AndreaBozzo/ceres-open-data-index huggingface dataset:
Atomic-level structure determination of amorphous molecular solids by NMR

Structure determination of amorphous materials remains challenging, owing to the disorder inherent to these materials. Nuclear magnetic resonance (NMR) powder crystallography is a powerful method to determine the structure of molecular solids, but disorder leads to both a high degree of overlap between measured signals, resulting in challenges for spectral assignment, and prevents the unambiguous identification of a single modelled periodic structure as representative of the whole material. Here, we determine the atomic-level ensemble structure of the amorphous form of the drug AZD4625 by combining solid-state NMR experiments with molecular dynamics (MD) simulations and machine-learned chemical shifts. By considering the combined shifts of all 1H and 13C atomic sites in the molecule, we determine the structure of the amorphous form by identifying an ensemble of local molecular environments that are in agreement with experiment. We then extract preferred conformations and intermolecular interactions in the amorphous sample, and analyze the structure in terms of the hydrogen bonding and conformational factors that stabilize the amorphous form of the drug.

Tags: amorphous-solids, machine-learning, marveldd1, molecular-dynamics-simulation, nmr, structure-determination
Simulated sulfur K-edge X-ray absorption spectroscopy database of lithium thiophosphate solid electrolytes

We present a sulfur K-edge X-ray absorption near-edge structure (XANES) database of 18 crystalline and 48 amorphous Lithium-Phosphorous-Sulfur (LPS) compounds. The database contains a total of 2681 XANES spectra of symmetrically inequivalent absorbing S sites. Structures were taken from Materials Cloud entry 2022.17 (archive.materialscloud.org/record/2022.17) and were originally generated by systematically removing Li, P and S atoms from known crystal structures using an evolutionary algorithm and an artificial neural network based interatomic potential. The details of this procedure can be found in Guo et al. (see references below). From this data set, low-energy structures were selected for spectral simulations. The excited electron and core hole method as implemented in VASP 6.2.1 was used to compute the XANES spectra for each symmetrically inequivalent Sulfur atom. The details of the VASP simulations can be found in the associated manuscript.

Acknowledgements: We acknowledge financial support by the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, Contract No. DE-SC0012704. These results used the computational resources of the Center for Functional Nanomaterials and the Scientific Data and Computing Center, a component of the Computational Science Initiative, at Brookhaven National Laboratory under the Contract No. DE-SC0012704. We also acknowledge computing resources from Columbia University's Shared Research Computing Facility project, which is supported by NIH Research Facility Improvement Grant 1G20RR030893-01, and associated funds from the New York State Empire State Development, Division of Science Technology and Innovation (NYSTAR) Contract C090171, both awarded April 15, 2010.

Tags: amorphous-lps, lps, vasp, x-ray-absorption-spectroscopy
Dynamic crystal rocking of nickel-based single crystal superalloy during the epitaxial growth of the additive manufacturing process

The understanding of dynamic process of epitaxial microstructure forming in laser additive manufacturing is of vital importance for achieving products with single crystalline texture. Here, we perform in-situ, real-time synchrotron Laue diffraction experiments to capture the microstructural evolution of nickel-based single-crystal superalloys during rapid laser remelting process. In-situ synchrotron radiation Laue diffraction characterizes the crystal rotation behavior and stray grains formation process. With complementary thermo-mechanical coupled finite element simulation and molecular dynamics simulation, we identify that the crystal rotation is governed by the localized heating/cooling heterogeneity induced deformation gradient, and that the subgrains rotation caused by rapid dislocation movement and complex stress field could be the major mechanism in the generation of granular stray grains at the bottom of the melt pool.

