materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).


$oid: OBSOLETE

en: We have analyzed structural motifs in the Deem database of hypothetical zeolites to investigate whether the structural diversity found in this database can be well-represented by classical descriptors, such as distances, angles, and ring sizes, or whether a more general representation of the atomic structure, furnished by the smooth overlap of atomic position (SOAP) method, is required to capture accurately structure–property relations. We assessed the quality of each descriptor by machine-learning the molar energy and volume for each hypothetical framework in the dataset. We have found that a SOAP representation with a cutoff length of 6 Å, which goes beyond near-neighbor tetrahedra, best describes the structural diversity in the Deem database by capturing relevant interatomic correlations. Kernel principal component analysis shows that SOAP maintains its superior performance even when reducing its dimensionality to those of the classical descriptors and that the first three kernel principal components capture the main variability in the dataset, allowing a 3D point cloud visualization of local environments in the Deem database. This "cloud atlas" of local environments was found to show good correlations with the contribution of a given motif to the density and stability of its parent framework. Local volume and energy maps constructed from the SOAP/machine learning analyses provide new images of zeolites that reveal smooth variations of local volumes and energies across a given framework and correlations between the contributions to volume and energy associated with each atom-centered environment.

approval_status: approved

en: Materials Cloud

de: Materials Cloud

fr: Materials Cloud

it: Materials Cloud

political_level: other

state: active

type: organization

psi

capacity: public

en: A New Kind of Atlas of Zeolite Building Blocks

type: dataset

key: guid

key: uri

value: DCAT Harvester Materials Cloud

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

erc

display_name: erc

machine-learning

display_name: machine-learning

marvel

display_name: marvel

sccer

display_name: sccer

zeolites

display_name: zeolites


en: This record mainly upload all the raw experimental data related to the manuscript. Fig1 include the transport data, magnetotransport data, AHE data, ESR data, uSR data. These data related to the conclusion that spin fluctuation established in the paramagnetic phase. Fig2 contains in-plane and out-of-plane 3D photoemission spectra, and high resolution cuts on top and side surface. Fig3 contains band electronic structure along high symmetry lines with spin along all kinds of typical directions. Fig4 contains 3-D in-plane and out-of-plane Fermi surfaces on the 101 cleavage, high resolution cuts, STM/STS data. The proved the observation of Weyl points.

en: Spin fluctuation induced Weyl semimetal state in the paramagnetic phase of EuCd2As2

arpes

display_name: arpes

magnetic-material

display_name: magnetic-material

magnetic-weyl-semimetal

display_name: magnetic-weyl-semimetal

spin-fluctuation

display_name: spin-fluctuation

topological-material

display_name: topological-material


en: This database includes Isotropic lattice thermal conductivities of MgSiO3 post-perovskite under the lowermost mantle conditions. The conductivity was calculated based on the ab initio anharmonic lattice dynamics with solving the linearized phonon Boltzmann transport equation.

en: Lattice thermal conductivity of MgSiO3 post-perovskite under the lowermost mantle conditions from ab initio anharmonic lattice dynamics

density-functional-theory

display_name: density-functional-theory

earths-lower-mantle-mineral

display_name: earths-lower-mantle-mineral

phonon-transport-properties

display_name: phonon-transport-properties


en: Coronoids, polycyclic aromatic hydrocarbons with geometrically defined cavities, are promising model structures of porous graphene. This record contains data to support our recent research where we report the on-surface synthesis of C168 and C140 coronoids, referred to as [6]- and [5]coronoid, respectively, using 5,9-dibromo-14-phenylbenzo[m]tetraphene as the precursor. These coronoids entail large cavities (>1 nm) with inner zigzag edges, distinct from their outer armchair edges. While [6]coronoid is planar, [5]coronoid is not. Low-temperature scanning tunneling microscopy/spectroscopy and noncontact atomic force microscopy unveil structural and electronic properties in accordance with those obtained from density functional theory calculations. Detailed analysis of ring current effects identifies the rings with the highest aromaticity of these coronoids, whose pattern matches their Clar structure. The pores of the obtained coronoids offer intriguing possibilities of further functionalization toward advanced host–guest applications.

en: Large-cavity coronoids with different inner and outer edge structures

ab-initio

display_name: ab-initio

aromaticity

display_name: aromaticity

coronoid

display_name: coronoid

cscs

display_name: cscs

snsf

display_name: snsf


en: This entry provides the snapshots of liquid water generated with ab initio molecular dynamics using rVV10 density functional at room temperature. Nuclear quantum effects are taken into account through path-integral molecular dynamics simulations.

en: Ab initio electronic structure of liquid water: Molecular dynamics snapshots

liquid-water

display_name: liquid-water

nuclear-quantum-effect

display_name: nuclear-quantum-effect


en:
Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here, we propose a universal standard protocol to verify publicly available pseudopotential libraries, based on several independent criteria including verification against all-electron equations of state and plane-wave convergence tests for phonon frequencies, band structure, cohesive energy and pressure. Adopting these criteria we obtain two optimal pseudopotential sets, namely the Standard Solid State Pseudopotential (SSSP) efficiency and precision libraries, tailored for high-throughput materials screening and high-precision materials modelling. As of today, the SSSP precision library is the most accurate open-source pseudopotential library available. This archive entry contains the database of calculations (phonons, cohesive energy, equation of state, band structure, pressure, etc.) together with the provenance of all data and calculations as stored by AiiDA.

*** UPDATE April 2020 ***
The zipped tarball archives and AiiDA export files had inconsistent internal formats and naming conventions, which made it difficult to work with them programmatically. In this update, the files are standardized according to the conventions that are detailed in the README.md file. Note that the actual content of pseudo potential files and the JSON metadata files has **not** changed, with the exception that the keys "cutoff" and "dual" in the JSON files have been replaced with "cutoff_wfc" and "cutoff_rho". Here the value of "cutoff_wfc" is equal to the old "cutoff", and "cutoff_rho" is equal to the product of the old "cutoff" and "dual". Besides that, the update concerns merely the renaming of certain files and the restructuring of archive formats.

*** UPDATE November 2020 ***
The AiiDA export files contained in the sssp.tar archive have been modified and migrated to version format 0.9 in order to be imported in AiiDA 1.2.0 and later versions. The modifications are detailed in the README.md file in the sssp.tar archive.
The AiiDA export files contained in the sssp_bands.tar archive have been migrated to version format 0.9 as well.

*** UPDATE April 2021 - Version 1.1.1 ***
The PBEsol pseudopotential files contained unescaped "&" characters. In this update, the files concerned have been fixed escaping the "&" characters contained in PP_INPUTFILE blocks.

*** UPDATE May 2021 - Version 1.1.2 ***
For compatibility issues, the mesh_size in the header of the pseudopotential files has been changed to be the same as the mesh value. These issues affected the pseudopotential files for the lanthanides.
Note that, starting from this version, for each minor version only the files of the corresponding latest patch version are provided. The files of the previous patch versions (i.e. 1.1, 1.1.1) can be retrieved from the previous versions of this record.
Note also that the AiiDA export archives of the different SSSP configurations are not provided any more. In order to use the SSSP configurations in AiiDA, it is recommended instead to install them through the aiida-pseudo package (https://aiida-pseudo.readthedocs.io/en/latest/).

*** UPDATE Nov 2022 - Version 1.2 ***
The PBE pseudopotentials for the Lanthanides (precision and efficiency) are regenerated with ATOMPAW-4.2.0.2. This 1) provides orbital labels for all the pseudo-wavefunctions (required by +U calculations), and 2) alleviates convergence issues related to negative pseudo-charge densities in ultrasoft/PAW potentials (La/Ce pseudopotentials are generated with adapted inputs courtesy of Simon Pintarelli (https://github.com/simonpintarelli/mineralscloud_paw_rccore)).
In the SSSP precision PBE library, the choices for 14 pseudopotentials (Na, Cu, Cs, Ca, Ba, As, Te, I, Hg, Ne, Ar, Kr, Xe, Rn) are updated after taking into consideration the equation-of-state results for oxides (X2O, X2O3, X2O5, XO, XO2, XO3) and uninaries (BCC, FCC, SC, Diamond) compared to the all-electron solution from WIEN2K.
The SSSP efficiency and SSSP precision pseudopotentials for Cu both are replaced by the pseudopotential from the pslibrary 1.0.0 low acc as proposed in v1.2.0 beta.
The SSSP precision pseudopotential for Ba is replaced by the pseudopotential from pseudo-dojo library name as Ba.nc.z_10.oncvpsp4.dojo.v4-sp.upf.
For elements Na, Cs, Ca, As, Te, Hg, I, Ne, Ar, Kr, Xe, and Rn, the SSSP precision pseudopotentials are replaced by the pseudopotentials with different recommended choices without changing.

