Growth and Redox Properties of Boron on Al(111): Competing Affinities in the Case of Honeycomb AlB2.

The complexity of the geometric and electronic structure of boron allotropes is associated with the multicentric bonding character and the consequent B polymorphism. When growth is limited to two-dimensions (2D), the structural and electronic confinement yields the borophenes family, where the interaction with the templating substrate actually determines the stability of inequivalent boron phases. We report here a detailed study of the growth of the honeycomb AlB2 phase on Al(111), followed by an investigation of its oxidation and reduction properties. By means of a combined experimental and theoretical approach, we show that the structure of the B/Al interface is affected by the complex interplay between B, Al, and common reactive agents like oxygen and hydrogen. While kinetic effects associated with diffusion and strain release influence the AlB2 growth in vacuo, Al, B, O, and H chemical affinities determine its redox behavior. Reduction with atomic hydrogen involves the B layer and yields an ordered honeycomb borophane H/AlB2 phase. Instead, oxidation takes place at the Al interface, giving origin to buried and 1D surface aluminum oxide phases.

From borophene polymorphs towards a single honeycomb borophane phase: reduction of hexagonal boron layers on Al(111).

The recent interest in characterizing 2D boron polymorphs has led to claims of the first stabilization of a honeycomb phase with conical Dirac-like electron dispersion. However, the synthesis of chemically stable, single, and homogeneous 2D boron phases still represents a significant experimental challenge. This is ascribed to the intrinsic boron electronic configuration that, at variance with carbon, leads to the formation of multi-center covalent bonds. External charge compensation by substrate-induced doping can steer the geometry of the layer, both in the buckling and in the density of B vacancies, like in the case of the recently achieved stabilization of honeycomb boron layers on Al(111). The price to pay is however a strong boron-support interaction, resulting in general in a limiting kinetic hindrance with respect to the synthesis of homogenous single phases. In the specific case of Al(111) an AlB2 layer is known to form at the surface, quite far from a desirable quasi-freestanding borophene monolayer and at variance with graphene, which can be easily synthesized in an almost freestanding configuration e.g. on Ir(111). We provide here evidence for the (reversible) formation of well-ordered honeycomb borophane upon hydrogenation of the honeycomb boron phase on Al(111).

Data-driven simulation and characterisation of gold nanoparticle melting.

The simulation and analysis of the thermal stability of nanoparticles, a stepping stone towards their application in technological devices, require fast and accurate force fields, in conjunction with effective characterisation methods. In this work, we develop efficient, transferable, and interpretable machine learning force fields for gold nanoparticles based on data gathered from Density Functional Theory calculations. We use them to investigate the thermodynamic stability of gold nanoparticles of different sizes (1 to 6 nm), containing up to 6266 atoms, concerning a solid-liquid phase change through molecular dynamics simulations. We predict nanoparticle melting temperatures in good agreement with available experimental data. Furthermore, we characterize the solid-liquid phase change mechanism employing an unsupervised learning scheme to categorize local atomic environments. We thus provide a data-driven definition of liquid atomic arrangements in the inner and surface regions of a nanoparticle and employ it to show that melting initiates at the outer layers.

Compact atomic descriptors enable accurate predictions via linear models.

We probe the accuracy of linear ridge regression employing a three-body local density representation derived from the atomic cluster expansion. We benchmark the accuracy of this framework in the prediction of formation energies and atomic forces in molecules and solids. We find that such a simple regression framework performs on par with state-of-the-art machine learning methods which are, in most cases, more complex and more computationally demanding. Subsequently, we look for ways to sparsify the descriptor and further improve the computational efficiency of the method. To this aim, we use both principal component analysis and least absolute shrinkage operator regression for energy fitting on six single-element datasets. Both methods highlight the possibility of constructing a descriptor that is four times smaller than the original with a similar or even improved accuracy. Furthermore, we find that the reduced descriptors share a sizable fraction of their features across the six independent datasets, hinting at the possibility of designing material-agnostic, optimally compressed, and accurate descriptors.

