AndreaBozzo/ceres-open-data-index huggingface dataset:
Reaction pathway for coke-free methane steam reforming on a Ni/CeO2 catalyst: Active sites and role of metal-support interactions

Methane steam reforming (MSR) plays a key role in the production of syngas and hydrogen from natural gas. The increasing interest in the use of hydrogen for fuel cell applications demands the development of catalysts with high activity at reduced operating temperatures. Ni-based catalysts are promising systems because of their high activity and low cost, but coke formation generally poses a severe problem. Studies of ambient-pressure X-ray photoelectron spectroscopy (AP-XPS) indicate that CH4/H2O gas mixtures react with Ni/CeO2(111) surfaces to form OH, CHx and CHxO at 300 K. All these species are easy to form and desorb at temperatures below 700 K when the rate of the MSR process accelerates. Density functional theory (DFT) modeling of the reaction over ceria-supported small Ni nanoparticles predicts relatively low activation barriers between 0.3–0.7 eV for the complete dehydrogenation of methane to carbon and the barrierless activation of water at interfacial Ni sites. Hydroxyls resulting from water activation allow CO formation via a COH intermediate with a barrier of about 0.9 eV, which is much lower than that through a pathway involving lattice oxygen from ceria. Neither methane nor water activation are rate-determining steps, and the OH-assisted CO formation through the COH intermediate constitutes a low-barrier pathway that prevents carbon accumulation. The interaction between Ni and the ceria support and the low metal loading are crucial for the reaction to proceed in a coke-free and efficient way. These results could pave the way for further advances in the design of stable and highly active Ni-based catalysts for hydrogen production.

Tags: ceria, dft, hydrogen, methane, nickel, steam-reforming
Impact of glutamate carboxylation in the adsorption of the alpha-1 domain of osteocalcin to hydroxyapatite and titania

This record contains files necessary to reproduce enhanced sampling well-tempered metadynamics (wtMTD) and parallel tempering metadynamics in the well-tempered ensemble (PT-MetaD-WTE) simulations in PLUMED using GROMACS 2018.3.

Tags: biomimetics, biomineralization, metadynamics, molecular-dynamics
Exploding and weeping ceramics

The systematic tuning of the lattice parameters to achieve improved kinematic compatibility between phases is a broadly effective strategy for improving the reversibility, and lowering the hysteresis, of solid-solid phase transformations. Here, "kinematic compatibility" refers to the fitting together of the phases. We present an apparently paradoxical example in which tuning to near perfect compatibility in (Zr/Hf)O2-(YNb)O4 results in a high degree of irreversibility, as manifested in explosive or "weeping" behavior on cooling through the tetragonal-to-monoclinic phase transformation. In the case of weeping the polycrystal slowly and steadily falls apart at the grain boundaries. These effects occur without chemical change. Finally, tuning to satisfy a condition we term the equidistance condition results in reversible behavior with the lowest hysteresis in this system. We give evidence that all these observations are explained by a more careful analysis of compatibility of the polycrystal, accounting for sample shape. These results show that an extreme diversity of behaviors, from reversible to explosive, is possible in a chemically homogeneous system by manipulating conditions of compatibility in unexpected ways. They provide critical concepts underlying the current search for a shape memory oxide ceramic.

Tags: ceramics, cystallographic-compatibility, shape-memory
Topological frustration induces unconventional magnetism in a nanographene

The chemical versatility of carbon imparts manifold properties to organic compounds, where magnetism remains one of the most desirable but elusive. Polycyclic aromatic hydrocarbons, also referred to as nanographenes, show a critical dependence of electronic structure on the topologies of the edges and the π-electron network, which makes them model systems with which to engineer unconventional properties including magnetism. In 1972, Erich Clar envisioned a bow-tie-shaped nanographene, C38H18, where topological frustration in the π-electron network renders it impossible to assign a classical Kekulé structure without leaving unpaired electrons, driving the system into a magnetically non-trivial ground state. In this record we include data needed to support our recent work where we demonstrate the experimental realization and in-depth characterization of this emblematic nanographene, known as Clar's goblet. Scanning tunnelling microscopy and spin excitation spectroscopy of individual molecules on a gold surface reveal a robust antiferromagnetic order with an exchange-coupling strength of 23 meV, exceeding the Landauer limit of minimum energy dissipation at room temperature. Through atomic manipulation, we realize switching of magnetic ground states in molecules with quenched spins. Our results provide direct evidence of carbon magnetism in a hitherto unrealized class of nanographenes, and prove a long-predicted paradigm where topological frustration entails unconventional magnetism, with implications for room-temperature carbon-based spintronics.

