cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.24435/materialscloud:t8-dv
title: A FEM dataset of Ge film profiles and elastic energies for machine learning approximation of strain state and morphological evolution

description: Machine Learning (ML) can be conveniently applied to continuum materials simulations, allowing for the investigation of larger systems and longer timescales, pushing the limits of tractable systems. Here we provide a comprehensive dataset of strained Ge films on Si and their corresponding strain states, which can be used to train a ML model capable of such acceleration. Approximately 80k 2D cases are included, reporting the profiles h(x) and the corresponding elastic energy densities and strain fields. The profiles are conveniently sampled using Perlin-noise and pure-sine waves. A 100nm-large computational domain is considered. The mechanical equilibrium problem is solved using Finite Element Method (FEM). Ge is modeled as an isotropic material and an eigenstrain of 3.99% is used, as in Ge/Si(001).
The database has been exploited for training a (fully) Convolutional Neural Network (CNN) which maps the free surface profile h(x) to the corresponding energy density. If plugged into the proper time-dependent Partial Differential Equation, this term can be used to accelerate continuum simulations of the morphological evolution of strained films while retaining FEM-level accuracy. Tests of the reliability of such CNN model are also provided in the repository, together with the output of surface morphology minimization procedures and morphological evolution simulations during coarsening and growth. In the latter, evolution by surface diffusion has been considered as an important case, but applications to other mechanisms are possible. Generalization examples to larger computational cells with respect to those in the dataset are also available.
DOI: 10.24435/materialscloud:9s-eb
title: Unveiling the self-assembly process of gellan-chitosan complexes through a combination of atomistic simulations and experiments

description: Polyelectrolyte complexes (PECs), formed via the self-assembly of oppositely charged polysaccharides, are highly valued for their biocompatibility, biodegradability, and hydrophilicity, offering significant potential for biotechnological applications. However, the complex nature and lack of insight at a molecular level into polyelectrolytes conformation and aggregation often hinders the possibility of achieving an optimal control of PEC systems, limiting their practical applications. To address this problem, an in-depth investigation of PECs microscopic structural organization is required. In this work, for the first time, a hybrid approach that combines experimental techniques with atomistic molecular dynamics simulations is used to elucidate, at a molecular level, the mechanisms underlying the aggregation and structural organization of complexes formed by gellan and chitosan, i.e. PECs commonly used in food technology. This combined analysis reveals a two-step complexation process: gellan initially self-assembles into a double-helix structure, subsequently surrounded and stabilized by chitosan via electrostatic interactions. Furthermore, these results show that complexation preserves the individual conformation and intrinsic functionality of both polyelectrolytes, thereby ensuring the efficacy of the PECs in biotechnological applications.
DOI: 10.24435/materialscloud:ej-m3
title: Emergent half-metal with mixed structural order in (111)-oriented (LaMnO₃)₂ₙ|(SrMnO₃)ₙ superlattices

description: Using first-principles techniques, we study the structural, magnetic, and electronic properties of (111)-oriented (LaMnO₃)₂ₙ|(SrMnO₃)ₙ superlattices of varying thickness (n=2,4,6). We find that the properties of the thinnest superlattice (n=2) are similar to the celebrated half-metallic ferromagnetic alloy La2/3Sr1/3⁢MnO₃, with quenched Jahn-Teller distortions. At intermediate thickness (n=4), the a⁻a⁻a⁻ tilting pattern transitions to the a⁻a⁻c⁺ tilting pattern, driven by the lattice degrees of freedom in the LaMnO₃ region. The emergence of the Jahn-Teller modes and the spatial extent needed for their development play a key role in this structural transition. For the largest thickness considered (n=6), we unveil an emergent separation of Jahn-Teller and volume-breathing orders in the ground-state structure with the a⁻a⁻c⁺ tilting pattern, whereas it vanishes in the antiferromagnetic configurations. The ground state of all superlattices is half-metallic ferromagnetic, not affected by the underlying series of structural transitions. Overall, these results outline a thickness-induced crossover between the physical properties of bulk La2/3Sr1/3⁢MnO₃ and bulk LaMnO₃. The dataset includes the fully relaxed atomic positions of the most favorable tilting patterns, as well as the main output files of the electronic structure calculations. Selected files for the density of states are also included.
DOI: 10.24435/materialscloud:ct-85
title: Unveiling the self-assembly process of gellan-chitosan complexes through a combination of atomistic simulations and experiments