The AiiDA export files are contained in the sssp-infos.aiida archive has been modified from sssp.tar and migrated to storage schema version "main_0001" in order to be imported in AiiDA 2.0.2 and later versions. The modifications are detailed in the README.md file in the sssp-infos.aiida archive.
The AiiDA export files are contained in the sssp-bands.aiida archive has been migrated to storage schema version "main_0001" as well.

en: A Standard Solid State Pseudopotentials (SSSP) library optimized for precision and efficiency

aiida

display_name: aiida

calculations

display_name: calculations

chessboards

display_name: chessboards

cohesive-energy

display_name: cohesive-energy

database

display_name: database

dft

display_name: dft

efficiency

display_name: efficiency

electronic-bands

display_name: electronic-bands

electronic-properties

display_name: electronic-properties

elemental-solids

display_name: elemental-solids

high-throughput

display_name: high-throughput

library

display_name: library

marvel

display_name: marvel

max

display_name: max

phonons

display_name: phonons

prace

display_name: prace

precision

display_name: precision

pseudopotentials

display_name: pseudopotentials

sssp

display_name: sssp

standard

display_name: standard

verification

display_name: verification


en:
With the growth of natural gas as an energy source, upgrading CO2-contaminated supplies has become increasingly important. Here we develop a single metric that captures how well an adsorbent performs the separation of CH4 and CO2, and we then use this metric to computationally screen tens of thousands of all-silica zeolites. We show that the most important predictors of separation performance are the CO2 heat of adsorption (Qst, CO2) and the CO2 saturation loading capacity. We find that a higher-performing material results when the absolute value of the CH4 heat of adsorption (Qst, CH4) is decreased independently of Qst, CO2, but a correlation that exists between Qst, CH4 and Qst, CO2 in all-silica zeolites leads to incongruity between the objectives of optimizing Qst, CO2 and minimizing Qst, CH4, rendering Qst, CH4 nonpredictive of separation performance. We also conduct a large-scale analysis of ideal adsorbed solution theory (IAST) by comparing results obtained using directly-generated mixture isotherms to those obtained using IAST; IAST appears adequate for the purposes of establishing performance trends and structure–property relationships in a high-throughput manner, but it must be tested for validity when analyzing individual adsorbents in detail since it can produce significant errors for materials in which there is site segregation of the adsorbate species.

Version 2 provides the structures in CIF format.

en: High-throughput computational screening of nanoporous adsorbents for CO 2 capture from natural gas

database

display_name: database

dc

display_name: dc

deliverable-capacities

display_name: deliverable-capacities

gcmc

display_name: gcmc

grand-canonical-monte-carlo

display_name: grand-canonical-monte-carlo

iza

display_name: iza

methane-storage

display_name: methane-storage

nanoporous

display_name: nanoporous

porous-polymer-networks

display_name: porous-polymer-networks

three-dimensional

display_name: three-dimensional

zeolites

display_name: zeolites


en: Molecular self-assembly plays a very important role in various aspects of technology as well as in biological systems. Governed by covalent, hydrogen or van der Waals interactions - self-assembly of alike molecules results in a large variety of complex patterns even in two dimensions (2D). Prediction of pattern formation for 2D molecular networks is extremely important, though very challenging, and so far, relied on computationally involved approaches such as density functional theory, classical molecular dynamics, Monte Carlo, or machine learning. Such methods, however, do not guarantee that all possible patterns will be considered and often rely on intuition. Here we introduce a much simpler, though rigorous, hierarchical geometric model founded on the mean-field theory of 2D polygonal tessellations to predict extended network patterns based on molecular-level information. Based on graph theory, this approach yields pattern classification and pattern prediction within well-defined ranges. When applied to existing experimental data, our model provides an entirely new view of self-assembled molecular patterns, leading to interesting predictions on admissible patterns and potential additional phases. While developed for hydrogen-bonded systems, an extension to covalently bonded graphene-derived materials or 3D structures such as fullerenes is possible, significantly opening the range of potential future applications.

materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).

en: Polygonal tessellations as predictive models of molecular monolayers

molecular-self-assembly

display_name: molecular-self-assembly

tesselation

display_name: tesselation


materialscloud

en: Materials Cloud


en:
Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here, we propose a universal standard protocol to verify publicly available pseudopotential libraries, based on several independent criteria including verification against all-electron equations of state and plane-wave convergence tests for phonon frequencies, band structure, cohesive energy and pressure. Adopting these criteria we obtain two optimal pseudopotential sets, namely the Standard Solid State Pseudopotential (SSSP) efficiency and precision libraries, tailored for high-throughput materials screening and high-precision materials modelling. As of today, the SSSP precision library is the most accurate open-source pseudopotential library available. This archive entry contains the database of calculations (phonons, cohesive energy, equation of state, band structure, pressure, etc.) together with the provenance of all data and calculations as stored by AiiDA.

*** UPDATE April 2020 ***
The zipped tarball archives and AiiDA export files had inconsistent internal formats and naming conventions, which made it difficult to work with them programmatically. In this update, the files are standardized according to the conventions that are detailed in the README.md file. Note that the actual content of pseudo potential files and the JSON metadata files has **not** changed, with the exception that the keys "cutoff" and "dual" in the JSON files have been replaced with "cutoff_wfc" and "cutoff_rho". Here the value of "cutoff_wfc" is equal to the old "cutoff", and "cutoff_rho" is equal to the product of the old "cutoff" and "dual". Besides that, the update concerns merely the renaming of certain files and the restructuring of archive formats.

envi

en: Environment

calculations

display_name: calculations

chessboards

display_name: chessboards

cohesive-energy

display_name: cohesive-energy

cscs

display_name: cscs

dft

display_name: dft

efficiency

display_name: efficiency

electronic-bands

display_name: electronic-bands

electronic-properties

display_name: electronic-properties

elemental-solids

display_name: elemental-solids

high-throughput

display_name: high-throughput

library

display_name: library

marvel

display_name: marvel

max

display_name: max

phonons

display_name: phonons

prace

display_name: prace

precision

display_name: precision

pseudopotentials

display_name: pseudopotentials

vibrational-properties

display_name: vibrational-properties


en: Interatomic potentials are often necessary to describe complex realistic systems that would be too costly to study from first-principles. Commonly, interatomic potentials are designed using functional forms driven by physical intuition and fitted to experimental or computational data. The moderate flexibility of these functional forms limits their ability to be systematically improved by increasing the fitting datasets; on the other hand, their qualitative description of the essential physical interactions ensures a modicum degree of transferability. Recently, a novel trend has emerged where potential-energy surfaces are represented by neural networks fitted on large numbers of first-principles calculations, thus maximizing flexibility but requiring extensive datasets to ensure transferability. Gaussian Approximation Potentials in particular are a novel class of potentials based on non-linear, non-parametric Gaussian-process regression. Here we generate a Gaussian Approximation model for the α-phase of iron training on energies, stresses and forces taken from first-principles molecular dynamics simulations of pristine and defected bulk systems, of surfaces and γ-surfaces with different crystallographic orientations.

en: Gaussian Approximation Potentials for iron from extended first-principles database (Data Download)

-iron

display_name: -iron

artificial-neural-networks

display_name: artificial-neural-networks

gaussian-approximation-potentials

display_name: gaussian-approximation-potentials

interatomic-potentials

display_name: interatomic-potentials

machine-learning

display_name: machine-learning


en: Several enhanced sampling methods, such as umbrella sampling or metadynamics, rely on the identification of an appropriate set of collective variables. Recently two methods have been proposed to alleviate the task of determining efficient collective variables. One is based on linear discriminant analysis; the other is based on a variational approach to conformational dynamics and uses time-lagged independent component analysis. In this paper, we compare the performance of these two approaches in the study of the homogeneous crystallization of two simple metals. We focus on Na and Al and search for the most efficient collective variables that can be expressed as a linear combination of X-ray diffraction peak intensities. We find that the performances of the two methods are very similar. Wherever the different metastable states are well-separated, the method based on linear discriminant analysis, based on its harmonic version, is to be preferred because simpler to implement and less computationally demanding. The variational approach, however, has the potential to discover the existence of different metastable states.

en: Improving collective variables: The case of crystallization

crystalization

display_name: crystalization

enhanced-sampling

display_name: enhanced-sampling

hlda

display_name: hlda

plumed

display_name: plumed


en: Rare-earth nickelates exhibit a metal–insulator transition accompanied by a structural distortion that breaks the symmetry between formerly equivalent Ni sites. The quantitative theoretical description of this coupled electronic–structural instability is extremely challenging. Here, we address this issue by simultaneously taking into account both structural and electronic degrees of freedom using a charge self-consistent combination of density functional theory and dynamical mean-field theory, together with screened interaction parameters obtained from the constrained random phase approximation. Our total energy calculations show that the coupling to an electronic instability toward a charge disproportionated insulating state is crucial to stabilize the structural distortion, leading to a clear first order character of the coupled transition. The decreasing octahedral rotations across the series suppress this electronic instability and simultaneously increase the screening of the effective Coulomb interaction, thus weakening the correlation effects responsible for the metal–insulator transition. Our approach allows to obtain accurate values for the structural distortion and thus facilitates a comprehensive understanding, both qualitatively and quantitatively, of the complex interplay between structural properties and electronic correlation effects across the nickelate series.

en: Energetics of the coupled electronic–structural transition in the rare-earth nickelates

dynamical-mean-field-theory

display_name: dynamical-mean-field-theory

electronic-properties-and-materials

display_name: electronic-properties-and-materials

quantum-materials

display_name: quantum-materials


marvel

display_name: marvel


en: We present all AMONs for GDB and Zinc data-bases using no more than 7 non-hydrogen atoms (AGZ7)---a calculated organic chemistry building-block dictionary based on the AMON approach [Huang and von Lilienfeld, Nature Chemistry (2020)]. AGZ7 records Cartesian coordinates of compositional and constitutional isomers, as well as properties for ∼140k small organic molecules obtained by systematically fragmenting all molecules of Zinc and the majority of GDB17 into smaller entities, saturating with hydrogens, and containing no more than 7 heavy atoms (excluding hydrogen atoms). AGZ7 cover the elements H, B, C, N, O, F, Si, P, S, Cl, Br, Sn and I and includes optimized geometries, total energy and its decomposition, Mulliken atomic charges, dipole moment vectors, quadrupole tensors, electronic spatial extent, eigenvalues of all occupied orbitals, LUMO, gap, isotropic polarizability, harmonic frequencies, reduced masses, force constants, IR intensity, normal coordinates, rotational constants, zero-point energy, internal energy, enthalpy, entropy, free energy, and heat capacity (all at ambient conditions) using B3LYP/cc-pVTZ (pseudopotentials were used for Sn and I) level of theory. We exemplify the usefulness of this data set with AMON based machine learning models of total potential energy predictions of seven of the most rigid GDB-17 molecules.

