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Kenics static mixers enhance mixing under laminar flow conditions. The ideal static mixer achieves efficient mixing at a low pressure drop. A modified design of the Kenics static mixer is analyzed,...

The metastable needlelike form of lysozyme can be obtained from continuous crystallization in mixed-suspension mixed-product-removal (MSMPR) crystallizers for conditions at which the stable tetrago...

In an earlier work, it was shown that single-slit diffraction of matter waves can be considered as position measurement of particles and that the Fresnel and Fraunhofer diffraction patterns result from the time evolution of the same collapsed quantum wave function. This quantum mechanical treatment of diffraction of particles, based on the standard postulates of quantum mechanics and the postulate of existence of quantum trajectories, leads to the ‘position measurement-induced collapse’ (PMIC) states. In the present work, an idealised experimental set-up to test these PMIC states is proposed. The apparatus consists of a modified Lloyd’s mirror in optics, with two reflectors instead of one. The diffraction patterns for this case predicted by the PMIC formalism are presented. They exhibit quantum fractal structures in space-time called ‘quantum carpets’, first discovered by Berry. The PMIC formalism in this case closely follows the ‘boundary bound diffraction’ analysed in a previous work by Tounli, Alverado and Sanz. In addition to having obtained their results, we have identified that the Fresnel and Fraunhofer patterns are indeed present here. It is anticipated that the verification of fractal and nonfractal features of the wave function at various times and also the predicted revival distances to the screen by this experiment will help to better understand ‘quantum collapse’.

Crystallization is an attractive separation and purification technique for proteins. However, protein crystallization often suffers from long batch times due to slow crystallization kinetics. Furthermore, brittle protein crystals may be subject to attrition in conventional crystallizers. An airlift crystallizer is fabricated using three-dimensional (3D) printing and characterized for crystallization of lysozyme. The desupersaturation profile is substantially shorter in the airlift crystallizer compared to a conventional stirred tank crystallizer for all tested conditions. Furthermore, the crystals from the airlift crystallizer are larger and less agglomerated. Finally, the biological activity of the product indicates that the airlift crystallizer preserves the functionality of the protein well. The increased throughput and larger crystals with reduced agglomeration demonstrate that an airlift crystallizer is well suitable for crystallization of a protein. This work also demonstrates how 3D printing can be used to fabricate innovative crystallizers rapidly and at a lower cost, which is especially important for early learning during process development.

We show that Pourbaix diagrams generated by combining first principles and tabulated experimental data can determine the electrochemical conditions needed to synthesize metastable phases in solutio...

Solution crystallization processes are challenged by the need to control crystal quality attributes such as the crystal size distribution (CSD). Emulsion crystallization is an attractive process intensification strategy to control crystal quality attributes through miniaturization. Droplets of an emulsion can act as tiny crystallizers by confining crystals so that crystal nucleation and growth are limited by the droplet size with available supersaturation. This work presents a novel process concept based on the integration of membrane emulsification and solution crystallization. A water-in-oil emulsion is created through membrane emulsification and glycine is crystallized inside droplets by cooling. The process is characterized in terms of the droplet size distribution, crystal number density, and CSD as a function of the emulsification method and supersaturation. Large and monodisperse droplets obtained from membrane emulsification can achieve a narrow and predictable CSD with higher productivity compared to a mechanical emulsification method. The crystal number density is strongly affected by the initial supersaturation when using membrane emulsification but not the final CSD. In contrast, the CSD changes with supersaturation when applying a mechanical emulsification method. The CSD obtained from a conventional bulk crystallization process is broader and lacks the control imposed by the uniform droplets from membrane emulsification.

The defect relaxation volumes obtained from density-functional theory (DFT) calculations of charged vacancies and interstitials are much larger than their neutral counterparts, seemingly unphysically large. We focus on UO2 as our primary material of interest, but also consider Si and GaAs to reveal the generality of our results. In this work, we investigate the possible reasons for this and revisit the methods that address the calculation of charged defects in periodic DFT. We probe the dependence of the proposed energy corrections to charged defect formation energies on relaxation volumes and find that corrections such as potential alignment remain ambiguous with regards to its contribution to the charged defect relaxation volume. We also investigate the volume for the net neutral defect reactions comprising individual charged defects, and find that the aggregate formation volumes have reasonable magnitudes. This work highlights the issue that, as is well-known for defect formation energies, the defect formation volumes depend on the choice of reservoir. We show that considering the change in volume of the electron reservoir in the formation reaction of the charged defects, analogous to how volumes of atoms are accounted for in defect formation volumes, can renormalize the formation volumes of charged defects such that they are comparable to neutral defects. This approach enables the description of the elastic properties of isolated charged defects within an overall neutral material.

