A combinatorial descriptor for volcano relationships of electrochemical nitrogen reduction reaction

Though touted as a potential way to realize clean ammonia synthesis,electrochemical ammonia synthesis is currently limited by its catalytic efficiency.Great effort has been made to find catalysts with improved activity toward electrochemical nitrogen reduction reaction(eNRR).Rational screening of catalysts can be facilitated using the volcano relationship between catalytic activity and adsorption energy of an intermediate,namely,the activity descriptor.In this work,we proposeΔG^(*)_(NH_(2))+ΔG^(*)_(NNH)as a combinatorial descriptor,which shows better predictive power than traditional descriptors using the adsorption free energies of single intermediates.The volcano plots based on the combinatorial descriptor exhibits peak activity fixedly at the descriptor value corresponding to the formation free energy of NH3,regardless of the catalyst types;while the descriptor values correspond to the top activities for eNRR on volcano plots based on single descriptors usually vary with the types of catalysts.

Induced growth of Fe-N_x active sites using carbon templates

Highly active Fe-N_x sites that effectively improve the performance of non-precious metal electrocatalysts for oxygen reduction reactions（ORRs） are desirable. Herein, we propose a strategy for introducing a carbon template into a melamine/Fe-salt mixture to inductively generate highly active Fe-N_x sites for ORR. Using 57 Fe M？sbauer spectroscopy, X-ray photoelectron spectroscopy, and X-ray diffraction, we studied the structural composition of the Fe and N co-doped carbon catalysts.Interestingly, the results showed that this system not only converted inactive Fe and Fe-carbides into active Fe-N_4 and other Fe-nitrides, but also improved their intrinsic activities.

Understanding the sluggish and highly variable transport kinetics of lithium ions in LiFePO_4

LiFePO_(4),one of the mainstream cathode materials of current EV batteries,exhibits experimental diffusion coefficients(D_(c))of Li^(+)which are not only several orders of magnitude lower than those predicted by the ionic hopping barriers obtained from theoretical calculations and spectroscopic measurements,but also span several orders from 10^(-14)to 10^(-18)cm^(2)s^(-1)under different states of charge(SOC)and the charging rates(C-rates).Atomic level understanding of such sluggishness and diversity of Li^(+)transport kinetics would be of significance in improving the rate performance of LiFePO_(4)through material and operation optimization but remain challenging.Herein,we show that the high sensitivity of Li^(+)hopping barriers on the local Li–Li coordination environments(numbers and configurations)plays a key role in the ion transport kinetics.This is due a neural network-based deep potential(DP)which allows accurate and efficient calculation of hopping barriers of Li^(+)in LiFePO_(4)with various Li–Li coordination environments,with which the kinetic Monte-Carlo(KMC)method was employed to determine the D_(c)values at various C-rates and SOC across a broad spectrum.Especially,an accelerated KMC simulation strategy is proposed to obtain the D_(c)values under a wide range of SOC at low C-rates,which agree well with that obtained from the galvanostatic intermittent titration technique(GITT).The present study provides accurate descriptions of Li^(+)transport kinetics at both very high and low C-rates,which remains challenging to experiments and first-principles calculations,respectively.Finally,it is revealed that the gradient distributions of Li^(+)density along the diffusion path result in great asymmetry in the barriers of the forward and backward hopping,causing very slow diffusion of Li^(+)and the diverse variation of D_(c).

Discrepant roles of adsorbed OH^* species on IrWOx for boosting alkaline hydrogen electrocatalysis

Improving the slow kinetics of alkaline hydrogen electrode reactions, involving hydrogen oxidation and evolution reactions(HOR/HER) is highly desirable for accelerating the commercialization of alkaline exchange membrane-based fuel cells(AEMFCs) and water electrolyzers(AEMWEs). However, fundamental understanding of the mechanism for HOR/HER catalysis under alkaline media is still debatable. Here we develop an amorphous tungsten oxide clusters modified iridium-tungsten nanocrystallines(Ir WOx)which exhibited by far the highest exchange current density and mass activity, about three times higher than the commercial Pt/C toward alkaline HOR/HER. Density functional theory(DFT) calculations reveal the WOxclusters act as a pivotal role to boost reversible hydrogen electrode reactions in alkaline condition but via different mechanisms, which are, hydrogen binding energy(HBE) mechanism for HOR and bifunctional mechanism for HER. This work is expected to promote our fundamental understanding about the alkaline HOR/HER catalysis and provide a new avenue for rational design of highly efficient electrocatalysts toward HOR/HER under alkaline electrolytes.

