AndreaBozzo/ceres-open-data-index huggingface dataset:
Density functional Bogoliubov-de Gennes theory for superconductors implemented in the SIESTA code

We present SIESTA-BdG, an implementation of the simultaneous solution of the Bogoliubov-de Gennes (BdG) and Density Functional Theory (DFT) problem in SIESTA, a first-principles method and code for material simulations which uses pseudopotentials and a localized basis set. This unified approach describes both conventional and unconventional superconducting states, and enables a description of inhomogeneous superconductors and heterostructures. We demonstrate the validity, accuracy, and efficiency of SIESTA-BdG by computing physically relevant quantities (superconducting charge density, band structure, superconducting gap features, density of states) for conventional singlet (Nb, Pb) and unconventional (FeSe) superconductors. We find excellent agreement with experiments and results obtained within the KKR-BdG computational framework. SIESTA-BdG forms the basis for modelling quantum transport in superconducting devices and including - in an approximate fashion - the superconducting DFT potential of Oliveira, Gross, and Kohn.

This dataset contains the calculations performed on bulk Nb and the associated notebooks used to generate figures from this data.

Tags: aiida, aiida-siesta, bogoliubov-de-gennes, density-functional-theory, h2020, horizon-europe, marie-curie-fellowship, max, nb, prace, siesta, superconductivity
Experimental and ab initio derivation of interface stress in nanomultilayered coatings: application to immiscible Cu/W system with variable in-plane stress

Interface stress is a fundamental descriptor for interphase boundaries and is defined in strict relation to the interface energy. In nanomultilayered coatings with their intrinsically high interface density, the functional properties are generally dictated by the interface structure, which in turn is governed by the delicate interaction of residual interface and volume stresses in the coating system. In the present work, experimental estimations of the interface stress in Cu/W NMLs (with a variable residual stress state from tensile to compressive) were compared with corresponding theoretical values as calculated using DFT (adopting an incoherent bcc W{110}/fcc Cu{111} interface with variable in-plane strain). The Cu/W interface stress was experimentally tuned monotonically from positive to negative values by changing the residual stress in the W nanolayers by increasing the Ar pressure during the W deposition steps. Qualitative agreement between experiment and simulation was achieved, both confirming a decrease of the interface stress from the compressive to the tensile regime. The DFT simulations showed that Cu atoms in the vicinity of the strained Cu/W interfaces are displaced along the in-plane and out-of-plane directions in response to the acting
interface stress. Using a preliminary developed neural network potential for the immiscible Cu-W system, specific in-plane crystallographic orientation relationships for the Cu/W interfaces were also tested, which improved quantitative agreement between experiment and theory. Assumptions and limitations in experiments and theory for deriving the interface stress are critically discussed.

Tags: ab-initio, copper-tungsten, interface-stress, marveldd1, neural-network-potential, xrd
Conformational tuning of magnetic interactions in coupled nanographenes

Phenalenyl (C₁₃H₉) is an open-shell spin-1/2 nanographene. Using scanning tunneling microscopy (STM) inelastic electron tunneling spectroscopy (IETS), covalently-bonded phenalenyl dimers have been shown to feature conductance steps associated with singlet-triplet excitations of a spin-1/2 dimer with antiferromagnetic exchange. In a recent work, we address the possibility of tuning the magnitude of the exchange interactions by varying the dihedral angle between the two molecules within a dimer. Theoretical methods, ranging from density functional theory calculations to many-body model Hamiltonians solved within different levels of approximation, are used to explain STM-IETS measurements of twisted phenalenyl dimers on a h-BN/Rh(111) surface. By means of first-principles calculations, we also propose strategies to induce sizable twist angles in surface-adsorbed phenalenyl dimers via functional groups, including a photoswitchable scheme. This record contains data that support the results discussed in the manuscript.

Tags: dmrg, magnetic-nanographenes, marvelp4, snsf, stmsts
Robustness of local predictions in atomistic machine learning models

Machine learning (ML) models for molecules and materials commonly rely on a decomposition of the global target quantity into local, atom-centered contributions. This approach is convenient from a computational perspective, enabling large-scale ML-driven simulations with a linear-scaling cost, and can also be used to deduce useful structure--property relations as they associate simple atomic motifs with complicated macroscopic properties. However, even though there exist practical justifications for these decompositions, only the global quantity is rigorously defined, and thus it is unclear to what extent the atomistic terms predicted by the model can be trusted.  Here, we introduce a quantitative metric, which we call the local prediction rigidity (LPR), to assess how robust the locally decomposed predictions of ML models are. We investigate the dependence of LPR on the details of model training, e.g. composition of the dataset, for several different problems ranging from simple toy models to real chemical systems. We present strategies to systematically enhance the LPR, which can be used to improve the robustness, interpretability, and transferability of the resulting atomistic ML models. 
This repository contains datasets and Jupyter notebooks employed to corroborate the results of the above study.

