Objective evaluation of the performance of electrocatalysts for CO_2 reduction has been complicated by a lack of standardized methods for measuring and reporting activity data. In this perspective, we advocate that standardizing these practices can aid in advancing research efforts toward the development of efficient and selective CO_2 reduction electrocatalysts. Using information taken from experimental studies, we identify variables that influence the measured activity of CO_2 reduction electrocatalysts and propose procedures to account for these variables in order to improve the accuracy and reproducibility of reported data. We recommend that catalysts be measured under conditions which do not introduce artifacts from impurities, from either the electrolyte or counter electrode, and advocate the acquisition of data measured in the absence of mass transport effects. Furthermore, measured rates of electrochemical reactions should be normalized to both the geometric electrode area as well as the electrochemically active surface area to facilitate the comparison of reported catalysts with those previously known. We demonstrate that, when these factors are accounted for, the CO_2 reduction activities of Ag and Cu measured in different laboratories exhibit little difference. Adoption of the recommendations presented in this perspective would greatly facilitate the identification of superior catalysts for CO_2 reduction arising solely from changes in their composition and pretreatment.

Methane is a relatively inexpensive and abundant resource and its partial transformation to chemicals and chemical fuels presents attractive yet challenging pathways for its utilization. Conventional synthesis for methanol involve a multistep process involving steam reforming of methane with subsequent catalytic reactions, which require high energy input and run at high cost [1]. Alternatively, methane oxidation over catalyst surfaces in an electrochemical cell is a promising single-step approach to achieve a direct conversion of methane to methanol at lower temperatures and low cost [2]. Previous studies have demonstrated that methane can be electrochemically converted into methanol with high selectivity but with low overall conversion efficiency. Increasing the rate of methane conversion can be achieved by systematic improvement of the electrochemical cell design along with the concurrent development of new efficient catalysts materials. Methane oxidation is energetically challenging process and dual role of the catalysts involve first, activation of the relatively inert C-H bond enabling the oxidative hydroxylation, and methanol formation. Second, the effective catalysts should simultaneously inhibit the methanol oxidation, which proceeds with a much lower energy barrier and can result in the formation of formaldehyde, formic acid, carbon monoxide, and carbon dioxide. To date, a variety of the catalysts, among different supported metals (Pd, Ru, Au, Ag) and metal oxides (V 2 O 5 , Fe 2 O 3 , CoO, Mn 2 O 3 , MoO 3 , CrO), have been tested in electrochemical cell and shown promise for the direct oxidation of methane [2]. However, further systematic studies are essential for understanding the mechanism for methane oxidation, enabling catalysts rational design. On the other hand, bioinspired supported binuclear metal catalysts show potential for high selectivity and conversion [3], but have not yet been explored for electrochemical methane conversion. In this study, first-row transition metal oxides as well as single and binuclear catalysts, supported on well-defined crystalline 2D materials including carbides, oxides, and nitrides will be presented. The catalysts are synthesized with wet-chemical synthesis routes and subsequently fabricated in membrane electrode assembly for testing their activity, methanol selectivity, and conversion efficiency in an electrochemical fuel-cell-type reactor. In-depth structural and chemical analyses of catalysts using a combination of various transmission electron microscopy techniques, complimented with spectroscopy analyses is used to establish structure-property relationship. These insights will provide valuable basis for a scientific-guided approach toward the optimization of the known, and the identification of the new metal oxide and single-site supported catalysts for this challenging process. Ravi, M., et al, Angew. Chemie Int. Ed., 2017 , 56 , 26464. Tomita, A., et al, Angew. Chemie Int. Ed., 2008 , 47 , 1462. Starokon, E. V., Phys Chem. C. , 2011 , 115 , 2155.