Tags: in-situ-laue-diffraction, laser-remelting, microstructural-evolution, nickel-based-superalloy
High-throughput thiophene adsorption calculations on bimetallic surfaces

We present a large dataset of density functional theory calculations of thiophene (C4H4S) adsorbed on metallic and bimetallic (100) surfaces performed in Quantum Espresso.  In total 1131 different surfaces were explored resulting in 2235 total calculations.  Slabs were built from 37 different possible elements in the stoichiometry of A3B, Ll2 structures.  The 37 single element slabs, A1 structures, were included as well.  Slabs were cleaved in the (100) direction.  Two hollow adsorption sites were chosen to be explored over bimetallic surfaces and one hollow configuration for the single metal surfaces.   Bader charge analysis files are also presented.

Tags: chemisorption, dft, heterogenous-catalysis, surfaces, thiophene
In silico study on probing atomistic insight into structural stability and tensile properties of Fe-doped hydroxyapatite single crystals

Hydroxyapatite (HA, Ca10PO4(OH)2) is a widely explored material in the experimental domain of biomaterials science, because of its resemblance with natural bone minerals. Specifically, in the bioceramic community, HA doped with multivalent cations (e.g., Mg+2, Fe+2, Sr+2, etc.) has been extensively investigated in the last few decades. Experimental research largely established the critical role of dopant content on the changes in mechanical and biocompatibility properties. The plethora of experimental measurements of mechanical response on doped HA is based on compression or indentation testing of polycrystalline materials. Such measurements, as well as computational predictions of me,  on single crystalline (doped) HA are scarce. On that premise, the present study aims to build atomistic models of Fe2+-doped HA, a model system, with varying Fe content (10, 20, 30, and 40 mol%) and to explore their uniaxial tensile response by means of molecular dynamics (MD) simulation, together with the calculation of IR spectrum. In the equilibrated unit cell structures, Ca(1) sites were found to be energetically favourable for Fe2+ substitution. The local distribution of Fe2+ ions significantly affect the atomic partial charge distribution and chemical symmetry surrounding the functional groups. These signatures are reflected in the significant decrease in the intensity of IR peaks and are found in the Fe-doped HA, together with peak splitting because of the symmetry change in the crystal structure. Another important objective of this work is to computationally predict the mechanical response of doped HA in their single crystal format. An interesting observation is that the elastic anisotropy of undoped HA was not compromised with Fe-doping. Tensile strength (TS) is systematically reduced in doped HA with Fe+2 dopant content and a decrease in TS with temperature can be attributed to the increased thermal agitation of atoms at elevated temperatures. The physics of the tensile response was rationalized in terms of the strain dependent changes in covalent/ionic framework (Ca-P distance, P-O bond strain, O-P-O angular strain, O-H bond distance). Further, the dynamic changes in covalent bond network were energetically analyzed by calculating the changes in O-H and P-O bond vibrational energy. Summarizing, the current work develops our foundational understanding of the atomistic phenomena involved in the phase stability and tensile response of Fe-doped HA single crystals.

Tags: hydroxyapatite, iron-doping, md-simulation, mechanical-response
Modeling high-entropy transition-metal alloys with alchemical compression: dataset HEA25

Alloys composed of several elements in roughly equimolar composition, often referred to as high-entropy alloys, have long been of interest for their thermodynamics and peculiar mechanical properties, and more recently for their potential application in catalysis. They are a considerable challenge to traditional atomistic modeling, and also to data-driven potentials that for the most part have memory footprint, computational effort and data requirements which scale poorly with the number of elements included. We apply a recently proposed scheme to compress chemical information in a lower-dimensional space, which reduces dramatically the cost of the model with negligible loss of accuracy, to build a potential that can describe 25 d-block transition metals. The model shows semi-quantitative accuracy for prototypical alloys and is remarkably stable when extrapolating to structures outside its training set. 
In this record, we provide a dataset containing 25,000 structures utilized for fitting the aforementioned potential, with a focus on 25 d-block transition metals, excluding Tc, Cd, Re, Os and Hg.