Tags: epsrc, erc, marie-curie-fellowship
Characteristics data for a new parameters extraction method of InGaP/GaAs/Ge multi-junction solar cell

This data presents the characteristics obtained using extracted parameters of multi- junction solar cells using a single diode triple-junction model. The proposed method combines analytical and numerical techniques to solve a nonlinear equation and determine the parameters, including the ideality factor, series resistance, shunt resistance, photocurrent, and saturation current, using manufacturer data and mathematical equations. The results show that the suggested approach achieves satisfactory performance and provide an accurate representation of the multi-junction circuit's parameters. Overall, this study provides a valuable contribution to the field of solar cell parameter extraction and offers insights for further research in this area.

Tags: i-v-characteristics, multi-junction, pv-parameter-extraction, solar-energy
Seebeck coefficient of ionic conductors from Bayesian regression analysis

We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo theory of linear response and Bayesian regression analysis. By exploiting the probability distribution of the off-diagonal elements of a Wishart matrix, we develop a consistent and unbiased estimator for the Seebeck coefficient, whose statistical uncertainty can be arbitrarily reduced in the long-time limit. We assess the efficacy of our method by benchmarking it against extensive equilibrium molecular dynamics simulations conducted on molten CsF using empirical force fields. We then employ this procedure to calculate the Seebeck coefficient of molten NaCl, KCl and LiCl using neural network force fields trained on ab initio data over a range of pressure-temperature conditions.

Tags: bayesian, ionic-conductors, seebeck
Effect of hydrogen on the local chemical bonding states and structure of amorphous alumina by atomistic and electrostatic modeling of auger parameter shifts

This study discloses the effect of hydrogen impurities on the local chemical bonding states and structure of amorphous alumina films by predicting measured Auger parameter shifts using a combination of atomistic and electrostatic modeling. Different amorphous alumina polymorphs with variable H-content and density, as grown by atomic layer deposition, were successfully modeled using a universal machine learning interatomic potential. The annealing of highly defective crystalline hydroxide structures with experimental H-contents at the corresponding atomic layer deposition temperatures led to excellent agreement between theory and experiment in the density and structure of the resulting amorphous alumina polymorphs. The measured Auger parameter shifts of Al cations in such polymorphs were accurately predicted with respect to the H content by assuming that all H atoms are present in the form of hydroxyl ligands in the randomly interconnected 4-fold, 5-fold, and 6-fold nearest-coordination spheres of Al. As revealed by a combination of atomistic and electrostatic modeling, the measured Auger shifts with an increase in the H content and an accompanying decrease in the oxide density depend on the complex correlations between local coordination, bond lengths, bond angles, and ligand type(s) around the core-ionized atoms. Moreover, cryogenic X-ray photoelectron spectroscopy is suggested to offer new insights into the local chemical and structural building blocks of crystalline and amorphous oxides by reducing thermal noise. These findings and fundamental knowledge contribute to advancing the design of e.g. hydrogen oxide barrier films, oxide membranes for H separation, H storage materials, and fuel cells for a hydrogen-based economy.

Tags: amorphous-oxide, atomic-layer-deposition-ald, auger-parameter, density-functional-theory-dft, electrostatic-modeling, hydrogen, marveldd1, molecular-dynamics-md, x-ray-photoelectron-spectroscopy-xps
Unraveling the crystallization kinetics of the Ge₂Sb₂Te₅ phase change compound with a machine-learned interatomic potential

The phase change compound Ge₂Sb₂Te₅ (GST225) is exploited in advanced non-volatile electronic memories and in neuromorphic devices which both rely on a fast and reversible transition between the crystalline and amorphous phases induced by Joule heating. The crystallization kinetics of GST225 is a key functional feature for the operation of these devices. We report here on the development of a machine-learned interatomic potential for GST225 that allowed us to perform large scale molecular dynamics simulations (over 10000 atoms for over 100 ns) to uncover the details of the crystallization kinetics in a wide range of temperatures of interest for the programming of the devices. The potential is obtained by fitting with a deep neural network (NN) scheme a large quantum-mechanical database generated within Density Functional Theory. The availability of a highly efficient and yet highly accurate NN potential opens the possibility to simulate phase change materials at the length and time scales of the real devices.

