cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.24435/materialscloud:5m-g6
title: An overview of the spin dynamics of antiferromagnetic Mn₅Si₃

description: The metallic compound Mn5Si3 hosts a series of antiferromagnetic phases that can be controlled by external stimuli, such as temperature and magnetic field. In this work, we investigate the spin-excitation spectrum of bulk Mn5Si3 by combining inelastic neutron scattering measurements and density functional theory calculations. We study the evolution of the dynamical response under external parameters and demonstrate that the spin dynamics of each phase is robust against any combination of temperature and magnetic field. In particular, the high-energy spin dynamics is very characteristic of the different phases consisting of either spin waves or broad fluctuation patterns. This data set contains the data relevant to performing the spin dynamics simulations with the Spirit code, the spin-wave calculations with the SWIS code, and the neutron scattering experimental data.
DOI: 10.24435/materialscloud:ec-yt
title: Screening of low-friction two-dimensional materials from high-throughput calculations using frictional figure of merit

description: Two-dimensional materials are excellent lubricants with inherent advantages. However, superlubricity has only been reported in a few of them. It is a regret that other promising 2D materials with different physical properties cannot be discovered and applied in production so that energy consumption can be greatly reduced. Here we carry out high-throughput calculations for 1475 two-dimensional materials and screen for low-friction ones. To set a standard, we propose, for the first time, a geometry-independent frictional figure of merit based on the condition for stick-slip transition and our theory of Moiré friction. For the efficient calculation of this figure of merit, an innovative approach is developed based on an improved registry index model. Through the calculation, 340 materials are found to have a figure of merit lower than 10-3. Eventually, a small set of 21 materials with a figure of merit lower than 10-4 are screened out within them. These materials can provide diversified choices for applications. In addition, the efficient computational approach demonstrated in this work can be used to study other stacking-dependent properties.
DOI: 10.24435/materialscloud:zc-45
title: Flat-band hybridization between f and d states near the Fermi energy of SmCoIn₅

description: We present high-quality angle-resolved photoemission (ARPES) and density functional theory calculations (DFT+U) of SmCoIn₅. We find broad agreement with previously published studies of LaCoIn₅ and CeCoIn₅, confirming that the Sm 4f electrons are mostly localized. Nevertheless, our model is consistent with an additional delocalized Sm component, stemming from hybridization between the 4f electrons and the metallic bands at "hot spot" positions in the Brillouin zone. The dominant hot spot, called γz, is similar to a source of delocalized f states found in previous experimental and theoretical studies of CeCoIn₅. In this work, we identify and focus on the role of geometric frustration in exploring the relationship between heavy quasiparticles and the magnetically ordered ground state of SmCoIn₅. Specifically, we find a globally flat band consisting of Co 3dxy/3dz2 orbital states near E = −0.7 eV, indicating a general role for geometric frustration in the "115" family of materials. We also show that the delocalized Sm 4f states can hybridize directly with the Co 3dxz/3dyz orbitals, which occurs in our model at the Brillouin zone boundary point R in a band that is locally flat and touches the Fermi level from above. Our work identifies microscopic ingredients for additional magnetic interactions in the "115" materials beyond the RKKY mechanism, and strongly suggests that the Co d bands are an important ingredient in the formation of both magnetic and superconducting ground states.
DOI: 10.24435/materialscloud:n0-va
title: Microscopic nature of the charge-density wave in the kagome superconductor RbV₃Sb₅

