Hematite's (α-FeO) major limitation to efficiently splitting water using sunlight is the low rate of the oxygen evolution reaction (OER). Thus, identifying the OER rate limiting step is a cornerstone to enhancing the current under low applied potential. Different measurement techniques showed similar absorption difference spectra during a change in applied potential on the hematite anode below and above the onset of the OER in the dark and under light. This absorption change was shown to result from surface modification during the OER, but the specific surface species could not be resolved. On the basis of ab initio calculations, we analyze the calculated absorption spectra in relation to previous measurements. We provide for the first time solid evidence to specify HO + *O → *OOH + H + e as the rate limiting step and *O as the bottleneck intermediate of the hematite OER.

Metal oxides are often used as catalysts for the oxygen evolution reaction which is of significant importance for water splitting as an alternative energy source. One of the best performing catalysts reported to date for water oxidation under alkaline conditions is nickel oxyhydroxide (NiOOH) doped with iron. However, NiOOH has hydrogen atoms whose positions are not known and may transfer through the material. In order to understand how hydrogen transfer affects catalytic efficiency, we use density functional theory+U (DFT+U) calculations that model oxygen evolution reaction catalysis for pure and Fe-doped NiOOH. Our calculations reveal that hydrogen transfer is possible in the Fe-doped case but is less probable in the pure case. The duality of proton and charge transfer at the surface of reactive materials provides further evidence to the effectiveness of doping for improving catalysis.

Diffusion describes the stochastic motion of particles and is often a key factor in determining the functionality of materials. Modeling diffusion of atoms can be very challenging for heterogeneous systems with high energy barriers. In this report, popular computational methodologies are covered to study diffusion mechanisms that are widely used in the community and both their strengths and weaknesses are presented. In static approaches, such as electronic structure theory, diffusion mechanisms are usually analyzed within the nudged elastic band (NEB) framework on the ground electronic surface usually obtained from a density functional theory (DFT) calculation. Another common approach to study diffusion mechanisms is based on molecular dynamics (MD) where the equations of motion are solved for every time step for all the atoms in the system. Unfortunately, both the static and dynamic approaches have inherent limitations that restrict the classes of diffusive systems that can be efficiently treated. Such limitations could be remedied by exploiting recent advances in artificial intelligence and machine learning techniques. Here, the most promising approaches in this emerging field for modeling diffusion are reported. It is believed that these knowledge-intensive methods have a bright future ahead for the study of diffusion mechanisms in advanced functional materials.observed in liquids, gases, and solid-state materials. One of the main cornerstones for the macroscopic understanding of diffusion was laid down in the mid-19th century by Adolf Fick. By observing Graham's experiments in gases and salt water, and by the analogy between Fourier's law of thermal conduction and diffusion, Fick developed two equations known as the Fick's laws , , , J D C x y z t

Nickel hydroxide phases are common in several energy conversion devices including battery electrochemical cell electrodes. These materials have a unique layered structure that may facilitate hydrogen transfer between oxygen sites and allow using this material also for proton conducting fuel cells. In order to assess this functionality, we use Density Functional Theory+U together with the Nudged Elastic Band method to calculate minimum energy diffusion paths and hydrogen vacancy formation energies of different crystal phases of NiOOH including β-NiOOH, β-Ni(OH)2 and α-Ni(OH)2. We follow several diffusion paths and mechanisms in several phases, both across layers and through them. We pin down the reason for efficient diffusion laterally on a layer and explain why diffusion through a layer is impossible. Our results suggest that hydrogen transfer may be possible for the β-NiOOH phase with hydrogen added interstitially and transferred along the layers. This study significantly advances our understanding of diffusion in an uncommonly structured material.

Efforts to improve energy storage depend greatly on the development of efficient electrode materials. Recently, strain has been employed as an alternate approach to improve ion mobility. While lattice strain has been well-researched in catalytic applications, its effects on electrochemical energy storage are largely limited to computational studies due to complexities associated with strain control in nanomaterials as well as loss of strain due to the phase change of the active material during charging–discharging. In this work, we overcome these challenges and investigate the effects of strain on supercapacitor performance in Li-ion-based energy devices. We synthesize epitaxial Fe3O4@MnFe2O4 (core@shell) nanoparticles with varying shell thickness to control the lattice strain. A narrow voltage window for electrochemical testing is used to limit the storage mechanism to lithiation–delithiation, preventing a phase change and maintaining structural strain. Cyclic voltammetry reveals a pseudocapacitive behavior and similar levels of surface charge storage in both strained- and unstrained-MnFe2O4 samples; however, diffusive charge storage in the strained sample is twice as high as the unstrained sample. The strained-MnFe2O4 electrode exceeds the performance of the unstrained-MnFe2O4 electrode in energy density by ∼33%, power density by ∼28%, and specific capacitance by ∼48%. Density functional theory shows lower formation energies for Li-intercalation and lower activation barrier for Li-diffusion in strained-MnFe2O4, corresponding to a threefold increase in the diffusion coefficient. The enhanced Li-ion diffusion rate in the strained-electrodes is further confirmed using the galvanostatic intermittent titration technique. This work provides a starting point to using strain engineering as a novel approach for designing high performance energy storage devices.

The charge transport properties in solids play an important role in the selection of materials for electrochemical devices. Spinels are a special class of solids that are very versatile and possess different properties based on changes in stoichiometry and cation distribution. In that way, their properties can be tailored to fit certain uses. Here we report a density functional theory study of the electronic structures of nine normal and inverse ternary AB2O4 (A, B= Fe, Co, Ni, Mn) and A3O4 spinels. We found that changing the cation distribution of CoMn2O4 into (Mn)[CoMn]O4 lowers the bandgap by about three times. Additionally, charge transport occurs mostly through octahedral sites while in (Co)[CoNi]O4 it occurs through tetrahedral sites. Bulk-based band alignment results are also reported for the spinels in this work in order to design materials with preferred charge transport pathways.

Abstract