en: Dictionary of 140k GDB and ZINC derived AMONs

building-blocks

display_name: building-blocks

erc

display_name: erc

organic-chemical-space

display_name: organic-chemical-space

quantum-machine-learning

display_name: quantum-machine-learning

snsf

display_name: snsf


en: We propose perovskite nitrides with magnetic rare-earth metals as novel materials with a range of technological applications. These materials appear to be thermodynamically stable and, in spite of possessing different crystal structures and different atomic environments, they retain the magnetic moment of the corresponding elemental rare-earth metal. We find both magnetic metals and semiconductors, with a wide range of magnetic moments and some systems posses record-high magnetic anisotropy energies. Further tuning of the electronic and magnetic properties can also be expected by doping with other rare-earths or by creating solid solutions. The synthesis of these exotic materials with unusual compositions would extend not only the accepted stability domain of perovskites but also open the way for a series of applications enabled by their rich physics.

en: Rare-earth magnetic nitride perovskites

magnetic-anisotropy-energy

display_name: magnetic-anisotropy-energy

nitride-perovskites

display_name: nitride-perovskites

rare-earth-metals

display_name: rare-earth-metals


rare-earth-magnetic-nitride-perovskites

title_for_slug: rare-earth-magnetic-nitride-perovskites


en: Covalent organic frameworks (COFs) are a class of advanced nanoporous polymeric materials which combine the crystallinity of metal–organic frameworks (MOFs) with the stability and potentially low-cost organic chemistry of porous polymer networks (PPNs). Like other advanced porous materials, COFs can potentially be designed to meet the needs of a variety of applications, from energy, to security, to human health. In this work, we construct in silico a database of hypothetical three-dimensional, crystalline COFs. In constructing this library we generate novel COFs using only established synthetic routes, previously utilized tetrahedral building units, and commercially available bridging "linker" molecules. This ensures that there are no known chemical barriers to synthesizing all materials in our database. We relaxed all materials in our database through semiempirical electronic structure calculations. In addition, for those structures that allow interpenetration, we designed interpenetrated versions of the basic structure. Then, we characterized the porosity of each of these structures. The final set of 4147 structures (based on 620 unique noninterpenetrated structures) and their computed properties are publicly available and can be screened to identify promising materials for a wide variety of applications. Here, we assess the suitability of our COFs for vehicular methane storage by performing molecular simulations to predict the equilibrium methane uptake.

en: In silico design of three-dimensional porous covalent organic frameworks via known synthesis routes and commercially available species

cofs

display_name: cofs

covalent-organic-frameworks

display_name: covalent-organic-frameworks

database

display_name: database

dc

display_name: dc

deliverable-capacities

display_name: deliverable-capacities

gcmc

display_name: gcmc

grand-canonical-monte-carlo

display_name: grand-canonical-monte-carlo

high-throughput

display_name: high-throughput

methane-storage

display_name: methane-storage

nanoporous

display_name: nanoporous

three-dimensional

display_name: three-dimensional


materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).


artificial-neural-networks

display_name: artificial-neural-networks

gaussian-approximation-potentials

display_name: gaussian-approximation-potentials

interatomic-potentials

display_name: interatomic-potentials

iron

display_name: iron

machine-learning

display_name: machine-learning

marvel

display_name: marvel


en: Metal-organic frameworks (MOFs) have emerged as versatile materials for applications ranging from gas separation and storage, catalysis, and sensing. The attractive feature of MOFs is that by changing the ligand and/or metal, they can be chemically tuned to perform optimally for a given application. In most, if not all, of these applications one also needs a material that has a sufficient mechanical stability, but our understanding of how changes in the chemical structure influence mechanical stability is limited. In this work, we rationalize how the mechanical properties of MOFs are related to framework bonding topology and ligand structure. We illustrate that the functional groups on the organic ligands can either enhance the mechanical stability through formation of a secondary network of non-bonded interactions, or soften the material by destabilizing the bonded network of a MOF. In addition, we show that synergistic effect of the bonding network of the material and the secondary network is required to achieve optimal mechanical stability of a MOF. The developed molecular insights in this work can be used for systematic improvement of the mechanical stability of the materials by careful selection of the functional groups.

en: Improving the Mechanical Stability of Metal-Organic Frameworks Using Chemical Caryatids

mechanical-properties

display_name: mechanical-properties

nanoporous-materials

display_name: nanoporous-materials

stability

display_name: stability


materialscloud

en: Materials Cloud


en: Methods based on the second order Møller–Plesset perturbation theory (MP2) and the Random Phase Approximation (RPA) have emerged as practicable and reliable approaches to improve the accuracy of density functional approximations for first principle atomistic simulations. Such approaches are in fact capable to account ab-initio for non-local dynamical electron correlation effects, which play a fundamental role, for example, in the description of non-bonded interactions. To assess the performance of MP2 and RPA for real applications, isobaric-isothermal Monte Carlo simulations have been performed to study the structural properties of bulk liquid water under ambient conditions. The choice of bulk liquid water as benchmark system is motivated by the complicated nature of the intermolecular interactions, where repulsion, polarization, hydrogen bonding and van der Waals forces play an important role and are particularly difficult to reproduce accurately in atomistic models. The results demonstrate the feasibility of such approaches which open the way for further applications.

en: Isobaric-Isothermal Monte Carlo Simulations of Bulk Liquid Water from MP2 and RPA Theory (MC Trajectories Data Download)

envi

en: Environment

bulk-liquid-water

display_name: bulk-liquid-water

isobaric-isothermal-npt

display_name: isobaric-isothermal-npt

monte-carlo-simulations

display_name: monte-carlo-simulations

rpa

display_name: rpa


en: The free energy landscapes of several fundamental processes are characterized by high barriers separating long-lived metastable states. In order to explore these type of landscapes enhanced sampling methods are used. While many such methods are able to obtain sufficient sampling in order to draw the free energy, the transition states are often sparsely sampled. We propose an approach based on the Variationally Enhanced Sampling Method to enhance sampling in the transition region. To this effect, we introduce a dynamic target distribution which uses the derivative of the instantaneous free energy surface to locate the transition regions on the fly and modulate the probability of sampling different regions. Finally, we exemplify  the effectiveness of this approach in enriching the number of configurations in the transition state region in the cases of a chemical reaction and of a nucleation process.

en: Enhanced sampling of transition states

critical-clusters

display_name: critical-clusters

enhanced-sampling

display_name: enhanced-sampling

molecular-modelling

display_name: molecular-modelling

nucleation

display_name: nucleation

transition-states

display_name: transition-states


en: Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here, we propose a universal standard protocol to verify publicly available pseudopotential libraries, based on several independent criteria including verification against all-electron equations of state and plane-wave convergence tests for phonon frequencies, band structure, cohesive energy and pressure. Adopting these criteria we obtain two optimal pseudopotential sets, namely the Standard Solid State Pseudopotential (SSSP) efficiency and accuracy libraries, tailored for high-throughput materials screening and high-precision materials modelling. As of today, the SSSP accuracy library is the most accurate open-source pseudopotential library available. This archive entry contains the database of calculations (phonons, cohesive energy, equation of state, band structure, pressure, etc.) together with the provenance of all data and calculations as stored by AiiDA.

en: A Standard Solid State Pseudopotentials (SSSP) library optimized for accuracy and efficiency (Version 1.0, data download)

accuracy

display_name: accuracy

calculations

display_name: calculations

chessboards

display_name: chessboards

cohesive-energy

display_name: cohesive-energy

database

display_name: database

dft

display_name: dft

efficiency

display_name: efficiency

electronic-bands

display_name: electronic-bands

electronic-properties

display_name: electronic-properties

elemental-solids

display_name: elemental-solids

high-throughput

display_name: high-throughput

library

display_name: library

phonons

display_name: phonons

pseudopotentials

display_name: pseudopotentials

sssp

display_name: sssp

standard

display_name: standard

verification

display_name: verification

vibrational-properties

display_name: vibrational-properties


en:
With the growth of natural gas as an energy source, upgrading CO2-contaminated supplies has become increasingly important. Here we develop a single metric that captures how well an adsorbent performs the separation of CH4 and CO2, and we then use this metric to computationally screen tens of thousands of all-silica zeolites. We show that the most important predictors of separation performance are the CO2 heat of adsorption (Qst, CO2) and the CO2 saturation loading capacity. We find that a higher-performing material results when the absolute value of the CH4 heat of adsorption (Qst, CH4) is decreased independently of Qst, CO2, but a correlation that exists between Qst, CH4 and Qst, CO2 in all-silica zeolites leads to incongruity between the objectives of optimizing Qst, CO2 and minimizing Qst, CH4, rendering Qst, CH4 nonpredictive of separation performance. We also conduct a large-scale analysis of ideal adsorbed solution theory (IAST) by comparing results obtained using directly-generated mixture isotherms to those obtained using IAST; IAST appears adequate for the purposes of establishing performance trends and structure–property relationships in a high-throughput manner, but it must be tested for validity when analyzing individual adsorbents in detail since it can produce significant errors for materials in which there is site segregation of the adsorbate species.