We introduce atomate, an open-source Python framework for computational materials science simulation, analysis, and design with an emphasis on automation and extensibility. Built on top of open source Python packages already in use by the materials community such as pymatgen, FireWorks, and custodian, atomate provides well-tested workflow templates to compute various materials properties such as electronic bandstructure, elastic properties, and piezoelectric, dielectric, and ferroelectric properties. Atomate also enables the computational characterization of materials by providing workflows that calculate X-ray absorption (XAS), Electron energy loss (EELS) and Raman spectra. One of the major features of atomate is that it provides both fully functional workflows as well as reusable components that enable one to compose complex materials science workflows that use a diverse set of computational tools. Additionally, atomate creates output databases that organize the results from individual calculations and contains a builder framework that creates summary reports for each computed material based on multiple simulations.

The discovery of emergent phenomena in two-dimensional (2D) materials has sparked substantial research efforts in the materials community. A significant experimental challenge for this field is exerting atomistic control over the structure and composition of the constituent 2D layers and understanding how the interactions between layers drives both structure and properties. Segregation of Pb to the surface of three bilayer thick PbSe-SnSe alloy layers was discovered within [(PbxSn1-xSe)1+δ]n(TiSe2)1 heterostructures using electron microscopy. We demonstrate that this segregation is thermodynamically favored to occur when PbxSn1-xSe layers are interdigitated with TiSe2 monolayers. Density-functional theory (DFT) calculations indicate that the observed segregation depends on what is adjacent to the PbxSn1-xSe layers. The interplay between interface and volume free energies controls both the structure and composition of the constituent layers, which can be tuned using layer thickness.

A hollow fiber membrane module was assessed for its potential in assisting crystallization processes. The membrane module was characterized in the sweeping gas membrane distillation configuration considering various solution and sweeping gas flow rates, temperatures and solution concentrations. A model, coupling mass and heat transfer, was developed to predict the membrane flux. The effect of the process conditions on the membrane flux was experimentally determined and the results were used to validate the model. Feed temperature and air flow rate were found to have a significant effect on the membrane flux. Having found the optimal process conditions for membrane distillation process, batch seeded crystallization experiment were performed to confirm the potential of membrane distillation in the generation of adequate rate and level of supersaturation. Since the desired supersaturation level could be maintained in the crystallizer while seeds were growing, it is confirmed that membrane distillation can be an efficient alternative to conventional supersaturation generation processes. Finally, comparing the modelling results with experiments confirms the acceptable accuracy and predictability capability of the developed model.

Thermodynamic equations of state (EOS) for crystalline solids describe material behaviors under changes in pressure, volume, entropy and temperature, making them fundamental to scientific research in a wide range of fields including geophysics, energy storage and development of novel materials. Despite over a century of theoretical development and experimental testing of energy–volume (E–V) EOS for solids, there is still a lack of consensus with regard to which equation is indeed optimal, as well as to what metric is most appropriate for making this judgment. In this study, several metrics were used to evaluate quality of fit for 8 different EOS across 87 elements and over 100 compounds which appear in the literature. Our findings do not indicate a clear “best” EOS, but we identify three which consistently perform well relative to the rest of the set. Furthermore, we find that for the aggregate data set, the RMSrD is not strongly correlated with the nature of the compound, e.g., whether it is a metal, insulator, or semiconductor, nor the bulk modulus for any of the EOS, indicating that a single equation can be used across a broad range of classes of materials.

We report the development of XASdb, a large database of computed reference X-ray absorption spectra (XAS), and a novel Ensemble-Learned Spectra IdEntification (ELSIE) algorithm for the matching of spectra. XASdb currently hosts more than 300,000 K-edge X-ray absorption near-edge spectra (XANES) for over 30,000 materials from the open-science Materials Project database. We discuss a high-throughput automation framework for FEFF calculations, built on robust, rigorously benchmarked parameters. We will demonstrate that the ELSIE algorithm, which combines 33 weak "learners" comprising a set of preprocessing steps and a similarity metric, can achieve up to 84.2% accuracy in identifying the correct oxidation state and coordination environment of a test set of 19 K-edge XANES spectra encompassing a diverse range of chemistries and crystal structures. The XASdb with the ELSIE algorithm has been integrated into a web application in the Materials Project, providing an important new public resource for the analysis of XAS to all materials researchers. Finally, the ELSIE algorithm itself has been made available as part of Veidt, an open source machine learning library for materials science., 19 Pages, 5 Figures, 1 Table

