AndreaBozzo/ceres-open-data-index huggingface dataset:
Density functional perturbation theory for one-dimensional systems: implementation and relevance for phonons and electron-phonon interactions

The electronic and vibrational properties and electron-phonon couplings of one-dimensional materials will be key to many prospective applications in nanotechnology. Dimensionality strongly affects these properties and has to be correctly accounted for in first-principles calculations. Here we develop and implement a formulation of density-functional and density-functional perturbation theory that is tailored for one-dimensional systems. A key ingredient is the inclusion of a Coulomb cutoff, a reciprocal-space technique designed to correct for the spurious interactions between periodic images in periodic-boundary conditions. This restores the proper one-dimensional open-boundary conditions, letting the true response of the isolated one-dimensional system emerge. In addition to total energies, forces and stress tensors, phonons and electron-phonon interactions are also properly accounted for. We demonstrate the relevance of the present method on a portfolio of realistic systems: BN atomic chains, BN armchair nanotubes, and GaAs nanowires. Notably, we highlight the critical role of the Coulomb cutoff by studying previously inaccessible polar-optical phonons and Fröhlich electron-phonon couplings. We also develop and apply analytical models to support the physical insights derived from the calculations and we discuss their consequences on electronic lifetimes. The present work unlocks the possibility to accurately simulate the linear response properties of one-dimensional systems, sheds light on the transition between dimensionalities and paves the way for further studies in several fields, including charge transport, optical coupling and polaritronics.

Tags: ab-initio, charge-transport, density-functional-theory, electron-phonon-coupling, marvel, one-dimensional-materials, phonons
Hydrogen-induced insulating state accompanied by inter-layer charge ordering in SmNiO₃

The effect of hydrogen doping on the crystal structure and the electronic state in SmNiO₃ is investigated by means of density-functional theory with a combinatorial structure-generation approach. While 100% of hydrogen doping per Ni atom has been supposed to be responsible for the experimentally observed insulating phase, we found that 50% of hydrogen doping results in an outstandingly stable atomic structure showing the insulating property. The stable crystal structure shows the peculiar layered pattern of charge disproportionation of Ni²⁺ and Ni³⁺ valences together with the strong Jahn-Teller distortion that causes the eg orbital state splitting and opens the band gap.

Tags: dft, hydrogen-doping, smnio3
High-throughput screening of nano-hybrid metal–organic-frameworks for photocatalytic CO₂ reduction

Photocatalytic conversion of CO₂ into fuel feed stocks is a promising method for sustainable fuel production. A highly attractive class of materials, inorganic-core@metal–organic-framework heterogeneous catalysts, boasts a significant increase in catalytic performance when compared to the individual materials. However, due to the ever-expanding chemical space of inorganic-core catalysts and metal–organic frameworks (MOFs), identification of these optimal heterojunctions is difficult without appropriate computational screening. In this work, a novel high-throughput screening method of nano-hybrid photocatalysts is presented by screening 65'784 inorganic-core materials and 20'375 MOF-shells for their ability to reduce CO₂ based on their synthesizability, aqueous stability, visible light absorption, and electronic structure; the passing materials were then paired based on their electronic structure to create novel heterojunctions. The results showed 58 suitable inorganic-core materials and 204 suitable MOFs ranging from never-beforesynthesized catalysts to catalysts that have been overlooked for their photocatalytic ability. These materials lay a new foundation of photocatalysts that have passed theoretical requirements and can significantly increase the rate of catalyst discovery.

Tags: coreshell, metal-organic-frameworks, photocatalyst
Rare-earth atoms on Nb(110) as a platform to engineer topological superconductivity

Our study reveals how Gd adatoms and dimers on a superconducting Nb(110) surface induce Yu-Shiba-Rusinov (YSR) states, offering valuable insights into magnetic interactions of rare-earth atoms on superconducting surfaces. By engineering Gd dimers along the [1-10] and [001] directions, we uncover an indirect coupling between the Gd magnetic moments and the Nb substrate via their valence d electrons, leading to significant alterations in the YSR spectrum around the dimers. We further demonstrate the possibility for Néel-type spin-spiral ground states in chains of Gd atoms on Nb(110). These findings highlight the potential of 4f elements like Gd as a promising platform for controlling a spin-spiral ground state, a crucial prerequisite for realizing a topological superconductor that can host Majorana zero modes. The combination of theoretical modeling based on density functional theory, atomistic spin-dynamics simulations and experimental techniques, including scanning tunneling microscopy and spectroscopy, provides a comprehensive understanding of the coupling mechanisms and their impact on the electronic properties of these systems and establishes rare-earth magnets on Nb as a promising platform in the field.

