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  1. To reduce the cobalt (Co) content in lithium-ion batteries, Ni-rich (high-Ni) lithium nickel manganese cobalt oxides (NMC) are pursued as one of the next-generation cathode materials. However, there is still debate on the crystal and electronic structures of the baseline, LiNiO2. Density Functional Theory (DFT) calculations were performed to provide a theoretical understanding of Ni-rich NMC. First, it was found that the commonly used R m structure for LiNiO2 is metallic, contrary to the experimentally reported mix-conducting behavior. Among the four different space groups, R m, C2/m, P21/c, and P2/c, P2/c with charge disproportionation of Ni2+ and Ni4+ is the most energetically stable and semiconducting structure of LiNiO2. Therefore, the atomic structures of representative Ni-rich NMC were built by partially replacing Ni with Co or Mn in the P2/c LiNiO2 to form LixNiyMnzCo1-y-zO2. In the fully lithiated (x = 1.0) high Ni content NMC (y > 0.5), the oxidation state of all Mn ions becomes 4+, while Co ions still maintain 3+, and part of the Ni ions become 2+ to compensate for the charge. Upon delithiation, the local environment shows more variation of the charge states on the transition metal (TM) ions. The average oxidation on each TM follows a sequence of losing electrons that starts from Ni2+ to Ni3+, then oxidizing Ni3+ and Co3+, while Mn4+ remains electrochemically inactive till x = 0. A general relationship for the oxidation state change in each TM as a function of x and y is derived and shows agreement with both modeling and experimental data. 
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  8. In this paper, we consider a large-scale heterogeneous mobile edge computing system, where each device’s mean computing task arrival rate, mean service rate, mean energy consumption, and mean offloading latency are drawn from different bounded continuous probability distributions to reflect the diverse compute-intensive applications, mobile devices with different computing capabilities and battery efficiencies, and different types of wireless access networks (e.g., 4G/5G cellular networks, WiFi). We consider a class of distributed threshold-based randomized offloading policies and develop a threshold update algorithm based on its computational load, average offloading latency, average energy consumption, and edge server processing time, depending on the server utilization. We show that there always exists a unique Mean-Field Nash Equilibrium (MFNE) in the large-system limit when the task processing times of mobile devices follow an exponential distribution. This is achieved by carefully partitioning the space of mean arrival rates to account for the discrete structure of each device’s optimal threshold. Moreover, we show that our proposed threshold update algorithm converges to the MFNE. Finally, we perform simulations to corroborate our theoretical results and demonstrate that our proposed algorithm still performs well in more general setups based on the collected real-world data and outperforms the well-known probabilistic offloading policy. 
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    Free, publicly-accessible full text available July 1, 2024
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