Version 2 provides the structures in CIF format.

en: High-throughput computational screening of nanoporous adsorbents for CO 2 capture from natural gas

dc

display_name: dc

deliverable-capacities

display_name: deliverable-capacities

gcmc

display_name: gcmc

grand-canonical-monte-carlo

display_name: grand-canonical-monte-carlo

iza

display_name: iza

methane-storage

display_name: methane-storage

nanoporous

display_name: nanoporous

porous-polymer-networks

display_name: porous-polymer-networks

three-dimensional

display_name: three-dimensional

zeolites

display_name: zeolites


en: With the growth of natural gas as an energy source, upgrading CO2-contaminated supplies has become increasingly important. Here we develop a single metric that captures how well an adsorbent performs the separation of CH4 and CO2, and we then use this metric to computationally screen tens of thousands of all-silica zeolites. We show that the most important predictors of separation performance are the CO2 heat of adsorption (Qst, CO2) and the CO2 saturation loading capacity. We find that a higher-performing material results when the absolute value of the CH4 heat of adsorption (Qst, CH4) is decreased independently of Qst, CO2, but a correlation that exists between Qst, CH4 and Qst, CO2 in all-silica zeolites leads to incongruity between the objectives of optimizing Qst, CO2 and minimizing Qst, CH4, rendering Qst, CH4 nonpredictive of separation performance. We also conduct a large-scale analysis of ideal adsorbed solution theory (IAST) by comparing results obtained using directly-generated mixture isotherms to those obtained using IAST; IAST appears adequate for the purposes of establishing performance trends and structure–property relationships in a high-throughput manner, but it must be tested for validity when analyzing individual adsorbents in detail since it can produce significant errors for materials in which there is site segregation of the adsorbate species.

database

display_name: database

high-throughput

display_name: high-throughput


critical-clusters

display_name: critical-clusters

enhanced-sampling

display_name: enhanced-sampling

molecular-modelling

display_name: molecular-modelling

nucleation

display_name: nucleation

transition-states

display_name: transition-states


enhanced-sampling-of-transition-states

title_for_slug: enhanced-sampling-of-transition-states


en:
Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here, we propose a universal standard protocol to verify publicly available pseudopotential libraries, based on several independent criteria including verification against all-electron equations of state and plane-wave convergence tests for phonon frequencies, band structure, cohesive energy and pressure. Adopting these criteria we obtain two optimal pseudopotential sets, namely the Standard Solid State Pseudopotential (SSSP) efficiency and precision libraries, tailored for high-throughput materials screening and high-precision materials modelling. As of today, the SSSP precision library is the most accurate open-source pseudopotential library available. This archive entry contains the database of calculations (phonons, cohesive energy, equation of state, band structure, pressure, etc.) together with the provenance of all data and calculations as stored by AiiDA.

*** UPDATE April 2020 ***
The zipped tarball archives and AiiDA export files had inconsistent internal formats and naming conventions, which made it difficult to work with them programmatically. In this update, the files are standardized according to the conventions that are detailed in the README.md file. Note that the actual content of pseudo potential files and the JSON metadata files has **not** changed, with the exception that the keys "cutoff" and "dual" in the JSON files have been replaced with "cutoff_wfc" and "cutoff_rho". Here the value of "cutoff_wfc" is equal to the old "cutoff", and "cutoff_rho" is equal to the product of the old "cutoff" and "dual". Besides that, the update concerns merely the renaming of certain files and the restructuring of archive formats.

*** UPDATE November 2020 ***
The AiiDA export files contained in the sssp.tar archive have been modified and migrated to version format 0.9 in order to be imported in AiiDA 1.2.0 and later versions. The modifications are detailed in the README.md file in the sssp.tar archive.
The AiiDA export files contained in the sssp_bands.tar archive have been migrated to version format 0.9 as well.

en: A Standard Solid State Pseudopotentials (SSSP) library optimized for precision and efficiency

calculations

display_name: calculations

chessboards

display_name: chessboards

cohesive-energy

display_name: cohesive-energy

cscs

display_name: cscs

dft

display_name: dft

efficiency

display_name: efficiency

electronic-bands

display_name: electronic-bands

electronic-properties

display_name: electronic-properties

elemental-solids

display_name: elemental-solids

library

display_name: library

marvel

display_name: marvel

max

display_name: max

phonons

display_name: phonons

prace

display_name: prace

precision

display_name: precision

pseudopotentials

display_name: pseudopotentials

sssp

display_name: sssp

standard

display_name: standard

verification

display_name: verification

vibrational-properties

display_name: vibrational-properties


en: Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here, we propose a universal standard protocol to verify publicly available pseudopotential libraries, based on several independent criteria including verification against all-electron equations of state and plane-wave convergence tests for phonon frequencies, band structure, cohesive energy and pressure. Adopting these criteria we obtain two optimal pseudopotential sets, namely the Standard Solid State Pseudopotential (SSSP) efficiency and precision libraries, tailored for high-throughput materials screening and high-precision materials modelling. As of today, the SSSP precision library is the most accurate open-source pseudopotential library available. This archive entry contains the database of calculations (phonons, cohesive energy, equation of state, band structure, pressure, etc.) together with the provenance of all data and calculations as stored by AiiDA.

en: A Standard Solid State Pseudopotentials (SSSP) library optimized for precision and efficiency (Version 1.0, data download)

calculations

display_name: calculations

chessboards

display_name: chessboards

cohesive-energy

display_name: cohesive-energy

database

display_name: database

high-throughput

display_name: high-throughput


en: Dipole polarizabilities, computed using linear response coupled cluster theory and density functional theory (using d-aug-cc-pVDZ basis set), for 7211 molecules from the QM7b dataset of small molecules and for 52 molecules from a showcase dataset.

materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).

en: Coupled-Cluster Polarizabilities in the QM7b and a Showcase Database

density-functional-theory

display_name: density-functional-theory

dipole-polarizability

display_name: dipole-polarizability

linear-response-coupled-cluster

display_name: linear-response-coupled-cluster


en: Metal–organic frameworks (MOFs), a class of porous materials, are of particular interest in gas storage and separation applications due largely to their high internal surface areas and tunable structures. MOF-5 is perhaps the archetypal MOF; in particular, many isoreticular analogues of MOF-5 have been synthesized, comprising alternative dicarboxylic acid ligands. In this contribution we introduce a new set of hypothesized MOF-5 analogues, constructed from commercially available organic molecules. We describe our automated procedure for hypothetical MOF design, comprising selection of appropriate ligands, construction of 3D structure models, and structure relaxation methods. 116 MOF-5 analogues were designed and characterized in terms of geometric properties and simulated methane uptake at conditions relevant to vehicular storage applications. A strength of the presented approach is that all of the hypothesized MOFs are designed to be synthesizable utilizing ligands purchasable online.

materialscloud

en: Materials Cloud

en: Mail-order metal-organic frameworks (MOFs): designing isoreticular MOF-5 analogues comprising commercially available organic molecules

dc

display_name: dc

deliverable-capacities

display_name: deliverable-capacities

gcmc

display_name: gcmc

grand-canonical-monte-carlo

display_name: grand-canonical-monte-carlo

methane-storage

display_name: methane-storage

nanoporous

display_name: nanoporous

three-dimensional

display_name: three-dimensional


en:
Metal–organic frameworks (MOFs), a class of porous materials, are of particular interest in gas storage and separation applications due largely to their high internal surface areas and tunable structures. MOF-5 is perhaps the archetypal MOF; in particular, many isoreticular analogues of MOF-5 have been synthesized, comprising alternative dicarboxylic acid ligands. In this contribution we introduce a new set of hypothesized MOF-5 analogues, constructed from commercially available organic molecules. We describe our automated procedure for hypothetical MOF design, comprising selection of appropriate ligands, construction of 3D structure models, and structure relaxation methods. 116 MOF-5 analogues were designed and characterized in terms of geometric properties and simulated methane uptake at conditions relevant to vehicular storage applications. A strength of the presented approach is that all of the hypothesized MOFs are designed to be synthesizable utilizing ligands purchasable online.

Version 2 includes the structures in CIF format.

envi

en: Environment


en: A Standard Solid State Pseudopotentials (SSSP) library optimized for precision and efficiency (Version 1.1, data download)

dft

display_name: dft

efficiency

display_name: efficiency

electronic-bands

display_name: electronic-bands

electronic-properties

display_name: electronic-properties

elemental-solids

display_name: elemental-solids

library

display_name: library

marvel

display_name: marvel

phonons

display_name: phonons

precision

display_name: precision

pseudopotentials

display_name: pseudopotentials

sssp

display_name: sssp

standard

display_name: standard

verification

display_name: verification


density-functional-theory

display_name: density-functional-theory

dipole-polarizability

display_name: dipole-polarizability

linear-response-coupled-cluster

display_name: linear-response-coupled-cluster


en:
Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here, we propose a universal standard protocol to verify publicly available pseudopotential libraries, based on several independent criteria including verification against all-electron equations of state and plane-wave convergence tests for phonon frequencies, band structure, cohesive energy and pressure. Adopting these criteria we obtain two optimal pseudopotential sets, namely the Standard Solid State Pseudopotential (SSSP) efficiency and precision libraries, tailored for high-throughput materials screening and high-precision materials modelling. As of today, the SSSP precision library is the most accurate open-source pseudopotential library available. This archive entry contains the database of calculations (phonons, cohesive energy, equation of state, band structure, pressure, etc.) together with the provenance of all data and calculations as stored by AiiDA.