A potential-driven switch of activity promotion mode for the oxygen evolution reaction at Co_(3)O_(4)/NiO_(x)H_(y) interface

Co_(3)O_(4)spinel oxides have manifested promising activity toward the oxygen evolution reaction(OER)through effective modifications.For them to become top electrocatalysts,however,accurate accounts of the catalytic kinetics are essential to gain a deep understanding of the activity promotion mechanisms.Herein,we use a newly proposed kinetic model based on energetic span as the rate-determining term for the electrocatalytic reaction to throw light on the promotion mechanism of Co_(3)O_(4)interfaced with nickel hydroxides(NiO_(x)H_(y))for the OER.We find that depending on the electrode potential,the OER kinetics at the designed interface between Co_(3)O_(4)and NiO_(x)H_(y)are boosted in entirely different ways.As a result,the OER can occur at a lower onset potential as well as a low Tafel slope.This work emphasizes the benefit of using rational theoretical models for electrocatalyst design.

Ion-vacancy coupled charge transfer model for ion transport in concentrated solutions

We present a conceptual framework for understanding and formulating ion transport in concentrated solutions, which pictures the ion transport as an ion-vacancy coupled charge transfer reaction. A key element in this picture is that the transport of an ion from an occupied to unoccupied site involves a transition state which exerts double volume exclusion. An ab initio random walk model is proposed to describe this process. Subsequent coarse-graining results in a continuum formula as a function of chemical potentials of the constituents, which are further derived from a lattice-gas model. The subtlety here is that what has been taken to be the chemical potential of the ion in the past is actually that of the ion-vacancy couple. By aid of this new concept, the driving force of ion transport is essentially the chemical affinity of the ion-vacancy coupled charge transfer reaction, which is a useful concept to unify transport and reaction, two fundamental processes in electrochemistry. This phenomenological model is parameterized for a specific material by the aid of first-principles calculations. Moreover, its extension to multiple-component systems is discussed.

Density functional theory (DFT)-based modified embedded atom method potentials: Bridging the gap between nanoscale theoretical simulations and DFT calculations

A density functional theory (DFT)-calculation scheme for constructing the modified embedded atom method (MEAM) potentials for face-centered cubic (fcc) metals is presented. The input quantities are carefully selected and a more reliable DFT approach for surface energy determination is introduced in the parameterization scheme, enabling MEAM to precisely predict the surface and nanoscale properties of metallic materials. Molecular dynamics simulations on Pt and Au crystals show that the parameterization employed leads to significantly improved accuracy of MEAM in calculating the surface and nanoscale properties, with the results agreeing well with both DFT calculations and experimental observations. The present study implies that rational DFT parameterization of MEAM may lead to a theoretical tool to bridge the gap between nanoscale theoretical simulations and DFT calculations.

High-Performance Ru_(2)P Anodic Catalyst for Alkaline Polymer Electrolyte Fuel Cells

Exploring efficient and economical electrocatalysts and understanding the mechanism for alkaline hydrogen oxidation reaction(HOR)are crucial to facilitate the development of alkaline polymer electrolyte fuel cells(APEFCs).Herein,Ru_(2)P was synthesized and used as an anodic HOR electrocatalyst for APEFC,achieving a peak power density of 1.3 W cm^(−2),the highest value among Pt-free anode electrocatalysts reported under the same conditions.Fromthe density functional theory(DFT)calculations and experimental results,it was found that besides the optimized hydrogen binding energy,the enhanced adsorption strength of oxygenated species(OH*)and the reduced work function of Ru_(2)P contributed to the enhanced HOR performance.The normalized exchange current densities of Ru_(2)P/C were 0.37 mA cm_(ECSA)^(−2) and 0.27 mAμgRu^(−1),respectively,both approximately three times higher than those of Ru when conducted in the rotating disk electrode(RDE)system.Our work provides a new pathway for exploring highly active Pt-free HOR electrocatalysts and expanding the family of anodic electrocatalysts for APEFCs.