Tags: crystallization, ge2sb2te5, molecular-dynamics-simulation, neural-network-potential, phase-change-materials, phase-change-memories
Correlations of spin splitting and orbital fluctuations due to 1/f charge noise in the Si/SiGe Quantum Dot

Fluctuations of electric fields can change the position of a gate-defined quantum dot in a semiconductor heterostructure. In the presence of magnetic field gradient, these stochastic shifts of electron's wavefunction lead to fluctuations of electron's spin splitting. The resulting spin dephasing due to charge noise limits the coherence times of spin qubits in isotopically purified Si/SiGe quantum dots. We investigate the spin splitting noise caused by such process caused by microscopic motion of charges at the semiconductor-oxide interface. We compare effects of isotropic and planar displacement of the charges, and estimate their densities and typical displacement magnitudes that can reproduce experimentally observed spin splitting noise spectra. We predict that for defect density of 10¹⁰ cm⁻², visible correlations between noises in spin splitting and in energy of electron's ground state in the quantum dot, are expected.

Tags: charge-noise, quantum-dots, simulations
Combined theoretical and experimental study of the Moiré dislocation network at the SrTiO₃-(La,Sr)(Al,Ta)O₃ interface

Recently a highly ordered Moiré dislocation lattice was identified at the interface between a SrTiO₃ (STO) thin film and the (LaAlO₃)₀.₃(Sr₂TaAlO₆)₀.₇ (LSAT) substrate. A fundamental understanding of the local ionic and electronic structure around the dislocation cores is crucial to further engineer the properties of these complex multifunctional heterostructures. Here we combine experimental characterization via analytical scanning transmission electron microscopy with results of molecular dynamics and density functional theory calculations to gain insights into the structure and defect chemistry of these dislocation arrays. Our results show that these dislocations lead to undercoordinated Ta/Al cations at the dislocation core, where oxygen vacancies can easily be formed, further facilitated by the presence of cation vacancies. The reduced Ti³⁺ observed experimentally at the dislocations by electron energy-loss spectroscopy are a consequence of both the structure of the dislocation itself, as well as of the electron-doping due to oxygen vacancy formation. Finally, the experimentally observed Ti diffusion into LSAT around the dislocation core occurs only together with cation-vacancy formation in LSAT or Ta diffusion into STO.

Tags: complex-oxide-interface, dislocation, marveldd5, point-defects
Dislocation-grain boundary interaction dataset for FCC Cu

Dislocation-grain boundary play a major role in the strength and ductility of structural materials. An understanding of governing parameters such as grain boundary local atomic structures on the outcome of this interaction can accelerate new alloy design strategies that tailors materials' microstructures. Previous studies have focused only on the subset of minimum-energy grain boundary structures. We present a comprehensive database of dislocation-grain boundary interaction for edge, screw, and 60o mixed dislocation with 449 < 110 > and < 112 > symmetric tilt grain boundary in FCC Cu consisting of 67 minimum-energy grain boundary structures and 389 metastable ones. The dataset contains the outcomes for 5593 unique interactions with a particular dislocation type, grain boundary structure, and applied shear stress.

Tags: dislocation-grain-boundary-interaction, grain-boundary-structure, material-science
Magnetostriction-driven muon localisation in an antiferromagnetic oxide

Magnetostriction drives a rhombohedral distortion in the cubic rock salt antiferromagnet MnO at the Nèel temperature TN=118 K.  As an unexpected consequence we show that this distortion acts to localize the site of an implanted muon due to the accompanying redistribution of electron density. This lifts the degeneracy between equivalent sites, resulting in a single observed muon precession frequency.  Above TN, the muon instead becomes delocalized around a network of equivalent sites.  Our first-principles simulations based on Hubbard-corrected density-functional theory and molecular dynamics are consistent with our experimental data and help to resolve a long-standing puzzle regarding muon data on MnO, as well as having wider applicability to other magnetic oxides.

Tags: dftuv, experimental, marvel, molecular-dynamics-simulation, muon-spin-rotation-relaxation-and-resonance
Ab initio functional-independent calculations of the clamped Pockels tensor of tetragonal barium titanate

We present an ab initio method to calculate the clamped Pockels tensor of ferroelectric materials from density-functional theory (DFT), the modern theory of polarization exploiting the electric-enthalpy functional, and automated first- and second-order finite-difference derivatives of the polarizations and the Hellmann-Feynman forces. Thanks to the functional-independent capabilities of our approach, we can determine the Pockels tensor of tetragonal barium titanate (BTO) beyond the local density approximation (LDA), with arbitrary exchange-correlation (XC) functionals, for example, PBEsol. The latter, together with RRKJ ultra-soft pseudo-potentials (PP) and a supercell exhibiting local titanium off-centering, enables us to stabilize the negative optical phonon modes encountered in tetragonal BTO when LDA and norm-conserving PP are combined. As a result, the correct value range of r51, the largest experimental Pockels coefficient of BTO, is recovered. We also reveal that r51 increases with decreasing titanium off-centering for this material. The lessons learned from the structural, dielectric, and vibrational investigations of BTO will be essential to design next-generation electro-optical modulators based on the Pockels effect.

