ABSTRACT
The electrocatalytic 5-hydroxymethylfurfural (HMF) oxidation reaction coupling with hydrogen evolution reaction (HER) serves as a promising strategy to generate both high-value-added products and clean energy, which is limited by the poor catalytic efficiency of bifunctional electrocatalysts and unclear electrocatalytic mechanism for HMF oxidation reaction. Herein, we fabricate a bifunctional NiSe2-NiMoO4 heterostructure nanowire electrocatalyst for the conversion of HMF to 2,5-furandicarboxylic acid (FDCA) and simultaneous H2 production. As expected, the NiSe2-NiMoO4 exhibits outstanding activity and selectivity toward HMF oxidation reaction. In particular, at a potential of 1.50 V, the yield of FDCA could reach 98 % with a faradaic efficiency of 96.5 %, as well as excellent stability. Density functional theory calculation results demonstrate that the NiSe2-NiMoO4 heterostructure could tune the adsorption energy of HMF, facilitate high-valence active species formation, and enhance electronic conductivity. Furthermore, a two-electrode electrolyzer assembled using NiSe2-NiMoO4 as a bifunctional catalyst requires 1.53 V to acquire a current density of 50 mA cm-2, which is 201 mV lower than that of water electrolysis. This work provides new insights for designing multifunctional catalysts for biomass upgrading coupled with hydrogen evolution.
ABSTRACT
Despite the abundant research on energy-efficient rate scheduling polices in energy harvesting communication systems, few works have exploited data sharing among multiple applications to further enhance the energy utilization efficiency, considering that the harvested energy from environments is limited and unstable. In this paper, to overcome the energy shortage of wireless devices at transmitting data to a platform running multiple applications/requesters, we design rate scheduling policies to respond to data requests as soon as possible by encouraging data sharing among data requests and reducing the redundancy. We formulate the problem as a transmission completion time minimization problem under constraints of dynamical data requests and energy arrivals. We develop offline and online algorithms to solve this problem. For the offline setting, we discover the relationship between two problems: the completion time minimization problem and the energy consumption minimization problem with a given completion time. We first derive the optimal algorithm for the min-energy problem and then adopt it as a building block to compute the optimal solution for the min-completion-time problem. For the online setting without future information, we develop an event-driven online algorithm to complete the transmission as soon as possible. Simulation results validate the efficiency of the proposed algorithm.