*** UPDATE November 2020 ***
The AiiDA export files contained in the sssp.tar archive have been modified and migrated to version format 0.9 in order to be imported in AiiDA 1.2.0 and later versions. The modifications are detailed in the README.md file in the sssp.tar archive.
The AiiDA export files contained in the sssp_bands.tar archive have been migrated to version format 0.9 as well.

*** UPDATE April 2021 - Version 1.1.1 ***
The PBEsol pseudopotential files contained unescaped "&" characters. In this update, the files concerned have been fixed escaping the "&" characters contained in PP_INPUTFILE blocks.

*** UPDATE May 2021 - Version 1.1.2 ***
For compatibility issues, the mesh_size in the header of the pseudopotential files has been changed to be the same as the mesh value. These issues affected the pseudopotential files for the lanthanides.
Note that, starting from this version, for each minor version only the files of the corresponding latest patch version are provided. The files of the previous patch versions (i.e. 1.1, 1.1.1) can be retrieved from the previous versions of this record.
Note also that the AiiDA export archives of the different SSSP configurations are not provided any more. In order to use the SSSP configurations in AiiDA, it is recommended instead to install them through the aiida-pseudo package (https://aiida-pseudo.readthedocs.io/en/latest/).
u
*** UPDATE Nov 2022 - Version 1.2 ***
The PBE pseudopotentials for the Lanthanides (precision and efficiency) are regenerated with ATOMPAW-4.2.0.2. This 1) provides orbital labels for all the pseudo-wavefunctions (required by +U calculations), and 2) alleviates convergence issues related to negative pseudo-charge densities in ultrasoft/PAW potentials (La/Ce pseudopotentials are generated with adapted inputs courtesy of Simon Pintarelli (https://github.com/simonpintarelli/mineralscloud_paw_rccore)).
In the SSSP precision PBE library, the choices for 14 pseudopotentials (Na, Cu, Cs, Ca, Ba, As, Te, I, Hg, Ne, Ar, Kr, Xe, Rn) are updated after taking into consideration the equation-of-state results for oxides (X2O, X2O3, X2O5, XO, XO2, XO3) and uninaries (BCC, FCC, SC, Diamond) compared to the all-electron solution from WIEN2K.
The SSSP efficiency and SSSP precision pseudopotentials for Cu both are replaced by the pseudopotential from the pslibrary 1.0.0 low acc as proposed in v1.2.0 beta.
The SSSP precision pseudopotential for Ba is replaced by the pseudopotential from pseudo-dojo library name as Ba.nc.z_10.oncvpsp4.dojo.v4-sp.upf.
For elements Na, Cs, Ca, As, Te, Hg, I, Ne, Ar, Kr, Xe, and Rn, the SSSP precision pseudopotentials are replaced by the pseudopotentials with different recommended choices without changing.

The AiiDA export files are contained in the sssp-infos.aiida archive has been modified from sssp.tar and migrated to storage schema version "main_0001" in order to be imported in AiiDA 2.0.2 and later versions. The modifications are detailed in the README.md file in the sssp-infos.aiida archive.
The AiiDA export files are contained in the sssp-bands.aiida archive has been migrated to storage schema version "main_0001" as well.

*** UPDATE Mar 2023 - Version 1.2.1 ***
The precision libraries for Iridium (Ir) have been updated with the latest pseudopotential from Pslibrary accuracy 1.0.0 US. It should be noted that the original Ir pseudopotential from the GBRV library contains a ghost state at 10eV. Despite this, the efficiency libraries continue to utilize the GBRV pseudopotential, therefore users relying on this pseudopotential should exercise caution.

aiida

display_name: aiida

calculations

display_name: calculations

chessboards

display_name: chessboards

cohesive-energy

display_name: cohesive-energy

cscs

display_name: cscs

database

display_name: database

high-throughput

display_name: high-throughput

max

display_name: max

prace

display_name: prace


en:
Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here, we propose a universal standard protocol to verify publicly available pseudopotential libraries, based on several independent criteria including verification against all-electron equations of state and plane-wave convergence tests for phonon frequencies, band structure, cohesive energy and pressure. Adopting these criteria we obtain two optimal pseudopotential sets, namely the Standard Solid State Pseudopotential (SSSP) efficiency and precision libraries, tailored for high-throughput materials screening and high-precision materials modelling. As of today, the SSSP precision library is the most accurate open-source pseudopotential library available. This archive entry contains the database of calculations (phonons, cohesive energy, equation of state, band structure, pressure, etc.) together with the provenance of all data and calculations as stored by AiiDA.

*** UPDATE April 2020 ***
The zipped tarball archives and AiiDA export files had inconsistent internal formats and naming conventions, which made it difficult to work with them programmatically. In this update, the files are standardized according to the conventions that are detailed in the README.md file. Note that the actual content of pseudo potential files and the JSON metadata files has **not** changed, with the exception that the keys "cutoff" and "dual" in the JSON files have been replaced with "cutoff_wfc" and "cutoff_rho". Here the value of "cutoff_wfc" is equal to the old "cutoff", and "cutoff_rho" is equal to the product of the old "cutoff" and "dual". Besides that, the update concerns merely the renaming of certain files and the restructuring of archive formats.

*** UPDATE November 2020 ***
The AiiDA export files contained in the sssp.tar archive have been modified and migrated to version format 0.9 in order to be imported in AiiDA 1.2.0 and later versions. The modifications are detailed in the README.md file in the sssp.tar archive.
The AiiDA export files contained in the sssp_bands.tar archive have been migrated to version format 0.9 as well.

*** UPDATE April 2021 - Version 1.1.1 ***
The PBEsol pseudopotential files contained unescaped "&" characters. In this update, the files concerned have been fixed escaping the "&" characters contained in PP_INPUTFILE blocks.

dft

display_name: dft

efficiency

display_name: efficiency

electronic-bands

display_name: electronic-bands

electronic-properties

display_name: electronic-properties

elemental-solids

display_name: elemental-solids

library

display_name: library

marvel

display_name: marvel

phonons

display_name: phonons

precision

display_name: precision


en: Dipole polarizabilities (and other molecular properties) computed using linear response coupled cluster theory (LR-CCSD/d-aug-cc-pVDZ) and hybrid density functional theory (B3LYP/d-aug-cc-pVDZ, SCAN0/d-aug-cc-pVDZ, and B3LYP/d-aug-cc-pVTZ) for the 7,211 molecules in the QM7b database and the 52 molecules in the AlphaML showcase database.

en: Quantum Mechanical Static Dipole Polarizabilities in the QM7b and AlphaML Showcase Databases

density-functional-theory

display_name: density-functional-theory

dipole-polarizability

display_name: dipole-polarizability

linear-response-coupled-cluster

display_name: linear-response-coupled-cluster


en:
Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here, we propose a universal standard protocol to verify publicly available pseudopotential libraries, based on several independent criteria including verification against all-electron equations of state and plane-wave convergence tests for phonon frequencies, band structure, cohesive energy and pressure. Adopting these criteria we obtain two optimal pseudopotential sets, namely the Standard Solid State Pseudopotential (SSSP) efficiency and precision libraries, tailored for high-throughput materials screening and high-precision materials modelling. As of today, the SSSP precision library is the most accurate open-source pseudopotential library available. This archive entry contains the database of calculations (phonons, cohesive energy, equation of state, band structure, pressure, etc.) together with the provenance of all data and calculations as stored by AiiDA.

*** UPDATE April 2020 ***
The zipped tarball archives and AiiDA export files had inconsistent internal formats and naming conventions, which made it difficult to work with them programmatically. In this update, the files are standardized according to the conventions that are detailed in the README.md file. Note that the actual content of pseudo potential files and the JSON metadata files has **not** changed, with the exception that the keys "cutoff" and "dual" in the JSON files have been replaced with "cutoff_wfc" and "cutoff_rho". Here the value of "cutoff_wfc" is equal to the old "cutoff", and "cutoff_rho" is equal to the product of the old "cutoff" and "dual". Besides that, the update concerns merely the renaming of certain files and the restructuring of archive formats.

*** UPDATE November 2020 ***
The AiiDA export files contained in the sssp.tar archive have been modified and migrated to version format 0.9 in order to be imported in AiiDA 1.2.0 and later versions. The modifications are detailed in the README.md file in the sssp.tar archive.
The AiiDA export files contained in the sssp_bands.tar archive have been migrated to version format 0.9 as well.

*** UPDATE April 2021 - Version 1.1.1 ***
The PBEsol pseudopotential files contained unescaped "&" characters. In this update, the files concerned have been fixed escaping the "&" characters contained in PP_INPUTFILE blocks.