Tags: alchemical-compression, high-entropy-alloys, machine-learning, marvel, neural-network-potential
Sampling the materials space for conventional superconducting compounds

We perform a large scale study of conventional superconducting materials using a machine-learning accelerated high-throughput workflow. We start by creating a comprehensive dataset of around 7000 electron-phonon calculations performed with reasonable convergence parameters. This dataset is then used to train a robust machine learning model capable of predicting the electron-phonon and superconducting properties based on structural, compositional, and electronic ground-state properties. Using this machine, we evaluate the transition temperature (Tc) of approximately 200000 metallic compounds, all of which on the convex hull of thermodynamic stability (or close to it) to maximize the probability of synthesizability. Compounds predicted to have Tc values exceeding 5 K are further validated using density-functional perturbation theory. As a result, we identify 541 compounds with Tc values surpassing 10 K, encompassing a variety of crystal structures and chemical compositions. This work is complemented with a detailed examination of several interesting materials, including nitrides, hydrides, and intermetallic compounds. Particularly noteworthy is LiMoN2, which we predict to be superconducting in the stoichiometric trigonal phase, with a Tc exceeding 38 K. LiMoN2 has been previously synthesized in this phase, further heightening its potential for practical applications.

Tags: density-functional-perturbation-theory, electron-phonon-coupling, high-throughput, superconductivity
Electron-phonon calculations using a wannier-based supercell approach: applications to the monolayer MoS₂ mobility

We present a first-principles method to calculate electron-phonon coupling elements in atomic systems, and showcase its application to the evaluation of the phonon-limited mobility of n-type single-layer MoS₂. The method combines a density functional theory (DFT) plane-wave supercell approach with a real-space maximally localized Wannier basis. It enables the calculation of electronic structure, phonon displacements with their corresponding frequencies, and real-space electron-phonon coupling elements on the same footing, without the need for density functional perturbation theory (DFPT) or Wannier interpolation. We report a low-field, intrinsic mobility of 274 cm²/Vs at room temperature for MoS₂, and highlight its dependence on carrier density and temperature. In addition, we compare our findings to the latest available modeling data and put them in perspective with the experimentally measured values. Based on these observations, the mobilities presented in this work appear to be compatible with experimental results, when taking into account other scattering sources. Hence, the proposed approach provides a reliable framework for mobility calculations that can be extended towards large-scale device simulations.

Tags: ab-initio, carrier-transport, dft, electron-mobility, electron-phonon-coupling, marveldd3, mos2, snsf
Donor-acceptor-donor "hot exciton" triads for high reverse intersystem crossing in OLEDs

Hot exciton materials have the potential to improve the quantum efficiency of organic light-emitting diodes (OLEDs) by promoting high Reversed InterSystem Crossing (hRISC) between a high-lying triplet (Tn, n≥2) and a radiative singlet (Sm). In recent years, donor–acceptor-donor (D-A-D) molecular systems have shown great promise in its ability to enhance the hRISC process under certain conditions. However, strategies to find appropriate D-A-D combinations beyond trial-and-error are still elusive. This work exposes the limited applicability of the current fragment-based design rules and proposes high-throughput screening as the optimal route to find promising candidates that fulfill the energy criteria for hot exciton materials. The strategy consists of first establishing the thresholds for large triplet-triplet splitting and small singlet-triplet gap, then filtering combinations through rate comparison of competitive crossing pathways, and finally confirming hRISC with spin-orbital coupling (SOC) evaluation. Based on a curated dataset of 234 D-A-D compounds, our protocol identifies 31 promising candidates with potential for hRISC, 4 of which have been previously reported in the literature. Remarkably, while most of the promising systems show prominent hybridized local and CT (HLCT) character, several candidates do not fulfill this condition, indicating that different routes are possible to design efficient OLED materials.