A Materials Project based open-source Python tool, MPInterfaces, has been developed to automate the high-throughput computational screening and study of interfacial systems. The framework encompasses creation and manipulation of interface structures for solid/solid hetero-structures, solid/implicit solvents systems, nanoparticle/ligands systems; and the creation of simple system-agnostic workflows for in depth computational analysis using density-functional theory or empirical energy models. The package leverages existing open-source high-throughput tools and extends their capabilities towards the understanding of interfacial systems. We describe the various algorithms and methods implemented in the package. Using several test cases, we demonstrate how the package enables high-throughput computational screening of advanced materials, directly contributing to the Materials Genome Initiative (MGI), which aims to accelerate the discovery, development, and deployment of new materials.

First-principles calculations are used to compare the binding energies of O, OH, and F on two-dimensional, metal carbide and nitride, or MXene, surfaces in order to predict the dependence of the thermodynamic stability of these compounds on their chemical composition. Solvation effects are implicitly included in the calculations to reproduce experimental conditions as closely as possible. The results indicate that all MXene surfaces are saturated with oxygen when exposed to H2O/HF solutions at low hydrogen chemical potential, μH, and that Sc-based MXenes can also be fluorinated in solutions of higher μH. After investigating the thermodynamic stability of all 54 MXene compounds Mn+1XnO2 (M = Sc, Ti, V, Cr, Zr, Nb, Mo, Hf, Ta; X = C, N; n = 1, 2, 3), 38 are predicted to have formation energies below 200 meV/atom. Of these, six are predicted to have formation energies below 100 meV/atom, only one of which has been synthesized. Sc-based MXenes are found to be highly stable when their surfaces are terminated w...

A new empirical variable charge potential has been developed for AlN within the third-generation charge optimized many-body (COMB3) potential framework. The potential is able to reproduce the fundamental physical properties of AlN, including cohesive energy, elastic constants, defect formation energies, surface energies and phonon properties of AlN obtained from experiments and first-principles calculations. The thermodynamic properties of the Al(1 1 1)-AlN ( 1 0 1 ¯ 0 ) and Al 2 O 3 (0 0 0 1)-AlN ( 1 0 1 ¯ 0 ) interfaces and the tensile response of AlN nanowires and nanotubes are investigated in classical molecular dynamical (MD) simulations using this COMB3 potential. The results demonstrate that the potential is well suited to model heterogeneous materials in the Al–O–N system. Most importantly, the fully transferrable potential parameters can be seamlessly coupled with existing COMB3 parameters of other elements to enable MD simulations for an even wider range of heterogeneous materials systems.

X-ray absorption spectroscopy (XAS) is a widely-used materials characterization technique. In this work we present a database of computed XAS spectra, using the Green's formulation of the multiple scattering theory implemented in the FEFF code. With more than 500,000 K-edge X-ray absorption near edge (XANES) spectra for more than 40,000 unique materials, this database constitutes the largest existing collection of computed XAS spectra to date. The data is openly distributed via the Materials Project, enabling researchers across the world to access it for free and use it for comparisons with experiments and further analysis.

Quantum trajectory-based descriptions of interference between two coherent stationary waves in a double-slit experiment are presented, as given by the de Broglie-Bohm (dBB) and modified de Broglie-Bohm (MdBB) formulations of quantum mechanics. In the dBB trajectory representation, interference between two spreading wave packets can be shown also as resulting from motion of particles. But a trajectory explanation for interference between stationary states is so far not available in this scheme. We show that both the dBB and MdBB trajectories are capable of producing the interference pattern for stationary as well as wave packet states. However, the dBB representation is found to provide the `which-way' information that helps to identify the hole through which the particle emanates. On the other hand, the MdBB representation does not provide any which-way information while giving a satisfactory explanation of interference phenomenon in tune with the de Broglie's wave particle duality. By counting the trajectories reaching the screen, we have numerically evaluated the intensity distribution of the fringes and found very good agreement with the standard results.