*** UPDATE May 2021 - Version 1.1.2 ***
For compatibility issues, the mesh_size in the header of the pseudopotential files has been changed to be the same as the mesh value. These issues affected the pseudopotential files for the lanthanides.
Note that, starting from this version, for each minor version only the files of the corresponding latest patch version are provided. The files of the previous patch versions (i.e. 1.1, 1.1.1) can be retrieved from the previous versions of this record.
Note also that the AiiDA export archives of the different SSSP configurations are not provided any more. In order to use the SSSP configurations in AiiDA, it is recommended instead to install them through the aiida-pseudo package (https://aiida-pseudo.readthedocs.io/en/latest/).

calculations

display_name: calculations

chessboards

display_name: chessboards

cohesive-energy

display_name: cohesive-energy

cscs

display_name: cscs

pseudopotentials

display_name: pseudopotentials

sssp

display_name: sssp

standard

display_name: standard

verification

display_name: verification

vibrational-properties

display_name: vibrational-properties


en: Data for the case study of TuTraSt on methane diffusion in zeolites, using a standard kinetic Monte Carlo simulation based on the output of our grid analysis. We find that it is accurate, fast, and rigorous without limitations to the geometries of the diffusion tunnels or transition states.

en: TuTraST data for methane diffusion in IZA structures

diffusion

display_name: diffusion

kinetic-monte-carlo

display_name: kinetic-monte-carlo

methane

display_name: methane

transition-state-theory

display_name: transition-state-theory

tutrast

display_name: tutrast

zeolite

display_name: zeolite


marvel

display_name: marvel


en:
Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here, we propose a universal standard protocol to verify publicly available pseudopotential libraries, based on several independent criteria including verification against all-electron equations of state and plane-wave convergence tests for phonon frequencies, band structure, cohesive energy and pressure. Adopting these criteria we obtain two optimal pseudopotential sets, namely the Standard Solid State Pseudopotential (SSSP) efficiency and precision libraries, tailored for high-throughput materials screening and high-precision materials modelling. As of today, the SSSP precision library is the most accurate open-source pseudopotential library available. This archive entry contains the database of calculations (phonons, cohesive energy, equation of state, band structure, pressure, etc.) together with the provenance of all data and calculations as stored by AiiDA.

*** UPDATE April 2023 - Version 1.3.0 ***
The pseudopotentials of elements At, Fr, Ra are added from PSlibrary. The pseudopotential of actinides are added from dataset of https://www.uni-marburg.de/de/fb15/arbeitsgruppen/anorganische_chemie/ag-kraus/forschung/paw_datasets_for_the_actinoids

en: A Standard Solid State Pseudopotentials (SSSP) library optimized for precision and efficiency

aiida

display_name: aiida

database

display_name: database

dft

display_name: dft

efficiency

display_name: efficiency

electronic-bands

display_name: electronic-bands

electronic-properties

display_name: electronic-properties

elemental-solids

display_name: elemental-solids

high-throughput

display_name: high-throughput

library

display_name: library

max

display_name: max

phonons

display_name: phonons

prace

display_name: prace

precision

display_name: precision


en:
Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here, we propose a universal standard protocol to verify publicly available pseudopotential libraries, based on several independent criteria including verification against all-electron equations of state and plane-wave convergence tests for phonon frequencies, band structure, cohesive energy and pressure. Adopting these criteria we obtain two optimal pseudopotential sets, namely the Standard Solid State Pseudopotential (SSSP) efficiency and precision libraries, tailored for high-throughput materials screening and high-precision materials modelling. As of today, the SSSP precision library is the most accurate open-source pseudopotential library available. This archive entry contains the database of calculations (phonons, cohesive energy, equation of state, band structure, pressure, etc.) together with the provenance of all data and calculations as stored by AiiDA.

*** Recent UPDATE April 2023 - Version 1.3.0 ***
The pseudopotentials of elements At, Fr, Ra are added from PSlibrary. The pseudopotential of actinides are added from dataset of https://www.uni-marburg.de/de/fb15/arbeitsgruppen/anorganische_chemie/ag-kraus/forschung/paw_datasets_for_the_actinoids

Please refer to the CHANGELOG.txt file within the archive to view a complete list of version changes.

materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).

calculations

display_name: calculations

chessboards

display_name: chessboards

cohesive-energy

display_name: cohesive-energy

cscs

display_name: cscs


aiida

display_name: aiida

marvel

display_name: marvel


en:
Regioselective derivatization of oligosaccharides is a challenging issue in carbohydrate chemistry. A commonly required series of (de)protection steps substantially lowers synthetic yields and increases time demands. We present here a regioselective one-step introduction of benzylic substituents at 3-hydroxy moieties of beta-D-galactopyranosyl-(1<->1)-thio-beta-D-galactopyranoside (TDG) employing tin butyl oxide in fair isolated yields. These glycomimetics act as inhibitors of galectins - human lectins, which are biomedically attractive targets for therapeutic inhibition. The affinity of prepared glycomimetics to recombinant galectin-1 and galectin-3 was studied in ELISA-type assay and their inhibitory potential was also demonstrated on the surface of a model HEK293 cell line. The results of biological experiments were correlated with data from molecular modelling with both galectins. The present work reveals a facile and elegant synthetic route for the preparation of glycomimetics that exhibit differing selectivity and affinity to various galectins depending on the choice of 3-O-substitution.
In order to rationalize structure-activity relationships of tested ligands we carried out a series of molecular dynamics simulations and quantum chemical calculations. We present input and output files for quantum chemical geometry optimizations and calculations of interactions energies. These calculations were carried out in Gaussian 09 package. These results can be visualized using Molden, Molekel or other programs.
Molecular dynamics simulations were carried out using Gromacs 5.1.3 package. Initial structures of production simulations and trajectories (without water) are presented. The results can be visualized by VMD or other structure visualization packages with a support for trajectory input.

en: Regioselective 3-O-Substitution of Unprotected Thiodigalactosides: Route to Specific Galectin Inhibitors

galectin

display_name: galectin

glycobiology

display_name: glycobiology

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation


en: We present a computational screening of experimental structural repositories for fast Li-ion conductors, with the goal of finding new candidate materials for application as solid-state electrolytes in next-generation batteries. We start from ~1400 unique Li-containing materials, of which ~900 are insulators at the level of density-functional theory. For those, we calculate the diffusion coefficient in a highly automated fashion, using extensive molecular dynamics simulations on a potential energy surface (the recently published pinball model) fitted on first-principles forces. The ~130 most promising candidates are studied with full first-principles molecular dynamics, first at high temperature and then more extensively for the 78 most promising candidates. The results of the first-principles simulations of the candidate solid-state electrolytes found are discussed in detail.

materialscloud

en: Materials Cloud

en: High-throughput computational screening for solid-state Li-ion conductors

big-map

display_name: big-map

computational-high-throughput-screening

display_name: computational-high-throughput-screening

first-principles-molecular-dynamics

display_name: first-principles-molecular-dynamics

li-ion-conductors

display_name: li-ion-conductors

solid-state-electrolytes

display_name: solid-state-electrolytes


en: The record contains data that support the work where we report the optical imaging and absorption spectroscopy on atomically precise armchair graphene nanoribbons (GNRs) on insulating fused silica substrates. This is achieved by controlling light polarization on macroscopically aligned GNRs which greatly enhances the optical contrast of the submonolayer GNRs on the insulating substrates. We measure the linear absorption spectra of 7-armchair and 9-armchair GNRs in this study, and the experimental data agree qualitatively with ab inito calculation results. The polarization spectroscopy technique enables an unambiguous optical identification of GNRs and provides a rapid tool to characterize the transferred film over a large area.

en: Optical imaging and spectroscopy of atomically precise armchair graphene nanoribbons

envi

en: Environment

absorption-spectroscopy

display_name: absorption-spectroscopy

graphene-nanoribbons

display_name: graphene-nanoribbons

optical-imaging

display_name: optical-imaging

snsf

display_name: snsf


en: The production of hydrogen fuels, via water splitting, is of practical relevance for meeting global energy needs and mitigating the environmental consequences of fossil-fuel-based transportation. Water photoelectrolysis has been proposed as a viable approach for generating hydrogen, provided that stable and inexpensive photocatalysts with conversion efficiencies over 10% can be discovered, synthesized at scale, and successfully deployed (Pinaud et al., Energy Environ. Sci., 2013, 6, 1983). While a number of first-principles studies have focused on the data-driven discovery of photocatalysts, in the absence of systematic experimental validation, the success rate of these predictions may be limited. We address this problem by developing a screening procedure with co-validation between experiment and theory to expedite the synthesis, characterization, and testing of the computationally predicted, most desirable materials. Starting with 70150 compounds in the Materials Project database, the proposed protocol yielded 71 candidate photocatalysts, 11 of which were synthesized as single-phase materials. Experiments confirmed hydrogen generation and favorable band alignment for 6 of the 11 compounds, with the most promising ones belonging to the families of alkali and alkaline-earth indates and orthoplumbates. This study shows the accuracy of a nonempirical, Hubbard-corrected density-functional theory method to predict band gaps and band offsets at a fraction of the computational cost of hybrid functionals, and outlines an effective strategy to identify photocatalysts for solar hydrogen generation.

en: Optimizing accuracy and efficacy in data-driven materials discovery for the solar production of hydrogen

density-functional-theory

display_name: density-functional-theory

dftu

display_name: dftu

high-throughput-screening

display_name: high-throughput-screening

photocatalysis

display_name: photocatalysis

water-splitting

display_name: water-splitting


marvel

display_name: marvel


en: 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.

en: Ab initio real-time quantum dynamics of charge carriers in momentum space

electron-phonon-coupling

display_name: electron-phonon-coupling

first-principles

display_name: first-principles

nonadiabatic-molecular-dynamics

display_name: nonadiabatic-molecular-dynamics


en: Regioselective 3-O-Substitution of Unprotected Thiodigalactosides: Direct Route to Galectin Inhibitors

galectin

display_name: galectin

glycobiology

display_name: glycobiology

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation


en: Optical materials play a key role in enabling modern optoelectronic technologies in a wide variety of domains such as the medical or the energy sector. Among them, nonlinear optical crystals are of primary importance to achieve a broader range of electromagnetic waves in the devices. However, numerous and contradicting requirements significantly limit the discovery of new potential candidates, which, in turn, hinders the technological development. In the present work, the static nonlinear susceptibility and dielectric tensor are computed via density functional perturbation theory for a set of 579 inorganic semiconductors. The aim of this work is to provide a relevant dataset to foster the identification of promising nonlinear optical crystals in order to motivate their subsequent experimental investigation.

en: Second-harmonic generation tensors from high-throughput density-functional perturbation theory

density-functional-perturbation-theory

display_name: density-functional-perturbation-theory

high-throughput

display_name: high-throughput

non-linear-optics

display_name: non-linear-optics

second-harmonic-generation

display_name: second-harmonic-generation


en:
We present a computational screening of experimental structural repositories for fast Li-ion conductors, with the goal of finding new candidate materials for application as solid-state electrolytes in next-generation batteries. We start from ~1400 unique Li-containing materials, of which ~900 are insulators at the level of density-functional theory. For those, we calculate the diffusion coefficient in a highly automated fashion, using extensive molecular dynamics simulations on a potential energy surface (the recently published pinball model) fitted on first-principles forces. The ~130 most promising candidates are studied with full first-principles molecular dynamics, first at high temperature and then more extensively for the 78 most promising candidates. The results of the first-principles simulations of the candidate solid-state electrolytes found are discussed in detail.