description: Polyelectrolyte complexes (PECs), formed via the self-assembly of oppositely charged polysaccharides, are highly valued for their biocompatibility, biodegradability, and hydrophilicity, offering significant potential for biotechnological applications. However, the complex nature and lack of insight at a molecular level into polyelectrolytes conformation and aggregation often hinders the possibility of achieving an optimal control of PEC systems, limiting their practical applications. To address this problem, an in-depth investigation of PECs microscopic structural organization is required. In this work, for the first time, a hybrid approach that combines experimental techniques with atomistic molecular dynamics simulations is used to elucidate, at a molecular level, the mechanisms underlying the aggregation and structural organization of complexes formed by gellan and chitosan, i.e. PECs commonly used in food technology. This combined analysis reveals a two-step complexation process: gellan initially self-assembles into a double-helix structure, subsequently surrounded and stabilized by chitosan via electrostatic interactions. Furthermore, these results show that complexation preserves the individual conformation and intrinsic functionality of both polyelectrolytes, thereby ensuring the efficacy of the PECs in biotechnological applications.
DOI: 10.24435/materialscloud:16-ac
title: Spectroscopic investigations of complex electronic interactions by elemental doping and material compositing of cobalt oxide for enhanced oxygen evolution reaction activity

description: Doping and compositing are two universal design strategies used to engineer the electronic state of a material and mitigate its disadvantages. These two strategies have been extensively applied to the design of efficient electrocatalysts for water splitting. Using cobalt oxide (CoO) as a model catalyst, we prove that the oxygen evolution reaction (OER) performance could be progressively improved, first by Fe-doping to form Fe-CoO solid solution, and further by the addition of CeO2 to produce a Fe-CoO/CeO2 composite. X-ray adsorption spectroscopy (XAS) reveals that distinct electronic interactions are induced by the processes of doping and compositing. Fe-doping of CoO can break down the structural symmetry in the pristine material, changing the electronic structure of both Co and O species at the surface and decreasing the flat-band potential (Vfb). In comparison, subsequent compositing of Fe-CoO with CeO2 induces negligible electronic changes in the as-synthesized Fe-CoO (as seen in ex-situ characterizations), but significantly modifies the oxidative transformations of both Co and Fe under OER conditions. Our spectroscopic investigations reveal that Fe-doping and CeO2 compositing play different roles in modifying the electronic properties of CoO in its pristine state and during OER catalysis, respectively, in return, providing useful guidance for the design of more efficient electrocatalysts using these two strategies.
DOI: 10.24435/materialscloud:6p-b4
title: Spectroscopic investigations of complex electronic interactions by elemental doping and material compositing of cobalt oxide for enhanced oxygen evolution reaction activity

description: Doping and compositing are two universal design strategies used to engineer the electronic state of a material and mitigate its disadvantages. These two strategies have been extensively applied to the design of efficient electrocatalysts for water splitting. Using cobalt oxide (CoO) as a model catalyst, we prove that the oxygen evolution reaction (OER) performance could be progressively improved, first by Fe-doping to form Fe-CoO solid solution, and further by the addition of CeO2 to produce a Fe-CoO/CeO2 composite. X-ray adsorption spectroscopy (XAS) reveals that distinct electronic interactions are induced by the processes of doping and compositing. Fe-doping of CoO can break down the structural symmetry in the pristine material, changing the electronic structure of both Co and O species at the surface and decreasing the flat-band potential (Vfb). In comparison, subsequent compositing of Fe-CoO with CeO2 induces negligible electronic changes in the as-synthesized Fe-CoO (as seen in ex-situ characterizations), but significantly modifies the oxidative transformations of both Co and Fe under OER conditions. Our spectroscopic investigations reveal that Fe-doping and CeO2 compositing play different roles in modifying the electronic properties of CoO in its pristine state and during OER catalysis, respectively, in return, providing useful guidance for the design of more efficient electrocatalysts using these two strategies.
DOI: 10.24435/materialscloud:kn-mb
title: Atomic insights into the oxidative degradation mechanisms of sulfide solid electrolytes

description: This database contains phosphorus and sulfur K-edge X-ray absorption near-edge structure (XANES) of delithiated Lithium-Phosphorus-Sulfur compounds. The structures were generated by a computational delithiation procedure of β-Li3PS4 with density functional theory calculations, where we systematically enumerated distinct lithium/vacancy orderings in the super cells with the general composition Li12-xP4S16 (i.e., four Li3PS4 formula units and x from 0 to 12). The database contains a total of 2227 P K-edge and 8885 S K-edge XANES spectra of symmetrically inequivalent absorbing P and S sites. The XANES spectra were calculated using the excited electron and core hole method as implemented in The Vienna Ab initio Simulation Package (VASP) 6.2.1. Details of the structure generation procedure as well as the VASP simulations can be found in the associated manuscript (see reference below).
DOI: 10.24435/materialscloud:9g-1r
title: High-throughput computation of ab initio Raman spectra for two-dimensional materials

description: Raman spectra play an important role in characterizing two-dimensional materials, as they provide a direct link between the atomic structure and the spectral features. In this work, we present an  automatic computational workflow for Raman spectra using all-electron density functional perturbation theory. Utilizing this workflow, we have successfully completed the Raman spectra calculation for 3504 different two-dimensional materials, with the resultant data saved in a data repository.
DOI: 10.24435/materialscloud:w7-89
title: Atomic insights into the oxidative degradation mechanisms of sulfide solid electrolytes

description: This database contains phosphorus and sulfur K-edge X-ray absorption near-edge structure (XANES) of delithiated Lithium-Phosphorus-Sulfur compounds. The structures were generated by a computational delithiation procedure of β-Li3PS4 with density functional theory calculations, where we systematically enumerated distinct lithium/vacancy orderings in the super cells with the general composition Li12-xP4S16 (i.e., four Li3PS4 formula units and x from 0 to 12). The database contains a total of 2227 P K-edge and 8885 S K-edge XANES spectra of symmetrically inequivalent absorbing P and S sites. The XANES spectra were calculated using the excited electron and core hole method as implemented in The Vienna Ab initio Simulation Package (VASP) 6.2.1. Details of the structure generation procedure as well as the VASP simulations can be found in the associated manuscript (see reference below).
DOI: 10.24435/materialscloud:m4-7f
title: Machine-learning accelerated identification of exfoliable two-dimensional materials

description: Two-dimensional (2D) materials have been a central focus of recent research because they host a variety of properties, making them attractive both for fundamental science and for applications. It is thus crucial to be able to identify accurately and efficiently if bulk three-dimensional (3D) materials are formed by layers held together by weak binding energy and, thus, can be potentially exfoliated into 2D materials. In this work, we develop a machine-learning (ML) approach that, combined with a fast preliminary geometrical screening, is able to efficiently identify potentially exfoliable materials. Starting from a combination of descriptors for crystal structures, we work out a subset of them that are crucial for accurate predictions. Our final ML model, based on a random forest classifier, has a very high recall of 98%. Using a SHapely Additive exPlanations (SHAP) analysis, we also provide an intuitive explanation of the five most important variables of the model. Finally, we compare the performance of our best ML model with a deep neural network architecture using the same descriptors.
To make our algorithms and models easily accessible, we publish an online tool on the Materials Cloud portal that only requires a bulk 3D crystal structure as input. Our tool thus provides a practical yet straightforward approach to assess whether any 3D compound can be exfoliated into 2D layers.
DOI: 10.24435/materialscloud:ah-st
title: Machine-learning accelerated identification of exfoliable two-dimensional materials