Finding Reaction Pathways and Transition States: r-ARTn and d-ARTn as an Efficient and Versatile Alternative to String Approaches.

Finding transition states and diffusion pathways is essential to understand the evolution of materials and chemical reactions. Such characterization is hampered by the heavy computation costs associated with exploring energy landscapes at ab initio accuracy. Here, we revisit the activation-relaxation technique (ARTn) to considerably reduce its costs when used with the density functional theory and propose three adapted versions of the algorithm to efficiently (i) explore the energy landscape of complex materials with the knowledge of a single minimum (ARTn); (ii) identify a transition state when two minima or a guess transition state is given (refining ART or r-ART); and (iii) reconstruct complex pathways between two given states (directed ART or d-ART). We show the application of these three variants on benchmark examples and on various complex defects in silicon. For the latter, the presented improvements to ART lead to much more precise transition states while being 2 to 6 times faster than the commonly used string methods such as the climbing image nudged elastic band method (CI-NEB).

The CECAM electronic structure library and the modular software development paradigm.

First-principles electronic structure calculations are now accessible to a very large community of users across many disciplines, thanks to many successful software packages, some of which are described in this special issue. The traditional coding paradigm for such packages is monolithic, i.e., regardless of how modular its internal structure may be, the code is built independently from others, essentially from the compiler up, possibly with the exception of linear-algebra and message-passing libraries. This model has endured and been quite successful for decades. The successful evolution of the electronic structure methodology itself, however, has resulted in an increasing complexity and an ever longer list of features expected within all software packages, which implies a growing amount of replication between different packages, not only in the initial coding but, more importantly, every time a code needs to be re-engineered to adapt to the evolution of computer hardware architecture. The Electronic Structure Library (ESL) was initiated by CECAM (the European Centre for Atomic and Molecular Calculations) to catalyze a paradigm shift away from the monolithic model and promote modularization, with the ambition to extract common tasks from electronic structure codes and redesign them as open-source libraries available to everybody. Such libraries include "heavy-duty" ones that have the potential for a high degree of parallelization and adaptation to novel hardware within them, thereby separating the sophisticated computer science aspects of performance optimization and re-engineering from the computational science done by, e.g., physicists and chemists when implementing new ideas. We envisage that this modular paradigm will improve overall coding efficiency and enable specialists (whether they be computer scientists or computational scientists) to use their skills more effectively and will lead to a more dynamic evolution of software in the community as well as lower barriers to entry for new developers. The model comes with new challenges, though. The building and compilation of a code based on many interdependent libraries (and their versions) is a much more complex task than that of a code delivered in a single self-contained package. Here, we describe the state of the ESL, the different libraries it now contains, the short- and mid-term plans for further libraries, and the way the new challenges are faced. The ESL is a community initiative into which several pre-existing codes and their developers have contributed with their software and efforts, from which several codes are already benefiting, and which remains open to the community.

Quantum ESPRESSO toward the exascale.

Quantum ESPRESSO is an open-source distribution of computer codes for quantum-mechanical materials modeling, based on density-functional theory, pseudopotentials, and plane waves, and renowned for its performance on a wide range of hardware architectures, from laptops to massively parallel computers, as well as for the breadth of its applications. In this paper, we present a motivation and brief review of the ongoing effort to port Quantum ESPRESSO onto heterogeneous architectures based on hardware accelerators, which will overcome the energy constraints that are currently hindering the way toward exascale computing.

ζ-Glycine: insight into the mechanism of a polymorphic phase transition.

Glycine is the simplest and most polymorphic amino acid, with five phases having been structurally characterized at atmospheric or high pressure. A sixth form, the elusive ζ phase, was discovered over a decade ago as a short-lived intermediate which formed as the high-pressure ∊ phase transformed to the γ form on decompression. However, its structure has remained unsolved. We now report the structure of the ζ phase, which was trapped at 100 K enabling neutron powder diffraction data to be obtained. The structure was solved using the results of a crystal structure prediction procedure based on fully ab initio energy calculations combined with a genetic algorithm for searching phase space. We show that the fate of ζ-glycine depends on its thermal history: although at room temperature it transforms back to the γ phase, warming the sample from 100 K to room temperature yielded ß-glycine, the least stable of the known ambient-pressure polymorphs.