Many multicomponent materials exhibit significant configurational disorder. Diffusing ions in such materials migrate along a network of sites that have different energies and that are separated by configuration dependent activation barriers. We describe a formalism that enables a first-principles calculation of the diffusion coefficient in solids exhibiting configurational disorder. The formalism involves the implementation of a local cluster expansion to describe the configuration dependence of activation barriers. The local cluster expansion serves as a link between accurate first-principles calculations of the activation barriers and kinetic Monte Carlo simulations. By introducing a kinetically resolved activation barrier, we show that a cluster expansion for the thermodynamics of ionic disorder can be combined with a local cluster expansion to obtain the activation barrier for migration in any configuration. This ensures that in kinetic Monte Carlo simulations, detailed balance is maintained at all times and kinetic quantities can be calculated in a properly equilibrated thermodynamic state. As an example, we apply this formalism for an investigation of lithium diffusion in ${\mathrm{Li}}_{x}{\mathrm{CoO}}_{2}.$ A study of the activation barriers in ${\mathrm{Li}}_{x}{\mathrm{CoO}}_{x}$ within the local density approximation shows that the migration mechanism and activation barriers depend strongly on the local lithium-vacancy arrangement around the migrating lithium ion. By parametrizing the activation barriers with a local cluster expansion and applying it in kinetic Monte Carlo simulations, we predict that lithium diffusion in layered ${\mathrm{Li}}_{x}{\mathrm{CoO}}_{2}$ is mediated by divacancies at all lithium concentrations. Furthermore, due to a strong concentration dependence of the activation barrier, the predicted diffusion coefficient varies by several orders of magnitude with lithium concentration x.

Electrochemical synthesis possesses substantial promise to utilize renewable energy sources to power the conversion of abundant feedstocks to value-added commodity chemicals and fuels. Of the potential system architectures for these processes, only systems employing 3-D structured porous electrodes have the capacity to achieve the high rates of conversion necessary for industrial scale. However, the phenomena and environments in these systems are not well understood and are challenging to probe experimentally. Fortunately, continuum modeling is well-suited to rationalize the observed behavior in electrochemical synthesis, as well as to ultimately provide recommendations for guiding the design of next-generation devices and components. In this review, we begin by presenting an historical review of modeling of porous electrode systems, with the aim of showing how past knowledge of macroscale modeling can contribute to the rising challenge of electrochemical synthesis. We then present a detailed overview of the governing physics and assumptions required to simulate porous electrode systems for electrochemical synthesis. Leveraging the developed understanding of porous-electrode theory, we survey and discuss the present literature reports on simulating multiscale phenomena in porous electrodes in order to demonstrate their relevance to understanding and improving the performance of devices for electrochemical synthesis. Lastly, we provide our perspectives regarding future directions in the development of models that can most accurately describe and predict the performance of such devices and discuss the best potential applications of future models.

The partition functions, heat capacities, entropies, and enthalpies of selected molecules were calculated using uncoupled mode (UM) approximations, where the full-dimensional potential energy surface for internal motions was modeled as a sum of independent one-dimensional potentials for each mode. The computational cost of such approaches scales the same with molecular size as standard harmonic oscillator vibrational analysis using harmonic frequencies (HO(hf)). To compute thermodynamic properties, a computational protocol for obtaining the energy levels of each mode was established. The accuracy of the UM approximation depends strongly on how the one-dimensional potentials of each modes are defined. If the potentials are determined by the energy as a function of displacement along each normal mode (UM-N), the accuracies of the calculated thermodynamic properties are not significantly improved versus the HO(hf) model. Significant improvements can be achieved by constructing potentials for internal rotations and vibrations using the energy surfaces along the torsional coordinates and the remaining vibrational normal modes, respectively (UM-VT). For hydrogen peroxide and its isotopologs at 300 K, UM-VT captures more than 70% of the partition functions on average. By contrast, the HO(hf) model and UM-N can capture no more than 50%. For a selected test set of C2 to C8 linear and branched alkanes and species with different moieties, the enthalpies calculated using the HO(hf) model, UM-N, and UM-VT are all quite accurate comparing with reference values though the RMS errors of the HO model and UM-N are slightly higher than UM-VT. However, the accuracies in entropy calculations differ significantly between these three models. For the same test set, the RMS error of the standard entropies calculated by UM-VT is 2.18 cal mol(-1) K(-1) at 1000 K. By contrast, the RMS error obtained using the HO model and UM-N are 6.42 and 5.73 cal mol(-1) K(-1), respectively. For a test set composed of nine alkanes ranging from C5 to C8, the heat capacities calculated with the UM-VT model agree with the experimental values to within a RMS error of 0.78 cal mol(-1) K(-1), which is less than one-third of the RMS error of the HO(hf) (2.69 cal mol(-1) K(-1)) and UM-N (2.41 cal mol(-1) K(-1)) models.

