AndreaBozzo/ceres-open-data-index huggingface dataset:
Towards a robust evaluation of nanoporous materials for carbon capture applications

In this paper, we present a workflow that is designed to work without manual intervention to efficiently predict, by using molecular simulations, the thermodynamic data that is needed to design a carbon capture process. We developed a procedure that does not rely on fitting of the adsorption isotherms. From molecular simulations, we can obtain accurate data for both, the pure component isotherms as well as the mixture isotherms. This allowed us to make a detailed comparison of the different methods to predict the mixture isotherms. All approaches rely on an accurate description of the pure component isotherms and a model to predict the mixture isotherms. As we are interested in low CO₂ concentrations, it is essential that these models correctly predict the low pressure limit, i.e., give a correct description of the Henry regime. Among the equations that describe this limit correctly, the dual-site Langmuir (DSL) model is often used for the pure components and the extended DSL (EDSL) for the mixtures. An alternative approach, which avoids describing the pure component isotherms with a model, is to numerically integrate the pure component isotherms in the context of IAST.  In this work we compare these two methods. In addition, we show that the way these data are fitted for DSL can significantly impact the ranking of materials, in particular for capture processes with low concentration of CO₂ in the feed stream.

Tags: dual-site-langmuir-dsl, ideal-adsorbed-solution-theory-iast, metal-organic-frameworks-mofs, temperature-swing-adsorption-tsa
Uncovering the catalyst/electrolyte interfacial process by frequency dispersion of capacitance

Electrochemical impedance spectroscopy (EIS) is the widely used technique to monitor the electrical properties of a catalyst under electrocatalytic conditions. Although it is extensively used for research in electrocatalysis, its effectiveness and power have not been fully harnessed to elucidate complex interfacial processes. Herein, we use the frequency dispersion parameter, n, which is extracted from EIS measurements, to describe the dispersion characteristics of capacitance and interfacial properties of Co3O4 under alkaline oxygen evolution reaction (OER) conditions. We first prove the n-value is sensitive to the interfacial electronic changes associated with Co redox processes and surface reconstruction. The n-value decreases by increasing the specific/active surface area of the catalysts. We further modify the interfacial properties by changing different components, i.e., replacing the proton with deuterium, adding ethanol as a new oxidant, and changing the cation in the electrolyte. Intriguingly, the n-value can identify different influences on the interfacial process from proton transfer, the decrease and carbon-poisoning of oxidized Co species, and the interfacial water structure. These findings convey that the frequency dispersion of capacitance is a convenient and useful method to uncover the interfacial properties under electrocatalytic conditions, which helps to advance the understanding of the interface-activity relationship.

Tags: catalystelectrolyte-interface, electrochemical-impedance-spectroscopy, frequency-dispersion-of-capacitance, interfacial-capacitance, oxygen-evolution-reaction
Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows

The automation of ab initio simulations is essential in view of performing high-throughput (HT) computational screenings oriented to the discovery of novel materials with desired physical properties. In this work, we propose algorithms and implementations that are relevant to extend this approach beyond density functional theory (DFT), in order to automate many-body perturbation theory (MBPT) calculations. Notably, a novel algorithm pursuing the goal of an efficient and robust convergence procedure for GW and BSE simulations is provided, together with its implementation in a fully automated framework. This is accompanied by an automatic GW band interpolation scheme based on maximally-localized Wannier functions, aiming at a reduction of the computational burden of quasiparticle band structures while preserving high accuracy. The proposed developments are validated on a set of representative semiconductor and metallic systems.

Tags: aiida, aiida-yambo, automated-many-body-perturbation-theory, big-map, bse, first-principles, g0w0-wannier-interpolation, gw, high-throughput, marvel, max, yambo-code
First-principles characterization of thermal conductivity in LaPO₄-based alloys

Alloys based on lanthanum phosphate (LaPO₄) are often employed as thermal barrier coatings, due to their low thermal conductivity and structural stability over a wide temperature range. To enhance the thermal-insulation performance of these alloys, it is essential to comprehensively understand the fundamental physics governing their heat conduction. Here, we employ the Wigner formulation of thermal transport in conjunction with first-principles calculations to elucidate how the interplay between anharmonicity and compositional disorder determines the thermal properties of La1-xGdxPO₄ alloys, and discuss the fundamental physics underlying the emergence and coexistence of particle-like and wave-like heat-transport mechanisms. Our predictions for microscopic vibrational properties (temperature-dependent Raman spectrum) and for macroscopic thermal conductivity are validated against experiments. Finally, we leverage these findings to devise strategies to optimize the performance of thermal barrier coatings.