Tags: computational-screening, donor-acceptor-donor, epfl, h2020, hot-exciton-oleds, marie-curie-fellowship
Orbital-resolved DFT+U for molecules and solids

We present an orbital-resolved extension of the Hubbard U correction to density-functional theory (DFT). Compared to the conventional shell-averaged approach, the prediction of energetic, electronic and structural properties is strongly improved, particularly for compounds characterized by both localized and hybridized states in the Hubbard manifold. The numerical values of all Hubbard parameters are readily obtained from linear-response calculations. The relevance of this more refined approach is showcased by its application to bulk solids pyrite (FeS₂) and pyrolusite (β-MnO₂), as well as to six Fe(II) molecular complexes. Our findings indicate that a careful definition of Hubbard manifolds is indispensable for extending the applicability of DFT+U beyond its current boundaries. The present orbital-resolved scheme aims to provide a computationally undemanding yet accurate tool for electronic structure calculations of charge-transfer insulators, transition-metal (TM) complexes and other compounds displaying significant orbital hybridization.
This dataset contains all Quantum ESPRESSO input and output files as well as all pseudopotentials that were used to generate the results of this study. Moreover, an ``EXAMPLES'' folder provides guidance on how to apply the LR-cDFT approach to evaluate orbital-resolved DFT+U parameters in practise.

Tags: cdft, constrained-dft, dft, dftu, dftuv, hubbard, linear-response, lr-cdft, marvel, orbital-resolved, quantum-espresso
Interplay between ferroelectricity and metallicity in hexagonal YMnO₃

We use first-principles density functional theory to investigate how the polar distortion is affected by doping in multiferroic hexagonal yttrium manganite, h-YMnO₃. While the introduction of charge carriers tends to suppress the polar distortion in conventional ferroelectrics, the behavior in improper geometric ferroelectrics, of which h-YMnO₃ is the prototype, has not been studied to date. Using both background charge doping and atomic substitution, we find an approximately linear dependence of the polar distortion on doping concentration, with hole doping reducing and electron doping enhancing it. We show that this behavior is a direct consequence of the improper geometric nature of the ferroelectricity. In addition to its doping effect, atomic substitution can further suppress or enhance the polar distortion through changes in the local chemistry and geometry.

Tags: dftu, erc, ethz, h-rmno3
Surface segregation in high-entropy alloys from alchemical machine learning: dataset HEA25S

High-entropy alloys (HEAs), containing several metallic elements in near-equimolar proportions, have long been of interest for their unique mechanical properties. More recently, they have emerged as a promising platform for the development of novel heterogeneous catalysts, because of the large design space, and the synergistic effects between their components. In this work we use a machine-learning potential that can model simultaneously up to 25 transition metals (d-block transition metals, excluding Tc, Cd, Re, Os and Hg) to study the tendency of different elements to segregate at the surface of a HEA.
In this record, we provide a dataset HEA25S, containing 10000 bulk HEA structures (Dataset O), 2640 HEA surface slabs (Dataset A), together with 1000 bulk and 1000 surface slabs snapshots from the molecular dynamics (MD) runs (Datasets B and C), and 500 MD snapshots of the 25 elements Cantor-style alloy surface slabs.
We also provide the HEA25-4-NN and HEA25S-4-NN final models, which were used in the study. Full description of both the dataset and the models can be found the reference paper below.

Tags: alchemical-compression, atomistic-modeling, cosmo, density-functional-theory, high-entropy-alloys, machine-learning, marvel, surface-segregation
A NN-Potential for phase transformations in Ge

In a recent preprint, entitled: "Development of a machine learning interatomic potential for exploring pressure-dependent kinetics of phase transitions in Germanium", we presented a novel Neural-Network (NN)  interatomic potential for Ge. We recall that Ge phases different from the cubic-diamond one are of particular interest for applications. Hexagonal Ge, for instance, displays superior optical properties. It is therefore important to investigate how, exploiting pressure, Ge can be transformed into different allotropes. In order to build a potential tackling kinetics of pressure-induced phase transformations, several kinetic paths (mainly sampled using the solid-state Nudged Elastic Band method) were added to the database, following a suitable active-learning procedure. Energies, forces, and stressed relative to the various configurations were computed ab initio using VASP with the PBE functional. The NN potential was trained using the Deep Potential Molecular Dynamic package (DeePMDkit). The potential greatly reproduces the relative stability of several Ge phases and yields at least a semi-quantitative description of the energetics along complex phase-transformation paths.  
In the present archive, we provide the full potential for use in LAMMPS and ASE, together with the full database produced using VASP.

