cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.24435/materialscloud:fv-ce
title: Asymmetric molecular adsorption and regioselective bond cleavage on chiral PdGa crystals

description: Homogenous enantioselective catalysis is nowadays the cornerstone in the manufacturing of enantiopure substances, but its technological implementation suffers from well-known impediments like the lack of endurable catalysts exhibiting long-term stability. The catalytically active intermetallic compound Palladium-Gallium (PdGa), conserving innate bulk chirality on its surfaces, represent a promising system to study asymmetric chemical reactions by heterogeneous catalysis, with prospective relevance for industrial processes. In a recent publication we investigate the adsorption of 10,10′-dibromo-9,9′-bianthracene (DBBA) on the PdGa:A(-1-1-1) Pd3-terminated surface by means of scanning tunneling microscopy (STM) and spectroscopy (STS). A highly enantioselective adsorption of the molecule evolving into a near 100% enantiomeric excess below room temperature is observed. This exceptionally high enantiomeric excess is attributed to temperature activated conversion of the S to the R chiral conformer. Tip-induced bond cleavage of the R conformer shows a very high regioselectivity of the DBBA debromination. The experimental results are interpreted by density functional theory atomistic simulations. This work extends the knowledge of chirality transfer onto the enantioselective adsorption of non-planar molecules and manifests the ensemble effect of PdGa surfaces resulting in robust regioselective debromination. This record contains data that support the results discussed in the manuscript.
DOI: 10.24435/materialscloud:2v-ft
title: Impact of orientation misalignments on black phosphorus ultrascaled field-effect transistors

description: Advanced quantum transport approach from first-principle to shed light on the influence of orientation misalignments on the performance of BP-based field-effect transistors, for which the input files are reported. Both n-and p-type configurations are investigated for six alignment angles, in the ballistic limit of transport and in the presence of electron-phonon and charged impurity scattering.
DOI: 10.24435/materialscloud:xw-ks
title: Asymmetric molecular adsorption and regioselective bond cleavage on chiral PdGa crystals

description: Homogenous enantioselective catalysis is nowadays the cornerstone in the manufacturing of enantiopure substances, but its technological implementation suffers from well-known impediments like the lack of endurable catalysts exhibiting long-term stability. The catalytically active intermetallic compound Palladium-Gallium (PdGa), conserving innate bulk chirality on its surfaces, represent a promising system to study asymmetric chemical reactions by heterogeneous catalysis, with prospective relevance for industrial processes. In a recent publication we investigate the adsorption of 10,10′-dibromo-9,9′-bianthracene (DBBA) on the PdGa:A(-1-1-1) Pd3-terminated surface by means of scanning tunneling microscopy (STM) and spectroscopy (STS). A highly enantioselective adsorption of the molecule evolving into a near 100% enantiomeric excess below room temperature is observed. This exceptionally high enantiomeric excess is attributed to temperature activated conversion of the S to the R chiral conformer. Tip-induced bond cleavage of the R conformer shows a very high regioselectivity of the DBBA debromination. The experimental results are interpreted by density functional theory atomistic simulations. This work extends the knowledge of chirality transfer onto the enantioselective adsorption of non-planar molecules and manifests the ensemble effect of PdGa surfaces resulting in robust regioselective debromination. This record contains data that support the results discussed in the manuscript.
DOI: 10.24435/materialscloud:a3-z0
title: Impact of orientation misalignments on black phosphorus ultrascaled field-effect transistors

description: Advanced quantum transport approach from first-principle to shed light on the influence of orientation misalignments on the performance of BP-based field-effect transistors, for which the input files are reported. Both n-and p-type configurations are investigated for six alignment angles, in the ballistic limit of transport and in the presence of electron-phonon and charged impurity scattering.
DOI: 10.24435/materialscloud:kf-h1
title: Tailoring interfacial properties in CaVO3 thin films and heterostructures with SrTiO3 and LaAlO3: A DFT+DMFT study