Tags: ab-initio, aiida-vibroscopy, barium-titanate, density-functional-theory, electro-optics, imaginary-phonons, pockels
Structural transitions of calcium carbonate by molecular dynamics simulation

Calcium carbonate (CaCO₃) plays a crucial role in the global carbon cycle, and its phase diagram is of significant scientific interest. We used molecular dynamics to investigate selected structural phase transitions of calcium carbonate. Using the Raiteri potential, we explored the structural transitions occurring at the constant pressure of 1 bar, with temperatures ranging from 300 to 2500 K, and at the constant temperature of 1600 K, with pressures ranging from 0 to 13 GPa. With increasing temperature, the transitions between calcite, CaCO₃-IV, and CaCO₃-V were characterized. In the calcite structure, the carbonate ions are ordered in a planar triangular arrangement, alternating with layers of calcium ions. As the temperature increases, the transition from calcite to CaCO₃-IV occurs, leading to partial disordering of the carbonate ions. At higher temperatures, CaCO₃-IV transforms into CaCO₃-V. Through free energy analysis, we classified the latter transition as a continuous phase transition. At a temperature of 2000 K, a 'disordered CaCO₃' structure appears, characterized by low order within the calcium and carbonate sublattices and the free rotation of the carbonate ions. With increasing pressure, two calcium carbonate transformations were observed. At P = 2 GPa, the CaCO₃-V phase undergoes a phase transition into CaCO₃-IV, demonstrating that the model can describe the transition between these two phases as pressure- and temperature-driven. At P = 4.25 GPa, CaCO₃-IV undergoes a phase transition into the CaCO₃-Vb phase. This transition is classified as first-order based on free energy calculations.

Tags: calcium-carbonate, high-pressure, high-temperature, metadynamics, molecular-dynamics, phase-transitions
Understanding the role of oxygen-vacancy defects in Cu₂O(111) from first-principle calculations

The presence of defects, such as copper and oxygen vacancies, in cuprous oxide films determines their characteristic carrier conductivity and consequently their application as semiconducting systems. There are still open questions on the induced electronic re-distribution, including the formation of polarons. Indeed, to accurately reproduce the structural and electronic properties at the cuprous oxide surface, very large slab models and theoretical approaches that go beyond the standard generalized gradient corrected density functional theory are needed. In this work we investigate oxygen vacancies formed in proximity of a reconstructed Cu₂O(111) surface, where the outermost unsaturated copper atoms are removed, thus forming non-stoichiometric surface layers with copper vacancies. We address simultaneously surface and bulk properties by modelling a thick and symmetric slab, to find that hybrid exchange-correlation functionals are needed to describe the oxygen vacancy in this system. Our simulations show that the formation of oxygen vacancies is favoured in the sub-surface layer. Moreover, the oxygen vacancy leads to a splitting and left-shift of the shallow hole states in the gap, which are associated with the deficiency of copper at the surface. These findings suggest that surface electronic structure and reactivity are sensitive to the presence of oxygen vacancies, also when the latter are formed deeper within the film.

Tags: cu2o, hybrid-dft, oxygen-vacancy-defects
Dataset for first-principles diagrammatic Monte Carlo for electron-phonon interactions and polaron

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, 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
Switching p-type to high-performance n-type organic electrochemical transistors via doped state engineering

High-performance n-type organic electrochemical transistors (OECTs) are essential for logic circuits and sensors. However, the performances of n-type OECTs lag far behind that of p-type ones. Conventional wisdom posits that the LUMO energy level dictates the n-type performance. Herein, we show that engineering the doped state is more critical for n-type OECT polymers. By balancing more charges to the donor moiety, we could effectively switch a p-type polymer to high-performance n-type material. Based on this concept, the polymer, P(gTDPP2FT), exhibits a record high n-type OECT performance with μC* of 54.8 F cm⁻¹ V⁻¹ s⁻¹, mobility of 0.35 cm² V⁻¹ s⁻¹, and response speed of τon/τoff = 1.75/0.15 ms. Calculations and comparison studies show that the conversion is primarily due to the more uniform charges, stabilized negative polaron, enhanced conformation, and backbone planarity at negatively charged states. Our work highlights the critical role of understanding and engineering polymers' doped states.

Tags: doped-state-engineering, n-type, organic-electrochemical-transistor