Chemical speciation changes of an all-solid-state lithium-ion battery caused by roasting determined by sequential acid leaching.

All-solid-state lithium-ion batteries (ASS-LIBs) are expected to replace current liquid-based LIBs in the near future owing to their high energy density and improved safety. It would be preferable if ASS-LIBs could be recycled by the current recycling processes used for liquid-based LIBs, but this possibility remains to be determined. Here, we subjected an ASS-LIB test cell containing an argyrodite-type solid electrolyte (Li6PS5Cl) and nickel-manganese-cobalt-type active material (Li(Ni0.5Mn0.3Co0.2)O2) to roasting, a treatment process commonly used for recycling of the valuable metals from liquid-based LIBs, and investigated the changes in chemical speciation. Roasting was performed at various temperatures (350-900 °C), for various times (60-360 min), and under various oxygen fugacity (air or O2) conditions. The chemical speciation of each metal element after roasting was determined by sequential elemental leaching tests and X-ray diffraction analysis. Li formed sulfates or phosphates over a wide temperature range. Ni and Co followed very complicated reaction paths owing to coexistence of S, P, and C, and they formed sulfides, phosphates, and complex oxides. The optimum conditions for minimizing formation of insoluble compounds, such as complex oxides, were a roasting temperature of 450-500 °C and a roasting time of 120 min. The results indicated that although ASS-LIBs can be treated by the same roasting processes as those used for current liquid-based LIBs, the optimal roasting conditions have narrow ranges. Thus, careful process control will be needed to achieve high extraction percentages of the valuable metals from ASS-LIBs.

Estimating asymptotic phase and amplitude functions of limit-cycle oscillators from time series data.

We propose a method for estimating the asymptotic phase and amplitude functions of limit-cycle oscillators using observed time series data without prior knowledge of their dynamical equations. The estimation is performed by polynomial regression and can be solved as a convex optimization problem. The validity of the proposed method is numerically illustrated by using two-dimensional limit-cycle oscillators as examples. As an application, we demonstrate data-driven fast entrainment with amplitude suppression using the optimal periodic input derived from the estimated phase and amplitude functions.

Sparse optimization of mutual synchronization in collectively oscillating networks.

We consider a pair of collectively oscillating networks of dynamical elements and optimize their internetwork coupling for efficient mutual synchronization based on the phase reduction theory developed by Nakao et al. [Chaos 28, 045103 (2018)]. The dynamical equations describing a pair of weakly coupled networks are reduced to a pair of coupled phase equations, and the linear stability of the synchronized state between the networks is represented as a function of the internetwork coupling matrix. We seek the optimal coupling by minimizing the Frobenius and L1 norms of the internetwork coupling matrix for the prescribed linear stability of the synchronized state. Depending on the norm, either a dense or sparse internetwork coupling yielding efficient mutual synchronization of the networks is obtained. In particular, a sparse yet resilient internetwork coupling is obtained by L1-norm optimization with additional constraints on the individual connection weights.