This dataset collects the experimental and theoretical results of this work.

Tags: adatoms, dftu, magnetism, majorana-zero-mode, rare-earth, spin-dynamics, spin-spiral, stm, superconductivity, topological-materials, topological-superconductor
First-principles diagrammatic Monte Carlo for electron-phonon interactions and polarons

Summing all Feynman diagrams with quantitative accuracy is a holy grail in theoretical physics. In condensed matter, the lattice vibration (phonon) field couples with the electrons, leading to the formation of entangled electron-phonon (e-ph) states called polarons.  In the intermediate- and strong-coupling regimes common to many conventional and quantum materials, a many-body treatment of polarons requires adding up a large number of e-ph diagrams. Diagrammatic Monte Carlo (DMC) is an efficient method for diagram summation and has been employed to study polarons within simplified \e-ph models (Holstein, Frohlich, etc.).  Here we show DMC calculations based on accurate first-principles e-ph interactions, enabling numerically exact results for ground-state and dynamical properties of polarons in real materials, including the polaron formation energy, effective mass, spectral weight, phonon cloud distribution, optical conductivity, and mobility. We demonstrate such DMC calculations in systems with polarons ranging from small (localized) to large (delocalized), including LiF, SrTiO3, and TiO2 rutile and anatase. This advance is enabled by our recently developed technique for compressing first-principles e-ph interaction matrices~\cite{SVD-paper}, together with a matrix-product formalism that mitigates the DMC sign problem from multiple electronic bands. Our work enables precise modeling of e-ph interactions and polarons in coupling regimes ranging from weak to strong, opening doors to studies of transport, linear response, and superconductivity in the strong e-ph coupling regime.

Tags: diagrammatic-monte-carlo, first-principles, lif, many-body-physics, polaron, strong-e-ph-interactions
Hamiltonian transformation for accurate and efficient band structure interpolation

Electronic band structures is a cornerstone of condensed matter physics and materials science. Conventional methods like Wannier interpolation (WI), which are commonly used to interpolate band structures onto dense k-point grids, often encounter difficulties with complex systems, such as those involving entangled bands or topological obstructions. In this work, we introduce the Hamiltonian transformation (HT) method, a novel framework that directly enhances interpolation accuracy by localizing the Hamiltonian. Using a pre-optimized transformation, HT produces a far more localized Hamiltonian than WI, achieving up to two orders of magnitude greater accuracy for entangled bands. Although HT utilizes a slightly larger, nonlocal numerical basis set, its construction is rapid and requires no optimization, resulting in significant computational speedups. These features make HT a more precise, efficient, and robust alternative to WI for band structure interpolation, as further verified by high-throughput calculations.

Tags: band-structure-interpolation, hamiltonian-transformation, localized-hamiltonian
Dataset for vibrational recognition of local structures in hydrogen boride sheets

We present a comprehensive vibrational analysis of hydrogen boride sheet through first-principles calculations, focusing on a variety of local structural configurations including surfaces, edges, and bilayer models - some of which contains vacancy and substitutional defects. A database of vibrational modes and simulated infrared spectra was constructed, revealing distinct spectral features that serve as characteristic fingerprints for different bonding environments. By analyzing mode distributions with respect to coordination environments, we identify the distinct contributions of terminal and bridging hydrogen atoms to specific spectral regions. The results show that structural modifications, such as interlayer stacking and edge termination, have a significant influence on vibrational characteristics, particularly in the intermediate and high frequency regions. The vibrational database enables the precise interpretation of infrared spectra and offers a reliable reference for model selection and peak analysis in both experimental and theoretical studies on hydrogen boride sheet and related materials. This archive contains the database compiled from this study, comprising (i) optimized structure files, (ii) energy and force datasets used to construct the Hessian matrix and (iii) the results from the vibrational analytics, such as simulated IR spectra and mode visualizations. The database was designed for maximum accessibility; consequently, all data are supplied in multiple standard formats.