description: In this paper we use density functional theory combined with dynamical mean-field theory (DFT+DMFT) to study interface effects between the correlated metal CaVO3 and the two typical substrate materials SrTiO3 and LaAlO3. We find that the CaVO3/SrTiO3 interface has only a marginal influence on the CaVO3 thin film, with the dominant effect being the (bulklike) epitaxial strain imposed by the large lattice mismatch, rendering the CaVO3 film insulating due to the enhanced orbital polarization related to the strong level splitting between the t2g orbitals. In contrast, at the polar CaVO3/LaAlO3 interface, the presence of the interface can have a huge effect on the physical properties, depending both on the specific interface termination and on the specific boundary conditions imposed by the multilayer geometry. We compare three approaches to modeling the CaVO3/LaAlO3 interface, all of which impose a different set of (electrostatic) boundary conditions. Our results demonstrate that different substrates, interface terminations, and electrostatic boundary conditions can drastically affect the properties of thin-film heterostructures, indicating the potential tunability of the interfacial properties via multilayer engineering.
DOI: 10.24435/materialscloud:br-t7
title: Tailoring interfacial properties in CaVO3 thin films and heterostructures with SrTiO3 and LaAlO3: A DFT+DMFT study

description: In this paper we use density functional theory combined with dynamical mean-field theory (DFT+DMFT) to study interface effects between the correlated metal CaVO3 and the two typical substrate materials SrTiO3 and LaAlO3. We find that the CaVO3/SrTiO3 interface has only a marginal influence on the CaVO3 thin film, with the dominant effect being the (bulklike) epitaxial strain imposed by the large lattice mismatch, rendering the CaVO3 film insulating due to the enhanced orbital polarization related to the strong level splitting between the t2g orbitals. In contrast, at the polar CaVO3/LaAlO3 interface, the presence of the interface can have a huge effect on the physical properties, depending both on the specific interface termination and on the specific boundary conditions imposed by the multilayer geometry. We compare three approaches to modeling the CaVO3/LaAlO3 interface, all of which impose a different set of (electrostatic) boundary conditions. Our results demonstrate that different substrates, interface terminations, and electrostatic boundary conditions can drastically affect the properties of thin-film heterostructures, indicating the potential tunability of the interfacial properties via multilayer engineering.
DOI: 10.24435/materialscloud:x9-qr
title: DFT investigation of Ca mobility in reduced-perovskite and oxidized-marokite oxides

description: Progress in the development of rechargeable Ca-ion batteries demands the discovery of potential cathode materials. Transition metal oxides are interesting candidates due to their theoretical high energy densities, but with the drawback of a low Ca mobility. Previous computational/experimental investigations associate the electrochemical inactivity of various oxides (CaMO3-perovskite, CaMn2O4-post-spinel and CaV2O5) to high energy barriers for Ca migration. The introduction of oxygen and/or Ca vacancies in ternary transition metal oxides is a likely way to reshape the local topology and hence improve the Ca diffusivity. In this work, the energy barriers for Ca migration are calculated and discussed for (i) oxygen-deficient perovskites within the related Ca2Fe2O5-brownmillerite and Ca2Mn2O5 structures, and (ii) tunnel CaMn4O8, a derivative of the CaMn2O4-marokite with Ca vacancies.
DOI: 10.24435/materialscloud:yt-4y
title: DFT investigation of Ca mobility in reduced-perovskite and oxidized-marokite oxides

description: Progress in the development of rechargeable Ca-ion batteries demands the discovery of potential cathode materials. Transition metal oxides are interesting candidates due to their theoretical high energy densities, but with the drawback of a low Ca mobility. Previous computational/experimental investigations associate the electrochemical inactivity of various oxides (CaMO3-perovskite, CaMn2O4-post-spinel and CaV2O5) to high energy barriers for Ca migration. The introduction of oxygen and/or Ca vacancies in ternary transition metal oxides is a likely way to reshape the local topology and hence improve the Ca diffusivity. In this work, the energy barriers for Ca migration are calculated and discussed for (i) oxygen-deficient perovskites within the related Ca2Fe2O5-brownmillerite and Ca2Mn2O5 structures, and (ii) tunnel CaMn4O8, a derivative of the CaMn2O4-marokite with Ca vacancies.
DOI: 10.24435/materialscloud:5a-7s
title: First-principles simulation of electron transport and thermoelectric property of materials, including electron-phonon scattering, defect scattering, and phonon drag

