AndreaBozzo/ceres-open-data-index huggingface dataset:
On-surface synthesis of tailored organic platforms for single metal atoms

Recent advances in nanomaterials have pushed the boundaries of nanoscale fabrication to the limit of single atoms, particularly in heterogeneous catalysis. Single atom catalysts, comprising minute amounts of transition metals dispersed on inert substrates, have emerged as prominent materials in this domain. However, overcoming the tendency of these single atoms to cluster beyond cryogenic temperatures and precisely arranging them on surfaces with desired local environments pose significant challenges. Employing organic templates for orchestrating and modulating the activity of single atoms holds promise. In recent work, we introduce a novel single-atom platform wherein atoms are firmly anchored to specific coordination sites distributed along carbon-based polymers, synthesised via on-surface synthesis. These platforms exhibit atomic-level structural precision and stability, even at elevated temperatures. The asymmetry in the structure and electronic states at the active sites anticipates the enhanced reactivity of these precisely defined reactive centers. Upon exposure to CO and CO2 gases at low temperatures, the platform demonstrates excellent trapping and conversion capabilities. Fine-tuning the structure and properties of the coordination sites offers unparalleled flexibility in tailoring functionalities, thus opening avenues for previously untapped potential in catalytic applications. This record contains data that support the results presented in the published work.

Tags: asymmetric-active-sites, cscs, dft, marvelp4, on-surface-synthesis, single-atom-catalyst, spm
Antagonistic impact of thermal expansion and phonon anharmonicity on the phonon-limited resistivity of elemental metals from first principles

Understanding electrical resistivity in metals remains a central challenge in quantifying charge transport at finite temperature. Current first-principles calculations based on the Boltzmann transport equation often match experiments, yet they almost always neglect the effect of thermal expansion and phonon anharmonicity. We show that both effects exert an opposite impact on electron–phonon coupling and on electrical resistivity. Thermal expansion enhances the coupling and leads to overestimation of resistivity, whereas anharmonic effects reduce it. By explicitly incorporating both effects, we establish a more complete description of resistivity in elemental metals, demonstrated here for Pb, Nb, and Al. This archive contains all our input, output files and the data.

Tags: electron-phonon-coupling, first-principles, transport
In search of the electron-phonon contribution to total energy

The total energy is a fundamental characteristic of solids, molecules, and nanostructures. In most first-principles calculations of the total energy, the nuclear kinetic operator is decoupled from the many-body electronic Hamiltonian and the dynamics of the nuclei is reintroduced afterwards. This two-step procedure introduced by Born and Oppenheimer (BO) is approximate. Energies beyond the electronic and vibrational (or phononic) main contributions might be relevant when small energy differences are important, such as when predicting stable polymorphs or describing magnetic energy landscape. We clarify the different flavors of BO decoupling and give an exact formulation for the total energy in the basis of BO electronic wavefunctions. Then, we list contributions, beyond the main ones, that appear in a perturbative expansion in powers of M0-1/4, where M0 is a typical nuclear mass, up to sixth order. Some of these might be grouped and denoted the electron-phonon contribution to total energy,  Eelph, that first appears at fourth order. The electronic inertial mass contributes at sixth order. We clarify that the sum of the Allen-Heine-Cardona zero-point renormalization of eigenvalues over occupied states is not the electron-phonon contribution to the total energy but a part of the phononic contribution. The computation of the lowest-order Eelph is implemented and shown to be small but non-negligible (3.8 meV per atom) in the case of diamond and its hexagonal polymorph. We also estimate the electronic inertial mass contribution and confirm the size-consistency of all computed terms.

Tags: ab-initio, diamond, electron-phonon-coupling, total-energy
Two-dimensional RMSD projections for reaction path visualization and validation

This record contains the complete optimization trajectories, potential model, and analysis data for the Nudged Elastic Band (NEB) calculation of the ethylene + N$_2$O cycloaddition, a Grignard rearrangement, and a bicyclobutane  reaction. This dataset supports the accompanying manuscript "Two-dimensional RMSD projections for reaction path visualization and validation" and enables the full reproduction of the reported 2D RMSD landscapes and 1D energy profiles.

The provided data encompasses the entire computational workflow: from the pre-trained PET-OMAT machine-learned potential and initial endpoint geometries to the intermediate NEB optimization steps and the final converged reaction path.

Tags: nudged-elastic-band, saddle-search-methods, transition-states, visualization
Identifying mechanistic differences between co-fed CO2 hydrogenation and reactive CO2 capture using Ru and Pd dual function materials

Dual function materials (DFMs) enable reactive carbon capture (RCC), an intensified approach to carbon dioxide capture and utilization for cost and energy input reductions. Yet, there is a fundamental lack of understanding of mechanisms around CO2 adsorption and subsequent conversion on these materials, hindering further development. Herein, we investigated several supported alkaline metal oxides for their CO2 adsorption characteristics to find that Na/Al2O3 had the highest CO2 adsorption capacity, accompanied by a variety of CO2 adsorption geometries as identified by in situ DRIFTS and computational modeling. The addition of catalytic metals (Ru, Pd) increased the adsorption capacity of Na/Al2O3 without altering binding modes. In the subsequent reactive desorption step, acetate and formate intermediates were observed. Notably, this mechanistic investigation identified that the formation of acetate species was unique to RCC on a DFM, as these species were not observed in co-fed hydrogenation over the DFM or RCC over a Na-free catalyst.

Herein, we share the structural CONTCARs obtained using periodic PBE calculations in VASP for hydrated (110) and (100) surfaces of gamma-alumina, Na2O-modified surface models for Na/Al2O3, subsequent structures of various surface carbonate (CO3*) and bicarbonate (HCO3*) configurations formed on each of these surfaces upon CO2 adsorption and adsorbed acetate and formate radicals on the surfaces.

Tags: alumina, co2-hydrogenation, density-functional-theory, dfm, dft, dual-function-material, na, na2o, rcc, reactive-carbon-capture
Electrolyte design for reversible zinc metal chemistry

Here we present an on-demand strategy for electrolytes design to surpass 99.9% Coulombic efficiency (CE) in zinc metal anode. This strategy synergizes various effects by specifically targeting the two critical factors: plating morphology and the anode-electrolyte interface.  In this dataset, we simulated the solvation structures and bilayer structures of various electrolytes by molecular dynamics simulations. We found Triethyl phosphate and dimethylformamide can  induce the free-water-poor inner Helmholtz plane and reduce the interfacial water activity. Furthermore, the MD results imply that the dual-salt introduces more anions into the Zn2+ primary solvation sheath, and the DMF co-solvent is also able to enter the solvation sheath.

Tags: batteries, electrolyte, molecular-dynamics
Robust Wannierization including magnetization and spin-orbit coupling via projectability disentanglement

Maximally-localized Wannier functions (MLWFs) are widely employed as an essential tool for calculating the physical properties of materials due to their localized nature and computational efficiency. Projectability-disentangled Wannier functions (PDWFs) have recently emerged as a reliable and efficient approach for automatically constructing MLWFs that span both occupied and lowest unoccupied bands. Here, we extend the applicability of PDWFs to magnetic systems and/or those including spin-orbit coupling, and implement such extensions in automated workflows. Furthermore, we enhance the robustness and reliability of constructing PDWFs by defining an extended protocol that automatically expands the projectors manifold, when required, by introducing additional appropriate hydrogenic atomic orbitals. We benchmark our extended protocol on a set of 200 chemically diverse materials, as well as on the 40 systems with the largest band distance obtained with the standard PDWF approach, showing that on our test set the present approach delivers a success rate of over 98% in obtaining accurate Wannier-function interpolations, defined as an average band distance below 20 meV between the DFT and Wannier-interpolated bands, up to 2 eV above the Fermi level for metals or above the conduction band minimum for insulators (and a 100% success rate when including only bands up to 1 eV above these values).