description: Two-dimensional (2D) materials have been a central focus of recent research because they host a variety of properties, making them attractive both for fundamental science and for applications. It is thus crucial to be able to identify accurately and efficiently if bulk three-dimensional (3D) materials are formed by layers held together by weak binding energy and, thus, can be potentially exfoliated into 2D materials. In this work, we develop a machine-learning (ML) approach that, combined with a fast preliminary geometrical screening, is able to efficiently identify potentially exfoliable materials. Starting from a combination of descriptors for crystal structures, we work out a subset of them that are crucial for accurate predictions. Our final ML model, based on a random forest classifier, has a very high recall of 98%. Using a SHapely Additive exPlanations (SHAP) analysis, we also provide an intuitive explanation of the five most important variables of the model. Finally, we compare the performance of our best ML model with a deep neural network architecture using the same descriptors.
To make our algorithms and models easily accessible, we publish an online tool on the Materials Cloud portal that only requires a bulk 3D crystal structure as input. Our tool thus provides a practical yet straightforward approach to assess whether any 3D compound can be exfoliated into 2D layers.
DOI: 10.24435/materialscloud:bq-vp
title: High-throughput computation of ab initio Raman spectra for two-dimensional materials

description: Raman spectra play an important role in characterizing two-dimensional materials, as they provide a direct link between the atomic structure and the spectral features. In this work, we present an  automatic computational workflow for Raman spectra using all-electron density functional perturbation theory. Utilizing this workflow, we have successfully completed the Raman spectra calculation for 3504 different two-dimensional materials, with the resultant data saved in a data repository.
DOI: 10.24435/materialscloud:2020.0026/v1
title: AIRSS data for carbon at 10GPa and the C+N+H+O system at 1GPa

description: Ab initio random structure searching (AIRSS) has been performed for carbon at 10GPa, a pressure at which diamond is expected to be the thermodynamic ground state. A small (~10K structures) and larger (~100K structures) set are provided. To demonstrate a search in a ternary composition space ~100K AIRSS structures for the C+N+H+O system are provided. All structures are generated at random using the buildcell tool of the AIRSS suite, and relaxed to a nearby local minimum in the DFT-PBE total energy using the CASTEP code. Computational details are provided in the REM block of the .res structure files.
DOI: 10.24435/materialscloud:d3-xk
title: High-throughput computation of ab initio Raman spectra for two-dimensional materials

description: Raman spectra play an important role in characterizing two-dimensional materials, as they provide a direct link between the atomic structure and the spectral features. In this work, we present an  automatic computational workflow for Raman spectra using all-electron density functional perturbation theory. Utilizing this workflow, we have successfully completed the Raman spectra calculation for 3504 different two-dimensional materials, with the resultant data saved in a data repository.
DOI: 10.24435/materialscloud:vk-b1
title: AIRSS data for carbon at 10GPa and the C+N+H+O system at 1GPa

description: Ab initio random structure searching (AIRSS) has been performed for carbon at 10GPa, a pressure at which diamond is expected to be the thermodynamic ground state. A small (~10K structures) and larger (~100K structures) set are provided. To demonstrate a search in a ternary composition space ~100K AIRSS structures for the C+N+H+O system are provided. All structures are generated at random using the buildcell tool of the AIRSS suite, and relaxed to a nearby local minimum in the DFT-PBE total energy using the CASTEP code. Computational details are provided in the REM block of the .res structure files.
DOI: 10.6084/m9.figshare.29390576
title: grey literature

description: This file contains all the selected grey literature for the MLR.
DOI: 10.6084/m9.figshare.29390576.v1
title: grey literature

