2020, Philipp, Martin, Gadermaier, Bernhard, Posch, Patrick, Hanzu, Ilie, Ganschow, Steffen, Meven, Martin, Rettenwander, Daniel, Redhammer, Günther J., Wilkening, H. Martin R.

The next-generation of all-solid-state lithium batteries need ceramic electrolytes with very high ionic conductivities. At the same time a negligible electronic conductivity σeon is required to eliminate self-discharge in such systems. A non-negligible electronic conductivity may also promote the unintentional formation of Li dendrites, being currently one of the key issues hindering the development of long-lasting all-solid-state batteries. This interplay is suggested recently for garnet-type Li7La3Zr2O12 (LLZO). It is, however, well known that the overall macroscopic electronic conductivity may be governed by a range of extrinsic factors such as impurities, chemical inhomogeneities, grain boundaries, morphology, and size effects. Here, advantage of Czochralski-grown single crystals, which offer the unique opportunity to evaluate intrinsic properties of a chemically homogeneous matrix, is taken to measure the electronic conductivity σeon. Via long-time, high-precision potentiostatic polarization experiments an upper limit of σeon in the order of 5 × 10−10 S cm−1 (293 K) is estimated. This value is by six orders of magnitude lower than the corresponding total conductivity σtotal = 10−3 S cm−1 of Ga-LLZO. Thus, it is concluded that the high values of σeon recently reported for similar systems do not necessarily mirror intragrain bulk properties of chemically homogenous systems but may originate from chemically inhomogeneous interfacial areas. © 2020 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

2020, Lorenz-Meyer, M. Nicolai L., Menzel, Robert, Dadzis, Kaspars, Nikiforova, Angelina, Riemann, Helge

In the present paper, a lumped parameter model for the novel Silicon Granulate Crucible (SiGC) method is proposed, which is the basis for a future model-based control system for the process. The model is analytically deduced based on the hydromechanical, geometrical, and thermal conditions of the process. Experiments are conducted to identify unknown model parameters and to validate the model. The physical consistency of the model is verified using simulation studies and a prediction error of below 2% is reached. © 2020 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim