AndreaBozzo/ceres-open-data-index huggingface dataset:
Atomistic simulations of the crystallization of amorphous GeTe nanoparticles

The effect of dimensionality reduction on the crystallization kinetics of phase change materials is of relevance for the operation of ultrascaled memory devices. Therefore, the crystallization of amorphous nanoparticles (NPs) of the prototypical phase change compounds, GeTe and Ge₂Sb₂Te₅, has been addressed by several experimental works in recent years. In this work, we performed molecular dynamics simulations of the crystallization process of amorphous GeTe NPs with diameter in the range 3-6 nm (512-4096 atoms) by exploiting a machine-learned interatomic potential. We saw a few crystal nucleation events in the larger NPs but no crystallization in the smallest NP, 3 nm in diameter, in simulations lasting up to 80 ns in the temperature range 500-750 K. The analysis of the crystallization kinetics suggests that the nucleation rate per volume decreases with the NP size to an extent that prevents us from seeing crystallization in the smallest NP on our simulation time scale. This result is consistent with the large raise in crystallization temperature observed experimentally for NPs with diameters shorter than 3.5 nm.

Tags: crystallization, gete, molecular-dynamics-simulation, neural-network-potential, neuromophic-computing, phase-change-materials
Quantum simulations of radiation damage in a molecular polyethylene analog

An atomic-level understanding of radiation-induced damage in simple polymers like polyethylene is essential for determining how these chemical changes can alter the physical and mechanical properties of important technological materials such as plastics. We performed ensembles of quantum simulations of radiation damage in a polyethylene analog using the Density Functional Tight Binding method to help bind its radiolysis and subsequent degradation as a function of radiation dose. Chemical degradation products are categorized with a graph theory approach, and we compute occurrence rates of unsaturated carbon bond formation, crosslinking, cycle formation, chain scission reactions, and out-gassing products. Statistical correlations between product pairs show significant correlations between chain scission reactions, unsaturated carbon bond formation, and out-gassing products, though these correlations decrease with increasing atom recoil energy. Our results present relatively simple chemical descriptors as possible indications of network rearrangements in the middle range of excitation energies. The data set contains how DFTB+ simulations were setup and running isomorphic analysis and graphs to obtain chemical structures.

Tags: dftb, graph-theory, isomorphic-analysis, molecular-dynamics-simulation
A prediction rigidity formalism for low-cost uncertainties in trained neural networks

Quantifying the uncertainty of regression models is essential to ensure their reliability, particularly since their application often extends beyond their training domain. Based on the solution of a constrained optimization problem, this work proposes 'prediction rigidities' as a formalism to obtain uncertainties of arbitrary pre-trained regressors. A clear connection between the suggested framework and Bayesian inference is established, and a last-layer approximation is developed and rigorously justified to enable the application of the method to neural networks. This extension affords cheap uncertainties without any modification to the neural network itself or its training procedure. The effectiveness of this approach is shown for a wide range of regression tasks, ranging from simple toy models to applications in chemistry and meteorology.
This record includes computational experiments supporting the MLST paper titled "A prediction rigidity formalism for low-cost uncertainties in trained neural networks".

Tags: confidence-interval, laplace-approximation, machine-learning, marvelp2, neural-networks, neural-tangent-kernel, prediction-rigidity, regressors, uncertainty-quantification
Magnons from time-dependent density-functional perturbation theory and nonempirical Hubbard functionals