Abstract Renewable fuel generation is essential for a low carbon footprint economy. Thus, over the last five decades, a significant effort has been dedicated towards increasing the performance of solar fuels generating devices. Specifically, the solar to hydrogen efficiency of photoelectrochemical cells has progressed steadily towards its fundamental limit, and the faradaic efficiency towards valuable products in CO 2 reduction systems has increased dramatically. However, there are still numerous scientific and engineering challenges that must be overcame in order to turn solar fuels into a viable technology. At the electrode and device level, the conversion efficiency, stability and products selectivity must be increased significantly. Meanwhile, these performance metrics must be maintained when scaling up devices and systems while maintaining an acceptable cost and carbon footprint. This roadmap surveys different aspects of this endeavor: system benchmarking, device scaling, various approaches for photoelectrodes design, materials discovery, and catalysis. Each of the sections in the roadmap focuses on a single topic, discussing the state of the art, the key challenges and advancements required to meet them. The roadmap can be used as a guide for researchers and funding agencies highlighting the most pressing needs of the field.

Structural and chemical disorder are part of almost any engineering material. Their detailed characterization with theoretical and experimental approaches therefore forms the cornerstone of modern materials science and engineering. To assess the state of this field, the Workshop on Thermodynamic and Structural Properties of Alloy Materials was held on 20-24 June 1999 at the Sonesta Hotel in Oranjestad, Aruba. The workshop brought together experimentalists and theorists in the fields of metals, oxides and semiconductors. Particular emphasis was placed on efforts to transfer the success of first-principles modelling of configurational disorder to topological disorder, as occurs in metallic glasses and liquids. Fittingly, the workshop was dedicated to Professor de Fontaine of the University of California at Berkeley, whose influence on the field of order-disorder reactions and first-principles phase diagram calculations has been of key importance to the development of the subject.

The dehydrogenation of propane over platinum-based bimetallic nanoparticles is analyzed by the application of density functional theory to a series of tetrahedral Pt₃X cluster models.

The development and characterization of active and selective catalysts is critical for the simulation and optimization of electrochemical synthesis of chemicals and fuels using renewable energy. The rate of electrochemical generation of a specific product as a function of electrode potential can be described by a Tafel equation, which depends on two parameters: the Tafel slope (or the related transfer coefficient) and the exchange current density. However, common methods for calculating Tafel slopes are subjective and limited by data insufficiency resulting from challenges associated with product quantification, and, as shown here, the effects of mass transport, bulk reaction occurring in the mass-transfer boundary layer, and the occurrence of competitive surface reactions. Errors in the Tafel slope extracted from experimental data can also lead to errors in the exchange current density estimation. To address these issues, we present a technique that leverages statistical learning methods informed by physics-based modeling to calculate kinetic parameters (the transfer coefficient and exchange current density) with quantified uncertainty. The method is applied to 21 sets of data for the electrochemical reduction of CO2 to CO and H2 on Ag catalysts acquired under similar experimental conditions. We find that fitted values for the transfer coefficient and exchange current density do not converge to a unique set of values, and that there is an apparent correlation of these parameters; however, the most probable value of the exchange coefficient for CO and H2 formation correspond reasonably well with the DFT-predicted values of this parameter. While the system explored is relatively simple, the techniques developed can be used to evaluate the transfer coefficient and exchange current density for many other electrochemical processes.