Reproducibility in density functional theory calculations of solids.

The widespread popularity of density functional theory has given rise to an extensive range of dedicated codes for predicting molecular and crystalline properties. However, each code implements the formalism in a different way, raising questions about the reproducibility of such predictions. We report the results of a community-wide effort that compared 15 solid-state codes, using 40 different potentials or basis set types, to assess the quality of the Perdew-Burke-Ernzerhof equations of state for 71 elemental crystals. We conclude that predictions from recent codes and pseudopotentials agree very well, with pairwise differences that are comparable to those between different high-precision experiments. Older methods, however, have less precise agreement. Our benchmark provides a framework for users and developers to document the precision of new applications and methodological improvements.

Nature of the Volume Isotope Effect in Ice.

The substitution of hydrogen (H) by deuterium (D) in ice Ih and in its H-ordered version, ice XI, produces an anomalous form of volume isotope effect (VIE), i.e., volume expansion. This VIE contrasts with the normal VIE (volume contraction) predicted in ice-VIII and in its H-disordered form, ice VII. Here we investigate the VIE in ice XI and in ice VIII using first principles quasiharmonic calculations. We conclude that normal and anomalous VIEs can be produced in ice VIII and ice XI in sequence by application of pressure (ice XI starting at negative pressures) followed by a third type-anomalous VIE with zero-point volume contraction. The latter should also contribute to the isotope effect in the ice VII → ice X transition. The predicted change between normal and anomalous VIE in ice VIII at 14.3 GPa and 300 K is well reproduced experimentally in ice VII using x-ray diffraction measurements. The present discussion of the VIE is general, and conclusions should be applicable to other solid phases of H(2)O, possibly to liquid water under pressure, and to other H-bonded materials.

Substrate doping: A strategy for enhancing reactivity on gold nanocatalysts by tuning sp bands.

We suggest that the reactivity of Au nanocatalysts can be greatly increased by doping the oxide substrate on which they are placed with an electron donor. To demonstrate this, we perform density functional theory calculations on a model system consisting of a 20-atom gold cluster placed on a MgO substrate doped with Al atoms. We show that not only does such substrate doping switch the morphology of the nanoparticles from the three-dimensional tetrahedral form to the two-dimensional planar form, but it also significantly lowers the barrier for oxygen dissociation by an amount proportional to the dopant concentration. At a doping level of 2.78%, the dissociation barrier is reduced by more than half, which corresponds to a speeding up of the oxygen dissociation rate by five orders of magnitude at room temperature. This arises from a lowering in energy of the s and p states of Au. The d states are also lowered in energy, however, this by itself would have tended to reduce reactivity. We propose that a suitable measure of the reactivity of Au nanoparticles is the difference in energy of sp and d states.

Isobaric first-principles molecular dynamics of liquid water with nonlocal van der Waals interactions.

We investigate the structural properties of liquid water at near ambient conditions using first-principles molecular dynamics simulations based on a semilocal density functional augmented with nonlocal van der Waals interactions. The adopted scheme offers the advantage of simulating liquid water at essentially the same computational cost of standard semilocal functionals. Applied to the water dimer and to ice Ih, we find that the hydrogen-bond energy is only slightly enhanced compared to a standard semilocal functional. We simulate liquid water through molecular dynamics in the NpH statistical ensemble allowing for fluctuations of the system density. The structure of the liquid departs from that found with a semilocal functional leading to more compact structural arrangements. This indicates that the directionality of the hydrogen-bond interaction has a diminished role as compared to the overall attractions, as expected when dispersion interactions are accounted for. This is substantiated through a detailed analysis comprising the study of the partial radial distribution functions, various local order indices, the hydrogen-bond network, and the selfdiffusion coefficient. The explicit treatment of the van der Waals interactions leads to an overall improved description of liquid water.

