Thanks to the low cost and earth's abundant potassium resources, potassium ion batteries (PIBs) have attracted much interest as alternative energy storage devices. However, there is still a great challenge to develop suitable anode materials for PIBs with high specific capacity, fast charge/discharge and stable ion storage. Nowadays, conductive metal-organic frameworks (c-MOFs) with excellent physicochemical properties are employed for different electrochemical applications, but the study of their potassium storage performance remains unknown, and the detailed potassium storage mechanism needs to be explored. Herein, nanostructured Co₃(HHTP)₂ c-MOF (Co-CAT MOF, HHTP: 2,3,6,7,10,11-hexahydroxytriphenylene) is synthesized by a liquid-phase method and evaluated as the anode for PIBs. The active sites and open pathways in the conductive Co-CAT MOF promote ion diffusion and electron transfer, exhibiting high reversible specific capacity (332 mA h g⁻¹ at 0.1 A g⁻¹), excellent long-cycle stability (230 mA h g⁻¹ at the current density of 1.0 A g⁻¹ after 700 cycles) and outstanding rate performance (165 mA h g⁻¹ at 4.0 A g⁻¹), which is superior to the typical PIB anodes. Combined with different ex situ characterization techniques, the potassium storage mechanism based on 8-electron transfer is revealed. Furthermore, Co-CAT MOF exhibits excellent Li-ion storage performance. In the half-cell, the Co-CAT MOF electrode displays a high reversible capacity of 800 mA h g⁻¹ at 200 mA g⁻¹. In addition, the Co-CAT//LiCoO₂ full cell cycles for 100 cycles at 200 mA h g⁻¹. It is believed that Co-CAT MOF is a promising electrode material for potassium/lithium storage, and the proposed ion storage mechanism can be used to discover other MOF-based electrodes for energy storage.

The work presented in this paper concerns a switching-based control formulation for multi-intersection and multiphase traffic light systems. A macroscopic traffic flow modeling approach is first presented, which is instrumental to the development of a model-based and switching-based optimization method for traffic signal operation, in the framework of adaptive dynamic programming (ADP). The main advantage of the switching-based formulation is its capability to determine both 'when' to switch and 'which' mode to switch on without the need to use the cycle-based average flow approximation typical of state-of-the-art formulations. In addition, the framework can handle different cycle times across intersections without the need for synchronization constraints and, moreover, minimum dwell-time constraints can be directly enforced to comply with minimum green/red times in each phase. The simulation experiments on a multi-intersection and multiphase traffic light systems are presented to show the effectiveness of the method.