description: We publish our code for electron transport and thermoelectric property calculations in solid state materials. This code is modified based on the EPW v4 code, originally from the open-source Quantum ESPRESSO suite (version 5.4.0), and is released under GNU General Public License. The original EPW v4 is developed by S. Poncé, E.R. Margine, C. Verdi, and, F. Giustino, initially released inside Quantum ESPRESSO in 2016. This modified version is dedicated to the simulation of electron-phonon transport properties in quantum materials. Specifically, it calculates the electron-phonon and electron-defect scattering rates and uses them as inputs in Boltzmann transport equation to obtain transport properties (e.g. electrical conductivity, mobility, Seebeck coefficient, thermoelectric power factor, and electronic thermal conductivity).
DOI: 10.24435/materialscloud:fp-p7
title: First-principles simulation of electron transport and thermoelectric property of materials, including electron-phonon scattering, defect scattering, and phonon drag

description: We publish our code for electron transport and thermoelectric property calculations in solid state materials. This code is modified based on the EPW v4 code, originally from the open-source Quantum ESPRESSO suite (version 5.4.0), and is released under GNU General Public License. The original EPW v4 is developed by S. Poncé, E.R. Margine, C. Verdi, and, F. Giustino, initially released inside Quantum ESPRESSO in 2016. This modified version is dedicated to the simulation of electron-phonon transport properties in quantum materials. Specifically, it calculates the electron-phonon and electron-defect scattering rates and uses them as inputs in Boltzmann transport equation to obtain transport properties (e.g. electrical conductivity, mobility, Seebeck coefficient, thermoelectric power factor, and electronic thermal conductivity).
DOI: 10.24435/materialscloud:yr-td
title: Pyrene-based metal organic frameworks

description: Pyrene is one of the most widely investigated aromatic hydrocarbons due to its unique optical and electronic properties. Hence, pyrene-based ligands have been investigated for the synthesis of metal-organic frameworks (MOFs) in the last few years. This dataset collects the atomic structures of the pyrene-based MOFs discussed in Table 1 of Ref. 1. 

The crystal structures have been manually curated to resolve partial occupancies and remove solvent molecules. Charge-neutral structures were optimized using DFT following the CURATED protocol described in 10.1021/acscentsci.9b00619.
DOI: 10.15468/dl.nbsdc9
title: Occurrence Download

description: A dataset containing 92439 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Living Specimen, Occurrence evidence)",
 "Continent is one of (Asia, Oceania)",
 "Issue is one of (Zero coordinate, Coordinate out of range, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate accuracy invalid, Coordinate uncertainty meters invalid, Coordinate precision/uncertainty mismatch, Footprint WKT mismatch, Footprint WKT invalid, Country mismatch, Country invalid, Country derived from coordinates, Continent invalid, Continent derived from country, Continent derived from coordinates, Presumed negated longitude, Presumed negated latitude, Recorded date mismatch, Recorded date invalid, Taxon match higher rank, Taxon match aggregate, The scientific name ID was not used in backbone matching, The taxon concept ID was not used in backbone matching, The taxon ID was not used in backbone matching, The scientific name ID was not found in the checklist, The taxon concept ID was not found in the checklist, The taxon ID was not found in the checklist, The scientific name differs on the record from that found in the checklist, Taxon match none, The backbone match found using the taxon IDs differs from what would be found if using the scientific names, Depth not metric, Depth unlikely, Depth min max swapped, Depth non numeric, Elevation unlikely, Elevation min max swapped, Elevation not metric, Elevation non numeric, Modified date invalid, Modified date unlikely, Identified date unlikely, Type status invalid, Multimedia date invalid, Multimedia URI invalid, Error during interpretation, Individual count invalid, Individual count conflicts with occurrence status, Occurrence status unparsable, Occurrence status inferred from individual count, ccurrence status inferred from basis of record, Georeferenced date unlikely, Georeferenced date invalid, Ambiguous institution, Collection match none, Institution collection mismatch, Possibly on loan, Different owner institution)",
 "OccurrenceStatus is Present",
 "TaxonKey is Fagaceae"
 ]
}