Tags: ab-initio, clar-goblet, erc, kondo, marveldd3, nanographene, snsf
Optical absorption properties of metal-organic frameworks: solid state versus molecular perspective

The vast chemical space of metal and ligand combinations in Transition Metal Complexes (TMCs) gives rise to a rich variety of electronic excited states with local and non-local character such as intra-ligand (IL), metal-centered (MC), metal-to-ligand (MLCT) or ligand-to-metal charge-transfer (LMCT) states. Those features are equally found in Metal Organic Frameworks (MOFs), defined as modular materials built from metal-nodes connected through organic-ligands. Because of the electronic and structural complexity of MOFs, the computational description of their excited states is a formidable challenge for which two different approaches have been usually followed: the solid state and the molecular perspective. The first consists in analysing the frontier electronic bands and crystal orbitals of the electronic ground state (GS) in periodic boundary conditions, while the latter points to an accurate computation of the excited states in representative clusters at the molecular level. Herein, we apply both approaches to evaluate the optical absorption properties of three experimentally reported Ti(IV) mononuclear MOFs with in silico metal substitutions with Zn(II), Cd(II), Fe(II), Ru(II) and Zr(IV) ions, thus covering d10, d6 and d0 electronic configurations of 1st and 2nd row TMCs in MOFs. Our analysis captures the main electronic features attributed to these systems while we discuss the main advantages and drawbacks of both approximations.

Tags: epfl, marveldd4, mof, optical-absorption
Impact of glutamate carboxylation in the adsorption of the alpha-1 domain of osteocalcin to hydroxyapatite and titania

One proposed mechanism of implant fouling is attributed to the nonspecific adsorption of non-collagenous bone matrix proteins (NCPs) onto a newly implanted interface. With the goal of capturing the fundamental mechanistic and thermodynamic forces that govern changes in these NCP recognition domains as a function of γ-carboxyglutamic acid (Gla) post-translational modification and surface chemistry, we probe the adsorption process of the most commonly occurring NCP, osteocalcin, onto a mineral and metal oxide surface. Here, we apply two enhanced sampling methods to independently probe the effects of post-translational modification and peptide structure on adsorption. First, well-tempered metadynamics was used to capture the binding of acetyl and N-methylamide capped glutamic acid and Gla single amino acids onto crystalline hydroxyapatite and titania model surfaces at physiological pH. Following this, parallel tempering metadynamics in the well-tempered ensemble (PTMetaD-WTE) was used to study adsorption of the α-1 domain of osteocalcin onto hydroxyapatite and titania. Simulations were performed for the α-1 domain of osteocalcin in both its fully decarboxylated (dOC) and fully carboxylated (OC) form. Our simulations find that increased charge density due to carboxylation results in increased interactions at the interface, and stronger adsorption of the single amino acids to both surfaces. Interestingly, the role of Gla in promoting compact and helical structure in the α-1 domain resulted in disparate binding modes at the two surfaces, which is attributed to differences in interfacial water behavior. Overall, this work provides a benchmark for understanding the mechanisms that drive adsorption of Gla-containing mineralizing proteins onto different surface chemistries.

This record contains files necessary to reproduce enhanced sampling well-tempered metadynamics (wtMTD) and parallel tempering metadynamics in the well-tempered ensemble (PT-MetaD-WTE) simulations in PLUMED using GROMACS 2018.3.

