Metal oxide/water interfaces play a crucial role in many electrochemical and photocatalytic processes, such as photoelectrochemical water splitting, the creation of fuel from sunlight, and electrochemical CO2 reduction. First-principles electronic structure calculations can reveal unique insights into these processes, such as the role of the alignment of the oxide electronic energy levels with those of liquid water. An essential prerequisite for the success of such calculations is the ability to predict accurate structural models of these interfaces, which in turn requires careful experimental validation. Here we report a general, quantitative validation protocol for first-principles molecular dynamics simulations of oxide/aqueous interfaces. The approach makes direct comparisons of interfacial x-ray reflectivity (XR) signals from experimental measurements and those obtained from ab initio simulations with semilocal and van der Waals functionals. The protocol is demonstrated here for the case of the Al2O3(001)/water interface, one of the simplest oxide/water interfaces. We discuss the technical requirements needed for validation, including the choice of the density functional, the simulation cell size, and the optimal choice of the thermodynamic ensemble. Our results establish a general paradigm for the validation of structural models and interactions at solid/water interfaces derived from first-principles simulations. While there is qualitative agreement between the simulated structures and the experimental best-fit structure, direct comparisons of simulated and measured XR intensities show quantitative discrepancies that derive from both bulk regions (i.e., alumina and water) as well as the interfacial region, highlighting the need for accurate density functionals to properly describe interfacial interactions. Our results show that XR data are sensitive not only to the atomic structure (i.e., the atom locations) but also to the electron-density distributions in both the substrate and at the interface.

In recent years, the use of silver-based materials for selective and highly active ethanol reactivity in single atom catalysis and the ethanol oxidation reaction in direct fuel cells highlights the importance of silver (Ag) in an ethanol economy. Understanding the interaction of ethanol with Ag(111) and the natural defects found on extended Ag(111) is critical to the overall understanding of more complex catalytic processes including ethanol activation over Ag-based catalysts. The research herein aims to characterize the interaction of ethanol molecules on undercoordinated defect sites of Ag(111) to mimic active sites found on Ag nanoparticle catalysts. The interaction between ethanol and Ag(111) was studied using temperature programed desorption (TPD), x-ray photoelectron spectroscopy, and density functional theory (DFT). Molecular ethanol adsorption and desorption from Ag(111) and the distinction between undercoordinated Ag(111) adsorption sites were determined using TPD in correlation with DFT. Complete analysis of TPD data for ethanol adsorbed to terrace sites was used to calculate a kinetic prefactor (3.4 × 1015) and desorption energy (0.54 eV). A better understanding of defect-dependent behavior for ethanol on silver can lead to a greater insight into high surface area nanoparticle catalysts used in industries, catalytic converters, and photo-, electro-, and heterogeneous catalysis. The results suggest that ethanol preferentially adsorbs to undercoordinated sites on Ag(111), resulting in higher binding energies for these molecules (Redhead first order approximation for desorption energies is terrace, 0.54 eV; step edge, 0.57 eV; and kink sites, 0.61 eV). Furthermore, alteration of the silver surface can lead to a redistribution of these sites.

In traditional models of heteroepitaxy, the substrate serves mainly as a crystalline template for the thin-film lattice, dictating the initial roughness of the film and the degree of coherent strain. Here, performing in situ surface x-ray diffraction during the heteroepitaxial growth of LaTiO 3 on SrTiO 3 (001), we find that a TiO 2 adlayer composed of the ( 13 × 13 ) R 33.7° and ( 2 × 2 ) R 45.0° reconstructions is a highly active participant in the growth process, continually diffusing to the surface throughout deposition. The effects of the TiO 2 adlayer on layer-by-layer growth are investigated using different deposition sequences and anomalous x-ray scattering, both of which permit detailed insight into the dynamic layer rearrangements that take place. Our work challenges commonly held assumptions regarding growth on TiO 2 -terminated SrTiO 3 (001) and demonstrates the critical role of excess TiO 2 surface stoichiometry on the initial stages of heteroepitaxial growth on this important perovskite oxide substrate material.

Reliable first-principles calculations of electrochemical processes require accurate prediction of the interfacial capacitance, a challenge for current computationally efficient continuum solvation methodologies. We develop a model for the double layer of a metallic electrode that reproduces the features of the experimental capacitance of Ag(100) in a non-adsorbing, aqueous electrolyte, including a broad hump in the capacitance near the potential of zero charge and a dip in the capacitance under conditions of low ionic strength. Using this model, we identify the necessary characteristics of a solvation model suitable for first-principles electrochemistry of metal surfaces in non-adsorbing, aqueous electrolytes: dielectric and ionic nonlinearity, and a dielectric-only region at the interface. The dielectric nonlinearity, caused by the saturation of dipole rotational response in water, creates the capacitance hump, while ionic nonlinearity, caused by the compactness of the diffuse layer, generates the capacitance dip seen at low ionic strength. We show that none of the previously developed solvation models simultaneously meet all these criteria. We design the nonlinear electrochemical soft-sphere solvation model which both captures the capacitance features observed experimentally and serves as a general-purpose continuum solvation model.

