Rabczuk, Timon}, title = {Thermal conductivity of graphene nanoribbons under shear deformation: A molecular dynamics simulation}, series = {Scientific Reports}, journal = {Scientific Reports}, doi = {10.1038/srep41398}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170428-31718}, abstract = {Tensile strain and compress strain can greatly affect the thermal conductivity of graphene nanoribbons (GNRs). However, the effect of GNRs under shear strain, which is also one of the main strain effect, has not been studied systematically yet. In this work, we employ reverse nonequilibrium molecular dynamics (RNEMD) to the systematical study of the thermal conductivity of GNRs (with model size of 4 nm × 15 nm) under the shear strain. Our studies show that the thermal conductivity of GNRs is not sensitive to the shear strain, and the thermal conductivity decreases only 12-16\% before the pristine structure is broken. Furthermore, the phonon frequency and the change of the micro-structure of GNRs, such as band angel and bond length, are analyzed to explore the tendency of thermal conductivity. The results show that the main influence of shear strain is on the in-plane phonon density of states (PDOS), whose G band (higher frequency peaks) moved to the low frequency, thus the thermal conductivity is decreased. The unique thermal properties of GNRs under shear strains suggest their great potentials for graphene nanodevices and great potentials in the thermal managements and thermoelectric applications.}, subject = {W{\"a}rmeleitf{\"a}higkeit}, language = {en} }