The exploration of large chemical spaces in search of new thermoelectric materials requires the integration of experiments, theory, simulations, and data science. The development of high-throughput strategies that combine DFT calculations with machine learning has emerged as a powerful approach to discovering new materials. However, experimental validation is crucial to confirm the accuracy of these workflows.
View Article and Find Full Text PDFIt has recently been demonstrated that MoS with irregular interlayer rotations can achieve an extreme anisotropy in the lattice thermal conductivity (LTC), which is, for example, of interest for applications in waste heat management in integrated circuits. Here, we show by atomic-scale simulations based on machine-learned potentials that this principle extends to other two-dimensional materials, including C and BN. In all three materials, introducing drives the through-plane LTC to the glass limit, while the in-plane LTC remains almost unchanged compared to those of the ideal bulk materials.
View Article and Find Full Text PDFThe densification of integrated circuits requires thermal management strategies and high thermal conductivity materials. Recent innovations include the development of materials with thermal conduction anisotropy, which can remove hotspots along the fast-axis direction and provide thermal insulation along the slow axis. However, most artificially engineered thermal conductors have anisotropy ratios much smaller than those seen in naturally anisotropic materials.
View Article and Find Full Text PDFPoly(ethylene oxide) is demonstrated to be a suitable matrix polymer for the solution-doped conjugated polymer poly(3-hexylthiophene). The polarity of the insulator combined with carefully chosen processing conditions permits the fabrication of tens of micrometer-thick films that feature a fine distribution of the F4TCNQ dopant:semiconductor complex. Changes in electrical conductivity from 0.
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