Tags: aiida, automation, marvel, projectability-disentanglement, snsf, wannier-functions, wannierization
High-quality, high-information datasets for universal atomistic machine learning

The quality, consistency, and information content of training data is often what determines the practical value of machine-learning models for atomistic simulations. Yet, many widely used electronic-structure databases are assembled having materials screening as primary goal rather than robust force-field learning, are limited in their scope to a specific class of chemical compounds, and/or employ inconsistent DFT functionals and settings. Here we introduce MAD-1.5, a highly curated dataset designed explicitly for training broadly applicable atomistic models across the periodic table at high levels of theory. MAD-1.5 extends the MAD dataset with targeted enrichment strategies that improve the coverage of chemical space to 102 elements while keeping the total number of configurations compact. All structures are computed with a single, standardized all-electron DFT workflow using the r2SCAN meta-GGA functional and consistent convergence settings, ensuring uniformity across chemically heterogeneous systems. The dataset encompasses molecules, clusters, bulk crystals, surfaces, and low-dimensional structures, and its quality and consistency are further enhanced by outlier removal using uncertainty quantification. We demonstrate the high accuracy that can be achieved with the proposed dataset by training PET-MAD-1.5, a generally applicable r2SCAN interatomic potential that covers 102 elements in the periodic table and achieves exceptional levels of benchmark accuracy and stability in challenging simulation protocols.

Tags: atomistic-simulations, dataset, density-functional-theory, interatomic-potentials, machine-learning, universal-models
Opposite impact of thermal expansion and phonon anharmonicity on the phonon-limited resistivity of elemental metals from first principles

Understanding electrical resistivity in metals remains a central challenge in quantifying charge transport at finite temperature. Current first-principles calculations based on the Boltzmann transport equation often match experiments, yet they almost always neglect the effect of thermal expansion and phonon anharmonicity. We show that both effects exert an opposite impact on electron–phonon coupling and on electrical resistivity. Thermal expansion enhances the coupling and leads to overestimation of resistivity, whereas anharmonic effects reduce it. By explicitly incorporating both effects, we establish a more complete description of resistivity in elemental metals, demonstrated here for Pb, Nb, and Al. This archive contains all our input, output files and the data.

Tags: electron-phonon-coupling, first-principles, transport
FlashMD: long-stride, universal prediction of molecular dynamics

Molecular dynamics (MD) provides insights into atomic-scale processes by integrating over time the equations that describe the motion of atoms under the action of interatomic forces. Machine learning models have substantially accelerated MD by providing inexpensive predictions of the forces, but they remain constrained to minuscule time integration steps, which are required by the fast time scale of atomic motion. In this work, we propose FlashMD, a method to predict the evolution of positions and momenta over strides that are between one and two orders of magnitude longer than typical MD time steps. We incorporate considerations on the mathematical and physical properties of Hamiltonian dynamics in the architecture, generalize the approach to allow the simulation of any thermodynamic ensemble, and carefully assess the possible failure modes of such a long-stride MD approach. We validate FlashMD's accuracy in reproducing equilibrium and time-dependent properties, using both system-specific and general-purpose models, extending the ability of MD simulation to reach the long time scales needed to model microscopic processes of high scientific and technological relevance. 

This repository contains the scripts used for the training and analysis of the FlashMD models presented in the associated paper/preprint.

Tags: atomistic-machine-learning, long-stride-simulations, ml-accerelated-simulations, molecular-dynamics
Getting the manifold right: The crucial role of orbital resolution in DFT+U for mixed d-f electron compounds

This dataset accompanies the study "Getting the manifold right: The crucial role of orbital resolution in DFT+U for mixed d-f electron compounds" and provides input and output files used to investigate the electronic structure of AUO4 compunds (A = Ni, Mn, Co). The calculations systematically compare standard PBEsol density-functional theory (DFT), shell-averaged DFT+U, and orbital-resolved DFT+U approaches based on orthogonalized atomic orbital (OAO) projectors. The dataset includes self-consistent-field calculations, geometry optimizations, and projected density of states data. In addition, hybrid-functional HSE06 calculations performed with VASP are provided for benchmarking purposes. A detailed molecular orbital and bonding analysis for NiUO4, carried out using the LOBSTER code, is also included to elucidate orbital hybridization and chemical bonding effects.