Spin excitations play a fundamental role in understanding magnetic properties of materials, and have significant technological implications for magnonic devices. However, accurately modeling these in transition-metal and rare-earth compounds remains a formidable challenge. Here, we present a fully first-principles approach for calculating spin-wave spectra based on time-dependent (TD) density-functional perturbation theory (DFPT), using nonempirical Hubbard functionals. This approach is implemented in a general noncollinear formulation, enabling the study of magnons in both collinear and noncollinear magnetic systems. Unlike methods that rely on empirical Hubbard U parameters to describe the ground state, and Heisenberg Hamiltonians for describing magnetic excitations, the methodology developed here probes directly the dynamical spin susceptibility (efficiently evaluated with TDDFPT throught the Liouville-Lanczos approach), and treats the linear variation of the Hubbard augmentation (in itself calculated non-empirically) in full at a self-consistent level. Furthermore, the method satisfies the Goldstone condition without requiring empirical rescaling of the exchange-correlation kernel or explicit enforcement of sum rules, in contrast to existing state-of-the-art techniques. We benchmark the novel computational scheme on prototypical transition-metal monoxides NiO and MnO, showing remarkable agreement with experiments and highlighting the fundamental role of these newly implemented Hubbard corrections. The method holds great promise for describing collective spin excitations in complex materials containing localized electronic states.

Tags: first-principles, hubbard-functionals, magnetism, marvel
Simulated 3d transition metal oxides cation K-edge XANES dataset

X-ray absorption spectroscopy (XAS) is a powerful characterization technique for probing the local chemical environment of absorbing atoms. However, analyzing XAS data presents with significant challenges, often requiring extensive, computationally intensive simulations, as well as significant domain expertise. These limitations hinder the development of fast, robust XAS analysis pipelines that are essential in high-throughput studies and for autonomous experimentation. We address these challenges with a suite of transfer learning approaches for XAS prediction, each uniquely contributing to improved accuracy and efficiency, as demonstrated on simulated K-edge X-ray absorption near-edge structure (XANES) spectra database covering eight 3d transition metals (Ti-Cu). This database contains FEFF and VASP K-edge XANES spectra of 3d transition metal-containing oxide materials used to develop the above machine learning models. The materials structures are sourced from the Materials Project, corresponding to primary, secondary, ternary and quaternary oxide materials. Specifically, FEFF9 was used to compute the spectra of Ti, V, Cr, Mn, Fe, Co, Ni and Cu compounds; VASP 6.2.1 was used to compute the spectra of Ti and Cu compounds.

Tags: materials, vasp, x-ray-absorption-spectroscopy
Paramagnetic half-moon shaped diffuse scattering arising from 3D magnetic frustration

We use spin dynamics simulations to determine the origin of the unusual correlated diffuse scattering, characterised by half-moon shapes bridging the magnetic Bragg peaks, observed in the polarised elastic neutron scattering from manganese tungstate, MnWO₄. We first fit a Heisenberg Hamiltonian with twelve nearest-neighbour exchange interactions and single-ion anisotropy to the experimental ground-state magnon dispersion. We then show via spin dynamics simulations that our model Hamiltonian both reproduces the experimentally observed half-moon features and captures their persistence into the paramagnetic regime. Moreover, we identify the three-dimensional, competing antiferromagnetic interactions driving this behavior. Our work complements earlier studies of half-moon-shaped signatures in pyrochlore and triangular structures, by providing insight into their origin in a zigzag chain geometry with three-dimensional competing exchange interactions.

Tags: diffuse-scattering, erc, horizon-europe, spin-dynamics, uppasd
Homogeneous nucleation of undercooled Al-Ni melts via a machine-learned interaction potential

Homogeneous nucleation processes are important for understanding solidification and the resulting microstructure of materials. Simulating this process requires accurately describing the interactions between atoms,  hich is further complicated by chemical order through cross-species interactions. The large scales needed to observe rare nucleation events are far beyond the capabilities of ab initio simulations. Machine-learning is used for overcoming these limitations in terms of both accuracy and speed, by building a high-dimensional neural network potential for binary Al-Ni alloys, which serve as a model system relevant to many industrial applications. The potential is validated against experimental diffusion, viscosity, and scattering data, and is applied to large-scale molecular dynamics simulations of homogeneous nucleation at equiatomic composition, as well as for pure Ni. Pure Ni nucleates in a single-step into an fcc crystal phase, in contrast to previous results obtained with a classical empirical potential. This highlights the sensitivity of nucleation pathways to the underlying atomic interactions. Our findings suggest that the nucleation pathway for AlNi proceeds in a single step toward a B2 structure, which is discussed in relation to the pure elements counterparts.