Tags: biomimetics, biomineralization, metadynamics, molecular-dynamics
Exploring DFT+U parameter space with a Bayesian calibration assisted by Markov chain Monte Carlo sampling

Density-functional theory is widely used to predict the physical properties of materials. However, it usually fails for strongly correlated materials. A popular solution is to use the Hubbard corrections to treat strongly correlated electronic states. Unfortunately, the exact values of the Hubbard U and J parameters are initially unknown, and they can vary from one material to another. In this semi-empirical study, we explore the U and J parameter space of a group of iron-based compounds to simultaneously improve the prediction of physical properties (volume, magnetic moment, and bandgap). We used a Bayesian calibration assisted by Markov chain Monte Carlo sampling for three different exchange-correlation functionals (LDA, PBE, and PBEsol). We found that LDA requires the largest U correction. PBE has the smallest standard deviation and its U and J parameters are the most transferable to other iron-based compounds. Lastly, PBE predicts lattice parameters reasonably well without the Hubbard correction.

Tags: bayesian-calibration, dftu, markov-chain-monte-carlo, mcmc
Machine learning for metallurgy: a neural network potential for Al-Mg-Si

High-strength metal alloys achieve their performance via careful control of the nucleation, growth, and kinetics of precipitation. Alloy mechanical properties are then controlled by atomic scale phenomena such as shearing of the precipitates by dislocations. Atomistic modeling to understand the operative mechanisms requires length and time scales far larger than those accessible by first-principles methods. Here, a family of Behler-Parinello neural-network potentials (NNPs) for the Al-Mg-Si system is developed to enable quantitative studies of Al-6xxx alloys. The NNP is trained on metallurgically-important quantities computed by first principles density functional theory (DFT) leading to high fidelity predictions of intermetallic compounds, elastic constants, dilute solid-solution energetics, precipitate/matrix interfaces, Al stacking fault energies, antisite defect energies, and other quantities. A preliminary examination of early-stage clustering kinetics and energetics in Al-6xxx is then made, showing the formation of low-energy Mg-Si structures and the trapping of vacancies in these clusters. The Generalized Stacking Fault Energy surfaces (GSFE) for the three prevalent β" precipitate compositions in peak-aged Al-6xxx are then computed with the NNP, and are validated by DFT computations at key points. The NNP thus shows significant transferability across structures, making it a powerful approach for chemically-accurate simulations of metallurgical phenomena in Al-Mg-Si alloys.

Tags: aluminum, machine-learning, marveldd2, metallurgy
On-surface synthesis and characterization of nitrogen-substituted undecacenes

In this record, we provide the data supporting our recent results on the synthesis of nitrogen-substituted undecacene analogs. Heteroatom substitution in acenes allows to tailor their remarkable electronic properties, expected to include spin-polarization and magnetism for larger members of the acene family. Here, we present a strategy for the on-surface synthesis of three undecacene analogs substituted with four nitrogen atoms on an Au(111) substrate, by employing specifically designed diethano-bridged precursors. A similarly designed precursor is used to synthesize the pristine undecacene molecule. In the publication where the results are discussed, the experimental features of scanning probe microscopy are compared with ab initio simulations, to demonstrate that the ground state of the synthesized tetraazaundecacene has considerable open-shell character on Au(111). Additionally, we demonstrate that electronegative nitrogen atoms induce a considerable shift in energy level alignment compared to the pristine undecacene, and that the introduction of hydro-aza groups causes local anti-aromaticity in the synthesized compounds. Our work provides access to the precise fabrication of nitrogen-substituted acene and its analogs, potential building-blocks of organic electronics and spintronics, and a rich playground to explore pi-electron correlation.

