cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.24435/materialscloud:66-dd
title: Non-Abelian reciprocal braiding of Weyl points and its manifestation in ZrTe

description: Weyl semimetals in three-dimensional crystals provide the paradigm example of topologically protected band nodes. It is usually taken for granted that a pair of colliding Weyl points annihilate whenever they carry opposite chiral charges. In stark contrast, here we report that Weyl points in systems symmetric under the composition of time-reversal with a π-rotation are characterized by a non-Abelian topological invariant. The topological charges of the Weyl points are transformed via braid phase factors which arise upon exchange inside symmetric planes of the reciprocal momentum space. We elucidate this process with an elementary two-dimensional tight-binding model implementable in cold-atoms setups and in photonic systems. In three dimensions, interplay of the non-Abelian topology with point-group symmetry is shown to enable topological phase transitions in which pairs of Weyl points may scatter or convert into nodal-line rings. By combining our theoretical arguments with first-principles calculations, we predict that Weyl points occurring near the Fermi level of zirconium telluride (ZrTe) carry non-trivial values of the non-Abelian charge, and that uniaxial compression strain drives a non-trivial conversion of the Weyl points into nodal lines.
DOI: 10.24435/materialscloud:ed-gp
title: A dual-cutoff machine-learned potential for condensed organic systems obtained via uncertainty-guided active learning

description: Machine-learned potentials (MLPs) trained on ab initio data combine the computational efficiency of classical interatomic potentials with the accuracy and generality of the first-principles method used in the creation of the respective training set. In this work, we implement and train a MLP to obtain an accurate description of the potential energy surface and property predictions for organic compounds, as both single molecules and in the condensed phase. We devise a dual descriptor, based on the atomic cluster expansion (ACE), that couples an information-rich short-range description with a coarser long-range description that captures weak intermolecular interactions. We employ uncertainty-guided active learning for the training set generation, creating a dataset that is comparatively small for the breadth of application and consists of alcohols, alkanes, and an adipate. Utilizing that MLP, we calculate densities of those systems of varying chain lengths as a function of temperature, obtaining a discrepancy of less than 4% compared with experiment. Vibrational frequencies calculated with the MLP have a root mean square error of less than 1 THz compared to DFT. The heat capacities of condensed systems are within 11% of experimental findings, which is strong evidence that the dual descriptor provides an accurate framework for the prediction of both short-range intramolecular and long-range intermolecular interactions.
DOI: 10.24435/materialscloud:5y-g6
title: A dual-cutoff machine-learned potential for condensed organic systems obtained via uncertainty-guided active learning

description: Machine-learned potentials (MLPs) trained on ab initio data combine the computational efficiency of classical interatomic potentials with the accuracy and generality of the first-principles method used in the creation of the respective training set. In this work, we implement and train a MLP to obtain an accurate description of the potential energy surface and property predictions for organic compounds, as both single molecules and in the condensed phase. We devise a dual descriptor, based on the atomic cluster expansion (ACE), that couples an information-rich short-range description with a coarser long-range description that captures weak intermolecular interactions. We employ uncertainty-guided active learning for the training set generation, creating a dataset that is comparatively small for the breadth of application and consists of alcohols, alkanes, and an adipate. Utilizing that MLP, we calculate densities of those systems of varying chain lengths as a function of temperature, obtaining a discrepancy of less than 4% compared with experiment. Vibrational frequencies calculated with the MLP have a root mean square error of less than 1 THz compared to DFT. The heat capacities of condensed systems are within 11% of experimental findings, which is strong evidence that the dual descriptor provides an accurate framework for the prediction of both short-range intramolecular and long-range intermolecular interactions.
DOI: 10.24435/materialscloud:2020.0042/v1
title: Unified picture of lattice instabilities in metallic transition metal dichalcogenides

description: Transition metal dichalcogenides (TMDs) in the 1T polymorph are subject to a rich variety of periodic lattice distortions, often referred to as charge-density waves (CDWs) when not too strong. We study from first principles the fermiology and phonon dispersion of three representative single-layer transition metal disulfides with different occupation of the t2g subshell: TaS2 (t1 2g), WS2 (t2 2g), and ReS2 (t3 2g) across a broad range of doping levels. While strong electron-phonon interactions are at the heart of these instabilities, we argue that away from half-filling of the t2g subshell, the doping dependence of the calculated CDW wave vector can be explained from simple fermiology arguments, so that a weak-coupling nesting picture is a useful starting point for understanding. On the other hand, when the t2g subshell is closer to half-filling, we show that nesting is irrelevant, while a real-space strong-coupling picture of bonding Wannier functions is more appropriate and simple bond-counting arguments apply. Our study thus provides a unifying picture of lattice distortions in 1T TMDs that bridges the two regimes, while the crossover between these regimes can be attained by tuning the filling of the t2g orbitals.
DOI: 10.24435/materialscloud:2020.0018/v1
title: Surface reconstructions and premelting of the (100) CaF2 surface