description: The recently discovered vanadium-based Kagome metals AV₃Sb₅ (A = K, Rb, Cs) undergo a unique phase transition into charge-density wave (CDW) order which precedes both unconventional superconductivity and time-reversal symmetry breaking. Therefore the essential first step in building a full understanding of the role of CDW in establishing these unconventional phases is to unveil the symmetries and the microscopic nature of the charge-ordered phase. Here, we determine the exact structure of the 2×2×2 superlattice that develops below the charge-density wave ordering temperature (TCDW) in RbV₃Sb₅. We present a comprehensive set of ⁵¹V, ⁸⁷Rb, and ¹²¹Sb nuclear magnetic resonance (NMR) measurements and density functional theory simulations of NMR observables to provide a unique site-selective view into the local nature of the charge-ordered phase. The combination of these experimental results with simulations provides compelling evidence that the CDW structure prevailing below 103 K in RbV₃Sb₅ is the so-called inverse Star of David pattern, π-shifted along the c axis. These findings put severe constraints on the topology of these Kagome compounds and thus provide essential guidance for the development of an appropriate theoretical framework for predicting properties of exotic electronic orders arising within the CDW phase.
DOI: 10.24435/materialscloud:x4-85
title: Flat-band hybridization between f and d states near the Fermi energy of SmCoIn₅

description: We present high-quality angle-resolved photoemission (ARPES) and density functional theory calculations (DFT+U) of SmCoIn₅. We find broad agreement with previously published studies of LaCoIn₅ and CeCoIn₅, confirming that the Sm 4f electrons are mostly localized. Nevertheless, our model is consistent with an additional delocalized Sm component, stemming from hybridization between the 4f electrons and the metallic bands at "hot spot" positions in the Brillouin zone. The dominant hot spot, called γz, is similar to a source of delocalized f states found in previous experimental and theoretical studies of CeCoIn₅. In this work, we identify and focus on the role of geometric frustration in exploring the relationship between heavy quasiparticles and the magnetically ordered ground state of SmCoIn₅. Specifically, we find a globally flat band consisting of Co 3dxy/3dz2 orbital states near E = −0.7 eV, indicating a general role for geometric frustration in the "115" family of materials. We also show that the delocalized Sm 4f states can hybridize directly with the Co 3dxz/3dyz orbitals, which occurs in our model at the Brillouin zone boundary point R in a band that is locally flat and touches the Fermi level from above. Our work identifies microscopic ingredients for additional magnetic interactions in the "115" materials beyond the RKKY mechanism, and strongly suggests that the Co d bands are an important ingredient in the formation of both magnetic and superconducting ground states.
DOI: 10.24435/materialscloud:6c-b3
title: Complexity of many-body interactions in transition metals via machine-learned force fields from the TM23 data set

description: This work examines challenges associated with the accuracy of machine-learned force fields (MLFFs) for bulk solid and liquid phases of d-block elements. In exhaustive detail, we contrast the performance of force, energy, and stress predictions across the transition metals for two leading MLFF models: a kernel-based atomic cluster expansion method implemented using sparse Gaussian processes (FLARE), and an equivariant message-passing neural network (NequIP). Early transition metals present higher relative errors and are more difficult to learn relative to late platinum- and coinage-group elements, and this trend persists across model architectures. Trends in complexity of interatomic interactions for different metals are revealed via comparison of the performance of representations with different many-body order and angular resolution. Using arguments based on perturbation theory on the occupied and unoccupied d states near the Fermi level, we determine that the large, sharp d density of states both above and below the Fermi level in early transition metals leads to a more complex, harder-to-learn potential energy surface for these metals. Increasing the fictitious electronic temperature (smearing) modifies the angular sensitivity of forces and makes the early transition metal forces easier to learn. This work illustrates challenges in capturing intricate properties of metallic bonding with current leading MLFFs and provides a reference data set for transition metals, aimed at benchmarking the accuracy and improving the development of emerging machine-learned approximations.
DOI: 10.24435/materialscloud:zc-bz
title: Microscopic nature of the charge-density wave in the kagome superconductor RbV₃Sb₅

