cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.24435/materialscloud:fd-31
title: Low-temperature crystallography and vibrational properties of rozenite (FeSO₄·4H₂O), a candidate mineral component of the polyhydrated sulfate deposits on Mars

description: Rozenite (FeSO₄·4H₂O) is a candidate mineral component of the polyhydrated sulfate deposits on the surface and in the subsurface of Mars. In order to better understand its behavior at temperature conditions prevailing on the martian surface and aid its identification in ongoing and future Rover missions we have carried out a combined experimental and computational study of the mineral's structure and properties. We collected neutron powder diffraction data at temperatures ranging from 21 – 290 K, room temperature synchrotron X-ray data and Raman spectra. Moreover, first-principles calculations of the vibrational properties of rozenite were carried out to aid the interpretation of the Raman spectrum.  In this work, we demonstrated how combining Raman spectroscopy and X-ray diffraction of the same sample material sealed inside a capillary with complementary first principles calculations yields accurate reference Raman spectra. This workflow enables the construction of a reliable Raman spectroscopic database for planetary exploration, which will be invaluable to shed light on the geological past as well as in identifying resources for the future colonization of planetary bodies throughout the solar system. 
In this dataset, the self-consistent DFT+U as well as Γ-point phonon calculations, that were compared to the experimentally determined frequencies of the Raman-active modes, are reported, whereas the experimental data was submitted to crystallographic data-bases (i.e., CCSD and ICSD).
DOI: 10.24435/materialscloud:xz-ba
title: Structure and energetics of dye-sensitized NiO interfaces in water from ab-initio MD and large-scale GW calculations

description: The energy level alignment across solvated molecule/semiconductor interfaces is a crucial property for the correct functioning of dye-sensitized photo-electrodes, where, following the absorption of solar light, a cascade of interfacial hole/electron transfer processes has to efficiently take place. In light of the difficulty of performing X-ray photoelectron spectroscopy measurements at the molecule/solvent/metal-oxide interface, being able to accurately predict the level alignment by first-principles calculations on realistic structural models would represent an important step toward the optimization of the device. In this respect dye/NiO surfaces, employed in p-type dye-sensitized solar cells, are undoubtedly challenging for ab initio methods and, also for this reason, much less investigated than the n-type dye/TiO2 counterpart. Here we consider the C343-sensitized NiO surface in water and combine ab initio Molecular Dynamics (AIMD) simulations with GW (G0W0) calculations, performed along the MD trajectory, to reliably describe the structure and energetics of the interface when explicit solvation and finite temperature effects are accounted for. We show that the differential perturbative correction on the NiO and molecule states obtained at GW level is mandatory to recover the correct (physical) interfacial energetics, allowing hole transfer from the semiconductor valence band to the HOMO of the dye. Moreover, the calculated average driving force quantitatively agrees with the experimental estimate.
DOI: 10.24435/materialscloud:2020.0010/v1
title: High Dielectric Ternary Oxides from Crystal Structure Prediction and High-throughput Screening

description: The development of new high dielectric materials is essential for advancement in modern electronics. Oxides are generally regarded as the most promising class of high dielectric materials for industrial applications as they possess both high dielectric constants and large band gaps. Most previous researches on high dielectrics were limited to already known materials. In this study, we conducted an extensive search for high dielectrics over a set of ternary oxides by combining crystal structure prediction and density functional perturbation theory calculations. From this search, we adopted multiple stage screening to identify 441 new low-energy high dielectric materials. Among these materials, 33 were identified as potential high dielectrics favorable for modern device applications. Our research has opened an avenue to explore novel high dielectric materials by combining crystal structure prediction and high throughput screening
DOI: 10.24435/materialscloud:tm-ym
title: Low-temperature crystallography and vibrational properties of rozenite (FeSO₄·4H₂O), a candidate mineral component of the polyhydrated sulfate deposits on Mars

