68 research outputs found
van der Waals Bonding in Layered Compounds from Advanced Density-Functional First-Principles Calculations
Although the precise microscopic knowledge of van der Waals interactions is crucial for understanding bonding in weakly bonded layered compounds, very little quantitative information on the strength of interlayer interaction in these materials is available, either from experiments or simulations. Here, using many-body perturbation and advanced density-functional theory techniques, we calculate the interlayer binding and exfoliation energies for a large number of layered compounds and show that, independent of the electronic structure of the material, the energies for most systems are around 20 meV/Å2. This universality explains the successful exfoliation of a wide class of layered materials to produce two-dimensional systems, and furthers our understanding the properties of layered compounds in general.Peer reviewe
Role of van der Waals forces in the adsorption and diffusion of organic molecules on an insulating surface
The adsorption and diffusion of 3,4,9,10-perylene-tetracarboxylic-dianhydride (PTCDA) molecules on a nanostructured KBr (001) surface were investigated by combining noncontact atomic force microscopy (NC-AFM) and first-principles calculations. Atomically resolved measurements demonstrate trapping of PTCDA molecules in intentionally created rectangular monolayer-deep substrate pits and a preferential adsorption at kink sites. In order to understand the experimental results, we found that it was essential to include a first-principles treatment of the van der Waals interactions. We show that at some sites on the surface, 85% of the molecular binding is provided by van der Waals interactions, and in general it is always the dominant contribution to the adsorption energy. It also qualitatively changes molecular diffusion on the surface. Based on the specificity of the molecular interaction at kink sites, the species of the imaged ionic sublattice in the NC-AFM measurements could be identified.Peer reviewe
Big-Data-Driven Materials Science and its FAIR Data Infrastructure
This chapter addresses the forth paradigm of materials research -- big-data
driven materials science. Its concepts and state-of-the-art are described, and
its challenges and chances are discussed. For furthering the field, Open Data
and an all-embracing sharing, an efficient data infrastructure, and the rich
ecosystem of computer codes used in the community are of critical importance.
For shaping this forth paradigm and contributing to the development or
discovery of improved and novel materials, data must be what is now called FAIR
-- Findable, Accessible, Interoperable and Re-purposable/Re-usable. This sets
the stage for advances of methods from artificial intelligence that operate on
large data sets to find trends and patterns that cannot be obtained from
individual calculations and not even directly from high-throughput studies.
Recent progress is reviewed and demonstrated, and the chapter is concluded by a
forward-looking perspective, addressing important not yet solved challenges.Comment: submitted to the Handbook of Materials Modeling (eds. S. Yip and W.
Andreoni), Springer 2018/201
Ab initio van der Waals interactions in simulations of water alter structure from mainly tetrahedral to high-density-like
The structure of liquid water at ambient conditions is studied in ab initio
molecular dynamics simulations using van der Waals (vdW) density-functional
theory, i.e. using the new exchange-correlation functionals optPBE-vdW and
vdW-DF2. Inclusion of the more isotropic vdW interactions counteracts highly
directional hydrogen-bonds, which are enhanced by standard functionals. This
brings about a softening of the microscopic structure of water, as seen from
the broadening of angular distribution functions and, in particular, from the
much lower and broader first peak in the oxygen-oxygen pair-correlation
function (PCF), indicating loss of structure in the outer solvation shells. In
combination with softer non-local correlation terms, as in the new
parameterization of vdW-DF, inclusion of vdW interactions is shown to shift the
balance of resulting structures from open tetrahedral to more close-packed. The
resulting O-O PCF shows some resemblance with experiment for high-density water
(A. K. Soper and M. A. Ricci, Phys. Rev. Lett., 84:2881, 2000), but not
directly with experiment for ambient water. However, an O-O PCF consisting of a
linear combination of 70% from vdW-DF2 and 30% from experiment on low-density
liquid water reproduces near-quantitatively the experimental O-O PCF for
ambient water, indicating consistency with a two-liquid model with fluctuations
between high- and low-density regions
Random-phase approximation and its applications in computational chemistry and materials science
The random-phase approximation (RPA) as an approach for computing the
electronic correlation energy is reviewed. After a brief account of its basic
concept and historical development, the paper is devoted to the theoretical
formulations of RPA, and its applications to realistic systems. With several
illustrating applications, we discuss the implications of RPA for computational
chemistry and materials science. The computational cost of RPA is also
addressed which is critical for its widespread use in future applications. In
addition, current correction schemes going beyond RPA and directions of further
development will be discussed.Comment: 25 pages, 11 figures, published online in J. Mater. Sci. (2012
Spin-half paramagnetism in graphene induced by point defects
Using magnetization measurements, we show that point defects in graphene -
fluorine adatoms and irradiation defects (vacancies) - carry magnetic moments
with spin 1/2. Both types of defects lead to notable paramagnetism but no
magnetic ordering could be detected down to liquid helium temperatures. The
induced paramagnetism dominates graphene's low-temperature magnetic properties
despite the fact that maximum response we could achieve was limited to one
moment per approximately 1000 carbon atoms. This limitation is explained by
clustering of adatoms and, for the case of vacancies, by losing graphene's
structural stability.Comment: 14 pages, 14 figure
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
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