Ag-Cu catalysts for ethylene epoxidation: selectivity and activity descriptors.

Ag-Cu alloy catalysts for ethylene epoxidation have been shown to yield higher selectivity towards ethylene oxide compared to pure Ag, the unique catalyst employed in the industrial process. Previous studies showed that under oxidizing conditions Cu forms oxide layers on top of Ag. Using first-principles atomistic simulations based on density functional theory, we investigate the reaction mechanism on the thin oxide layer structures and establish the reasons for the improved selectivity. We extend the range of applicability of the selectivity descriptor proposed by Kokalj et al. [J. Catal. 254, 304 (2008)], based on binding energies of reactants, intermediates, and products, by refitting its parameters so as to include thin oxide layer catalysts. We show that the selectivity is mainly controlled by the relative strength of the metal-carbon vs. metal-oxygen bonds, while the height of the reaction barriers mostly depend on the binding energy of the common oxametallacycle intermediate.

Structural evolution of amino acid crystals under stress from a non-empirical density functional.

Use of the non-local correlation functional vdW-DF (from 'van der Waals density functional'; Dion M et al 2004 Phys. Rev. Lett. 92 246401) has become a popular approach for including van der Waals interactions within density functional theory. In this work, we extend the vdW-DF theory and derive the corresponding stress tensor in a fashion similar to the LDA and GGA approach, which allows for a straightforward implementation in any electronic structure code. We then apply our methodology to investigate the structural evolution of amino acid crystals of glycine and l-alanine under pressure up to 10 GPa-with and without van der Waals interactions-and find that for an accurate description of intermolecular interactions and phase transitions in these systems, the inclusion of van der Waals interactions is crucial. For glycine, calculations including the vdW-DF (vdW-DF-c09x) functional are found to systematically overestimate (underestimate) the crystal lattice parameters, yet the stability ordering of the different polymorphs is determined accurately, at variance with the GGA case. In the case of l-alanine, our vdW-DF results agree with recent experiments that question the phase transition reported for this crystal at 2.3 GPa, as the a and c cell parameters happen to become equal but no phase transition is observed.

Complete 13C NMR chemical shifts assignment for cholesterol crystals by combined CP-MAS spectral editing and ab initio GIPAW calculations with dispersion forces.

We report here the first fully ab initio determination of (13)C NMR spectra for several crystal structures of cholesterol, observed in various biomaterials. We combine Gauge-Including Projector Augmented Waves (GIPAW) calculations at relaxed structures, fully including dispersion forces, with Magic Angle Spinning Solid State NMR experiments and spectral editing to achieve a detailed interpretation of the complex NMR spectra of cholesterol crystals. By introducing an environment-dependent secondary referencing scheme in our calculations, not only do we reproduce the characteristic spectral features of the different crystalline polymorphs, thus clearly discriminating among them, but also closely represent the spectrum in the region of several highly overlapping peaks. This, in combination with spectral editing, allows us to provide a complete peak assignment for monohydrate (ChM) and low-temperature anhydrous (ChAl) crystal polymorphs. Our results show that the synergy between ab initio calculations and refined experimental techniques can be exploited for an accurate and efficient NMR crystallography of complex systems of great interest for biomaterial studies. The method is general in nature and can be applied for studies of various complex biomaterials.

Tuning the morphology of gold clusters by substrate doping.

The morphology of small metal clusters can have a big impact on their electronic, magnetic, and chemical properties. This has been shown earlier, for example, for Au(20) clusters on MgO(001), where planar and tetrahedral geometries are possible for the gold atoms. While the planar geometry is more desirable for catalytic applications, it is disfavored in the usual situation. While earlier suggestions that have been made for tilting this balance in favor of the planar isomer are of considerable fundamental interest, they do not easily lend themselves to practical applications. Here, we suggest a conceptually simple but practicable way of achieving the same goal: viz., by doping the MgO substrate with Al atoms. We show, by performing density functional theory calculations, that this stabilizes the planar over the tetrahedral arrangement by an energy difference that is linearly proportional to the dopant concentration and is insensitive to the position of the dopant atom. The charge transferred to the Au cluster also depends monotonically on the doping concentration. This work is of interest for possible applications in the field of gold nanocatalysis.

QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials.

QUANTUM ESPRESSO is an integrated suite of computer codes for electronic-structure calculations and materials modeling, based on density-functional theory, plane waves, and pseudopotentials (norm-conserving, ultrasoft, and projector-augmented wave). The acronym ESPRESSO stands for opEn Source Package for Research in Electronic Structure, Simulation, and Optimization. It is freely available to researchers around the world under the terms of the GNU General Public License. QUANTUM ESPRESSO builds upon newly-restructured electronic-structure codes that have been developed and tested by some of the original authors of novel electronic-structure algorithms and applied in the last twenty years by some of the leading materials modeling groups worldwide. Innovation and efficiency are still its main focus, with special attention paid to massively parallel architectures, and a great effort being devoted to user friendliness. QUANTUM ESPRESSO is evolving towards a distribution of independent and interoperable codes in the spirit of an open-source project, where researchers active in the field of electronic-structure calculations are encouraged to participate in the project by contributing their own codes or by implementing their own ideas into existing codes.

Toward an accurate and efficient theory of physisorption. I. Development of an augmented density-functional theory model.

Currently available density functionals cannot describe the dispersion component of the interaction energy present in weakly bound complexes. Moreover, the exchange energy as obtained from the density-functional theory is often incorrect. Examples of problematic cases include clusters of van der Waals-bound rare-gas atoms and most hydrogen-bonded molecular systems. Thus, accurate ab initio methods to treat intermolecular forces should be used in such systems. These methods are, however, too slow to be applicable to the large systems needed to model adsorption. This is why DFT continues to be used, where, in addition, a quite common compensation of errors sometimes produces some sort of agreement with the corresponding experimental data. In this paper, we analyze in detail the inadequacy of standard DFT for describing the weak binding present in a few rare gas-rare gas, metal atom-rare gas, and metal atom-metal atom dimers.Inspired by the success of the Hartree-Fock plus (damped) dispersion (HFD) method, we test the use of an improved hybrid model in which to a density-functional interaction energy (with corrected exchange and avoidance of double-counting of dispersion), a (damped) dispersion expansion is added in the usual way.Comparisons with accurate theoretical or experimental benchmarks show that our DFdD method using the revPBEx or revPBEx+VWNc functionals and accurate dispersion coefficients is found to recover the interaction energy curves very well for many of the tested systems. The sec and paper in this series will describe the use of the DFdD method for physisorption for the previously well-studied (but not solved) case of Xe/Cu(111).

Interplay between bonding and magnetism in the binding of NO to Rh clusters.

We have studied the binding of NO to small Rh clusters, containing one to five atoms, using density functional theory in both spin-polarized and non-spin-polarized forms. We find that NO bonds more strongly to Rh clusters than it does to Rh(100) or Rh(111), suggesting that Rh clusters may be good catalysts for NO reduction. However, binding to NO also quenches the magnetism of the clusters. This (local) effect results in reducing the magnitude of the NO binding energy, and also washes out the clear size-dependent trend observed in the nonmagnetic case. Our results illustrate the competition present between the tendencies to bond and to magnetize, in small clusters.

Core level shifts of undercoordinated Pt atoms.

We present the results of high-energy resolution core level photoelectron spectroscopy experiments paralleled by density functional theory calculations to investigate the electronic structure of highly undercoordinated Pt atoms adsorbed on Pt(111) and its correlation with chemical activity. Pt4f(7/2) core level binding energies corresponding to atoms in different configurations are shown to be very sensitive not only to the local atomic coordination number but also to the interatomic bond lengths. Our results are rationalized by introducing an indicator, the effective coordination, which includes both contributions. The calculated energy center of the valence 5d-band density of states, which is a well known depicter of the surface chemical reactivity, shows a noteworthy correlation with the Pt4f(7/2) core level shifts and with the effective coordination.