Soft and transferable pseudopotentials from multi-objective optimization

Ab initio pseudopotentials are a linchpin of modern molecular and condensed matter electronic structure calculations. In this work, we employ multi-objective optimization to maximize pseudopotential softness while maintaining high accuracy and transferability. To accomplish this, we develop a formulation in which softness and accuracy are simultaneously maximized, with accuracy determined by the ability to reproduce all-electron energy differences between Bravais lattice structures, whereupon the resulting Pareto frontier is scanned for the softest pseudopotential that provides the desired accuracy in established transferability tests. We employ an evolutionary algorithm to solve the multi-objective optimization problem and apply it to generate a comprehensive table of optimized norm-conserving Vanderbilt (ONCV) pseudopotentials (https://github.com/SPARC-X/SPMS-psps). We show that the resulting table is softer than existing tables of comparable accuracy, while more accurate than tables of comparable softness. The potentials thus afford the possibility to speed up calculations in a broad range of applications areas while maintaining high accuracy.Comment: 13 pages, 4 figure

Machine learning potentials for complex aqueous made

Simulation techniques based on accurate and efficient representations of potential energy surfaces are urgently needed for the understanding of complex systems such as solid–liquid interfaces. Here we present a machine learning framework that enables the efficient development and validation of models for complex aqueous systems. Instead of trying to deliver a globally optimal machine learning potential, we propose to develop models applicable to specific thermodynamic state points in a simple and user-friendly process. After an initial ab initio simulation, a machine learning potential is constructed with minimum human effort through a data-driven active learning protocol. Such models can afterward be applied in exhaustive simulations to provide reliable answers for the scientific question at hand or to systematically explore the thermal performance of ab initio methods. We showcase this methodology on a diverse set of aqueous systems comprising bulk water with different ions in solution, water on a titanium dioxide surface, and water confined in nanotubes and between molybdenum disulfide sheets. Highlighting the accuracy of our approach with respect to the underlying ab initio reference, the resulting models are evaluated in detail with an automated validation protocol that includes structural and dynamical properties and the precision of the force prediction of the models. Finally, we demonstrate the capabilities of our approach for the description of water on the rutile titanium dioxide (110) surface to analyze the structure and mobility of water on this surface. Such machine learning models provide a straightforward and uncomplicated but accurate extension of simulation time and length scales for complex systems

Roadmap on electronic structure codes in the exascale era

Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry, and device physics, is underscored by the large fraction of available public supercomputing resources devoted to these calculations. As we enter the exascale era, exciting new opportunities to increase simulation numbers, sizes, and accuracies present themselves. In order to realize these promises, the community of electronic structure software developers will however first have to tackle a number of challenges pertaining to the efficient use of new architectures that will rely heavily on massive parallelism and hardware accelerators. This roadmap provides a broad overview of the state-of-the-art in electronic structure calculations and of the various new directions being pursued by the community. It covers 14 electronic structure codes, presenting their current status, their development priorities over the next five years, and their plans towards tackling the challenges and leveraging the opportunities presented by the advent of exascale computing

Roadmap on Electronic Structure Codes in the Exascale Era

Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry and device physics, is underscored by the large fraction of available public supercomputing resources devoted to these calculations. As we enter the exascale era, exciting new opportunities to increase simulation numbers, sizes, and accuracies present themselves. In order to realize these promises, the community of electronic structure software developers will however first have to tackle a number of challenges pertaining to the efficient use of new architectures that will rely heavily on massive parallelism and hardware accelerators. This roadmap provides a broad overview of the state-of-the-art in electronic structure calculations and of the various new directions being pursued by the community. It covers 14 electronic structure codes, presenting their current status, their development priorities over the next five years, and their plans towards tackling the challenges and leveraging the opportunities presented by the advent of exascale computing