Update April 2024:
Files are added that facilitate the Materials Cloud Archive OPTIMADE service to serve the structural data of this Archive entry via an OPTIMADE API. The molecular dynamics trajectories are served as individual structures per time-step.

big-map

display_name: big-map

computational-high-throughput-screening

display_name: computational-high-throughput-screening

first-principles-molecular-dynamics

display_name: first-principles-molecular-dynamics

li-ion-conductors

display_name: li-ion-conductors

solid-state-electrolytes

display_name: solid-state-electrolytes


materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).


en: We study the oxo-hexametallate Li7TaO6 with first-principles and classical molecular dynamics simulations, obtaining a low activation barrier for diffusion of ∼0.29 eV and a high ionic conductivity of 5.7×10−4 S cm−1 at room temperature (300 K). We find evidence for a wide electrochemical stability window from both calculations and experiments, suggesting its viable use as a solid-state electrolyte in next-generation solid-state Li-ion batteries. To assess its applicability in an electrochemical energy storage system, we performed electrochemical impedance spectroscopy measurements on multicrystalline pellets, finding substantial ionic conductivity, if below the values predicted from simulation. We further elucidate the relationship between synthesis conditions and the observed ionic conductivity using X-ray diffraction, inductively coupled plasma optical emission spectrometry, and X-ray photoelectron spectroscopy, and study the effects of Zr and Mo doping.

en: The solid-state Li-ion conductor Li7TaO6: A combined computational and experimental study

density-functional-theory

display_name: density-functional-theory

electrochemical-stability

display_name: electrochemical-stability

li-ion-batteries

display_name: li-ion-batteries

molecular-dynamics

display_name: molecular-dynamics

polarizable-force-fields

display_name: polarizable-force-fields

solid-state-electrolyte

display_name: solid-state-electrolyte


en: This dataset provides DFT (density functional theory as implemented in VASP, Vienna Ab Initio Simulation Package) calculations for pure Magnesium. It was designed by Binglun Yin, Markus Stricker and William A. Curtin for fitting a neural network potential with Behler-Parrinello symmetry functions. Binglun Yin carried out the calculation.

en: Pure Magnesium DFT calculations for interatomic potential fitting

decohesion

display_name: decohesion

dft

display_name: dft

elasticity

display_name: elasticity

magnesium

display_name: magnesium

metallurgy

display_name: metallurgy

stacking-faults

display_name: stacking-faults

surfaces

display_name: surfaces


en: We perform a thorough structural search with the minima hopping method (MHM) to explore low-energy structures of methylammonium lead iodide. By combining the MHM with a forcefield, we efficiently screen vast portions of the configurational space with large simulation cells containing up to 96 atoms. Our search reveals two structures of methylammonium iodide perovskite (MAPI) that are substantially lower in energy than the well-studied experimentally observed low-temperature orthorhombic phase. The data set containing approximately ~180,000 crystal structures is provided.

materialscloud

en: Materials Cloud

en: Emergence of hidden phases of methylammonium lead-iodide (CH3NH3PbI) upon compression

force-field-gulp

display_name: force-field-gulp

mapi-perovskites

display_name: mapi-perovskites

minima-hopping-method

display_name: minima-hopping-method

structure-prediction

display_name: structure-prediction

vasp-scan--functional

display_name: vasp-scan--functional


envi

en: Environment


en:
This dataset provides DFT (density functional theory as implemented in VASP, Vienna Ab Initio Simulation Package) calculations for pure Magnesium. It was designed by Binglun Yin, Markus Stricker and William A. Curtin for fitting a neural network potential with Behler-Parrinello symmetry functions. Binglun Yin carried out the calculation.

It corresponds to a dataset that is commonly used to fit interatomic potentials for mechanics applications and includes structure-energy relationships for structures used to calculate:
1. Bulk properties
2. Generalized stacking fault energies
3. Decohesion and relaxed surfaces
4. Dimer
5. Corner and rod geometries
6. Vacancy formation energy

epfl

display_name: epfl

snsf

display_name: snsf


en:
Many enhanced sampling techniques rely on the identification of a number of collective variables that describe all the slow modes of the system. By constructing a bias potential in this reduced space one is then able to sample efficiently and reconstruct the free energy landscape. In methods like metadynamics, the quality of these collective variables plays a key role in convergence efficiency. Unfortunately in many systems of interest it is not possible to identify an optimal collective variable, and one must deal with the non-ideal situation of a system in which some slow modes are not accelerated.
We propose a two-step approach in which, by taking into account the residual multiscale nature of the problem, one is able to significantly speed up convergence. To do so, we combine an exploratory metadynamics run with an optimization of the free energy difference between metastable states, based on the recently proposed variationally enhanced sampling method. This new method is well parallelizable and is especially suited for complex systems, because of its simplicity and clear underlying physical picture.

en: Making the best of a bad situation: a multiscale approach to free energy calculation

enhanced-sampling

display_name: enhanced-sampling

free-energy

display_name: free-energy

metadynamics

display_name: metadynamics


en: Generalized stacking fault energy (GSFE) is a crucial material property for describing nanoscale plasticity in crystalline materials, such as dislocation dissociation, nucleation, and twinning. The dependence of the GSFE on applied stress normal to the stacking fault (SF) plane has been suggested to influence such phenomena. Here, the SF stress dependence is analyzed through (i) the generalized stacking fault potential energy (GSFE) and (ii) the generalized stacking fault enthalpy (GSFH). Our DFT calculations reveal that the GSFE is almost independent of the applied normal stress, which contradicts the long-standing wisdom and previous studies. We also reveal the inelastic inter-planar normal displacement associated with the SF. The coupling between the positive inelastic normal displacement and the applied normal stress decreases the GSFH.

en: Stress-dependence of generalized stacking fault energies: a DFT study

erc

display_name: erc

generalized-stacking-fault-energy

display_name: generalized-stacking-fault-energy

stacking-fault-stress-dependence

display_name: stacking-fault-stress-dependence


en: The data contained in this record, raw data of images and input files to reproduce calculations, support our recent report for the on-surface synthesis and characterization of two ultralow-gap open-shell molecules, namely peri-tetracene, a benzenoid graphene fragment with zigzag edge topology, and dibenzo[a,m]dicyclohepta[bcde,nopq]rubicene, a nonbenzenoid nonalternant structural isomer of peri-tetracene with two embedded azulene units. Our results provide an understanding of the ramifications of altered bond topologies at the single-molecule scale, with the prospect of designing functionalities in carbon-based nanostructures via engineering of bond topology

en: Tailoring Bond Topologies in Open-Shell Graphene Nanostructures

atom-manipulation

display_name: atom-manipulation

density-functional-theory

display_name: density-functional-theory

scanning-tunneling-microscopy

display_name: scanning-tunneling-microscopy

scanning-tunneling-spectroscopy

display_name: scanning-tunneling-spectroscopy


en:
This data set contains atomic structures of liquid water and amorphous Li(x)Si in the XCrySDen structure format (XSF) [1]. Total energies are included as additional meta information. The extended XSF format is compatible with the Atomic Energy Network (ænet) package [2,3] for artificial neural network (ANN) potential construction and application.

Liquid water: The liquid water data set comprises energies and forces of 9,189 condensed-phase structures. The data was obtained in an iterative procedure described in detail in Ref. [4]. The final ANN potential was employed in Refs. [4,5].

Initial structures (iteration 0) were obtained from classical and path integral AIMD simulations of bulk liquid water in a cubic box containing 64 water molecules at 300 K as reported in Ref. [6]. Distorted configurations with higher forces were added by randomly displacing the Cartesian coordinates. Iteration 1 contains 500 configurations from MD simulations with the fully flexible SPC/E flex water model [7] employing a 25% increased water density (80 water molecules) and elevated temperatures (T= 500 K) to sample highly repulsive configurations. Structures in iteration 2 were obtained by classical MD simulations with preliminary ANN potentials at T= 300, 325, 350, and 370 K using cubic 64-molecule boxes and experimental densities. Iteration 3 data contains structures from preliminary ANN simulations with classical and quantum nuclei at a wide range of temperatures (T= 258, 268, 280, 290, 300, 310, 320, 330, 340, 350, 360, and 370 K) using experimental densities.

Energies and atomic forces were calculated with CP2K [8,9] using the revPBE exchange-correlation functional [10,11] with D3 dispersion correction [12] following Ref. [4]. Atomic cores were represented using the dual-space Goedecker-Teter-Hutter pseudopotentials [13], Kohn-Sham orbitals were expanded in the TZV2P basis set within the GPW method [14], and the density was represented by an auxiliary plane-wave basis with a cutoff of 400 Ry.