Tags: aluminium, interaction-potential, machine-learning, nickel
Tight-binding calculation files of modulated Dirac bands and integer hopping ratios in a honeycomb lattice of phenalenyl-tessellation molecules

The dataset uploaded here records atomic positions, lattices vectors and Python scripts for tight-binding calculations related to the paper entitled "Modulated Dirac bands and integer hopping ratios in a honeycomb lattice of phenalenyl-tessellation molecules." In a family of nanographene called phenalenyl-tessellation molecules (PTMs), two types of zero modes appear: one is uniformly extended over the entire molecule and the other is localized around vacancies. Therefore, it is expected that energy bands reflecting the properties of these two types of zero modes will appear in a honeycomb PTM (H-PTM). In this study, we show that modulated energy gap and the Fermi velocity of Dirac bands appear in H-PTMs and that the effective two-site model has positive integer hopping ratios based on the uniformly extended zero mode and  the number of connections between PTMs. Furthermore, we find that the localized zero modes around vacancies can coexist with the modulated Dirac bands. The tight-binding calculations confirm that modulated Dirac bands with integer hopping ratios and coexisting localized zero modes that are consistent with analytical solutions for H-PTMs.

Tags: band-gap, flat-bands, graphene, honeycomb-lattice, tight-binding-model
Influence of carrier-carrier interactions on the sub-threshold swing of band-to-band tunnelling transistors

Band-to-band tunnelling field-effect transistors (TFETs) have long been considered as promising candidates for future low-power logic applications. However, fabricated TFETs rarely reach sub-60 mV/dec sub-threshold swings (SS) at room temperature. Previous theoretical studies identified Auger processes as possible mechanisms for the observed degradation of SS. Through first-principles quantum transport simulations incorporating carrier-carrier interactions within the Non-equilibrium Green's Function formalism through self-consistent GW approximation, we confirm here that Auger processes are indeed at least partly responsible for the poor performance of TFETs. Using a carbon nanotube TFET as testbed, we show that carrier-carrier scattering alone significantly increases the OFF-state current of these devices, thus worsening their sub-threshold behavior. The results are in the folder uploaded.

Tags: electronic-structure, transport, wannier-functions
Teaching oxidation states to neural networks

The accurate description of redox reactions remains a challenge for first-principles calculations, but it has been shown that extended Hubbard functionals (DFT+U+V) can provide a reliable approach, mitigating self-interaction errors, in materials with strongly localized d or f electrons. Here, we first show that DFT+U+V molecular dynamics is capable to follow the adiabatic evolution of oxidation states over time, using representative Li-ion cathode materials.  In turn, this allows to develop redox-aware machine-learned potentials. We show that considering atoms with different oxidation states (as accurately predicted by DFT+U+V) as distinct species in the training leads to potentials that are able to identify the correct ground state and pattern of oxidation states for redox elements present. This is achieved, e.g., trough a combinatorial search for the lowest energy configuration. This brings the advantages of machine-learned potential to key technological applications (e.g., rechargeable batteries), which require an accurate description of the evolution of redox states.

Tags: dftuv, machine-learning, max, oxidation-states
Dataset of self-consistent Hubbard parameters for Ni, Mn and Fe from linear-response

Density-functional theory with extended Hubbard functionals (DFT+U+V) provides a robust framework to accurately describe complex materials containing transition-metal or rare-earth elements. It does so by mitigating self-interaction errors inherent to semi-local functionals which are particularly pronounced in systems with partially-filled d and f electronic states. However, achieving accuracy in this approach hinges upon the accurate determination of the on-site U and inter-site V Hubbard parameters. In practice, these are obtained either by semi-empirical tuning, requiring prior knowledge, or, more correctly, by using predictive but expensive first-principles calculations.  This archive entry contains Hubbard parameters, occupation matrices and other data calculated for 28 materials and covers all steps in a self-consistent procedure where, at each step new Hubbard parameters are obtained via linear-response, a process that is repeated until the parameters no longer change. The primary purpose of this dataset is to support the development and validation of machine learning models that can be used to predict Hubbard parameters, sidestepping the need for expensive ab-initio density functional perturbation theory calculations.