Position measurement-induced collapse states are shown to provide a unified quantum description of diffraction of particles passing through a single slit. These states, which we here call `quantum location states', are represented by the conventional rectangular wave function at the initial moment of position measurement. We expand this state in terms of the position eigenstates, which in turn can be represented as a linear combination of energy eigenfunctions of the problem, using the closure property. The time-evolution of the location states in the case of free particles is shown to have position probability density patterns closely resembling diffraction patterns in the Fresnel region for small times and the same in Fraunhofer region for large times. Using the quantum trajectory representations in the de Broglie-Bohm, modified de Broglie-Bohm and Floyd-Faraggi-Matone formalisms, we show that Fresnel and Fraunhofer diffractions can be described using a single expression. We also discuss how to obtain the probability density of location states for the case of particles moving in a general potential, detected at some arbitrary point. In the case of the harmonic oscillator potential, we find that they have oscillatory properties similar to that of coherent states., Comment: Minor changes

Two-dimensional (2D) materials exhibit a range of extraordinary electronic, optical, and mechanical properties different from their bulk counterparts with potential applications for 2D materials emerging in energy storage and conversion technologies. In this Perspective, we summarize the recent developments in the field of solar water splitting using 2D materials and review a computational screening approach to rapidly and efficiently discover more 2D materials that possess properties suitable for solar water splitting. Computational tools based on density-functional theory can predict the intrinsic properties of potential photocatalyst such as their electronic properties, optical absorbance, and solubility in aqueous solutions. Computational tools enable the exploration of possible routes to enhance the photocatalytic activity of 2D materials by use of mechanical strain, bias potential, doping, and pH. We discuss future research directions and needed method developments for the computational design and optimization of 2D materials for photocatalysis.

In the present study, effect of internals and other hydrodynamic variables on pressure drop and expansion ratio were examined. The parameters studied include inlet air flow rate, bed height, spacing of internal, column diameter and percentage open area. Disc promoters of three different percentages of open area (48.03%, 55.15%, 66.26%) were used. The pressure drop was found to increase significantly with increase in bed height and decrease with open area of internals. As the spacing was decreased, the pressure drop increased first and then decreased due to effective breaking of bubbles in the presence of internals. The expansion ratio was seen to decrease significantly with decrease in the internal spacing and decrease in open area of internals. Correlations for pressure drop and expansion ratio have been found using dimensional analysis. The calculated values of pressure drop and expansion ratio were compared with experimental values. Several models have been developed using the Artificial Neural...

In this investigation, hydrodynamic studies on fluidized beds with internals were conducted by varying the parameters such as inlet air flow rate, bed height, internal spacing, internal size and column diameter. Internals of width 25, 50 and 75% of the radius of the column were used. The effect of the above mentioned parameters on pressure drop, expansion ratio and fluctuation ratio was studied. The pressure drop was found to increase significantly with increase in bed height and decrease with increase in internal width. With internal, the pressure drop was seen to be only 30% of that with the unpromoted bed, thus resulting in lower power consumption. In the case of spacing, as the spacing was decreased the pressure drop was found to increase first and then decrease due to the effective breaking of bubbles in the presence of internals. Expansion ratio was found to reduce in the presence of internals and decrease with increase in internal width and with decrease in internal spacing. Fluctuation ratio was found to reduce in the presence of internals and decrease with increase in internal width and with decrease in internal spacing. The effect of internals on quality of fluidization was also studied. By the introduction of internals, the quality of fluidization in terms of fluidization index had improved. Correlations for pressure drop and expansion ratio have been developed with R2 value of 0.998 and error of 0.076 for the pressure drop and R2 value of 0.942 and error of 0.098 for the expansion ratio. A two layered feed forward back propagation Artificial Neural Network (ANN) model was developed to predict the pressure drop and expansion ratio and with 17 neurons, and it gave high R2 values of 0.999 and 0.9898 for pressure drop and expansion ratio respectively with errors of 0.0148 and 0.0322. The model predictions and the experimental data are in excellent agreement.

International audience; The ab-initio computational treatment of electrochemical systems requires an appropriate treatment of the solid/liquid interfaces. A fully quantum mechanical treatment of the interface is computationally demanding due to the large number of degrees of freedom involved. In this work, we describe a computationally efficient model where the electrode part of the interface is described at the density-functional theory (DFT) level, and the electrolyte part is represented through an implicit solvation model based on the Poisson-Boltzmann equation. We describe the implementation of the linearized Poisson-Boltzmann equation into the Vienna Ab-initio Simulation Package (VASP), a widely used DFT code, followed by validation and benchmarking of the method. To demonstrate the utility of the implicit electrolyte model, we apply it to study the surface energy of Cu crystal facets in an aqueous electrolyte as a function of applied electric potential. We show that the applied potential enables the control of the shape of nanocrystals from an octahedral to a truncated octahedral morphology with increasing potential.