description: Rozenite (FeSO₄·4H₂O) is a candidate mineral component of the polyhydrated sulfate deposits on the surface and in the subsurface of Mars. In order to better understand its behavior at temperature conditions prevailing on the martian surface and aid its identification in ongoing and future Rover missions we have carried out a combined experimental and computational study of the mineral's structure and properties. We collected neutron powder diffraction data at temperatures ranging from 21 – 290 K, room temperature synchrotron X-ray data and Raman spectra. Moreover, first-principles calculations of the vibrational properties of rozenite were carried out to aid the interpretation of the Raman spectrum.  In this work, we demonstrated how combining Raman spectroscopy and X-ray diffraction of the same sample material sealed inside a capillary with complementary first principles calculations yields accurate reference Raman spectra. This workflow enables the construction of a reliable Raman spectroscopic database for planetary exploration, which will be invaluable to shed light on the geological past as well as in identifying resources for the future colonization of planetary bodies throughout the solar system. 
In this dataset, the self-consistent DFT+U as well as Γ-point phonon calculations, that were compared to the experimentally determined frequencies of the Raman-active modes, are reported, whereas the experimental data was submitted to crystallographic data-bases (i.e., CCSD and ICSD).
DOI: 10.24435/materialscloud:wv-dy
title: High Dielectric Ternary Oxides from Crystal Structure Prediction and High-throughput Screening

description: The development of new high dielectric materials is essential for advancement in modern electronics. Oxides are generally regarded as the most promising class of high dielectric materials for industrial applications as they possess both high dielectric constants and large band gaps. Most previous researches on high dielectrics were limited to already known materials. In this study, we conducted an extensive search for high dielectrics over a set of ternary oxides by combining crystal structure prediction and density functional perturbation theory calculations. From this search, we adopted multiple stage screening to identify 441 new low-energy high dielectric materials. Among these materials, 33 were identified as potential high dielectrics favorable for modern device applications. Our research has opened an avenue to explore novel high dielectric materials by combining crystal structure prediction and high throughput screening
DOI: 10.24435/materialscloud:jg-km
title: Oxidation states, Thouless' pumps, and nontrivial ionic transport in nonstoichiometric electrolytes

description: Thouless' quantization of adiabatic particle transport permits to associate an integer topological charge with each atom of an electronically gapped material. If these charges are additive and independent of atomic positions, they provide a rigorous definition of atomic oxidation states and atoms can be identified as integer-charge carriers in ionic conductors. Whenever these conditions are met, charge transport is necessarily convective, i.e. it cannot occur without substantial ionic flow, a transport regime that we dub trivial. We show that the topological requirements that allow these conditions to be broken are the same that would determine a Thouless' pump mechanism if the system were subject to a suitably defined time-periodic Hamiltonian. The occurrence of these requirements determines a non-trivial transport regime whereby charge can flow without any ionic convection, even in electronic insulators.
These results are first demonstrated with a couple of simple molecular models that display a quantum pump mechanism upon introduction of a fictitious time dependence of the atomic positions along a closed loop in configuration space. We finally examine the impact of our findings on the transport properties of non-stoichiometric alkali-halide melts, where the same topological conditions that would induce a quantum pump mechanism along certain closed loops in configuration space also determine a non-trivial transport regime such that most of the total charge current results to be uncorrelated from the ionic ones.
In this record we collect the time series of the electric currents, displaced dipoles, and energy band gaps supporting the plots and relevant results supporting our findings.
DOI: 10.24435/materialscloud:fr-r0
title: Profiling novel high-conductivity 2D semiconductors

description: When complex mechanisms are involved, pinpointing high-performance materials within large databases is a major challenge in materials discovery. We focus here on phonon-limited conductivities, and study 2D semiconductors doped by field effects. Using state-of-the-art density-functional perturbation theory and Boltzmann transport equation, we discuss 11 monolayers with outstanding transport properties.
These materials are selected from a computational database of exfoliable materials providing monolayers that are dynamically stable and that do not have more than 6 atoms per unit cell. We first analyze electron-phonon scattering in two well-known systems: electron-doped InSe and hole-doped phosphorene. Both are single-valley systems with weak electron-phonon interactions, but they represent two distinct pathways to fast transport: a steep and deep isotropic valley for the former and strongly anisotropic electron-phonon physics for the latter.
We identify similar features in the database and compute the conductivities of the relevant monolayers. This process yields several high-conductivity materials, some of them only very recently emerging in the literature (GaSe, Bi₂SeTe₂, Bi₂Se₃, Sb₂SeTe₂), others never discussed in this context (AlLiTe₂, BiClTe, ClGaTe, AuI). Comparing these 11 monolayers in detail, we discuss how the strength and angular dependency of the electron-phonon scattering drives key differences in the transport performance of materials despite similar valley structure. We also discuss the high conductivity of hole-doped WSe₂, and how this case study shows the limitations of a selection process that would be based on band properties alone.
In this entry we provide the AiiDA database with the calculations of phonons and electron-phonon interactions for the 11 materials, along with the python library to collect and visualise the data, solve the Botzmann transport equation, and launch the same workflows for other 2D materials. To guide the reader, we include a Jupyter notebook showing how to extract the data, use the basic functionalities of the library, and regenerate the plots included in the associated paper.
DOI: 10.24435/materialscloud:g0-q9
title: Profiling novel high-conductivity 2D semiconductors