description: The recently discovered vanadium-based Kagome metals AV₃Sb₅ (A = K, Rb, Cs) undergo a unique phase transition into charge-density wave (CDW) order which precedes both unconventional superconductivity and time-reversal symmetry breaking. Therefore the essential first step in building a full understanding of the role of CDW in establishing these unconventional phases is to unveil the symmetries and the microscopic nature of the charge-ordered phase. Here, we determine the exact structure of the 2×2×2 superlattice that develops below the charge-density wave ordering temperature (TCDW) in RbV₃Sb₅. We present a comprehensive set of ⁵¹V, ⁸⁷Rb, and ¹²¹Sb nuclear magnetic resonance (NMR) measurements and density functional theory simulations of NMR observables to provide a unique site-selective view into the local nature of the charge-ordered phase. The combination of these experimental results with simulations provides compelling evidence that the CDW structure prevailing below 103 K in RbV₃Sb₅ is the so-called inverse Star of David pattern, π-shifted along the c axis. These findings put severe constraints on the topology of these Kagome compounds and thus provide essential guidance for the development of an appropriate theoretical framework for predicting properties of exotic electronic orders arising within the CDW phase.
DOI: 10.24435/materialscloud:h2-8q
title: Complexity of many-body interactions in transition metals via machine-learned force fields from the TM23 data set

description: This work examines challenges associated with the accuracy of machine-learned force fields (MLFFs) for bulk solid and liquid phases of d-block elements. In exhaustive detail, we contrast the performance of force, energy, and stress predictions across the transition metals for two leading MLFF models: a kernel-based atomic cluster expansion method implemented using sparse Gaussian processes (FLARE), and an equivariant message-passing neural network (NequIP). Early transition metals present higher relative errors and are more difficult to learn relative to late platinum- and coinage-group elements, and this trend persists across model architectures. Trends in complexity of interatomic interactions for different metals are revealed via comparison of the performance of representations with different many-body order and angular resolution. Using arguments based on perturbation theory on the occupied and unoccupied d states near the Fermi level, we determine that the large, sharp d density of states both above and below the Fermi level in early transition metals leads to a more complex, harder-to-learn potential energy surface for these metals. Increasing the fictitious electronic temperature (smearing) modifies the angular sensitivity of forces and makes the early transition metal forces easier to learn. This work illustrates challenges in capturing intricate properties of metallic bonding with current leading MLFFs and provides a reference data set for transition metals, aimed at benchmarking the accuracy and improving the development of emerging machine-learned approximations.
DOI: 10.24435/materialscloud:qy-dp
title: Randomly-displaced methane configurations

description: Most of the datasets to benchmark machine-learning models contain minimum-energy structures, or small fluctuations around stable geometries, and focus on the diversity of chemical compositions, or the presence of different phases. This dataset provides a large number (7732488) configurations for a simple CH4 composition, that are generated in an almost completely unbiased fashion. Hydrogen atoms are randomly distributed in a 3A sphere centered around the carbon atom, and the only structures that are discarded are those with atoms that are closer than 0.5A, or such that the reference DFT calculation does not converge.
This dataset is ideal to benchmark structural representations and regression algorithms, verifying whether they allow reaching arbitrary accuracy in the data rich regime.
DOI: 10.24435/materialscloud:65-yc
title: Enhanced catalytic performance towards CO oxidation of broccoli-like Ceria microsphere by dilute Ga doping

description: The process of catalytically oxidizing carbon monoxide (CO) remains a critical issue across various industrial sectors. However, it continues to be a challenge to achieve effective CO oxidation at low temperatures using non-noble metal catalysts. This study addresses these gaps by investigating the effects of dilute gallium (Ga) doping on the catalytic performance of flower-like ceria (CeO₂) microspheres. By using a modified hydrothermal synthesis method, we prepared the Ga-doped CeO₂ microspheres and characterized their morphology, surface area, and evidence of oxygen vacancy through various experimental techniques as well as computational simulation method. Our findings disclosed that the incorporation of Ga significantly enhances the catalytic performance of CeO₂, with the optimal doping level (2 mol% Ga) achieving a 90% CO conversion temperature (T90) of 388.9 °C, obviously lower than that of pristine CeO₂ (488.5 °C). This work demonstrates that dilute Ga doping effectively improves the catalytic properties of CeO₂-based materials, offering a potential strategy for developing effective CO oxidation catalysts.
DOI: 10.24435/materialscloud:j5-he
title: Randomly-displaced methane configurations