The following text has been added to the Acknowledgements section: “L. F. J. P. acknowledges support from the National Science Foundation (DMREF-1627583)”

Several two-dimensional (2D) materials have been synthesized experimentally, but many theoretically predicted 2D materials are yet to be synthesized. Here, we will review a density-functional theory based framework to enable high-throughput screening of suitable substrates for the stabilization and functionalization of 2D layers. A Materials Project based open source python tool, MPInterfaces, based on this framework, is being developed to automate the search of suitable substrates as well as to characterize their effect on the structural and electronic properties of 2D materials. Lattice-matching, symmetry-matching, substrate surface termination, configuration sampling, substrate induced structural distortion and doping estimation algorithms are being developed and will be described in this article. This computational tool will be employed to identify suitable substrates for scores of technologically relevant 2D materials, leading to acceleration of their synthesis and application, and more efficient use of experimental resources.

Complex quantum trajectory approach, which arose from a modified de Broglie-Bohm interpretation of quantum mechanics, has attracted much attention in recent years. The exact complex trajectories for the Eckart potential barrier and the soft potential step, plotted in a previous work, show that more trajectories link the left and right regions of the barrier, when the energy is increased. In this paper, we evaluate the reflection probability using a new ansatz based on these observations, as the ratio between the total probabilities of reflected and incident trajectories. While doing this, we also put to test the complex-extended probability density previously postulated for these quantum trajectories. The new ansatz is preferred since the evaluation is solely done with the help of the complex-extended probability density along the imaginary direction and the trajectory pattern itself. The calculations are performed for a rectangular potential barrier, symmetric Eckart and Morse barriers, and a soft potential step. The predictions are in perfect agreement with the standard results for potentials such as the rectangular potential barrier. For the other potentials, there is very good agreement with standard results, but it is exact only for low and high energies. For moderate energies, there are slight deviations. These deviations result from the periodicity of the trajectory pattern along the imaginary axis and have a maximum value only as much as $0.1 \%$ of the standard value. Measurement of such deviation shall provide an opportunity to falsify the ansatz., Comment: Submitted version

We demonstrate dual interface formation in nanocrystals (NCs) through cation exchange, creating epitaxial heterostructures within spherical NCs. The thickness of the inner-disk layer can be tuned to form two-dimensional (2D), single atomic layers (1 nm). During the cation exchange reaction from copper sulfide to zinc sulfide (ZnS), we observe a solid-solid phase transformation of the copper sulfide phase in heterostructured NCs. As the cation exchange reaction is initiated, Cu ions replaced by Zn ions at the interfaces are accommodated in intrinsic Cu vacancy sites present in the initial roxbyite (Cu1.81S) phase of copper sulfide, inducing a full phase transition to djurleite (Cu1.94S)/low chalcocite (Cu2S), a more thermodynamically stable phase than roxbyite. As the reaction proceeds and reduces the size of the copper sulfide layer, the epitaxial strain at the interfaces between copper sulfide and ZnS increases and is maximized for a copper sulfide disk ∼ 5 nm thick. To minimize this strain energy, a second phase transformation occurs back to the roxbyite phase, which shares a similar sulfur sublattice to wurtzite ZnS. The observation of a solid-solid phase transformation in our unique heterostructured NCs provides a new pathway to control desired phases and an insight into the influence of cation exchange on nanoscale phase transitions in heterostructured materials.

Solid-liquid interfaces are at the heart of many modern-day technologies and provide a challenge to many materials simulation methods. A realistic first-principles computational study of such systems entails the inclusion of solvent effects. In this work, we implement an implicit solvation model that has a firm theoretical foundation into the widely used density-functional code Vienna ab initio Software Package. The implicit solvation model follows the framework of joint density functional theory. We describe the framework, our algorithm and implementation, and benchmarks for small molecular systems. We apply the solvation model to study the surface energies of different facets of semiconducting and metallic nanocrystals and the SN2 reaction pathway. We find that solvation reduces the surface energies of the nanocrystals, especially for the semiconducting ones and increases the energy barrier of the SN2 reaction.