Tags: deepmd, germanium, neural-network, phase-transitions
Atomistic simulations reveal strength reductions due to short-range order in alloys

A theory for strengthening for multicomponent non-dilute alloys possessing short-range order (SRO) has recently been developed. The theory predicts that, in addition to a well-known athermal strengthening, there is a notable effect of SRO on the solute–dislocation interactions that can decrease or increase the strength relative to a random alloy. Here, carefully designed atomistic simulations in a model binary NbW alloy are used to demonstrate that alloy strength due to solute–dislocation interactions can be increased or decreased, depending on the SRO and consistent with theoretical predictions. Specifically, SRO is introduced using fictitious solute– solute interactions in an alloy system with very small true solute–solute interactions, and the Nudged Elastic Band (NEB) method is then used to compute the energy barriers for edge dislocation motion for various levels of SRO. Energy barriers, and hence alloy strengths, can be decreased when the Warren-Cowley SRO parameters are negative (attraction of unlike solutes). The theoretical predictions for the same system are in reasonable quantitative agreement with the simulation results. These findings demonstrate the unexpected possibility of reduced strength due to SRO and also further validate the analytical theory as a tool to guide alloy design.

Tags: alloys, marvel, short-range-order, simulation, theory, yield-strength
Probing the Mott-insulating behavior of Ba₂MgReO₆ with DFT+DMFT

We investigate the interplay of spin-orbit coupling, electronic correlations, and lattice distortions in the 5d¹ double perovskite Ba₂MgReO₆. Combining density-functional theory (DFT) and dynamical mean-field theory (DMFT), we establish the Mott-insulating character of Ba₂MgReO₆ in both its cubic and tetragonal paramagnetic phases. Despite substantial spin-orbit coupling, its impact on the formation of the insulating state is minimal, consistent with theoretical expectations for d¹ systems. We further characterize the electronic properties of the cubic and tetragonal phases by analyzing spectral functions and local occupations in terms of multipole moments centered on the Re sites. Our results confirm the presence of ferroically ordered z² quadrupoles in addition to the antiferroic x²-y²-type order. We compare two equivalent but complementary descriptions in terms of either effective Re-t2g frontier orbitals or more localized atomic-like Re-d and O-p orbitals. The former maps directly on a physically intuitive picture in terms of nominal d¹ Re cations, while the latter explicitly demonstrates the role of hybridization with the ligands in the spin-orbit splitting and the formation of the charge quadrupoles around the Re sites. Finally, we compare our DFT+DMFT results with a previous DFT+U study of the tetragonal paramagnetic state. We find good qualitative agreement for the dominant charge quadrupoles, but also notable differences in the corresponding spectral functions, underscoring the need for more comparative studies between these two methods.

Tags: constrained-random-phase-approximation, density-functional-theory, double-perovskite, dynamical-mean-field-theory, mott-insulator
Oxygen vacancy induced defect dipoles in BiVO4 for photoelectrocatalytic partial oxidation of methane

A strong driving force for charge separation and transfer in semiconductors is essential for designing effective photoelectrodes for solar energy conversion. While defect engineering and polarization alignment can enhance this process, their potential interference within a photoelectrode remains unclear. Here we show that oxygen vacancies in bismuth vanadate (BiVO4) can create defect dipoles due to a disruption of symmetry. The modified photoelectrodes exhibit a strong correlation between charge separation and transfer capability and external electrical poling, which is not seen in unmodified samples. Applying poling at -150 Volt boosts charge separation and transfer efficiency to over 90 %. A photocurrent density of 6.3 mA cm-2 is achieved on the photoelectrode after loading with a nickel-iron oxide-based cocatalyst. Furthermore, using generated holes for methane partial oxidation can produce methanol with a Faradaic efficiency of approximately 6 %. These findings provide valuable insights into the photoelectrocatalytic conversion of greenhouse gases into valuable chemical products.

Tags: arc, electronic-structure, experimental