Tags: density-functional-theory, hubbard-corrections, machine-learning, marvel
Exploring strong electronic correlations in the breathing kagome metal Fe₃Sn

Kagome metals have emerged as pivotal materials in condensed matter physics due to their unique geometric arrangement and intriguing electronic properties. Understanding the origin of magnetism in these materials, particularly in iron rich Fe-Sn binary compounds like Fe₃Sn, holds a significant importance, as they represent potential candidates for permanent magnets with a high Curie temperature and a strong magnetic anisotropy. In the present study, we employ density-functional theory and dynamical mean-field theory to analyze the electronic structure and magnetic properties of Fe₃Sn. Our investigation reveals the presence of several nearly-flat bands and Weyl nodes at low excitation energies. The inclusion of local correlation effects is shown to push these features even closer to the Fermi energy, which may be important for their manipulation via external stimuli. Regarding magnetism, the Hubbard-like interaction leads to an increase of orbital polarization at the expenses of a minor reduction of the spin moment. The magnetic anisotropy energy exhibits a strong dependence on the particular choice of the Coulomb interaction parameters. Additionally, our detailed analysis of the interatomic exchange interactions indicates a significant contribution from the antisymmetric exchange, i.e. the Dzyaloshinskii-Moriya interaction, which showcases the existence of magnetic chirality in the system. Overall, our investigation highlights a strong interplay between the flat bands near the Fermi level, the local Coulomb interaction and the triangular geometry of the lattice, which plays a crucial role in driving the magnetic properties of this material.

Tags: dftdmft, dzyaloshinskii-moriya-interaction-dmi, electronic-structure, flat-band, kagome-metal, magnetism
Electric field tunable bandgap in twisted double trilayer graphene

Twisted van der Waals heterostructures have recently emerged as a versatile platform for engineering interaction-driven, topological phenomena with a high degree of control and tunability. Since the initial discovery of correlated phases in twisted bilayer graphene, a wide range of moiré materials have emerged with fascinating electronic properties. While the field of twistronics has rapidly evolved and now includes a range of multi-layered systems, moiré systems comprised of double trilayer graphene remain elusive. Here, we report electrical transport measurements combined with tight-binding calculations in twisted double trilayer graphene (TDTLG). We demonstrate that small-angle TDTLG (~1.7−2.0ᵒ) exhibits an intrinsic bandgap at the charge neutrality point. Moreover, by tuning the displacement field, we observe a continuous insulator-semimetal-insulator transition at the CNP, which is also captured by tight-binding calculations. These results establish TDTLG systems as a highly tunable platform for further exploration of magneto-transport and optoelectronic properties.

Tags: 2d-materials, experimental, marvel, tight-binding, twisted-multilayer-graphene, wanniertools
Prediction of a novel type-I antiferromagnetic Weyl semimetal

Topological materials have been a main focus of studies in the past decade due to their protected properties that can be exploited for the fabrication of new devices. Among them, Weyl semimetals are a class of topological semimetals with non-trivial linear band crossing close to the Fermi level. The existence of such crossings requires the breaking of either time-reversal or inversion symmetry and is responsible for the exotic physical properties. In this work we identify the full-Heusler compound InMnTi₂, as a promising, easy to synthesize, T- and I-breaking Weyl semimetal. This material exhibits several features that are comparatively more intriguing with respect to other known Weyl semimetals: the distance between two neighboring nodes is large enough to observe a wide range of linear dispersions in the bands, and only one kind of such node's pairs is present in the Brillouin zone. We also show the presence of Fermi arcs stable across a wide range of chemical potentials. Finally, the lack of contributions from trivial points to the low-energy properties makes the materials a promising candidate for practical devices.