description: Most of the datasets to benchmark machine-learning models contain minimum-energy structures, or small fluctuations around stable geometries, and focus on the diversity of chemical compositions, or the presence of different phases. This dataset provides a large number (7732488) configurations for a simple CH4 composition, that are generated in an almost completely unbiased fashion. Hydrogen atoms are randomly distributed in a 3A sphere centered around the carbon atom, and the only structures that are discarded are those with atoms that are closer than 0.5A, or such that the reference DFT calculation does not converge.
This dataset is ideal to benchmark structural representations and regression algorithms, verifying whether they allow reaching arbitrary accuracy in the data rich regime.
DOI: 10.24435/materialscloud:yy-sy
title: Enhanced catalytic performance towards CO oxidation of broccoli-like Ceria microsphere by dilute Ga doping

description: The process of catalytically oxidizing carbon monoxide (CO) remains a critical issue across various industrial sectors. However, it continues to be a challenge to achieve effective CO oxidation at low temperatures using non-noble metal catalysts. This study addresses these gaps by investigating the effects of dilute gallium (Ga) doping on the catalytic performance of flower-like ceria (CeO₂) microspheres. By using a modified hydrothermal synthesis method, we prepared the Ga-doped CeO₂ microspheres and characterized their morphology, surface area, and evidence of oxygen vacancy through various experimental techniques as well as computational simulation method. Our findings disclosed that the incorporation of Ga significantly enhances the catalytic performance of CeO₂, with the optimal doping level (2 mol% Ga) achieving a 90% CO conversion temperature (T90) of 388.9 °C, obviously lower than that of pristine CeO₂ (488.5 °C). This work demonstrates that dilute Ga doping effectively improves the catalytic properties of CeO₂-based materials, offering a potential strategy for developing effective CO oxidation catalysts.
DOI: 10.24435/materialscloud:yy-ds
title: Automated computational workflows for muon spin spectroscopy

description: Muon spin rotation and relaxation spectroscopy is a powerful tool for studying magnetic materials, offering a local probe that complements scattering techniques and provides advantages in cases of strong incoherent scattering or neutron absorption. By integrating computational methods (DFT+μ), the microscopic interactions driving the observed signals can be precisely quantified, enhancing the technique's predictive power. We present a set of efficient algorithms and workflows - implemented in the AiiDA framework - that automate the DFT+μ procedure, where the muon is treated as a hydrogen impurity within the density functional theory framework. Our approach automates the identification of muon stopping sites, dipolar interactions, and hyperfine interactions. In this record we share the result of our calculations on well-known compounds, to demonstrate the accuracy and ease of use of our protocol.
DOI: 10.24435/materialscloud:7c-4a
title: Automated computational workflows for muon spin spectroscopy

description: Muon spin rotation and relaxation spectroscopy is a powerful tool for studying magnetic materials, offering a local probe that complements scattering techniques and provides advantages in cases of strong incoherent scattering or neutron absorption. By integrating computational methods (DFT+μ), the microscopic interactions driving the observed signals can be precisely quantified, enhancing the technique's predictive power. We present a set of efficient algorithms and workflows - implemented in the AiiDA framework - that automate the DFT+μ procedure, where the muon is treated as a hydrogen impurity within the density functional theory framework. Our approach automates the identification of muon stopping sites, dipolar interactions, and hyperfine interactions. In this record we share the result of our calculations on well-known compounds, to demonstrate the accuracy and ease of use of our protocol.
DOI: 10.24435/materialscloud:tx-2p
title: 3D ordering at the liquid–solid polar interface of nanowires