Tags: alloys, anharmonicity-and-disorder, first-principles, thermal-barrier-coating, thermal-transport
A robust framework for generating adsorption isotherms to screen materials for carbon capture

In this paper, we present a workflow that is designed to work without manual intervention to efficiently predict, by using molecular simulations, the thermodynamic data that is needed to design a carbon capture process. We developed a procedure that does not rely on fitting of the adsorption isotherms. From molecular simulations, we can obtain accurate data for both, the pure component isotherms as well as the mixture isotherms. This allowed us to make a detailed comparison of the different methods to predict the mixture isotherms. All approaches rely on an accurate description of the pure component isotherms and a model to predict the mixture isotherms. As we are interested in low CO₂ concentrations, it is essential that these models correctly predict the low pressure limit, i.e., give a correct description of the Henry regime. Among the equations that describe this limit correctly, the dual-site Langmuir (DSL) model is often used for the pure components and the extended DSL (EDSL) for the mixtures. An alternative approach, which avoids describing the pure component isotherms with a model, is to numerically integrate the pure component isotherms in the context of IAST.  In this work we compare these two methods. In addition, we show that the way these data are fitted for DSL can significantly impact the ranking of materials, in particular for capture processes with low concentration of CO₂ in the feed stream.

Tags: dual-site-langmuir-dsl, ideal-adsorbed-solution-theory-iast, metal-organic-frameworks-mofs, temperature-swing-adsorption-tsa
Large-scale machine-learning-assisted exploration of the whole materials space

Crystal-graph attention networks have emerged recently as remarkable tools for the prediction of thermodynamic stability and materials properties from unrelaxed crystal structures. Previous networks trained on two million materials exhibited, however, strong biases originating from underrepresented chemical elements and structural prototypes in the available data. We tackled this issue computing additional data to provide better balance across both chemical and crystal-symmetry space. Crystal-graph networks trained with this new data show unprecedented generalization accuracy, and allow for reliable, accelerated exploration of the whole space of inorganic compounds. We applied this universal network to performed machine-learning assisted high-throughput materials searches including 2500 binary and ternary prototypes and spanning about 1 billion compounds. After validation using density-functional theory, we uncover in total 19512 additional materials on the convex hull of thermodynamic stability and around 150000 compounds with a distance of less than 50 meV/atom from the hull. Here we include the DCGAT-1, DCGAT-2, and DCGAT-3 datasets used in this work.

Tags: crystal-graph-attention-networks, density-functional-theory, high-throughput
Mechanism and prediction of hydrogen embrittlement in fcc stainless steels and high entropy alloys

The urgent need for clean energy coupled with the exceptional promise of hydrogen (H) as a clean fuel is driving development of new metals resistant to hydrogen embrittlement. Experiments on new fcc high entropy alloys present a paradox: these alloys absorb more H than Ni or SS304 (austenitic 304 stainless steel) while being more resistant to embrittlement. Here, a new theory of embrittlement in fcc metals is presented based on the role of H in driving an intrinsic ductile-to-brittle transition at a crack tip. The theory quantitatively predicts the H concentration at which a transition to embrittlement occurs in good agreement with experiments for SS304, SS316L, CoCrNi, CoNiV, CoCrFeNi, and CoCrFeMnNi. The theory rationalizes why CoNiV is the alloy most resistant to embrittlement and why SS316L is more resistant than the high entropy alloys CoCrFeNi and CoCrFeMnNi, which opens a path for the computationally guided discovery of new embrittlement-resistant alloys.