Tags: density-functional-theory, hydrogen-boride-sheets, spectroscopy, two-dimensional
High-throughput magnetic co-doping and design of exchange interactions in topological insulators

Using high-throughput automation of ab-initio impurity-embedding simulations we created a database of 3d and 4d transition metal defects embedded into the prototypical topological insulators (TIs) Bi₂Te₃ and Bi₂Se₃. We simulate both single impurities as well as impurity dimers at different impurity-impurity distances inside the topological insulator matrix. We extract changes to magnetic moments, analyze the polarizability of non-magnetic impurity atoms via nearby magnetic impurity atoms and calculate the exchange coupling constants for a Heisenberg Hamiltonian. 
We uncover chemical trends in the exchange coupling constants and discuss the impurities' potential with respect to magnetic order in the fields of quantum anomalous Hall insulators. In particular, we predict that co-doping of different magnetic dopants is a viable strategy to engineer the magnetic ground state in magnetic TIs.

Tags: co-doping, dft, jukkr, magnetic-doping, quantum-anomalous-hall, topological-insulator, topological-materials
2D pentagonal-graphene and pentagonal-silicene sheets engineered for the detection of DNA nucleobases for genetic biomarker: A DFT study

The deposited structure models of DNA adsorbed on prisitne PG/p-Si and metal (Au/W) doped PG/p-Si sheets, have been subjected to first principles calculations  based on DFT (PBE+vdW). The calculated binding affinity on PG and p-Si surface by M062X/6-31G* level of theory and adsorption energies by DFT predicts that PG has higher sensitivity towards DNA nucleic bases compared to p-Si with evident changes in their band structure properties.

Tags: 2d-materials, dft, electronic-structure
Mechanism of charge transport in lithium thiophosphate

Lithium ortho-thiophosphate (Li₃PS₄) has emerged as a promising candidate for solid-state-electrolyte batteries, thanks to its highly conductive phases, cheap components, and large electrochemical stability range. Nonetheless, the microscopic mechanisms of Li-ion transport in Li₃PS₄ are far to be fully understood, the role of PS₄ dynamics in charge transport still being controversial. We build machine learning potentials targeting state-of-the-art DFT references (PBEsol, r²SCAN, and PBE0) to tackle this problem in all known phases of Li₃PS₄ (α, β and γ), for large system sizes and timescales. We discuss the physical origin of the observed superionic behavior of Li₃PS₄: the activation of PS₄ flipping drives a structural transition to a highly conductive phase, characterized by an increase of Li-site availability and by a drastic reduction in the activation energy of Li-ion diffusion. We also rule out any paddle-wheel effects of PS₄ tetrahedra in the superionic phases–previously claimed to enhance Li-ion diffusion–due to the orders-of-magnitude difference between the rate of PS₄ flips and Li-ion hops at all temperatures below melting. 
This archive provides all the relevant data and input files that were used to fit the ML interatomic potentials used in this work, along with the relevant Density-Functional Theory calculations that were used for the training set construction, the validation of the ML models and the calculation of the electronic band structure of the β and γ structure. Furthermore, it provides input files of all the molecular dynamics trajectories needed to investigate Li-ion diffusion properties of Li₃PS₄ and the rotational dynamics of PS₄ tetrahedra. Finally, it provides the raw data to reproduce the figures of the manuscript associated with this archive.