description: The nature of the liquid–solid interface determines the characteristics of a variety of physical phenomena, including catalysis, electrochemistry, lubrication, and crystal growth. Most of the established models for crystal growth are based on macroscopic thermodynamics, neglecting the atomistic nature of the liquid–solid interface. Here, experimental observations and molecular dynamics simulations are employed to identify the 3D nature of an atomic‐scale ordering of liquid Ga in contact with solid GaAs in a nanowire growth configuration. An interplay between the liquid ordering and the formation of a new bilayer is revealed, which, contrary to the established theories, suggests that the preference for a certain polarity and polytypism is influenced by the atomic structure of the interface. The conclusions of this work open new avenues for the understanding of crystal growth, as well as other processes and systems involving a liquid–solid interface.
DOI: 10.24435/materialscloud:6h-5y
title: 3D ordering at the liquid–solid polar interface of nanowires

description: The nature of the liquid–solid interface determines the characteristics of a variety of physical phenomena, including catalysis, electrochemistry, lubrication, and crystal growth. Most of the established models for crystal growth are based on macroscopic thermodynamics, neglecting the atomistic nature of the liquid–solid interface. Here, experimental observations and molecular dynamics simulations are employed to identify the 3D nature of an atomic‐scale ordering of liquid Ga in contact with solid GaAs in a nanowire growth configuration. An interplay between the liquid ordering and the formation of a new bilayer is revealed, which, contrary to the established theories, suggests that the preference for a certain polarity and polytypism is influenced by the atomic structure of the interface. The conclusions of this work open new avenues for the understanding of crystal growth, as well as other processes and systems involving a liquid–solid interface.
DOI: 10.24435/materialscloud:th-d5
title: First-principles thermodynamics of precipitation in aluminum-containing refractory alloys

description: Materials for high-temperature environments are actively being investigated for deployment in aerospace and nuclear applications. This study uses computational approaches to unravel the crystallography, and thermodynamics of a promising class of refractory alloys containing aluminum. Accurate first-principles calculations, cluster expansion models, and statistical mechanics techniques are employed to rigorously analyze precipitation in a prototypical senary Al-Nb-Ta-Ti-V-Zr alloy. Finite-temperature calculations reveal a strong tendency for aluminum to segregate to a single sublattice at elevated temperatures. Precipitate and matrix compositions computed with our ab-initio model are in excellent agreement with previous experimental measurements (Soni et al., 2020). Surprisingly, conventional B2-like orderings are found to be both thermodynamically and mechanically unstable in this alloy system. Complex anti-site defects are essential to forming a stable ordered precipitate. Our calculations reveal that the instability of B2 compounds can be related to a simple electron counting rule across all binary alloys formed by elements in groups 4,5, and 6. The results of this study provide viable routes toward designing high-temperature materials for deployment in extreme environments.
DOI: 10.15468/dl.qrz35y
title: Occurrence Download

description: A dataset containing 21819779 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Plantae)",
 "Year 1970-2024",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is United States of America",
 "BasisOfRecord is one of (Human Observation, Observation, Machine Observation, Occurrence evidence)"
 ]
}

 The dataset includes 21819779 records from 177 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067081-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.24435/materialscloud:fn-1m
title: First-principles thermodynamics of precipitation in aluminum-containing refractory alloys

description: Materials for high-temperature environments are actively being investigated for deployment in aerospace and nuclear applications. This study uses computational approaches to unravel the crystallography, and thermodynamics of a promising class of refractory alloys containing aluminum. Accurate first-principles calculations, cluster expansion models, and statistical mechanics techniques are employed to rigorously analyze precipitation in a prototypical senary Al-Nb-Ta-Ti-V-Zr alloy. Finite-temperature calculations reveal a strong tendency for aluminum to segregate to a single sublattice at elevated temperatures. Precipitate and matrix compositions computed with our ab-initio model are in excellent agreement with previous experimental measurements (Soni et al., 2020). Surprisingly, conventional B2-like orderings are found to be both thermodynamically and mechanically unstable in this alloy system. Complex anti-site defects are essential to forming a stable ordered precipitate. Our calculations reveal that the instability of B2 compounds can be related to a simple electron counting rule across all binary alloys formed by elements in groups 4,5, and 6. The results of this study provide viable routes toward designing high-temperature materials for deployment in extreme environments.