Tags: fracture, high-entropy-alloys, hydrogen-embrittlement, snsf
Theory of twin strengthening in fcc high entropy alloys

Twinning in fcc High Entropy Alloys (HEAs) has been implicated as a possible mechanism for hardening that enables enhanced ductility. Here, a theory for the twinning stress is developed analogous to recent theories for yield stress. Specifically, the stress to move a twin dislocation, i.e an fcc partial dislocation moving along a pre-existing twin boundary, through a random multicomponent alloy is determined. A reduced elasticity theory is then introduced in which atoms interact with the twin dislocation pressure field and the twin boundary. The theory is applied to NiCoCr using results from both interatomic potentials and elasticity theory. Results are also used to predict the increased stress for the motion of (i) a single partial dislocation leaving a trailing stacking fault and (ii) adjacent partial dislocations involved in twin nucleation. Increased strength is predicted for all processes involved in the nucleation and growth of fcc twins. Comparison to single-crystal experiments at room temperature then suggests that twinning is controlled by twin nucleation, with reasonable quantitative agreement. When solute/fault interactions are neglected, the theory shows that twinning and lattice flow stresses are related. The theory also provides insight into how other dilute solute additions could suppress twinning, as found experimentally.

Tags: random-alloys, snsf, solute-strengthening, twinning
Shadow-light images of simulated 25 classes of surface roughness for automatic classification

Many relationships important to civil engineering depend on surface roughness (morphology). Examples are the bond strength between concrete layers, the adhesion of a wheel to the pavement, the angle of friction in the soil in contact with a wall surface, and many other cases when we deal with a material with a surface having the characteristics of a Gaussian field. Based on scans of the natural concrete surfaces subjected to different smoothing processes, theoretical models were made. The observed features of the models were grouped into 25 categories belonging to the spherical semivariogram model. Each category is described by two parameters: range (with discrete domain 0.01, 0.04, 0.08, 0.16, 0.32) and upper limits (also with discrete domain 1, 2, 4 , 8, 16) with zero trend. For all combinations of range-limit pairs, homogeneous Gaussian random fields satisfying the spatial dependence of the category were generated in R software by using the RandomFields library. In the final step, the Blender rendering software was used. 1,000 images were taken for each category type using constant angle lighting and moving the camera over the generated surface. Users can download a set of 25,000 images to build or verify the surface classifier. The generated 25 types of surfaces are also provided.

Tags: civil-engineering, classification, concrete, deep-learning, machine-learning, shadow-light-images, virtual-modeling
Intrinsic fracture behavior of Mg–Y alloys

Pure magnesium (Mg) is an attractive metal for structural applications due to its low density, but also has low ductility and low fracture toughness. Dilute alloying of Mg with rare earth elements in small amounts improves the ductility, but the effects of alloying on fracture are not well-established. Here, the intrinsic fracture of a model Mg-3at%Y solid solution alloy is studied using a combination of anisotropic linear elastic fracture mechanics and atomistic simulations applied to a comprehensive set of crack configurations under mode I loading. The competition between brittle cleavage and ductile dislocation emission at the crack tip in Mg is improved slightly by alloying, because local fluctuations of the random solutes enable dislocation emission rather than cleavage fracture for a number of configurations where the differences in critical load for cleavage and emission are small. However, basalplane cleavage remains strongly preferred, as in pure Mg. The alloys do show higher fracture toughness for all configurations due to local solute-induced deformation phenomena at the crack tip. Thus, alloying with Y is expected to improve the fracture toughness of Mg, but the persistence of basal cleavage prevents the alloy from becoming intrinsically ductile for all orientations.

Tags: alloy, fracture, magnesium, molecular-dynamics-simulation, snsf
Flat bands with fragile topology through superlattice engineering on single-layer graphene

'Magic'-angle twisted bilayer graphene has received a lot of interest due to its flat bands with potentially non-trivial topology that lead to intricate correlated phases. A spectrum with flat bands, however, does not require a twist between multiple sheets of van der Waals materials, but rather can be realized with the application of an appropriate periodic potential. Here, we propose the imposition of a tailored periodic potential onto a single graphene layer through local perturbations that could be created via lithography or adatom manipulation, which also results in an energy spectrum featuring flat bands. Our first-principle calculations for an appropriate decoration of graphene with adatoms indeed show the presence of flat bands in the spectrum. Furthermore, we reveal the topological nature of the flat bands through a symmetry-indicator analysis. This non-trivial topology manifests itself in corner-localized states with a filling anomaly as we show using a tight-binding model. Our proposal of a single decorated graphene sheet provides a new versatile route to study correlated phases in topologically non-trivial, flat band structures.

