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Abstract The current change in battery technology followed by the almost immediate adoption of lithium as a key resource powering our energy needs in various applications is undeniable. Lithium-ion batteries (LIBs) are at the forefront of the industry and offer excellent performance. The application of LIBs is expected to continue to increase. The adoption of renewable energies has spurred this LIB proliferation and resulted in a dramatic increase in LIB waste. In this review, we address waste LIB collection and segregation approaches, waste LIB treatment approaches, and related economics. We have coined a “green score” concept based on a review of several quantitative analyses from the literature to compare the three mainstream recycling processes: pyrometallurgical, hydrometallurgical, and direct recycling. In addition, we analyze the current trends in policymaking and in government incentive development directed toward promoting LIB waste recycling. Future LIB recycling perspectives are analyzed, and opportunities and threats to LIB recycling are presented. 

Abstract In this paper, we study a new discrete tree and the resulting branching process, which we call the erlang weighted tree(EWT). The EWT appears as the local weak limit of a random graph model proposed in La and Kabkab, Internet Math. 11 (2015), no. 6, 528–554. In contrast to the local weak limit of well‐known random graph models, the EWT has an interdependent structure. In particular, its vertices encode a multi‐type branching process with uncountably many types. We derive the main properties of the EWT, such as the probability of extinction, growth rate, and so forth. We show that the probability of extinction is the smallest fixed point of an operator. We then take a point process perspective and analyze the growth rate operator. We derive the Krein–Rutman eigenvalue and the corresponding eigenfunctions of the growth operator, and show that the probability of extinction equals one if and only if .