Tags: actinide-materials, dftu, electronic-structure, orbital-resolved
Migration of hole polarons in anatase and rutile TiO₂ through piecewise-linear functionals

This dataset contains the optimized structures of hole polarons in anatase and rutile TiO₂, calculated using the DFT+U and PBE0(α) functionals, with parameters tuned to satisfy the piecewise linearity condition. It also includes hole polaron migration paths in anatase and rutile, optimized using the nudged elastic band method at the DFT+U level. Additionally, pristine TiO₂ structures and an example input file for Quantum ESPRESSO are provided.

Tags: anatase, hopping, polaron, rutile, semiconductor, tio2
Fine-tuning catalysts: The role of support nanomorphology in shaping Cu/CeO2 CO-PROX properties

Understanding how oxide nanomorphology directs metal–support interactions is key to designing selective, low-cost catalysts. The preferential oxidation of CO (CO-PROX) is vital for purifying H₂ streams for fuel cell applications, as even trace CO strongly poisons the electrode catalysts. Cu/CeO2 systems provide a cost-effective alternative to noble metals, yet the influence of ceria morphology on performance remains unclear. Here, we compare low-loaded Cu catalysts supported on CeO2 nanospheres and nanocubes. Although distinct in shape, electron microscopy, low-temperature CO adsorption infrared spectroscopy, and DFT calculations reveal surface reconstructions in nanocubes that diminish structural differences between the two supports. Nevertheless, the Cu/nanosphere catalyst shows higher CO oxidation activity, while the Cu/nanocube catalyst offers superior CO₂ selectivity and a broader full-conversion temperature window. In situ DRIFTS and DFT attribute these contrasts to stronger CO adsorption sites in the nanocube system. Copper speciation and the nature of surface carbonyls were resolved through complementary techniques including STEM-HAADF imaging, XEDS mapping, EPR, and CO adsorption IR spectroscopy, together with DFT. These results demonstrate that subtle variations in ceria morphology steer interfacial chemistry and reaction pathways, providing design principles for next-generation Cu-based catalysts for CO-PROX and related oxidation reactions.

Tags: carbonyls-infrared, co-prox, cuceo2-catalysts, dft, electron-microscopy, hydrogen
Comparative study of magnetic exchange parameters and magnon dispersions in NiO and MnO from first principles

Spin-wave excitations are fundamental to understanding the behavior of magnetic materials and hold promise for future information and communication technologies. Yet, modeling these accurately in transition-metal compounds remains challenging, starting from the self-interaction errors affecting localized and partially filled $d$-orbitals in density-functional theory (DFT) with (semi-)local functionals. In this work, we compare three advanced first-principles approaches for computing magnetic exchange parameters and magnon dispersions in NiO and MnO, all based on a common DFT+$U$ ground state with ab initio Hubbard $U$ values obtained from density-functional perturbation theory. Two methods extract exchange parameters directly: one via total-energy differences using the four-state mapping ($\Delta E$), and the other via the magnetic force theorem (MFT) using infinitesimal spin rotations. Magnon dispersions are then obtained from a Heisenberg Hamiltonian through linear spin-wave theory (LSWT). The third approach, time-dependent density-functional perturbation theory with $U$ (TDDFPT+$U$), yields magnon dispersions directly from the dynamical spin susceptibility, with exchange parameters fitted a posteriori, for comparison, via LSWT. Our results show that TDDFPT+$U$ and the Heisenberg model based on $\Delta E$-derived parameters align well with experimental neutron scattering data, whereas the MFT-based approach shows larger discrepancies, possibly due to some inherent approximations and limitations of the particular implementation used. This study benchmarks the accuracy of state-of-the-art first-principles techniques for spin-wave modeling and contributes to advancing reliable computational tools for the study and design of magnetic materials.