 The dataset includes 92439 records from 138 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067078-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.24435/materialscloud:d5-9h
title: Improved photoelectrochemical water splitting of CaNbO2N photoanodes by Co-Pi photodeposition and surface passivation

description: Photoelectrochemical solar water splitting is a promising approach to convert solar energy into sustainable hydrogen fuel using semiconductor electrodes. Due to their visible light absorption properties, oxynitrides have shown to be attractive photocatalysts for this application. In this study, the influence of the preparation method of CaNbO2N particles on their morphological and optical properties, and thereby their photoelectrochemical performance, is investigated. The best performing CaNbO2N photoanode is produced by ammonolysis of Nb enriched calcium niobium oxide. The enhanced photoactivity arises from an enlarged surface area and superior visible light absorption properties. The photoactivity of this photoanode was further enhanced by photodeposition of Co-Pi co-catalyst and by atomic layer deposition of an Al2O3 overlayer. A photocurrent density of 70 mA at 1.23 V vs RHE was achieved. The observed enhancement of the photoelectrochemical performance after Co-Pi/Al2O3 deposition is the combined effect of the improved kinetics of oxygen evolution due to the Co-Pi co-catalyst and the reduced surface recombination of the photogenerated carriers at the Al2O3 surface layer.
DOI: 10.24435/materialscloud:yz-bc
title: Improved photoelectrochemical water splitting of CaNbO2N photoanodes by Co-Pi photodeposition and surface passivation

description: Photoelectrochemical solar water splitting is a promising approach to convert solar energy into sustainable hydrogen fuel using semiconductor electrodes. Due to their visible light absorption properties, oxynitrides have shown to be attractive photocatalysts for this application. In this study, the influence of the preparation method of CaNbO2N particles on their morphological and optical properties, and thereby their photoelectrochemical performance, is investigated. The best performing CaNbO2N photoanode is produced by ammonolysis of Nb enriched calcium niobium oxide. The enhanced photoactivity arises from an enlarged surface area and superior visible light absorption properties. The photoactivity of this photoanode was further enhanced by photodeposition of Co-Pi co-catalyst and by atomic layer deposition of an Al2O3 overlayer. A photocurrent density of 70 mA at 1.23 V vs RHE was achieved. The observed enhancement of the photoelectrochemical performance after Co-Pi/Al2O3 deposition is the combined effect of the improved kinetics of oxygen evolution due to the Co-Pi co-catalyst and the reduced surface recombination of the photogenerated carriers at the Al2O3 surface layer.
DOI: 10.24435/materialscloud:6h-yj
title: CA-9, a dataset of carbon allotropes for training and testing of neural network potentials

description: The use of machine learning to accelerate computer simulations is on the rise. In atomistic simulations, the use of machine learning interatomic potentials (ML-IAPs) can significantly reduce computational costs while maintaining accuracy close to that of ab initio methods. To achieve this, ML-IAPs are trained on large datasets of images, meaning atomistic configurations labeled with data from ab initio calculations. Focusing on carbon, we have created a dataset, CA-9, consisting of 48000 images labeled with energies, forces and stress tensors obtained via ab initio molecular dynamics (AIMD). We use deep learning to train state-of-the-art neural network potentials (NNPs), a form of ML-IAP, on the CA-9 dataset and investigate how training and validation data can affect the performance of the NNPs. Our results show that image generation with AIMD causes a high degree of similarity between the generated images, which has a detrimental effect on the NNPs. However, by carefully choosing which images from the dataset are included in the training and validation data, this effect can be mitigated. We end by benchmarking our trained NNPs in real-world applications and show we can reproduce results from ab initio calculations with an accuracy higher than previously published ML- or classic IAPs.
DOI: 10.24435/materialscloud:p3-30
title: CA-9, a dataset of carbon allotropes for training and testing of neural network potentials