Tags: aromaticity, cscs, experimental, heteroacenes, marveldd3, on-surface-synthesis, open-shell, snsf
Understanding the diversity of the metal-organic framework ecosystem

By combining metal nodes and organic linkers one can make millions of different metal-organic frameworks (MOFs). At present over 90,000 MOFs have been synthesized and there are databases with over 500,000 predicted structures. This raises the question of whether a new experimental or predicted structure adds new information. For MOF-chemists the chemical design space is a combination of pore geometry, metal nodes, organic linkers, and functional groups, but at present we do not have a formalism to quantify optimal coverage of chemical design space. In this work, we show how machine learning can be used to quantify similarities of MOFs. This quantification allows us to use techniques from ecology to analyse the chemical diversity of these materials in terms of diversity metrics. In particular, we show that this diversity analysis can identify biases in the databases, and how such bias can lead to incorrect conclusions. This formalism provides us with a simple and powerful practical guideline to see whether a set of new structures will have the potential for new insights, or constitute a relatively small variation of existing structures.

Tags: chemical-space, diversity, machine-learning, metal-organic-frameworks
On-surface synthesis of unsaturated carbon nanostructures with regularly fused pentagon-heptagon pairs

In this record we provide data to support our recent findings for the fabrication of Unsaturated Carbon Nanostructures with Regularly Fused Pentagon–Heptagon Pairs. Multiple fused pentagon–heptagon pairs are frequently found as defects at the grain boundaries of the hexagonal graphene lattice and are suggested to have a fundamental influence on graphene-related materials. However, the construction of sp2-carbon skeletons with multiple regularly fused pentagon–heptagon pairs is challenging. In this work, we found that the pentagon–heptagon skeleton of azulene was rearranged during the thermal reaction of an azulene-incorporated organometallic polymer on Au(111). The resulting sp2-carbon frameworks were characterized by high-resolution scanning probe microscopy techniques and feature novel polycyclic architectures composed of multiple regularly fused pentagon–heptagon pairs. Moreover, the calculated analysis of its aromaticity revealed a peculiar polar electronic structure.

Tags: carbon-nanostructures, cscs, marveldd3, on-surface-synthesis, open-shell-systems, polymers, snsf
Correlation between electronic and structural orders in 1T-TiSe2

The correlation between electronic and crystal structures of 1T -TiSe2 in the charge-density wave (CDW) state is studied by x-ray diffraction in order to clarify basic properties in the CDW state, transport properties, and chirality. Three families of reflections are used to probe atomic displacements and the orbital asymmetry in Se. Two distinct onset temperatures are found: TCDW and a lower T∗ indicative for an onset of Se out-of-plane atomic displacements. T∗ coincides with a DC resistivity maximum and the onset of the proposed gyrotropic (chiral) electronic structure. However, no indication for chirality is found. The relation between the atomic displacements and the transport properties is discussed in terms of Ti 3d and Se 4p states that only weakly couple to the CDW order.

Tags: charge-density-wave, crystal-symmetry, electrical-conductivity, experimental, marvel, paul-scherrer-institute, resonant-elastic-x-ray-scattering, snsf, structural-order-parameter, tise2, transition-metal-dichalcogenide, x-ray-diffraction
Effect of charge self-consistency in DFT+DMFT calculations for complex transition metal oxides

We investigate the effect of charge self-consistency (CSC) in density-functional theory plus dynamical mean-field theory calculations compared to simpler "one-shot" calculations for materials where interaction effects lead to a strong redistribution of electronic charges between different orbitals or between different sites. We focus on two systems close to a metal-insulator transition (MIT), for which the importance of CSC is currently not well understood. Specifically, we analyze the strain-related orbital polarization in the correlated metal CaVO3 and the spontaneous electronic charge disproportionation in the rare-earth nickelate LuNiO3. In both cases, we find that the CSC treatment reduces the charge redistribution compared to cheaper one-shot calculations. However, while the MIT in CaVO3 is only slightly shifted due to the reduced orbital polarization, the effect of the site polarization on the MIT in LuNiO3 is more subtle. Furthermore, we highlight the role of the double-counting correction in CSC calculations containing different inequivalent sites.