In this work, the preparation and characterization of modified LiMn2O4 (LMO) cathodes utilizing chemisorbed alkylphosphonic acids to chemically modify their surfaces are reported. Electrochemical methods to study ionic and molecular mobility through the alkylphosphonate self-assembled monolayers (SAMs) for different alkyl chain compositions, in order to better understand their impact on the lithium-ion electrochemistry, are utilized. Electrochemical trends for different chains correlate to trends observed in contact angle measurements and solvation energies obtained from computational methods, indicating that attributes of the microscopic wettability of these interfaces with the battery electrolyte have an important impact on ionic mobility. The effects of surface modification on Mn dissolution are also reported. The alkylphosphonate layer provides an important mode of chemical stabilization to the LMO, suppressing Mn dissolution by 90% during extended immersion in electrolytes. A more modest reduction in dissolution is found upon galvanostatic cycling, in comparison to pristine LMO cathodes. Taken together, the data suggest that alkylphosphonates provide a versatile means for the surface modification of lithium-ion battery cathode materials allowing the design of specific interfaces through modification of organic chain functionalities.

Quantum-chemical processes in liquid environments impact broad areas of science, from molecular biology to geology to electrochemistry. While density-functional theory (DFT) has enabled efficient quantum-mechanical calculations which profoundly impact understanding of atomic-scale phenomena, realistic description of the liquid remains a challenge. Here, we present an approach based on joint density-functional theory (JDFT) which addresses this challenge by leveraging the DFT approach not only for the quantum mechanics of the electrons in a solute, but also simultaneously for the statistical mechanics of the molecules in a surrounding equilibrium liquid solvent. Specifically, we develop a new universal description for the interaction of electrons with an arbitrary liquid, providing the missing link to finally transform JDFT into a practical tool for the realistic description of chemical processes in solution. This approach predicts accurate solvation free energies and surrounding atomic-scale liquid structure for molecules and surfaces in multiple solvents without refitting, all at a fraction of the computational cost of methods of comparable detail and accuracy. To demonstrate the potential impact of this method, we determine the structure of the solid/liquid interface, offering compelling agreement with more accurate (but much more computationally intensive) theories and with X-ray reflectivity measurements.

Journal Article Leveraging First Principles Modeling and Machine Learning for Microscopy Data Inversion Get access Eric Schwenker, Eric Schwenker Center for Nanoscale Materials, Argonne National Laboratory, Lemont IL, USA Search for other works by this author on: Oxford Academic Google Scholar Fatih Sen, Fatih Sen Center for Nanoscale Materials, Argonne National Laboratory, Lemont IL, USA Search for other works by this author on: Oxford Academic Google Scholar Spencer Hills, Spencer Hills Center for Nanoscale Materials, Argonne National Laboratory, Lemont IL, USA Search for other works by this author on: Oxford Academic Google Scholar Tadas Pualauskas, Tadas Pualauskas Department of Physics, University of Illinois at Chicago, Chicago IL, USA Search for other works by this author on: Oxford Academic Google Scholar Ce Sun, Ce Sun Department of Materials Science and Engineering, University of Texas at Dallas, Dallas TX, USA Search for other works by this author on: Oxford Academic Google Scholar Liang Li, Liang Li Center for Nanoscale Materials, Argonne National Laboratory, Lemont IL, USA Search for other works by this author on: Oxford Academic Google Scholar Alper Kinaci, Alper Kinaci Center for Nanoscale Materials, Argonne National Laboratory, Lemont IL, USA Search for other works by this author on: Oxford Academic Google Scholar Kendra Letchworth-Weaver, Kendra Letchworth-Weaver Center for Nanoscale Materials, Argonne National Laboratory, Lemont IL, USA Search for other works by this author on: Oxford Academic Google Scholar Moon Kim, Moon Kim Department of Materials Science and Engineering, University of Texas at Dallas, Dallas TX, USA Search for other works by this author on: Oxford Academic Google Scholar Robert Klie, Robert Klie Department of Physics, University of Illinois at Chicago, Chicago IL, USA Search for other works by this author on: Oxford Academic Google Scholar ... Show more Jianguo Wen, Jianguo Wen Center for Nanoscale Materials, Argonne National Laboratory, Lemont IL, USA Search for other works by this author on: Oxford Academic Google Scholar Maria K Y Chan Maria K Y Chan Center for Nanoscale Materials, Argonne National Laboratory, Lemont IL, USA Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 23, Issue S1, 1 July 2017, Pages 178–179, https://doi.org/10.1017/S143192761700157X Published: 04 August 2017

Density-functional theory (DFT) has revolutionized computational prediction of atomic-scale properties from first principles in physics, chemistry and materials science. Continuing development of new methods is necessary for accurate predictions of new classes of materials and properties, and for connecting to nano- and mesoscale properties using coarse-grained theories. JDFTx is a fully-featured open-source electronic DFT software designed specifically to facilitate rapid development of new theories, models and algorithms. Using an algebraic formulation as an abstraction layer, compact C++11 code automatically performs well on diverse hardware including GPUs (Graphics Processing Units). This code hosts the development of joint density-functional theory (JDFT) that combines electronic DFT with classical DFT and continuum models of liquids for first-principles calculations of solvated and electrochemical systems. In addition, the modular nature of the code makes it easy to extend and interface with, facilitating the development of multi-scale toolkits that connect to ab initio calculations, e.g. photo-excited carrier dynamics combining electron and phonon calculations with electromagnetic simulations.

