Three-dimensional (3D) lithiophilic host is one of the most effective ways to regulate the Li dendrites and volume change in working Li metal anode. The state-of-the-art 3D lithiophilic hosts are facing one main challenge in that the lithiophilic layer would melt or fall off in high-temperature environment when using the thermal infusion method. Herein, a 3D porous CuZn alloy host containing anchored lithiophilic Zn sites is employed to prestore Li using the thermal infusion strategy, and a 3D composite Li is thus fabricated. Benefiting from the lithiophilic Zn sites with a strong adsorption capacity with Li, which is based on the analyses of the nucleation overpotential, binding energy calculation, and the operando optical observation of Li plating/stripping behaviors, facile uniform Li nucleation and dendrite-free Li deposition could be achieved in the interior of the 3D porous CuZn alloy host and the 3D composite Li shows remarkable enhancement in electrochemical performance.

No abstract

Abstract-This paper studies the problem of stochastic dynamic pricing and energy management policy for electric vehicle (EV) charging service providers. In the presence of renewable energy integration and energy storage system, EV charging service providers must deal with multiple uncertainties -charging demand volatility, inherent intermittency of renewable energy generation, and wholesale electricity price fluctuation. The motivation behind our work is to offer guidelines for charging service providers to determine proper charging prices and manage electricity to balance the competing objectives of improving profitability, enhancing customer satisfaction, and reducing impact on power grid in spite of these uncertainties. We propose a new metric to assess the impact on power grid without solving complete power flow equations. To protect service providers from severe financial losses, a safeguard of profit is incorporated in the model. Two algorithms -stochastic dynamic programming (SDP) algorithm and greedy algorithm (benchmark algorithm) -are applied to derive the pricing and electricity procurement policy. A Pareto front of the multiobjective optimization is derived. Simulation results show that using SDP algorithm can achieve up to 7% profit gain over using greedy algorithm. Additionally, we observe that the charging service provider is able to reshape spatial-temporal charging demands to reduce the impact on power grid via pricing signals.

Two nanostructured proton-containing δ-MnO2 (H-δ-MnO2) materials were synthesized through proton exchange for K-containing δ-MnO2 (K-δ-MnO2) nanosheets and nanoparticles prepared by the hydrothermal homogeneous precipitation method and solid-state reaction.

No abstract