Tags: dftdmft, dynamical-mean-field-theory, electronic-properties-and-materials, electronic-structure, marvel
The role of water in host-guest interaction

One of the main applications of atomistic computer simulations is the calculation of ligand binding free energies. The accuracy of these calculations depends on the force field quality and on the thoroughness of configuration sampling. Sampling is an obstacle in simulations due to the frequent appearance of kinetic bottlenecks in the free energy landscape. Very often this difficulty is circumvented by enhanced sampling techniques. Typically, these techniques depend on the introduction of appropriate collective variables that are meant to capture the system's degrees of freedom. In ligand binding, water has long been known to play a key role, but its complex behaviour has proven difficult to fully capture. In this paper we combine machine learning with physical intuition to build a non-local and highly efficient water-describing collective variable. We use it to study a set of of host-guest systems from the SAMPL5 challenge. We obtain highly accurate binding free energies and good agreement with experiments. The role of water during the binding process is then analysed in some detail.

Tags: enhanced-sampling, erc, host-guest, ligand-binding, marveldd1, molecular-dynamics, neural-network, sampl5, snsf, water
Local kernel regression and neural network approaches to the conformational landscapes of oligopeptides

The application of machine learning to theoretical chemistry has made it possible to combine the accuracy of quantum chemical energetics with the thorough sampling of finite-temperature fluctuations. To reach this goal, a diverse set of methods has been proposed, ranging from simple linear models to kernel regression and highly nonlinear neural networks. Here we apply two widely different approaches to the same, challenging problem - the sampling of the conformational landscape of polypeptides at finite temperature. We develop a Local Kernel Regression (LKR) coupled with a supervised sparsity method and compare it with a more established approach based on Behler-Parrinello type Neural Networks. In the context of the LKR, we discuss how the supervised selection of the reference pool of environments is crucial to achieve accurate potential energy surfaces at a competitive computational cost and leverage the locality of the model to infer which chemical environments are poorly described by the DFTB baseline. We then discuss the relative merits of the two frameworks and perform Hamiltonian-reservoir replica-exchange Monte Carlo sampling and metadynamics simulations, respectively, to demonstrate that both frameworks can achieve converged and transferable sampling of the conformational landscape of complex and flexible biomolecules with comparable accuracy and computational cost.

Tags: behler-parrinello-neural-network, enhanced-sampling, epfl, erc, hamiltonian-replica-exchange, local-kernel-regression, machine-learning, marveldd1, oligopeptides, snsf, supervised-sparsity
Reaction pathway towards 7-atom-wide armchair graphene nanoribbon formation and identification of intermediate species on Au(111)

In this record we provide data supporitng our recent results discussed in the characterization of the fabrication process of graphene nanoribbons. The prototypical surface reaction of 10,10′-dibromo-9,9′-bianthryl (DBBA) toward the seven-atom-wide armchair graphene nanoribbon (7-AGNR) on the Au(111) surface has been investigated by means of vibrational spectroscopy, thermal desorption spectroscopy, and density functional theory. Specifically, a direct correlation between annealing temperature and the formation of various intermediate species is derived. By comparison of IR spectra with results from DFT calculations, an identification of reaction intermediates has been achieved, allowing for a precise mapping of individual reaction steps. Thereby, we identify a prior unknown partially dehalogenated and strongly tilted DBBA* monoradical species (DBBA-1Br) after mild annealing (380–450 K). This inclined adsorption geometry stabilizes the second Br atom, preventing full dehalogenation. According to our calculations, dimerization of DBBA-1Br reverses this inclination and provides an efficient way to enable abstraction of the second Br atom and initiate polyanthracene chain formation by means of DBBA* addition. As a competitive process to dimerization, a small number of the DBBA* monoradicals recombine with previously released bromine atoms, leading to associative DBBA desorption. In the course of thermal processing, hydrogen release signals planarization of the twisted anthracene units of DBBA by means of cyclodehydrogenation and formation of the final 7-AGNR. Based on the results of this work, an in-depth understanding of the on-surface synthesis of 7-AGNR on Au(111), starting with a DBBA molecular precursor, has been attained.

Tags: cscs, dfg, graphene-nanoribbons, ir-spectroscopy, marveldd3, on-surface-synthesis, snsf