description: In this work, surface reconstructions on the (100) surface of CaF2 are comprehensively investigated. The configurations were explored by employing the Minima Hopping Method (MHM) coupled to a machine-learning interatomic potential, that is based on a charge equilibration scheme steered by a neural network (CENT). The combination of these powerful methods revealed about 80 different morphologies for the (100) surface with very similar surface formation energies differing by not more than 0.3 J m−2. To take into account the effect of temperature on the dynamics of this surface as well as to study the solid–liquid transformation, molecular dynamics simulations were carried out in the canonical (NVT) ensemble. By analyzing the atomic mean-square displacements (MSD) of the surface layer in the temperature range of 300–1200 K, it was found that in the surface region the F sublattice is less stable and more diffusive than the Ca sublattice. Based on these results we demonstrate that not only a bulk system, but also a surface can exhibit a sublattice premelting that leads to superionicity. Both the surface sublattice premelting and surface premelting occur at temperatures considerably lower than the bulk values. The complex behaviour of the (100) surface is contrasted with the simpler behavior of other low index crystallographic surfaces.
DOI: 10.24435/materialscloud:gz-f8
title: Unified picture of lattice instabilities in metallic transition metal dichalcogenides

description: Transition metal dichalcogenides (TMDs) in the 1T polymorph are subject to a rich variety of periodic lattice distortions, often referred to as charge-density waves (CDWs) when not too strong. We study from first principles the fermiology and phonon dispersion of three representative single-layer transition metal disulfides with different occupation of the t2g subshell: TaS2 (t1 2g), WS2 (t2 2g), and ReS2 (t3 2g) across a broad range of doping levels. While strong electron-phonon interactions are at the heart of these instabilities, we argue that away from half-filling of the t2g subshell, the doping dependence of the calculated CDW wave vector can be explained from simple fermiology arguments, so that a weak-coupling nesting picture is a useful starting point for understanding. On the other hand, when the t2g subshell is closer to half-filling, we show that nesting is irrelevant, while a real-space strong-coupling picture of bonding Wannier functions is more appropriate and simple bond-counting arguments apply. Our study thus provides a unifying picture of lattice distortions in 1T TMDs that bridges the two regimes, while the crossover between these regimes can be attained by tuning the filling of the t2g orbitals.
DOI: 10.24435/materialscloud:en-be
title: Surface reconstructions and premelting of the (100) CaF2 surface

description: In this work, surface reconstructions on the (100) surface of CaF2 are comprehensively investigated. The configurations were explored by employing the Minima Hopping Method (MHM) coupled to a machine-learning interatomic potential, that is based on a charge equilibration scheme steered by a neural network (CENT). The combination of these powerful methods revealed about 80 different morphologies for the (100) surface with very similar surface formation energies differing by not more than 0.3 J m−2. To take into account the effect of temperature on the dynamics of this surface as well as to study the solid–liquid transformation, molecular dynamics simulations were carried out in the canonical (NVT) ensemble. By analyzing the atomic mean-square displacements (MSD) of the surface layer in the temperature range of 300–1200 K, it was found that in the surface region the F sublattice is less stable and more diffusive than the Ca sublattice. Based on these results we demonstrate that not only a bulk system, but also a surface can exhibit a sublattice premelting that leads to superionicity. Both the surface sublattice premelting and surface premelting occur at temperatures considerably lower than the bulk values. The complex behaviour of the (100) surface is contrasted with the simpler behavior of other low index crystallographic surfaces.
DOI: 10.24435/materialscloud:2020.0035/v1
title: Data-Driven Collective Variables for Enhanced Sampling

description: Designing an appropriate set of collective variables is crucial to the success of several enhanced sampling methods. Here we focus on how to obtain such variables from information limited to the metastable states. We characterize these states by a large set of descriptors and employ neural networks to compress this information in a lower-dimensional space, using Fisher's linear discriminant as an objective function to maximize the discriminative power of the network. We test this method on alanine dipeptide, using the non-linearly separable dataset composed by atomic distances. We then study an intermolecular aldol reaction characterized by a concerted mechanism. The resulting variables are able to promote sampling by drawing non-linear paths in the physical space connecting the fluctuations between metastable basins. Lastly, we interpret the behavior of the neural network by studying its relation to the physical variables. Through the identification of its most relevant features, we are able to gain chemical insight into the process.
DOI: 10.24435/materialscloud:2020.0019/v1
title: Data from Uniaxial Compression testing and validation scripts for Cauchy stress modeling to design anatomical silicone replicas