description: The use of machine learning to accelerate computer simulations is on the rise. In atomistic simulations, the use of machine learning interatomic potentials (ML-IAPs) can significantly reduce computational costs while maintaining accuracy close to that of ab initio methods. To achieve this, ML-IAPs are trained on large datasets of images, meaning atomistic configurations labeled with data from ab initio calculations. Focusing on carbon, we have created a dataset, CA-9, consisting of 48000 images labeled with energies, forces and stress tensors obtained via ab initio molecular dynamics (AIMD). We use deep learning to train state-of-the-art neural network potentials (NNPs), a form of ML-IAP, on the CA-9 dataset and investigate how training and validation data can affect the performance of the NNPs. Our results show that image generation with AIMD causes a high degree of similarity between the generated images, which has a detrimental effect on the NNPs. However, by carefully choosing which images from the dataset are included in the training and validation data, this effect can be mitigated. We end by benchmarking our trained NNPs in real-world applications and show we can reproduce results from ab initio calculations with an accuracy higher than previously published ML- or classic IAPs.
DOI: 10.24435/materialscloud:z5-ct
title: Pyrene-based metal organic frameworks

description: Pyrene is one of the most widely investigated aromatic hydrocarbons due to its unique optical and electronic properties. Hence, pyrene-based ligands have been investigated for the synthesis of metal-organic frameworks (MOFs) in the last few years. This dataset collects the atomic structures of the pyrene-based MOFs discussed in Table 1 of Ref. 1. 

The crystal structures have been manually curated to resolve partial occupancies and remove solvent molecules. Charge-neutral structures were optimized using DFT following the CURATED protocol described in 10.1021/acscentsci.9b00619.
DOI: 10.24435/materialscloud:d8-0h
title: Impact of quantum-chemical metrics on the machine learning prediction of electron density

description: Machine learning (ML) algorithms have undergone an explosive development impacting every aspect of computational chemistry. To obtain reliable predictions, one needs to maintain the proper balance between the black-box nature of ML frameworks and the physics of the target properties. One of the most appealing quantum-chemical properties for regression models is the electron density, and some of us recently proposed a transferable and scalable model based on the decomposition of the density onto an atom-centered basis set. The decomposition, as well as the training of the model, is at its core a minimization of some loss function, which can be arbitrarily chosen and may lead to results of different quality. Well-studied in the context of density fitting (DF), the impact of the metric on the performance of ML models has not been analyzed yet. In this work, we compare predictions obtained using the overlap and the Coulomb repulsion metrics for both the decomposition and training. As expected, the Coulomb metric used as both the DF and ML loss functions leads to the best results for the electrostatic potential and dipole moments. The origin of this difference lies in the fact that the model is not constrained to predict densities that integrate to the exact number of electrons N. Since an a posteriori correction for the number of electrons decreases the errors, we proposed a modification of the model where N is included directly into the kernel function, which allowed to lower the errors on the test and out-of-sample sets.
DOI: 10.24435/materialscloud:x7-v8
title: Pyrene-based metal organic frameworks

description: Pyrene is one of the most widely investigated aromatic hydrocarbons due to its unique optical and electronic properties. Hence, pyrene-based ligands have been investigated for the synthesis of metal-organic frameworks (MOFs) in the last few years. This dataset collects the atomic structures of the pyrene-based MOFs discussed in Table 1 of Ref. 1. 

The crystal structures have been manually curated to resolve partial occupancies and remove solvent molecules. Charge-neutral structures were optimized using DFT following the CURATED protocol described in 10.1021/acscentsci.9b00619.