Tags: electrical-conductivity, green-kubo-time-correlation-functions, lithium-ion-diffusion, lithium-thiophosphate, machine-learning, marvel, molecular-dynamics, phase-transitions, post-gga-density-functional-theory, ps4-rotational-dynamics, snsf-sinergia
SPAᴴM(a,b): encoding the density information from guess Hamiltonian in quantum machine learning representations

Recently, we introduced a class of molecular representations for kernel-based regression methods — the spectrum of approximated Hamiltonian matrices (SPAᴴM) — that takes advantage of lightweight one-electron Hamiltonians traditionally used as an SCF initial guess. The original SPAᴴM variant is built from occupied-orbital energies (\ie, eigenvalues) and naturally contains all the information about nuclear charges, atomic positions, and symmetry requirements. Its advantages were demonstrated on datasets featuring a wide variation of charge and spin, for which traditional structure-based representations commonly fail. SPAᴴM(a,b), as introduced here, expands eigenvalue SPAᴴM into local and transferable representations. It relies upon one-electron density matrices to build fingerprints from atomic or bond density overlap contributions inspired from preceding state-of-the-art representations. The performance and efficiency of SPAᴴM(a,b) is assessed on the predictions for datasets of prototypical organic molecules (QM7) of different charges and azoheteroarene dyes in an excited state. Overall, both SPAᴴM(a) and SPAᴴM(b) outperform state-of-the-art representations on difficult prediction tasks such as the atomic properties of charged open-shell species and of π-conjugated systems.

Tags: epfl, erc, guess-hamiltonians, machine-learning, marvelp2, molecular-representation, snsf, spahm
Effects of spin-orbit coupling and thermal expansion on the phonon-limited resistivity of Pb from first principles

Using density functional theory calculations with spin-orbit coupling (SOC), we report on the temperature-dependent thermodynamical properties of Pb: electrical resistivity, thermal expansion (TE), heat capacity, bulk modulus and its pressure derivative. For the former, we employed the state-of-the-art ab initio Boltzmann Transport Equation formalism, and we calculated the effect of TE. In accordance with previous work, we show that SOC improves the description of the phonon dispersion and the resistivity. We argue that this is caused by a joint mutual effect of an increase in the electronic nesting and an increase in the electron-phonon coupling. Interestingly, including TE incorporates non-linearity into the resistivity at high temperatures, whose magnitude depends on whether SOC is included or not. We suggest that mechanisms beyond the quasi-harmonic approximation should be considered to get a better description of Pb with SOC at high temperatures.

Tags: ab-initio, density-functional-theory, electron-phonon-coupling, electronic-structure, first-principles, phonons, quantum-espresso, transport
High-throughput magnetic co-doping and design of exchange interactions in a topological insulator

Using high-throughput automation of ab-initio impurity-embedding simulations we created a database of 3d and 4d transition metal defects embedded into the prototypical topological insulator (TI) Bi₂Te₃. We simulate both single impurities as well as impurity dimers at different impurity-impurity distances inside the topological insulator matrix. We extract changes to magnetic moments, analyze the polarizability of non-magnetic impurity atoms via nearby magnetic impurity atoms and calculate the exchange coupling constants for a Heisenberg Hamiltonian. 
We uncover chemical trends in the exchange coupling constants and discuss the impurities' potential with respect to magnetic order in the fields of quantum anomalous Hall insulators. In particular, we predict that co-doping of different magnetic dopants is a viable strategy to engineer the magnetic ground state in magnetic TIs.

Tags: co-doping, dft, jukkr, magnetic-doping, quantum-anomalous-hall, topological-insulator, topological-materials
Oxygen reduction reaction on single-atom catalysts from density functional theory calculations combined with an implicit solvation model

We present a density functional theory study of the oxygen reduction reaction (ORR) on a single atom catalyst embedded in graphene, namely, TM-N₄-C (TM = Fe and Co), using the effective screening medium method combined with the reference interaction site model (ESM-RISM). It was found that Fe-N₄-C and Co-N₄-C show comparable ORR activities from the constant electrode potential simulations, in contrast to the results obtained using the constant (neutral) charge simulation, in which the superior performance of Co-N₄-C has been predicted. The constant potential method allows the variable charge and thus, resulting in a potential dependence of the reaction free energies different from that with the constant charge method in which the potential dependence is included as an ad hoc manner. We suggest the importance of the variable charge in the simulation of the electrochemical reaction, which is enabled by ESM-RISM.

