Improving the electrocatalytic properties by regulating the surface electronic structure of supported metals has always been a hot issue in electrocatalysis. Herein, two novel catalysts Pd/B–N–Ti3C2 and Pd/N–B–Ti3C2 are used as the models to explore the effect of the B and N co-doping sequence on the surface electronic structure of metals, together with the electrocatalytic properties of ethanol oxidation reaction. The two catalysts exhibit obviously stratified morphology, and the Pd nanoparticles having the same amount are both uniformly distributed on the surface. However, the electron binding energy of Ti and Pd elements of Pd/B–N–Ti3C2 is smaller than that of Pd/N–B–Ti3C2. By exploring the electrocatalytic properties for EOR, it can be seen that all the electrochemical surface area, maximum peak current density, and antitoxicity of the Pd/B–N–Ti3C2 catalyst are much better than its counterpart. Such different properties of the catalysts can be attributed to the various doping species of B and N introduced by the doping sequence, which significantly affect the surface electronic structure and size distribution of supported metal Pd. Density functional theory calculations demonstrate that different B-doped species can offer sites for the H atom from CH3CH2OH of dehydrogenation in Pd/B–N–Ti3C2, thereby facilitating the progress of the EOR to a favorable pathway. This work provides a new insight into synthesizing the high-performance anode materials for ethanol fuel cells by regulating the supported metal catalyst with multielement doping.
This paper presents a variable-depth neighborhood search (VDNS) algorithm for solving the minimumconnected dominating-set problem. By considering the problem structure of the minimum-connected dominatingset problem, this paper introduces an effective partition-based neighborhood structure, which consists of a series of basic neighborhood moves, restricts the search space to traverse towards more promising search regions, and generates better solutions during the search. This paper also presents two techniques to further improve the search efficiency of the algorithm: pruning the search branch, and the incremental evaluation technique. Applying the proposed VDNS algorithm to solve the 91 public instances used in the literature, VDNS outperforms the reference algorithms in the literature by improving 38 of the best-known results, demonstrating the efficacy of the proposed VDNS algorithm.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.