361 research outputs found
Long-Range Repulsion Between Spatially Confined van der Waals Dimers
It is an undisputed textbook fact that non-retarded van der Waals (vdW)
interactions between isotropic dimers are attractive, regardless of the
polarizability of the interacting systems or spatial dimensionality. The
universality of vdW attraction is attributed to the dipolar coupling between
fluctuating electron charge densities. Here we demonstrate that the long-range
interaction between \textit{spatially confined} vdW dimers becomes repulsive
when accounting for the full Coulomb interaction between charge fluctuations.
Our analytic results are obtained by using the Coulomb potential as a
perturbation over dipole-correlated states for two quantum harmonic oscillators
embedded in spaces with reduced dimensionality, however the long-range
repulsion is expected to be a general phenomenon for spatially-confined quantum
systems. We suggest optical experiments to test our predictions, analyze their
relevance in the context of intermolecular interactions in nanoscale
environments, and rationalize the recent observation of anomalously strong
screening of the lateral vdW interactions between aromatic hydrocarbons
adsorbed on metal surfaces.Comment: 2 figure
Quantum Tunneling of Thermal Protons Through Pristine Graphene
Atomically thin two-dimensional materials such as graphene and hexagonal
boron nitride have recently been found to exhibit appreciable permeability to
thermal protons, making these materials emerging candidates for separation
technologies [S. Hu et al., Nature 516, 227 (2014); M. Lozada-Hidalgo et al.,
Science 351, 68 (2016).]. These remarkable findings remain unexplained by
density-functional electronic structure calculations, which instead yield
barriers that exceed by 1.0 eV those found in experiments. Here we resolve this
puzzle by demonstrating that the proton transfer through pristine graphene is
driven by quantum nuclear effects, which substantially reduce the transport
barrier by up to 1.4 eV compared to the results of classical molecular dynamics
(MD). Our Feynman-Kac path-integral MD simulations unambiguously reveal the
quantum tunneling mechanism of strongly interacting hydrogen ions through
two-dimensional materials. In addition, we predict a strong isotope effect of 1
eV on the transport barrier for graphene in vacuum and at room temperature.
These findings not only shed light on the graphene permeability to protons and
deuterons, but also offer new insights for controlling the underlying quantum
ion transport mechanisms in nanostructured separation membranes
Fluctuational Electrodynamics in Atomic and Macroscopic Systems: van der Waals Interactions and Radiative Heat Transfer
We present an approach to describing fluctuational electrodynamic (FED)
interactions, particularly van der Waals (vdW) interactions as well as
radiative heat transfer (RHT), between material bodies of vastly different
length scales, allowing for going between atomistic and continuum treatments of
the response of each of these bodies as desired. Any local continuum
description of electromagnetic (EM) response is compatible with our approach,
while atomistic descriptions in our approach are based on effective electronic
and nuclear oscillator degrees of freedom, encapsulating dissipation,
short-range electronic correlations, and collective nuclear vibrations
(phonons). While our previous works using this approach have focused on
presenting novel results, this work focuses on the derivations underlying these
methods. First, we show how the distinction between "atomic" and "macroscopic"
bodies is ultimately somewhat arbitrary, as formulas for vdW free energies and
RHT look very similar regardless of how the distinction is drawn. Next, we
demonstrate that the atomistic description of material response in our approach
yields EM interaction matrix elements which are expressed in terms of
analytical formulas for compact bodies or semianalytical formulas based on
Ewald summation for periodic media; we use this to compute vdW interaction free
energies as well as RHT powers among small biological molecules in the presence
of a metallic plate as well as between parallel graphene sheets in vacuum,
showing strong deviations from conventional macroscopic theories due to the
confluence of geometry, phonons, and EM retardation effects. Finally, we
propose formulas for efficient computation of FED interactions among material
bodies in which those that are treated atomistically as well as those treated
through continuum methods may have arbitrary shapes, extending previous
surface-integral techniques.Comment: 25 pages, 5 figures, 2 appendice
Many-body dispersion effects in the binding of adsorbates on metal surfaces
A correct description of electronic exchange and correlation effects for
molecules in contact with extended (metal) surfaces is a challenging task for
first-principles modeling. In this work we demonstrate the importance of
collective van der Waals dispersion effects beyond the pairwise approximation
for organic--inorganic systems on the example of atoms, molecules, and
nanostructures adsorbed on metals. We use the recently developed many-body
dispersion (MBD) approach in the context of density-functional theory [Phys.
Rev. Lett. 108, 236402 (2012); J. Chem. Phys. 140, 18A508 (2014)] and assess
its ability to correctly describe the binding of adsorbates on metal surfaces.
We briefly review the MBD method and highlight its similarities to
quantum-chemical approaches to electron correlation in a quasiparticle picture.