Solvation plays a key role in determining the capacitance behavior of the electrochemical interface, yet it presents significant challenges for computational modeling due to its complexity. We have recently demonstrated (doi: 10.1063/1.4976971) that the solvation models currently implemented in density functional theory (DFT) codes such as VASP perform poorly for the capacitance of aqueous metallic interfaces. In this talk, I identify solvation model characteristics that are necessary for capturing the nonlinear capacitance behavior of aqueous metallic interfaces.

Creating an artificial cathode-electrolyte interface (CEI) from self-assembled monolayers of phosphonic acids offers a promising avenue to prevent capacity loss in Li-ion batteries due to metal dissolution from the cathode. A complete theoretical description of the complex and inherently multi-scale interface between the battery electrode surface and an organic electrolyte can enable rational design of such functionalized cathode coatings. We first present a microscopically informed continuum model for organic electrolyte [1,2] which reproduces key solvation phenomena relevant to battery operation. We go on to predict how the structure and energetics of the metal oxide cathode in Li-ion batteries change due to the presence of liquid electrolyte. We find that compared to vacuum calculations [3], the voltage stability window of the Li-terminated (001) and (111) surfaces of the spinel LiMn2O4 (LMO) cathode in solution is enhanced. Furthermore, we demonstrate that our solvation model, in combination with density-functional theory and classical molecular dynamics, simultaneously captures both the formation of a stable artificial CEI on the LMO surface and the interaction of the CEI molecules with the electrolyte. Our theoretical description captures the experimentally observed trends in solubility and cyclic voltammetry of the coated LMO surface, demonstrating how adjusting the length and functionalization of the phosphonates can balance the competing needs of maximizing Li-ion conductivity but minimizing cathode dissolution. Use of the Center for Nanoscale Materials, an Office of Science user facility, was supported by the U. S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. DE-AC02-06CH11357. [1] K. Letchworth-Weaver and T.A. Arias, Phys. Rev. B. 86, 075140 (2012). [2] D. Gunceler et al, Modelling Simul. Mater. Sci. Eng. 21,074005 (2013). [3] R. Warburton et al, ACS Applied Materials and Interfaces, 8 (17), 11108–11121 (2016).

A major goal of energy research is to use visible light to cleave water directly, without an applied voltage, into hydrogen and oxygen. Although SrTiO3 requires ultraviolet light, after four decades, it is still the "gold standard" for the photo-catalytic splitting of water. It is chemically robust and can carry out both hydrogen and oxygen evolution reactions without an applied bias. While ultrahigh vacuum surface science techniques have provided useful insights, we still know relatively little about the structure of these electrodes in contact with electrolytes under operating conditions. Here, we report the surface structure evolution of a n-SrTiO3 electrode during water splitting, before and after "training" with an applied positive bias. Operando high-energy X-ray reflectivity measurements demonstrate that training the electrode irreversibly reorders the surface. Scanning electrochemical microscopy at open circuit correlates this training with a 3-fold increase of the activity toward the photo-induced water splitting. A novel first-principles joint density functional theory simulation, constrained to the X-ray data via a generalized penalty function, identifies an anatase-like structure as the more active, trained surface.

Understanding the complex and inherently multi-scale interface between a charged electrode surface and a fluid electrolyte would inform design of more efficient and less costly electrochemical energy storage and conversion devices. Joint density-functional theory (JDFT) [1] bridges the relevant length-scales by joining a fully ab initio description of the electrode with a highly efficient, yet atomically detailed classical DFT description [2] of the liquid electrolyte structure, avoiding the costly statistical sampling of the liquid required by molecular dynamics calculations. Leveraging JDFT within our framework to treat charged systems in periodic boundary conditions [3], we then predict the voltage-dependent structure and energetics at the interface between a liquid electrolyte and single-crystalline metallic electrodes. We compare the JDFT-predicted interfacial water structure next to a metallic electrode with results obtained from classical and ab initio molecular dynamics simulations. We go on to elucidate the physical origin of the experimentally measured voltage-dependent differential capacitance of an Ag(111) electrode in aqueous electrolytes, examining the crucial role of ion desolvation and plating onto the electrolyte. Finally, we conclude with an exploration of how the choice of cation and anion in the electrolyte affects the atomically-detailed structure of the metal-liquid interface, yielding fundamental insight into processes in electrodeposition and corrosion. Use of the Center for Nanoscale Materials, an Office of Science user facility, was supported by the U. S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. DE-AC02-06CH11357. [1] S.A. Petrosyan et al, Phys. Rev. B 75, 205105 (2007) [2] R. Sundararaman, K. Letchworth-Weaver, T. A. Arias, J. Chem. Phys. 140, 144504 (2014) [3] K. Letchworth-Weaver and T. A. Arias, Phys. Rev. B. 86, 075140 (2012)