Surface energies are important for predicting the shapes of nanocrystals and describing the faceting and roughening of surfaces. Copper surfaces are of particular interest in recent years since they are the preferred surfaces for growing graphene using chemical vapor deposition. In this study we calculate the surface energies of copper for the three low-index facets (111), (100), and (110) and one high-index facet, (210), using density-functional theory with both the local-density approximation and various parametrizations of the generalized-gradient approximation to the exchange-correlation functional. To assess the accuracy of the different functionals, we obtain the average surface energies of an isotropic crystal using a broken-bond model. We use this method, which can be generalized to other crystal structures, to compare calculated surface energies to experimental surface energies for fcc crystals. We find that the recent exchange-correlation functionals AM05 and PBEsol are the most accurate functionals for calculating the surface energies of copper. To determine how solvents affect the surface energies of copper, we perform calculations using a continuum solvation model. We find that aqueous solvation changes the overall magnitude of the surface energies only slightly but leads to more isotropic surface energies.

The Li-Si materials system holds promise for use as an anode in Li-ion battery applications. For this system, we determine the charge capacity, voltage profiles, and energy storage density solely by ab initio methods without any experimental input. We determine the energetics of the stable and metastable Li-Si phases likely to form during the charging and discharging of a battery. Ab initio molecular dynamics simulations are used to model the structure of amorphous Li-Si as a function of composition, and a genetic algorithm coupled to density-functional theory searches the Li-Si binary phase diagram for small-cell, metastable crystal structures. Calculations of the phonon densities of states using density-functional perturbation theory for selected structures determine the importance of vibrational, including zero-point, contributions to the free energies. The energetics and local structural motifs of these metastable Li-Si phases closely resemble those of the amorphous phases, making these small unit cell crystal phases good approximants of the amorphous phase for use in further studies. The charge capacity is estimated, and the electrical potential profiles and the energy density of Li-Si anodes are predicted. We find, in good agreement with experimental measurements, that the formation of amorphous Li-Si only slightly increases the anode potential. Additionally, the genetic algorithm identifies a previously unreported member of the Li-Si binary phase diagram with composition Li${}_{5}$Si${}_{2}$ which is stable at 0 K with respect to previously known phases. We discuss its relationship to the partially occupied Li${}_{7}$Si${}_{3}$ phase.

This paper examines the nature of classical correspondence in the case of coherent states at the level of quantum trajectories. We first show that for a harmonic oscillator, the coherent state complex quantum trajectories and the complex classical trajectories are identical to each other. This congruence in the complex plane, not restricted to high quantum numbers alone, illustrates that the harmonic oscillator in a coherent state executes classical motion. The quantum trajectories are those conceived in a modified de Broglie-Bohm scheme and we note that identical classical and quantum trajectories for coherent states are obtained only in the present approach. The study is extended to Gazeau-Klauder and SUSY quantum mechanics-based coherent states of a particle in an infinite potential well and that in a symmetric Poschl-Teller (PT) potential by solving for the trajectories numerically. For the coherent state of the infinite potential well, almost identical classical and quantum trajectories are obtained whereas for the PT potential, though classical trajectories are not regained, a periodic motion results as t --> \infty., More examples

We systematically elucidate the optoelectronic properties of rare-earth doped and Ce co-doped yttrium aluminum garnet (YAG) using hybrid exchange-correlation functional based density functional theory. The predicted optical transitions agree with the experimental observations for single doped Ce:YAG, Pr:YAG, and co-doped Er,Ce:YAG. We find that co-doping of Ce-doped YAG with any lanthanide except Eu and Lu lowers the transition energies; we attribute this behavior to the lanthanide-induced change in bonding environment of the dopant atoms. Furthermore, we find infrared transitions only in case of the Er, Tb, and Tm co-doped Ce:YAG and suggest Tm,Ce:YAG and Tb,Ce:YAG as possible functional materials for efficient spectral up-conversion devices.

We present a computational study of the interface of a Pt electrode and an aqueous electrolyte employing semi-empirical dispersion corrections and an implicit solvent model within first-principles calculations. The electrode potential is parametrized within the computational hydrogen electrode scheme. Using one explicit layer, we find that the most realistic interface configuration is a water bilayer in the H-up configuration. Furthermore, we focus on the contribution of the dispersion interaction and the presence of water on H, O, and OH adsorption energies. This study demonstrates that the implicit water scheme represents a computationally efficient method to take the presence of an aqueous electrolyte interface with a metal electrode into account.