In particular, we study the binding properties of xenon,
3,4,9,10-perylene-tetracarboxylic acid (PTCDA), and a graphene sheet adsorbed
on the Ag(111) surface. Accounting for MBD effects we are able to describe
changes in the anisotropic polarizability tensor, improve the description of
adsorbate vibrations, and correctly capture the adsorbate--surface interaction
screening. Comparison to other methods and experiment reveals that inclusion of
MBD effects improves adsorption energies and geometries, by reducing the
overbinding typically found in pairwise additive dispersion-correction
approaches
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
We introduce a machine learning model to predict atomization energies of a
diverse set of organic molecules, based on nuclear charges and atomic positions
only. The problem of solving the molecular Schr\"odinger equation is mapped
onto a non-linear statistical regression problem of reduced complexity.
Regression models are trained on and compared to atomization energies computed
with hybrid density-functional theory. Cross-validation over more than seven
thousand small organic molecules yields a mean absolute error of ~10 kcal/mol.
Applicability is demonstrated for the prediction of molecular atomization
potential energy curves
Long-range correlation energy calculated from coupled atomic response functions
An accurate determination of the electron correlation energy is essential for
describing the structure, stability, and function in a wide variety of systems,
ranging from gas-phase molecular assemblies to condensed matter and
organic/inorganic interfaces. Even small errors in the correlation energy can
have a large impact on the description of chemical and physical properties in
the systems of interest. In this context, the development of efficient
approaches for the accurate calculation of the long-range correlation energy
(and hence dispersion) is the main challenge. In the last years a number of
methods have been developed to augment density functional approximations via
dispersion energy corrections, but most of these approaches ignore the
intrinsic many-body nature of correlation effects, leading to inconsistent and
sometimes even qualitatively incorrect predictions. Here we build upon the
recent many-body dispersion (MBD) framework, which is intimately linked to the
random-phase approximation for the correlation energy. We separate the
correlation energy into short-range contributions that are modeled by
semi-local functionals and long-range contributions that are calculated by
mapping the complex all-electron problem onto a set of atomic response
functions coupled in the dipole approximation. We propose an effective
range-separation of the coupling between the atomic response functions that
extends the already broad applicability of the MBD method to non-metallic
materials with highly anisotropic responses, such as layered nanostructures.
Application to a variety of high-quality benchmark datasets illustrates the
accuracy and applicability of the improved MBD approach, which offers the
prospect of first-principles modeling of large structurally complex systems
with an accurate description of the long-range correlation energy.Comment: 15 pages, 3 figure
Force Field Analysis Software and Tools (FFAST): Assessing Machine Learning Force Fields Under the Microscope
As the sophistication of Machine Learning Force Fields (MLFF) increases to
match the complexity of extended molecules and materials, so does the need for
tools to properly analyze and assess the practical performance of MLFFs. To go
beyond average error metrics and into a complete picture of a model's
applicability and limitations, we develop FFAST (Force Field Analysis Software
and Tools): a cross-platform software package designed to gain detailed
insights into a model's performance and limitations, complete with an
easy-to-use graphical user interface. The software allows the user to gauge the
performance of many popular state-of-the-art MLFF models on various popular
dataset types, providing general prediction error overviews, outlier detection
mechanisms, atom-projected errors, and more. It has a 3D visualizer to find and
picture problematic configurations, atoms, or clusters in a large dataset. In
this paper, the example of the MACE and Nequip models are used on two datasets
of interest -- stachyose and docosahexaenoic acid (DHA) -- to illustrate the
use cases of the software. With it, it was found that carbons and oxygens
involved in or near glycosidic bonds inside the stachyose molecule present
increased prediction errors. In addition, prediction errors on DHA rise as the
molecule folds, especially for the carboxylic group at the edge of the
molecule. We emphasize the need for a systematic assessment of MLFF models for
ensuring their successful application to study the dynamics of molecules and
materials.Comment: 22 pages, 11 figure
Interatomic Methods for the Dispersion Energy Derived from the Adiabatic Connection Fluctuation-Dissipation Theorem
Interatomic pairwise methods are currently among the most popular and
accurate ways to include dispersion energy in density functional theory (DFT)
calculations. However, when applied to more than two atoms, these methods are
still frequently perceived to be based on \textit{ad hoc} assumptions, rather
than a rigorous derivation from quantum mechanics. Starting from the adiabatic
connection fluctuation-dissipation (ACFD) theorem, an exact expression for the
electronic exchange-correlation energy, we demonstrate that the pairwise
interatomic dispersion energy for an arbitrary collection of isotropic
polarizable dipoles emerges from the second-order expansion of the ACFD
formula. Moreover, for a system of quantum harmonic oscillators coupled through
a dipole--dipole potential, we prove the equivalence between the full
interaction energy obtained from the Hamiltonian diagonalization and the ACFD
correlation energy in the random-phase approximation. This property makes the
Hamiltonian diagonalization an efficient method for the calculation of the
many-body dispersion energy. In addition, we show that the switching function
used to damp the dispersion interaction at short distances arises from a
short-range screened Coulomb potential, whose role is to account for the
spatial spread of the individual atomic dipole moments. By using the ACFD
formula we gain a deeper understanding of the approximations made in the
interatomic pairwise approaches, providing a powerful formalism for further
development of accurate and efficient methods for the calculation of the
dispersion energy
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