Tags: marvelp3, surface-properties, topological-materials, weyl-semimetal
Disorder-resilient transition of Helical to Conical ground states in M1/3NbS2, M=Cr,Mn

The discovery of chiral helical magnetism (CHM) in Cr1/3NbS2 and the stabilization of a chiral soliton lattice (CSL) has attracted considerable interest in view of their potential technological applications. However, there is an ongoing debate regarding whether the sister compound, Mn1/3NbS2, which shares the same crystal structure, exhibits similar nontrivial properties, which rely on the stabilization of the lack of inversion symmetry at the magnetic ion. In this study, we conduct a comprehensive investigation of the magnetically ordered states of both compounds, using 53Cr, 55Mn and 93Nb nuclear magnetic resonance.  Our results, supported by density functional  calculations, detect in a high quality single crystal of Cr1/3NbS2 all the signatures of the monoaxial CHM in  a magnetic field, identifying it as a textbook NMR case. The detailed understanding of this prototypic  behavior provides a reference for Mn1/3NbS2.
Despite the much larger density of specific defects in this second single crystal, we confirm the presence of a CHM phase in the Mn compound, characterized by a very large critical field for the forced ferromagnetic phase (~ 10 T for H || c).

Tags: chiral-helical-magnetism, chiral-soliton-lattice, dft, nuclear-magnetic-resonance
Spin excitations in nanographene-based antiferromagnetic spin-½  Heisenberg chains

Antiferromagnetic Heisenberg chains exhibit two distinct types of excitation spectra: gapped for integer-spin chains and gapless for half-integer-spin chains. However, in finite-length half-integer-spin chains, quantization induces a gap, requiring precise control over sufficiently long chains to study its evolution. In a recent publication, we created length-controlled spin-1/2 Heisenberg chains by covalently linking olympicenes—Olympic ring-shaped magnetic nanographenes. With large exchange interactions, tunable lengths, and negligible magnetic anisotropy, this system is ideal for investigating length-dependent spin excitations, probed via inelastic electron tunneling spectroscopy. We observe a power-law decay of the lowest excitation energy with length L, following a 1/L dependence in the large-L regime, consistent with theory. For L=50, a V-shaped excitation continuum confirms gapless behavior in the thermodynamic limit. Additionally, low-bias current maps reveal the standing wave of a single spinon in odd-numbered chains. Our findings provide evidence for the realization of a one-dimensional analog of a gapless spin liquid within an artificial graphene lattice. This record includes all the data that support the results discussed in the publication.

Tags: cscs, dft, fractional-excitation, marvelp4, spin-excitation, spin-liquid, spinon
Delta project — archive of old website

The widespread popularity of density functional theory has given rise to an extensive range of dedicated codes for predicting molecular and crystalline properties. However, each code implements the formalism in a different way, raising questions about the reproducibility of such predictions. In K. Lejaeghere et al., Science 351 (6280), aad3000 (2016) (https://doi.org/10.1126/science.aad3000), we reported the results of a community-wide effort that compared 15 solid-state codes, using 40 different potentials or basis set types, to assess the quality of the Perdew-Burke-Ernzerhof equations of state for 71 elemental crystals. We conclude that predictions from recent codes and pseudopotentials agree very well, with pairwise differences that are comparable to those between different high-precision experiments. Older methods, however, have less precise agreement. Our benchmark provides a framework for users and developers to document the precision of new applications and methodological improvements. The underlying data of this paper were accessible during 2016-2023 at https://molmod.ugent.be/deltacodesdft. Several additions that made use of the same protocol were added later. As this website is obsolete and to ensure long-term continued access, these data are stored now under the present record of the Materials Cloud Archive.

Tags: delta-project, dft-benchmarking, precision, unary-crystals, verification