Roadmap on Electronic Structure Codes in the Exascale Era

Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry and device physics, is underscored by the large fraction of available public supercomputing resources devoted to these calculations. As we enter the exascale era, exciting new opportunities to increase simulation numbers, sizes, and accuracies present themselves. In order to realize these promises, the community of electronic structure software developers will however first have to tackle a number of challenges pertaining to the efficient use of new architectures that will rely heavily on massive parallelism and hardware accelerators. This roadmap provides a broad overview of the state-of-the-art in electronic structure calculations and of the various new directions being pursued by the community. It covers 14 electronic structure codes, presenting their current status, their development priorities over the next five years, and their plans towards tackling the challenges and leveraging the opportunities presented by the advent of exascale computing.Comment: Submitted as a roadmap article to Modelling and Simulation in Materials Science and Engineering; Address any correspondence to Vikram Gavini ([email protected]) and Danny Perez ([email protected]

Generating and grading 34 Optimised Norm-Conserving Vanderbilt Pseudopotentials for Actinides and Super Heavy Elements in the PseudoDojo

In the last decades, material discovery has been a very active research field driven by the necessity of new materials for different applications. This has also included materials incorporating heavy elements, beyond the stable isotopes of lead. Most of actinides exhibit unique properties that make them useful in various applications. Further, new heavy elements, taking the name of super-heavy elements, have been synthesized, filling previously empty space of Mendeleev periodic table. Their chemical bonding behaviour, of academic interest at present, would also benefit of state-of-the-art modelling approaches. In particular, in order to perform first-principles calculations with planewave basis sets, one needs corresponding pseudopotentials. In this work, we present a series of fully-relativistic optimised norm-conserving Vanderbilt pseudopotentials (ONCVPs) for thirty-four actinides and super-heavy elements. The scalar relativistic version of these ONCVPs is tested by comparing equations of states for crystals, obtained with \textsc{abinit} 9.6, with those obtained by all-electron zeroth-order regular approximation (ZORA) calculations performed with the Amsterdam Modelling Suite BAND code. $\Delta$-Gauge and $\Delta_1$-Gauge indicators are used to validate these pseudopotentials. This work is a contribution to the PseudoDojo project, in which pseudopotentials for the whole periodic table are developed and systematically tested. The fully-relativistic pseudopotential files (i.e. including spin-orbit coupling) are available on the PseudoDojo web-interface pseudo-dojo.org under the name NC FR (ONCVPSP) v4.x. Pseudopotentials are made available in psp8 and UPF2 formats, both convenient for \textsc{abinit}, the latter being also suitable for Quantum ESPRESSO

Atomic structures and properties of oxide interfaces

This thesis uses computational approaches, mainly first-principles methods, to study interfaces in oxide thin films. One of the difficulties in interface studies is the lack of definitive atomistic models, yet they are essential input for any calculations. Here, this problem is tackled by ab initio random structure searching (AIRSS), or more broadly speaking, random structure searching (RSS). The initial work studies the interfaces in vertically aligned nanocomposites (VANs) that consist of CeO₂ pillars embedded in a SrTiO₃ matrix. Enhanced ionic conductivity has been found in these VANs in prior studies, but the role of vertical interfaces is not explained. The initial interface searches are performed with interatomic potentials due to the large size of the interface, followed by refinement first-principles calculations. Based on the obtained structures, it is shown that the majority interfaces are unlikely to directly enhance ionic conductivity. However, a parallel solid-state O¹⁷ NMR study by our collaborators later obtained interface signals that suggest fast ionic conduction. First-principles NMR calculations show the observed signals are not consistent with the majority interface initially studied; instead, they can be assigned to the minority interfaces that are in different orientations. The following work studies the planar interfaces between epitaxial films of CeO₂ and STO substrates. A significant amount of research has been devoted to fluorite-perovskite interfaces since the controversial report of colossal ionic conductivity enhancement in YSZ/STO heterostructures. However, the exact atomic structures of these interfaces are not well understood. AIRSS is used for finding stable CeO₂/STO planar interfaces taking account of different terminations and local stoichiometries. When the STO terminates with a TiO₂ layer, a rock salt structured CeO layer emerges at the interface. On the other hand, with SrO termination, the stable structure contains a partially occupied anion lattice, which gives rise to lateral diffusion of oxygen anions in molecular dynamics simulations. In both cases, the interfaces are found to attract oxygen vacancies, which hinders ionic transport in the perpendicular direction. The subsequent work starts with addressing the perovskite-perovskite interfaces between La₀.₉Ba₀.₁MnO₃ (LBMO) and STO. LBMO is a ferromagnetic insulator with a relatively high ferromagnetic transition temperature, which makes it an ideal material for spintronics applications. However, thin films of LBMO are conductive except when the thickness is less than eight unit cells. This has been attributed to the octahedral proximity effects, as electron microscopy reveals that octahedral tilting in LBMO is suppressed near the interfaces. Whist some experimental observations are successfully accounted for by the first-principles calculations, the predicted tilt angle suppression is much weaker than that observed. By studying the response of octahedral networks to corner perturbations, it is shown that a competing LBMO phase with an alternative tilt configuration is stable as a result of interface coupling.Cambridge Commonwealth, European and International Trust China Scholarship Counci