Tags: graphene, marvel, topological-materials, vasp
Analytical models of short-range order in FCC and BCC alloys

A statistical-mechanics analysis is used to create analytic estimates for the short-range order (SRO) parameters in FCC and BCC solid solution alloys as a function of composition and temperature. As in the classic quasi-chemical method, the analysis assumes pair interactions among atoms at different distances and partitions the entire crystal into a set of identical independent clusters that are then treated like molecules in a gas.  This enables analytic development of the probabilities that govern SRO.  For binary and ternary alloys, increasingly complex clusters are considered that systematically extend the range of accuracy of the analytic model relative to reference Monte Carlo simulations.  The results enable fast assessment of likely SRO using estimated inputs for atom-atom interaction energies. In this record we provide our analytical solution as well as the simulation data supporting our theoretical prediction of the short-range order parameter in both FCC and BCC alloys.

Tags: high-entropy-alloys, short-range-order, snsf, solid-solutions, statistical-mechanics
Dynamic response of oxygen vacancies on the Deacon reaction over reduced single crystalline CeO₂-x(111) surfaces

The heterogeneously catalyzed HCl oxidation reaction (Deacon reaction) over ceria leads under typical reaction conditions to a reduction and surface chlorination of CeO2. The reduced single crystalline CeO2-x(111) model surface stabilizes various ordered surface structures, e.g. (√7 × √7)R19.1°, (3 × 3), or (4 × 4), depending on the concentration of oxygen vacancies (VO). Saturating these phases with HCl at room temperature, followed by annealing to the process temperature of 700 K, leads in all cases to a uniformly covering (√3 × √3)R30° overlayer structure with identical Cl coverage and identical adsorption geometry. Low energy electron diffraction (LEED) fingerprinting, density functional theory (DFT) calculations and X-ray photoelectron spectroscopy (XPS) evidence that Cl adsorbs into the O-vacancy at the surface (Clvac) with a high adsorption energy (>2 eV). From thermal desorption spectroscopy (TDS) and XPS of Cl 2p the adsorption energy of Clvac and the water formation is found to dependent sensitively on the degree of bulk-reduction x of CeO2-x(111). Chlorine desorption in TDS shifts from 1175 K to 1320 K when the the reduction degree x is increased from CeO1.8(111) (x = 0.2) to CeO1.6(111) (x = 0.4). In order to rationalize why the formation of (√3 × √3)R30°-Clvac structure on CeO2-x(111) is independent of the original reduction degree x of CeO2 x(111), efficient diffusion of surface and bulk oxygen vacancies (VO) is required.

Tags: chlorine-adsorption, deacon-process, hcl-oxidation, leed-fingerprinting, oxygen-vacancy-mobility, reduced-ceria
Infrared spectra in amorphous alumina

We present a combined study based on experimental measurements of infrared (IR) dielectric function and first-principles calculations of IR spectra and vibrational density of states (VDOS) of amorphous alumina (am-Al₂O₃). In particular, we show that the main features of the imaginary part of the dielectric function ε₂(ω) at ~380 and 630 cm-¹ are related to the motions of threefold coordinated oxygen atoms, which are the vast majority of oxygen atoms in am-Al₂O₃. Our analysis (involving three model structures) provides an alternative point of view with respect to an earlier suggested assignment of the vibrational modes, which relates them to the stretching and bending vibrational modes of AlOₙ (n = 4, 5, and 6) polyhedra. Our assignment is based on the additive decomposition of the VDOS and ε₂(ω) spectra, which shows that: (i) the band at ~380 cm-¹ features oxygen motions occurring in a direction normal to the plane defined by the three nearest-neighbor aluminum atoms, i.e. out-of-plane motions of oxygen atoms; (ii) Al-O stretching vibrations (i.e. in-plane motions of oxygen atoms) appear at frequencies above ~500 cm-¹, which characterize the vibrational modes underlying the band at ~630 cm-¹.