Tags: dftu, four-state-mapping-analysis, heisenberg-j, linear-spin-wave-theory, magnetic-force-theorem, magnon-dispersion, magnons, mno, nio, quantum-espresso, spin-waves, tb2j, time-dependent-density-functional-perturbation-theory, wannier90
Predicting the structure and swelling of microgels with different crosslinker concentrations by combining machine learning with numerical simulations

Microgels made of poly(N-isopropylacrylamide) are the prototype of soft, thermoresponsive particles widely used to study fundamental problems in condensed matter physics. However, their internal structure is far from homogeneous, and existing mean-field approaches, such as Flory–Rehner theory, provide only qualitative descriptions of their thermoresponsive behavior. Here, we combine machine learning and numerical simulations to accurately predict the concentration and spatial distribution of crosslinkers, the latter hitherto unknown experimentally, as well as the full swelling behavior of microgels, using only polymer density profiles. Our approach provides unprecedented insight into the structural and thermodynamic properties of any standard microgel.

Tags: machine-learning, microgels, volume-phase-transition
Uncovering the origin of interface stress enhancement and compressive-to-tensile stress transition in immiscible nanomultilayers

The intrinsic stress in nanomultilayers (NMLs) is typically dominated by interface stress, which is particularly high in immiscible Cu/W NMLs. Here, atomistic simulations with a chemically-accurate neural network potential reveal the role of interfacial intermixing and metastable phase formation on the interface stress levels.  These results rationalize an experimentally-reported compressive-to-tensile transition as a function of NML deposition conditions and the extremely high interface stresses under some conditions.

Tags: cuw-nanomultilayers, interface-stress, intermixing, marveldd1, metastable-phases, molecular-statics
Numerical investigation of realistic core-shell microgels: insights on two- and three-body effective interactions

Core-shell (CS) microgels–comprising a solid core chemically linked to a crosslinked polymer shell–are an important class of stimuli-responsive colloids widely employed for both fundamental and applied studies. Despite extensive experimental investigations, their numerical modeling remains underdeveloped; in particular, a detailed, temperature-resolved insight of their effective interactions is missing. While pairwise descriptions known for standard microgels are expected to be partially extensible to CS-microgels, the effect of the solid core and in turn, the extent and character of many-body contributions remain elusive. To clarify these open issues, this work introduces a computational method to generate realistic CS-microgels at different crosslinker concentrations, accurately reproducing the structure of experimental silica core–poly-N-isopropylacrylamide (pNIPAM) shell microgels at different temperatures across the Volume Phase Transition (VPT) and for different shell-to-core ratios. After validating the model, effective interactions between CS-microgels are calculated, extracting not only two-body interactions but also providing the first quantitative investigation of three-body effects in any microgel system. The present findings show that, albeit small, the latter contributions are non-negligible and exhibit an intriguing sign reversal: while being predominantly attractive at low temperatures, they become repulsive at high ones, nearly canceling out at the VPT. These results reveal a subtle interplay between microgel architecture, temperature and many-body correlations, with direct implications on the design of responsive soft materials and their mutual interactions.

Tags: coarse-grained-models, core-shell-microgels, effective-interaction, many-body-effects, molecular-simulation
Novel fast Li-ion conductors for solid-state electrolytes from first-principles

We present a high-throughput computational screening for fast lithium-ion conductors to identify promising materials for application in all solid-state electrolytes. Starting from more than 30,000 Li-containing experimental structures sourced from Crystallography Open Database, Inorganic Crystal Structure Database and Materials Platform for Data Science, we perform highly automated calculations to identify electronic insulators. On these ~1000 structures, we use molecular dynamics simulations to estimate Li-ion diffusivities using the pinball model, which describes the potential energy landscape of diffusing lithium with accuracy similar to density functional theory while being 200-500 times faster. Then we study the ~60 most promising and previously unknown fast conductors with full first-principles molecular dynamics simulations at several temperatures to estimate their activation barriers. The MD trajectories of these structures are included along with all the structures on which electronic strutcure calculations were performed. The entire screening provenance is provided for one structure to facilitate the reproduction of this screening.

Tags: computational-high-throughput-screening, dft, first-principles, li-ion-conductors, molecular-dynamics, solid-state-electrolytes