description: Anatomically realistic organ replicas or phantoms allow for accurate studies and reproducible research. To recreate a human kidney, mimicry of the viscoelastic properties of the human kidney is crucial. However, none of the related work addressed the design and development of a kidney phantom using only silicone as material. In contrast to paraffin and hydrogel, silicone is an ideal variant for its extended shelf life, soft-tissue-like feeling, and viscoelastic modularity. To this end, we conducted uniaxial compression testing and Cauchy stress modeling. Results indicate that none of the available manufacturer silicone brands are suitable for the task of creating a realistic kidney phantom. Indeed, the tested silicone mixtures in low and high strain do not fall within the required approximate target compressive moduli of 20 kPa and 500 kPa, respectively. This work provides a frame of reference for future work by avoiding the pitfalls of the selected ready-made silicones and reusing the reported theoretical and experimental setup to design a realistic replica of the kidney organ.
DOI: 10.24435/materialscloud:8n-tk
title: Data-Driven Collective Variables for Enhanced Sampling

description: Designing an appropriate set of collective variables is crucial to the success of several enhanced sampling methods. Here we focus on how to obtain such variables from information limited to the metastable states. We characterize these states by a large set of descriptors and employ neural networks to compress this information in a lower-dimensional space, using Fisher's linear discriminant as an objective function to maximize the discriminative power of the network. We test this method on alanine dipeptide, using the non-linearly separable dataset composed by atomic distances. We then study an intermolecular aldol reaction characterized by a concerted mechanism. The resulting variables are able to promote sampling by drawing non-linear paths in the physical space connecting the fluctuations between metastable basins. Lastly, we interpret the behavior of the neural network by studying its relation to the physical variables. Through the identification of its most relevant features, we are able to gain chemical insight into the process.
DOI: 10.24435/materialscloud:2020.0043/v1
title: Crystal field, ligand field, and interorbital effects in two-dimensional transition metal dichalcogenides across the periodic table

description: Two-dimensional (2D) transition metal dichalcogenides (TMDs) exist in two polymorphs, referred to as 1T and 1H, depending on the coordination sphere of the transition metal atom. The broken octahedral and trigonal prismatic symmetries lead to different crystal and ligand field splittings of the d electron states, resulting in distinct electronic properties. In this work, we quantify the crystal and ligand field parameters of 2D TMDs using a Wannier-function approach. We adopt the methodology proposed by Scaramucci et al (2015 J. Phys.: Condens. Matter 27 175503) that allows to separate various contributions to the ligand field by choosing different manifolds in the construction of the Wannier functions. We discuss the relevance of the crystal and ligand fields in determining the relative stability of the two polymorphs as a function of the filling of the d-shell. Based on the calculated parameters, we conclude that the ligand field, while leading to a small stabilizing factor for the 1H polymorph in the d1 and d2 TMDs, plays mostly an indirect role and that hybridization between different d orbitals is the dominant feature. We investigate trends across the periodic table and interpret the variations of the calculated crystal and ligand fields in terms of the change of charge-transfer energy, which allows developing simple chemical intuition
DOI: 10.24435/materialscloud:2020.0048/v1
title: Molecular Recognition and Specificity of Biomolecules to Titanium Dioxide from MD Simulations

description: Titania (TiO2) is used extensively in biomedical applications; efforts to boost the biocompatibility of TiO2 include coating it with the titania binding hexamer, RKLPDA. To understand the binding mechanism of this peptide, we employ molecular dynamics simulations enhanced by metadynamics to study three amino acids present in the peptide – arginine (R), lysine (K), and aspartate (D), on four TiO2 variants that have different degrees of surface hydroxyl groups. We find that binding is a function of both sidechain charge and structure, with R binding to all four surfaces, whereas the affinity of K and D is dependent on the distribution of hydroxyl groups. Informed by this, we study the binding of the titania binding hexamer and 12mer (RKLPDAPGMHTW) on two of the four surfaces, and we see strong correlations between the binding free energy and the primary binding residues, in agreement with prior experiments and simulations. We propose that the discrepancies observed in prior work stem from distribution of surface hydroxyl groups that may be difficult to precisely control on the TiO2 interface.
DOI: 10.24435/materialscloud:61-hh
title: Crystal field, ligand field, and interorbital effects in two-dimensional transition metal dichalcogenides across the periodic table

description: Two-dimensional (2D) transition metal dichalcogenides (TMDs) exist in two polymorphs, referred to as 1T and 1H, depending on the coordination sphere of the transition metal atom. The broken octahedral and trigonal prismatic symmetries lead to different crystal and ligand field splittings of the d electron states, resulting in distinct electronic properties. In this work, we quantify the crystal and ligand field parameters of 2D TMDs using a Wannier-function approach. We adopt the methodology proposed by Scaramucci et al (2015 J. Phys.: Condens. Matter 27 175503) that allows to separate various contributions to the ligand field by choosing different manifolds in the construction of the Wannier functions. We discuss the relevance of the crystal and ligand fields in determining the relative stability of the two polymorphs as a function of the filling of the d-shell. Based on the calculated parameters, we conclude that the ligand field, while leading to a small stabilizing factor for the 1H polymorph in the d1 and d2 TMDs, plays mostly an indirect role and that hybridization between different d orbitals is the dominant feature. We investigate trends across the periodic table and interpret the variations of the calculated crystal and ligand fields in terms of the change of charge-transfer energy, which allows developing simple chemical intuition
DOI: 10.24435/materialscloud:1x-d3
title: Molecular Recognition and Specificity of Biomolecules to Titanium Dioxide from MD Simulations