description: When complex mechanisms are involved, pinpointing high-performance materials within large databases is a major challenge in materials discovery. We focus here on phonon-limited conductivities, and study 2D semiconductors doped by field effects. Using state-of-the-art density-functional perturbation theory and Boltzmann transport equation, we discuss 11 monolayers with outstanding transport properties.
These materials are selected from a computational database of exfoliable materials providing monolayers that are dynamically stable and that do not have more than 6 atoms per unit cell. We first analyze electron-phonon scattering in two well-known systems: electron-doped InSe and hole-doped phosphorene. Both are single-valley systems with weak electron-phonon interactions, but they represent two distinct pathways to fast transport: a steep and deep isotropic valley for the former and strongly anisotropic electron-phonon physics for the latter.
We identify similar features in the database and compute the conductivities of the relevant monolayers. This process yields several high-conductivity materials, some of them only very recently emerging in the literature (GaSe, Bi₂SeTe₂, Bi₂Se₃, Sb₂SeTe₂), others never discussed in this context (AlLiTe₂, BiClTe, ClGaTe, AuI). Comparing these 11 monolayers in detail, we discuss how the strength and angular dependency of the electron-phonon scattering drives key differences in the transport performance of materials despite similar valley structure. We also discuss the high conductivity of hole-doped WSe₂, and how this case study shows the limitations of a selection process that would be based on band properties alone.
In this entry we provide the AiiDA database with the calculations of phonons and electron-phonon interactions for the 11 materials, along with the python library to collect and visualise the data, solve the Botzmann transport equation, and launch the same workflows for other 2D materials. To guide the reader, we include a Jupyter notebook showing how to extract the data, use the basic functionalities of the library, and regenerate the plots included in the associated paper.
DOI: 10.24435/materialscloud:hv-yd
title: Comparative density functional theory study for predicting oxygen reduction activity of single-atom catalyst

description: It has been well established that nitrogen coordinated transition metal, TM-N4-C (TM=Fe and Co) moieties, are responsible for the higher catalytic activity for the electrochemical oxygen reduction reaction. However, the results obtained using density functional theory calculations vary from one to another, which can lead to controversy. Herein, we assess the accuracy of the theoretical approach using different class of exchange-correlation functionals, i.e., Perdew-Burke-Ernzerhof (PBE) and revised PBE (RPBE), those with the Grimme's semiempirical dispersion correction (PBE+D3 and RPBE+D3), and the Bayesian error estimate functional with the nonlocal correlation (BEEF-vdW) on the reaction energies of oxygen reduction reaction on TM-N4 moieties in graphene and those with OH-termination. We found that the predicted overpotentials using RPBE+D3 are comparable and consistent with those using BEEF-vdW. Our finding indicates that a proper choice of the exchange-correlation functional is crucial to a precise description of the catalytic activity of this system.
DOI: 10.24435/materialscloud:2n-3j
title: Ab initio real-time quantum dynamics of charge carriers in momentum space

description: Application of the nonadiabatic molecular dynamics (NAMD) approach is severely limited to studying carrier dynamics in the momentum space, since a supercell is required to sample the phonon excitation and electron-phonon (e-ph) interaction at different momenta in a molecular dynamics simulation. Here, we develop an ab initio approach for the real-time quantum dynamics for charge carriers in the momentum space (NAMD_k) by directly introducing the e-ph coupling into the Hamiltonian based on the harmonic approximation. The NAMD_k approach maintains the quantum zero-point energy and proper phonon dispersion, and includes memory effects of phonon excitation. The application of NAMD_k to the hot carrier dynamics in graphene reveals the phonon-specific relaxation mechanism. An energy threshold of 0.2eV, defined by two optical phonon modes strongly coupled to the electrons, separates the hot electron relaxation into fast and slow regions with the lifetimes of pico- and nano-seconds, respectively. The NAMD_k approach provides a powerful tool to understand real-time carrier dynamics in the momentum space for different materials.
DOI: 10.24435/materialscloud:7n-jz
title: Comparative density functional theory study for predicting oxygen reduction activity of single-atom catalyst