Roadmap on Electronic Structure Codes in the Exascale Era

Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry and device physics, is underscored by the large fraction of available public supercomputing resources devoted to these calculations. As we enter the exascale era, exciting new opportunities to increase simulation numbers, sizes, and accuracies present themselves. In order to realize these promises, the community of electronic structure software developers will however first have to tackle a number of challenges pertaining to the efficient use of new architectures that will rely heavily on massive parallelism and hardware accelerators. This roadmap provides a broad overview of the state-of-the-art in electronic structure calculations and of the various new directions being pursued by the community. It covers 14 electronic structure codes, presenting their current status, their development priorities over the next five years, and their plans towards tackling the challenges and leveraging the opportunities presented by the advent of exascale computing

A universal interatomic potential for perovskite oxides

With their celebrated structural and chemical flexibility, perovskite oxides have served as a highly adaptable material platform for exploring emergent phenomena arising from the interplay between different degrees of freedom. Molecular dynamics (MD) simulations leveraging classical force fields, commonly depicted as parameterized analytical functions, have made significant contributions in elucidating the atomistic dynamics and structural properties of crystalline solids including perovskite oxides. However, the force fields currently available for solids are rather specific and offer limited transferability, making it time-consuming to use MD to study new materials systems since a new force field must be parameterized and tested first. The lack of a generalized force field applicable to a broad spectrum of solid materials hinders the facile deployment of MD in computer-aided materials discovery (CAMD). Here, by utilizing a deep-neural network with a self-attention scheme, we have developed a unified force field that enables MD simulations of perovskite oxides involving 14 metal elements and conceivably their solid solutions with arbitrary compositions. Notably, isobaric-isothermal ensemble MD simulations with this model potential accurately predict the experimental phase transition sequences for several markedly different ferroelectric oxides, including a 6-element ternary solid solution, Pb(In$_{1/2}$Nb$_{1/2}$)O$_3$--Pb(Mg$_{1/3}$Nb$_{2/3}$)O$_3$--PbTiO$_3$. We believe the universal interatomic potential along with the training database, proposed regression tests, and the auto-testing workflow, all released publicly, will pave the way for a systematic improvement and extension of a unified force field for solids, potentially heralding a new era in CAMD.Comment: 18 pages, 4 figure

Universal QM/MM Approaches for General Nanoscale Applications

Hybrid quantum mechanics/molecular mechanics (QM/MM) hybrid models allow one to address chemical phenomena in complex molecular environments. However, they are tedious to construct and they usually require significant manual preprocessing and expertise. As a result, these models may not be easily transferable to new application areas and the many parameters are not easy to adjust to reference data that are typically scarce. Therefore, it has been difficult to devise automated procedures of controllable accuracy, which makes such type of modelling far from being standardized or of black-box type. Although diverse best-practice protocols have been set up for the construction of individual components of a QM/MM model (e.g., the MM potential, the type of embedding, the choice of the QM region), no automated procedures are available for all steps of the QM/MM model construction. Here, we review the state of the art of QM/MM modeling with a focus on automation. We elaborate on the MM model parametrization, on atom-economical physically-motivated QM region selection, and on embedding schemes that incorporate mutual polarization as critical components of the QM/MM model. In view of the broad scope of the field, we mostly restrict the discussion to methodologies that build de novo models based on first-principles data, on uncertainty quantification, and on error mitigation with a high potential for automation. Ultimately, it is desirable to be able to set up reliable QM/MM models in a fast and efficient automated way without being constrained by some specific chemical or technical limitations.Comment: 54 pages, 3 figures, 1 tabl