description: Titania (TiO2) is used extensively in biomedical applications; efforts to boost the biocompatibility of TiO2 include coating it with the titania binding hexamer, RKLPDA. To understand the binding mechanism of this peptide, we employ molecular dynamics simulations enhanced by metadynamics to study three amino acids present in the peptide – arginine (R), lysine (K), and aspartate (D), on four TiO2 variants that have different degrees of surface hydroxyl groups. We find that binding is a function of both sidechain charge and structure, with R binding to all four surfaces, whereas the affinity of K and D is dependent on the distribution of hydroxyl groups. Informed by this, we study the binding of the titania binding hexamer and 12mer (RKLPDAPGMHTW) on two of the four surfaces, and we see strong correlations between the binding free energy and the primary binding residues, in agreement with prior experiments and simulations. We propose that the discrepancies observed in prior work stem from distribution of surface hydroxyl groups that may be difficult to precisely control on the TiO2 interface.
DOI: 10.24435/materialscloud:2020.0019/v2
title: Data from Uniaxial Compression testing and validation scripts for Cauchy stress modeling to design anatomical silicone replicas

description: Anatomically realistic organ replicas or phantoms allow for accurate studies and reproducible research. To recreate a human kidney, mimicry of the viscoelastic properties of the human kidney is crucial. However, none of the related work addressed the design and development of a kidney phantom using only silicone as material. In contrast to paraffin and hydrogel, silicone is an ideal variant for its extended shelf life, soft-tissue-like feeling, and viscoelastic modularity. To this end, we conducted uniaxial compression testing and Cauchy stress modeling. Results indicate that none of the available manufacturer silicone brands are suitable for the task of creating a realistic kidney phantom. Indeed, the tested silicone mixtures in low and high strain do not fall within the required approximate target compressive moduli of 20 kPa and 500 kPa, respectively. This work provides a frame of reference for future work by avoiding the pitfalls of the selected ready-made silicones and reusing the reported theoretical and experimental setup to design a realistic replica of the kidney organ.
DOI: 10.24435/materialscloud:xt-yz
title: Data from Uniaxial Compression testing and validation scripts for Cauchy stress modeling to design anatomical silicone replicas

description: Anatomically realistic organ replicas or phantoms allow for accurate studies and reproducible research. To recreate a human kidney, mimicry of the viscoelastic properties of the human kidney is crucial. However, none of the related work addressed the design and development of a kidney phantom using only silicone as material. In contrast to paraffin and hydrogel, silicone is an ideal variant for its extended shelf life, soft-tissue-like feeling, and viscoelastic modularity. To this end, we conducted uniaxial compression testing and Cauchy stress modeling. Results indicate that none of the available manufacturer silicone brands are suitable for the task of creating a realistic kidney phantom. Indeed, the tested silicone mixtures in low and high strain do not fall within the required approximate target compressive moduli of 20 kPa and 500 kPa, respectively. This work provides a frame of reference for future work by avoiding the pitfalls of the selected ready-made silicones and reusing the reported theoretical and experimental setup to design a realistic replica of the kidney organ.
DOI: 10.24435/materialscloud:1r-cb
title: The JuDiT database of impurities embedded into a topological insulator

description: We present JuDiT (Jülich Database of impurities embedded into a Topological insulator) which collects first principles calculation of impurities embedded into the prototypical topological insulator Sb2Te3. The density functional calculations of this work were performed with the JuKKR package [1], which allows to embed translational invariance breaking impurities into a crystalline host system based on the Korringa-Kohn-Rostoker Green function method, and were performed with the AiiDA-KKR package [2]. Our database collects, among others, predicted impurity properties like charge doping introduced by the defects, magnetic moments of the impurities and impurity density of states calculations. We include calculations for the intrinsic Fermi level in the middle of the bulk band gap as well as for shifted Fermi level into valence and conduction band which models different experimental conditions. The impurities were embedded into different layers throughout a 6 quintuple layer thick film which allows to investigate the effect of the topological surface state (localized at the surface) on impurity properties. The JuDiT database allows to uncover chemical trends in impurity properties and can help optimizing the next generation of topological materials.

[1] https://jukkr.fz-juelich.de and www.judft.de
[2] https://github.com/JuDFTteam/aiida-kkr