Promoted self-construction of β-NiOOH in amorphous high entropy electrocatalysts for the oxygen evolution reaction

The exploration of an efficient electrocatalyst for the oxygen evolution reaction (OER) is urgently required for sustainable renewable-energy conversion and storage. Due to the increased chemical complexity, multimetallic catalysts provide flexibility to alter their electronic and crystal structure to attain a superior intrinsic catalytic activity via synergistic effects, which is seldom accomplished using single metal catalysts. However, the high chemical complexity increases the difficulty to prepare elemental homogenous catalysts and reveal their synergistic effect during OER process, which further hinder the design of multimetallic catalysts. Here, high entropy concept is utilized to design an NiFeCoMnAl oxide with amorphous structure as OER catalyst. The direct evidence of active Ni sites is provided by the operando Raman measurements and Fe can modify oxygen intermediates binding energy on Ni sites. The X-ray photoelectron spectroscopy (XPS) and X-ray absorption spectroscopy (XAS) reveal that the incorporation of Mn can construct the electron-rich environment of active Ni center, and the relatively lower oxidation state of Ni facilitates the self-construction of β-NiOOH intermediates, which shows promoted OER activity as confirmed by density functional theory calculations. Doping Co can enhance the conductivity and doping Al leads to the formation of nanoporous structure through dealloying process, thus each component is essential for improving OER performance. The optimized NiFeCoMnAl catalyst exhibits an overpotential of 190 mV at 10 mA cm−2 in 1 M KOH solution, much superior to the ternary and quaternary counterparts. This work sheds light on understanding the origin of high entropy catalysts’ OER activity and thereby enables the rational design of multinary transition metallic catalysts

A Surface Reconstruction Route to High Productivity and Selectivity in CO2 Electroreduction toward C2+ Hydrocarbons

© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim Electrochemical carbon dioxide reduction (CO2) is a promising technology to use renewable electricity to convert CO2 into valuable carbon-based products. For commercial-scale applications, however, the productivity and selectivity toward multi-carbon products must be enhanced. A facile surface reconstruction approach that enables tuning of CO2-reduction selectivity toward C2+ products on a copper-chloride (CuCl)-derived catalyst is reported here. Using a novel wet-oxidation process, both the oxidation state and morphology of Cu surface are controlled, providing uniformity of the electrode morphology and abundant surface active sites. The Cu surface is partially oxidized to form an initial Cu (I) chloride layer which is subsequently converted to a Cu (I) oxide surface. High C2+ selectivity on these catalysts are demonstrated in an H-cell configuration, in which 73% Faradaic efficiency (FE) for C2+ products is reached with 56% FE for ethylene (C2H4) and overall current density of 17 mA cm-2. Thereafter, the method into a flow-cell configuration is translated, which allows operation in a highly alkaline medium for complete suppression of CH4 production. A record C2+ FE of ≈84% and a half-cell power conversion efficiency of 50% at a partial current density of 336 mA cm-2 using the reconstructed Cu catalyst are reported

ELSI: A unified software interface for Kohn–Sham electronic structure solvers

Solving the electronic structure from a generalized or standard eigenproblem is often the bottleneck in large scale calculations based on Kohn–Sham density-functional theory. This problem must be addressed by essentially all current electronic structure codes, based on similar matrix expressions, and by high-performance computation. We here present a unified software interface, ELSI, to access different strategies that address the Kohn–Sham eigenvalue problem. Currently supported algorithms include the dense generalized eigensolver library ELPA, the orbital minimization method implemented in libOMM, and the pole expansion and selected inversion (PEXSI) approach with lower computational complexity for semilocal density functionals. The ELSI interface aims to simplify the implementation and optimal use of the different strategies, by offering (a) a unified software framework designed for the electronic structure solvers in Kohn–Sham density-functional theory; (b) reasonable default parameters for a chosen solver; (c) automatic conversion between input and internal working matrix formats, and in the future (d) recommendation of the optimal solver depending on the specific problem. Comparative benchmarks are shown for system sizes up to 11,520 atoms (172,800 basis functions) on distributed memory supercomputing architectures. Program summary Program title: ELSI Interface Program Files doi: http://dx.doi.org/10.17632/y8vzhzdm62.1 Licensing provisions: BSD 3-clause Programming language: Fortran 2003, with interface to C/C++ External routines/libraries: MPI, BLAS, LAPACK, ScaLAPACK, ELPA, libOMM, PEXSI, ParMETIS, SuperLU_DIST Nature of problem: Solving the electronic structure from a generalized or standard eigenvalue problem in calculations based on Kohn–Sham density functional theory (KS-DFT). Solution method: To connect the KS-DFT codes and the KS electronic structure solvers, ELSI provides a unified software interface with reasonable default parameters, hierarchical control over the interface and the solvers, and automatic conversions between input and internal working matrix formats. Supported solvers are: ELPA (dense generalized eigensolver), libOMM (orbital minimization method), and PEXSI (pole expansion and selected inversion method). Restrictions: The ELSI interface requires complete information of the Hamiltonian matrix