description: It has been well established that nitrogen coordinated transition metal, TM-N4-C (TM=Fe and Co) moieties, are responsible for the higher catalytic activity for the electrochemical oxygen reduction reaction. However, the results obtained using density functional theory calculations vary from one to another, which can lead to controversy. Herein, we assess the accuracy of the theoretical approach using different class of exchange-correlation functionals, i.e., Perdew-Burke-Ernzerhof (PBE) and revised PBE (RPBE), those with the Grimme's semiempirical dispersion correction (PBE+D3 and RPBE+D3), and the Bayesian error estimate functional with the nonlocal correlation (BEEF-vdW) on the reaction energies of oxygen reduction reaction on TM-N4 moieties in graphene and those with OH-termination. We found that the predicted overpotentials using RPBE+D3 are comparable and consistent with those using BEEF-vdW. Our finding indicates that a proper choice of the exchange-correlation functional is crucial to a precise description of the catalytic activity of this system.
DOI: 10.24435/materialscloud:nq-sm
title: Ab initio real-time quantum dynamics of charge carriers in momentum space

description: Application of the nonadiabatic molecular dynamics (NAMD) approach is severely limited to studying carrier dynamics in the momentum space, since a supercell is required to sample the phonon excitation and electron-phonon (e-ph) interaction at different momenta in a molecular dynamics simulation. Here, we develop an ab initio approach for the real-time quantum dynamics for charge carriers in the momentum space (NAMD_k) by directly introducing the e-ph coupling into the Hamiltonian based on the harmonic approximation. The NAMD_k approach maintains the quantum zero-point energy and proper phonon dispersion, and includes memory effects of phonon excitation. The application of NAMD_k to the hot carrier dynamics in graphene reveals the phonon-specific relaxation mechanism. An energy threshold of 0.2eV, defined by two optical phonon modes strongly coupled to the electrons, separates the hot electron relaxation into fast and slow regions with the lifetimes of pico- and nano-seconds, respectively. The NAMD_k approach provides a powerful tool to understand real-time carrier dynamics in the momentum space for different materials.
DOI: 10.24435/materialscloud:f3-yh
title: A fourth-generation high-dimensional neural network potential with accurate electrostatics including non-local charge transfer

description: Machine learning potentials have become an important tool for atomistic simulations in many fields, from chemistry via molecular biology to materials science. Most of the established methods, however, rely on local properties and are thus unable to take global changes in the electronic structure into account, which result from long-range charge transfer or different charge states. In this work we overcome this limitation by introducing a fourth-generation high-dimensional neural network potential that combines a charge equilibration scheme employing environment-dependent atomic electronegativities with accurate atomic energies. The method, which is able to correctly describe global charge distributions in arbitrary systems, yields much improved energies and substantially extends the applicability of modern machine learning potentials. This is demonstrated for a series of systems representing typical scenarios in chemistry and materials science that are incorrectly described by current methods, while the fourth-generation neural network potential is in excellent agreement with electronic structure calculations.
DOI: 10.24435/materialscloud:3m-e6
title: Viscosity in water from first-principles and deep-neural-network simulations

description: We report on an extensive study of the viscosity of liquid water at near-ambient conditions, performed within the Green-Kubo theory of linear response and equilibrium ab initio molecular dynamics (AIMD), based on density-functional theory (DFT). In order to cope with the long simulation times necessary to achieve an acceptable statistical accuracy, our ab initio approach is enhanced with deep-neural-network potentials (NNP). This approach is first validated against AIMD results, obtained by using the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional and paying careful attention to crucial, yet often overlooked, aspects of the statistical data analysis. Then, we train a second NNP to a dataset generated from the strongly-constrained and appropriately-normed SCAN-DFT functional. Once the error resulting from the imperfect prediction of the melting line is offset by referring the simulated temperature to the theoretical melting one, our SCAN DFT predictions of the shear viscosity of water are in very good agreement with experiments.
DOI: 10.24435/materialscloud:dz-zg
title: A fourth-generation high-dimensional neural network potential with accurate electrostatics including non-local charge transfer

description: Machine learning potentials have become an important tool for atomistic simulations in many fields, from chemistry via molecular biology to materials science. Most of the established methods, however, rely on local properties and are thus unable to take global changes in the electronic structure into account, which result from long-range charge transfer or different charge states. In this work we overcome this limitation by introducing a fourth-generation high-dimensional neural network potential that combines a charge equilibration scheme employing environment-dependent atomic electronegativities with accurate atomic energies. The method, which is able to correctly describe global charge distributions in arbitrary systems, yields much improved energies and substantially extends the applicability of modern machine learning potentials. This is demonstrated for a series of systems representing typical scenarios in chemistry and materials science that are incorrectly described by current methods, while the fourth-generation neural network potential is in excellent agreement with electronic structure calculations.