Tags: amorphous-al2o3, dft, infrared, vdos
Force-based method to determine the potential dependence in electrochemical barriers

Determining ab-initio potential dependent energetics are critical to investigating mechanisms for electrochemical reactions. While methodology for evaluating reaction thermodynamics is established, simulation techniques for the corresponding kinetics is still a major challenge owing to a lack of potential control, finite cell size effects or computational expense. In this work, we develop a model which allows for computing electrochemical activation energies from just a handful of Density Functional Theory (DFT) calculations. The sole input into the model are the atom centered forces obtained from DFT calculations performed on a homogeneous grid composed of varying field-strengths. We show that the activation energies as a function of the potential obtained from our model are consistent for different super-cell sizes and proton concentrations for a range of electrochemical reactions. This record contains output files from all the DFT calculations needed to reproduce the figures in the manuscript.

Tags: electrochemical-barriers, electrochemical-kinetics, proton-electron-transfer-reactions
Thermal transport of Li₃PS₄ solid electrolytes with ab initio accuracy

The vast amount of computational studies on electrical conduction in solid-state electrolytes is not mirrored by comparable efforts addressing thermal conduction, which has been scarcely investigated despite its relevance to thermal management and (over)heating of batteries. The reason for this lies in the complexity of the calculations: on one hand, the diffusion of ionic charge carriers makes lattice methods formally unsuitable due to the lack of equilibrium atomic positions needed for normal-mode expansion. On the other hand, the prohibitive cost of large-scale molecular dynamics (MD) simulations of heat transport in large systems at ab initio levels has hindered the use of MD-based methods. In this work, we leverage recently developed machine-learning potentials targeting different ab initio functionals (PBEsol, r2SCAN, PBE0) and a state-of-the-art formulation of the Green-Kubo theory of heat transport in multicomponent systems to compute the thermal conductivity of a promising solid-state-electrolyte, Li3PS4, in all its polymorphs (α, β and γ). By comparing MD estimates with lattice methods on the low-temperature, non-diffusive γ-Li3PS4, we highlight strong anharmonicities and negligible nuclear quantum effects, hence further justifying MD-based methods even for non-diffusive phases. Finally, for the ion-conducting α and β phases, where the multicomponent Green-Kubo MD approach is mandatory, our simulations indicate a weak temperature dependence of the thermal conductivity, a glass-like behavior due to the effective local disorder characterizing these Li-diffusing phases.

Tags: epfl, lab-cosmo, machine-learning, marvel, max, snsf, solid-state-electrolytes, swissuniversities, thermal-transport
Rich nature of Van Hove singularities in Kagome superconductor CsV₃Sb₅

The recently discovered layered kagome metals AV₃Sb₅ (A=K, Rb, Cs) exhibit diverse correlated phenomena, which are intertwined with a topological electronic structure with multiple van Hove singularities (VHSs) in the vicinity of the Fermi level. As the VHSs with their large density of states enhance correlation effects, it is of crucial importance to determine their nature and properties. Here, we combine polarization-dependent angle- resolved photoemission spectroscopy with density functional theory to directly reveal the sublattice properties of 3d-orbital VHSs in CsV₃Sb₅. Four VHSs are identified around the M point and three of them are close to the Fermi level, with two having sublattice-pure and one sublattice-mixed nature. Remarkably, the VHS just below the Fermi level displays an extre- mely flat dispersion along MK, establishing the experimental discovery of higher-order VHS. The characteristic intensity modulation of Dirac cones around K further demonstrates the sublattice interference embedded in the kagome Fermiology. The crucial insights into the electronic structure, revealed by our work, provide a solid starting point for the understanding of the intriguing correlation phenomena in the kagome metals AV₃Sb₅.

Tags: arpes-dft, kagome-metal-csv3sb5, nccr-marvel, vhss