Tags: density-functional-theory, implicit-solvation-model, oxygen-reduction-reaction, single-atom-catalyst
High-throughput computation of Raman spectra from first principles

Raman spectroscopy is a widely-used non-destructive material characterization method, which provides information about the vibrational modes of the material and therefore of its atomic structure and chemical composition. Raman spectra can be simulated using atomistic first-principles methods but these are computationally demanding and thus the existing databases of computational Raman spectra are fairly small. We developed an optimized workflow to efficiently calculate the Raman tensors, from which the Raman spectra can be straightforwardly simulated. The workflow was benchmarked and validated by comparison to experiments and previous computational methods for select technologically relevant material systems. Using the workflow, we performed high-throughput calculations for a large set of materials (5099) belonging to many different material classes, and collected the results to a database.

Tags: density-functional-theory, high-throughput, raman-tensors
SPAᴴM: the spectrum of approximated hamiltonian matrices representations

Physics-inspired molecular representations are the cornerstone of similarity-based learning applied to solve chemical problems. Despite their conceptual and mathematical diversity, this class of descriptors shares a common underlying philosophy: they all rely on the molecular information that determines the form of the electronic Schrödinger equation. Existing representations take the most varied forms, from non-linear functions of atom types and positions to atom densities and potential, up to complex quantum chemical objects directly injected into the ML architecture. In this work, we present the Spectrum of Approximated Hamiltonian Matrices (SPAᴴM) as an alternative pathway to construct quantum machine learning representations through leveraging the foundation of the electronic Schrödinger equation itself: the electronic Hamiltonian. As the Hamiltonian encodes all quantum chemical information at once, SPAᴴM representations not only distinguish different molecules and conformations, but also different spin, charge, and electronic states. As a proof of concept, we focus here on efficient SPAᴴM representations built from the eigenvalues of a hierarchy of well-established and readily-evaluated "guess" Hamiltonians. These SPAᴴM representations are particularly compact and efficient for kernel evaluation and their complexity is independent of the number of different atom types in the database

Tags: epfl, erc, guess-hamiltonians, machine-learning, marveldd1, molecular-representation, snsf, spahm
Oxygen evolution and reduction on Fe‑doped NiOOH

This dataset includes the full computational workflows of a proof-of-concept study of various possible mechanisms (standard and bifunctional ones) for oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) on exfoliated NiOOH as electrocatalyst, including active edge sites (M5) and hydrogen acceptor sites in the same model system. Furthermore, explicit water is included in the model to describe the equilibration of the M-OOH species to M-OOH/eq, a crucial step that enables a bifunctional route to be operative. Additionally, different single Fe-dopant positions (M1, M2, M3, M4, M5, M6 and M7) are considered and four different reaction schemes (S1, S2, S3 and S4) are studied for the OER and the reverse ORR process. The results are relevant in alkaline conditions, where the studied model systems are stable. Certain Fe-dopant positions result in active Ni-edge sites with very low overpotentials provided that water is present within the model system.

Tags: electrochemical-overpotential, mixed-metal-oxyhydroxides, oxygen-evolution-reaction, oxygen-reduction-reaction
Active learning of reactive Bayesian force fields applied to heterogeneous catalysis dynamics of H/Pt

Atomistic modeling of chemically reactive systems has so far relied on either expensive ab initio methods or bond-order force fields requiring arduous parametrization. Here, we describe a Bayesian active learning framework for autonomous ``on-the-fly'' training of fast and accurate reactive many-body force fields during molecular dynamics simulations. At each time step, predictive uncertainties of a sparse Gaussian process are evaluated to automatically determine whether additional ab initio training data are needed. We introduce a general method for mapping trained kernel models onto equivalent polynomial models whose prediction cost is much lower and independent of the training set size. As a demonstration, we perform direct two-phase simulations of heterogeneous H2 turnover on the Pt(111) catalyst surface at chemical accuracy. The model trains itself in three days and performs at twice the speed of a ReaxFF model, while maintaining much higher fidelity to DFT and excellent agreement with experiment.

Tags: density-functional-theory, machine-learning, molecular-dynamics