description: This file contains all the selected grey literature for the MLR.
DOI: 10.24435/materialscloud:2017.0008/v2
title: Two-dimensional materials from high-throughput computational exfoliation of  experimentally known compounds

description: Two-dimensional (2D) materials have emerged as promising candidates for next-generation electronic and optoelectronic applications. Yet, only a few dozens of 2D materials have been successfully synthesized or exfoliated. Here, we search for novel 2D materials that can be easily exfoliated from their parent compounds. Starting from 108423 unique, experimentally known three-dimensional compounds we identify a subset of 5619 that appear layered according to robust geometric and bonding criteria. High-throughput calculations using van-der-Waals density-functional theory, validated against experimental structural data and calculated random-phase-approximation binding energies, allow to identify 1825 compounds that are either easily or potentially exfoliable. In particular, the subset of 1036 easily exfoliable cases provides novel structural prototypes and simple ternary compounds as well as a large portfolio of materials to search from for optimal properties. For a subset of 258 compounds we explore vibrational, electronic, magnetic, and topological properties, identifying 56 ferromagnetic and antiferromagnetic systems, including half-metals and half-semiconductors. This archive entry contains the database of 2D materials (structural parameters, band structures, binding energies, etc.) together with the provenance of all data and calculations as stored by AiiDA.
DOI: 10.24435/materialscloud:2017.0008/v1
title: Two-dimensional materials from high-throughput computational exfoliation of  experimentally known compounds (Data download)

description: Two-dimensional (2D) materials have emerged as promising candidates for next-generation electronic and optoelectronic applications. Yet, only a few dozens of 2D materials have been successfully synthesized or exfoliated. Here, we search for novel 2D materials that can be easily exfoliated from their parent compounds. Starting from 108423 unique, experimentally known three-dimensional compounds we identify a subset of 5619 that appear layered according to robust geometric and bonding criteria. High-throughput calculations using van-der-Waals density-functional theory, validated against experimental structural data and calculated random-phase-approximation binding energies, allow to identify 1825 compounds that are either easily or potentially exfoliable. In particular, the subset of 1036 easily exfoliable cases provides novel structural prototypes and simple ternary compounds as well as a large portfolio of materials to search from for optimal properties. For a subset of 258 compounds we explore vibrational, electronic, magnetic, and topological properties, identifying 56 ferromagnetic and antiferromagnetic systems, including half-metals and half-semiconductors. This archive entry contains the database of 2D materials (structural parameters, band structures, binding energies, etc.) together with the provenance of all data and calculations as stored by AiiDA.
DOI: 10.5281/zenodo.15728687
title: GUGUGUGUGULUULULULU
DOI: 10.5281/zenodo.15728688
title: GUGUGUGUGULUULULULU
DOI: 10.24435/materialscloud:4f-n7
title: Unconventional transverse transport above and below the magnetic transition temperature in Weyl semimetal EuCd₂As₂

description: As exemplified by the growing interest in the quantum anomalous Hall effect, the research on topology as an organizing principle of quantum matter is greatly enriched from the interplay with magnetism. In this vein, we present a combined electrical and thermoelectrical transport study on the magnetic Weyl semimetal EuCd₂As₂. Unconventional contribution to the anomalous Hall and anomalous Nernst effects were observed both above and below the magnetic transition temperature of EuCd₂As₂, indicating the existence of significant Berry curvature. EuCd₂As₂ represents a rare case in which this unconventional transverse transport emerges both above and below the magnetic transition temperature in the same material. The transport properties evolve with temperature and field in the antiferromagnetic phase in a different manner than in the paramagnetic phase, suggesting different mechanisms to their origin. Our results indicate EuCd₂As₂ is a fertile playground for investigating the interplay between magnetism and topology, and potentially a plethora of topologically nontrivial phases rooted in this interplay. This record contains the raw data for this manuscript [Physical Review Letters 126, 076602 (2021)].