Amorphous LiSi: The amorphous LiSi data set comprises ~45,000 atomic bulk, surface, and cluster structures of elemental Li and Si, and Li(x)Si alloys of various compositions (0.0 ≤ x ≤ 4.75) as well as the corresponding energies and interatomic forces, which were generated using an iterative approach. An initial data set was based on the crystal structures of Li, Si, and the LiSi alloys with distorted lattice parameters and perturbed atomic positions. Additional partially delithiated alloy structures were generated using an evolutionary algorithm and further refined by including structures from ANN-potential MD simulations. Further details are given in references [15, 16].

The energies and forces of the LiSi structures were obtained from DFT calculations using the PBE [10] exchange-correlation functional and PAW pseudopotentials [17], as implemented in VASP [18,19]. We employed a plane-wave basis set with a cutoff of 520 eV and a uniform gamma-centered k-point grid with a mesh density corresponding to a number of k points of at least 1000 divided by the number of atoms. Most calculations in this data set were obtained from single-point DFT calculations. For ground state crystal structures, the atomic positions and lattice parameters were optimized until residual forces were below 20 meV/Å.

[1] A. Kokalj, J. Mol. Graphics Modell. 17, 176-179 (1999).
[2] N. Artrith, A. Urban, Comput. Mater. Sci. 114, 135-150 (2016).
[3] N. Artrith, A. Urban, G. Ceder, Phys. Rev. B 96, 014112 (2017).
[4] T. Morawietz, O. Marsalek, S. R. Pattenaude, L. M. Streacker, D. Ben-Amotz, and T. E. Markland, J. Phys. Chem. Lett. 9, 851 (2018).
[5] T. Morawietz, A. S. Urbina, P. K. Wise, X. Wu, W. Lu, D. Ben-Amotz, and T. E. Markland, J. Phys. Chem. Lett. 10, 6067 (2019).
[6] O. Marsalek and T. E. Markland, J. Phys. Chem. Lett. 8, 1545 (2017).
[7] X. B. Zhang, Q. L. Liu, and A. M. Zhu, Fluid Ph. Equilibria 262, 210 (2007).
[8] J. VandeVondele, M. Krack, F. Mohamed, M. Parrinello, T. Chassaing, and J. Hutter, Comput. Phys. Commun. 167, 103 (2005).
[9] J. Hutter, M. Iannuzzi, F. Schiffmann, and J. VandeVondele, WIRES Comput. Mol. Sci. 4, 15 (2014).
[10] J. P. Perdew, K. Burke, and M. Ernzerhof, Phys. Rev. Lett. 77, 3865 (1996).
[11] Y. Zhang and W. Yang, Phys. Rev. Lett. 80, 890 (1998).
[12] S. Grimme, J. Antony, S. Ehrlich, and H. Krieg, J. Chem. Phys. 132, 154104 (2010).
[13] S. Goedecker, M. Teter, and J. Hutter, Phys. Rev. B 54, 1703 (1996).
[14] B. G. Lippert, J. Hutter, and M. Parrinello, Mol. Phys. 92, 477 (1997).
[15] N. Artrith, A. Urban, G. Ceder, J. Chem. Phys. 148, 241711 (2018).
[16]  N. Artrith, A. Urban, Y. Wang, G. Ceder, https://arxiv.org/abs/1901.09272 (2019).
[17] P. E. Blöchl, Phys. Rev. B 50, 17953–17979 (1994).
[18] G. Kresse, J. Furthmüller, Phys. Rev. B 54, 11169-11186 (1996).
[19] G. Kresse, J. Furthmüller, Comput. Mater. Sci. 6, 15-50 (1996).

en: AENET-LAMMPS and AENET-TINKER: interfaces for accurate and efficient molecular dynamics simulations with machine learning potentials

aenet

display_name: aenet

amorphous-lisi

display_name: amorphous-lisi

liquid-water

display_name: liquid-water

path-integral-aimd

display_name: path-integral-aimd

vasp

display_name: vasp


materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).


en: 2D semiconductors are considered as a promising alternative to silicon for future electronics. This class of materials possesses different advantages including atomically sharp surfaces and the ability to scale channel thickness down to a single layer. However, they typically exhibit lower charge carrier mobility as well as higher contact resistance compared to 3D semiconductors, which deters the development of high-performance devices at scale. In this work, we searched for high-mobility 2D materials by combining high-throughput screening approach and advanced transport calculations based on the ab initio Boltzmann transport equation. Based on our calculations, we identified several promising candidates channel materials, and in particular monolayer WS₂ which exhibits a phonon-limited hole mobility in excess of 1300 cm²/Vs. Our work suggests that WS₂ can be ideal for channel of high-performance 2D transistors with Ohmic contacts and low defect density. This work has been published in [npj Comput. Mater. 10, 229 (2024)].

en: High-throughput screening of 2D materials identifies p-type monolayer WS2 as potential ultra-high mobility semiconductor

ab-initio-boltzmann-transport-equation

display_name: ab-initio-boltzmann-transport-equation

high-throughput-computing

display_name: high-throughput-computing


en: Nonempirical hybrid functionals are investigated for band-gap predictions of inorganic metal-halide perovskites belonging to the class CsBX3 , with B = Ge, Sn, Pb and X = Cl, Br, I. We consider both global and range-separated hybrid functionals and determine the parameters through two different schemes. The first scheme is based on the static screening response of the material and thus yields dielectric-dependent hybrid functionals. The second scheme defines the hybrid functionals through the enforcement of Koopmans' condition for localized defect states. We also carry out quasiparticle self-consistent GW calculations with vertex corrections to establish state-of-the-art references. For the investigated class of materials, dielectric-dependent functionals and those fulfilling Koopmans' condition yield band gaps of comparable accuracy (∼0.2 eV), but the former only require calculations for the primitive unit cell and are less subject to the specifics of the material.

en: Nonempirical hybrid functionals for band gaps of inorganic metal-halide perovskites

band-gaps

display_name: band-gaps

epfl

display_name: epfl

nonempirical-hybrid-functionals

display_name: nonempirical-hybrid-functionals

perovskites

display_name: perovskites

snsf

display_name: snsf


materialscloud

en: Materials Cloud


en: Graphene nanoribbons (GNRs) produced by means of bottom-up chemical self-assembly are considered promising candidates for the next-generation nanoelectronic devices. We address the electronic transport properties of angled two-terminal GNR junctions, which are inevitable in the interconnects in graphene-based integrated circuits. We construct a library of over 400000 distinct configurations of 60° and 120° junctions connecting armchair GNRs of different widths. Numerical calculations combining the tight-binding approximation and the Green's function formalism allow identifying numerous junctions with conductance close to the limit defined by the GNR leads. Further analysis reveals underlying structure-property relationships with crucial roles played by the bipartite symmetry of graphene lattice and the presence of resonant states localized at the junction. In particular, we discover and explain the phenomenon of binary conductance in 120° junctions connecting metallic GNR leads that guarantee maximum possible conductance. Overall, our study defines the guidelines for engineering GNR junctions with desired electrical properties.

en: Design rules for interconnects based on graphene nanoribbon junctions

electronic-transport

display_name: electronic-transport

gnr

display_name: gnr

graphene

display_name: graphene

junctions

display_name: junctions

nanoribbon

display_name: nanoribbon


envi

en: Environment


en:
Many enhanced sampling techniques rely on the identification of a number of collective variables that describe all the slow modes of the system. By constructing a bias potential in this reduced space one is then able to sample efficiently and reconstruct the free energy landscape. In methods like metadynamics, the quality of these collective variables plays a key role in convergence efficiency. Unfortunately in many systems of interest it is not possible to identify an optimal collective variable, and one must deal with the non-ideal situation of a system in which some slow modes are not accelerated.
We propose a two-step approach in which, by taking into account the residual multiscale nature of the problem, one is able to significantly speed up convergence. To do so, we combine an exploratory metadynamics run with an optimization of the free energy difference between metastable states, based on the recently proposed variationally enhanced sampling method. This new method is well parallelizable and is especially suited for complex systems, because of its simplicity and clear underlying physical picture.

enhanced-sampling

display_name: enhanced-sampling

free-energy

display_name: free-energy

metadynamics

display_name: metadynamics


en: Quantum spin Hall insulators (QSHIs) make up a class of two-dimensional materials with a finite electronic band gap in the bulk and gapless helical edge states.  Some of the phenomena that can be hosted in these materials, from one-dimensional low-dissipation electronic transport to spin filtering, could be promising for many technological applications in the fields of electronics, spintronics, and topological quantum computing. Nevertheless, the rarity of two-dimensional materials that can exhibit nontrivial topological order at room temperature hinders development. In the publication, we report on our screening of a comprehensive database we recently identified of 1825 monolayers that can be exfoliated from experimentally known compounds to search for novel quantum spin Hall insulators.  In this entry we provide the AiiDA database with the calculations of the DFT band structures (both with and without spin-orbit coupling) and the DFPT phonon dispersions for the QSHI candidates that we identify. All the data are also displayed in the dedicated DISCOVER section "2D topological insulators" https://www.materialscloud.org/discover/2dtopo/dashboard/ptable .

en: Relative Abundance of Z2 Topological Order in Exfoliable Two-Dimensional Insulators

dfpt

display_name: dfpt

dft

display_name: dft

first-principles

display_name: first-principles

marvel

display_name: marvel

quantum-spin-hall

display_name: quantum-spin-hall

spin-orbit

display_name: spin-orbit

topological-insulator

display_name: topological-insulator