arXiv subjects

Angelos Michaelides

Publications and source records attributed to Angelos Michaelides.

At least 91 records · Page 5Linked to original sources

arXiv2018

Heterogeneous Seeded Molecular Dynamics as a Tool to Probe the Ice Nucleating Ability of Crystalline Surfaces

Ice nucleation plays a significant role in a large number of natural and technological processes, but it is challenging to investigate experimentally because of the small time (ns) and short length scales (nm) involved. On the other hand, conventional molecular simulations struggle to cope with the relatively long timescale required for critical ice nuclei to form. One way to tackle this issue is to take advantage of free energy or path sampling techniques. Unfortunately, these are computationally costly. Seeded molecular dynamics is a much less demanding alternative that has been successfully applied already to study the homogeneous freezing of water. However, in the case of heterogeneous ice nucleation, nature's favourite route to form ice, an array of suitable interfaces between the ice seeds and the substrate of interest has to be built - and this is no trivial task. In this paper, we present a Heterogeneous SEEDing approach (HSEED) which harnesses a random structure search framework to tackle the ice-substrate challenge, thus enabling seeded molecular dynamics simulations of heterogeneous ice nucleation on crystalline surfaces. We validate the HSEED framework by investigating the nucleation of ice on: (i) model crystalline surfaces, using the coarse-grained mW model; and (ii) cholesterol crystals, employing the fully atomistic TIP4P/Ice water model. We show that the HSEED technique yields results in excellent agreement with both metadynamics and forward flux sampling simulations. Because of its computational efficiency, the HSEED method allows one to rapidly assess the ice nucleation ability of whole libraries of crystalline substrates - a long-awaited computational development in e.g. atmospheric science.

cond-mat.mtrl-sci↗

arXiv2018

Fast and accurate quantum Monte Carlo for molecular crystals

Computer simulation plays a central role in modern day materials science. The utility of a given computational approach depends largely on the balance it provides between accuracy and computational cost. Molecular crystals are a class of materials of great technological importance which are challenging for even the most sophisticated \emph{ab initio} electronic structure theories to accurately describe. This is partly because they are held together by a balance of weak intermolecular forces but also because the primitive cells of molecular crystals are often substantially larger than those of atomic solids. Here, we demonstrate that diffusion quantum Monte Carlo (DMC) delivers sub-chemical accuracy for a diverse set of molecular crystals at a surprisingly moderate computational cost. As such, we anticipate that DMC can play an important role in understanding and predicting the properties of a large number of molecular crystals, including those built from relatively large molecules which are far beyond reach of other high accuracy methods.

physics.chem-ph↗

arXiv2017

A Machine Learning Potential for Graphene

We present an accurate interatomic potential for graphene, constructed using the Gaussian Approximation Potential (GAP) machine learning methodology. This GAP model obtains a faithful representation of a density functional theory (DFT) potential energy surface, facilitating highly accurate (approaching the accuracy of ab initio methods) molecular dynamics simulations. This is achieved at a computational cost which is orders of magnitude lower than that of comparable calculations which directly invoke electronic structure methods. We evaluate the accuracy of our machine learning model alongside that of a number of popular empirical and bond-order potentials, using both experimental and ab initio data as references. We find that whilst significant discrepancies exist between the empirical interatomic potentials and the reference data - and amongst the empirical potentials themselves - the machine learning model introduced here provides exemplary performance in all of the tested areas. The calculated properties include: graphene phonon dispersion curves at 0 K (which we predict with sub-meV accuracy), phonon spectra at finite temperature, in-plane thermal expansion up to 2500 K as compared to NPT ab initio molecular dynamics simulations and a comparison of the thermally induced dispersion of graphene Raman bands to experimental observations. We have made our potential freely available online at [http://www.libatoms.org].

cond-mat.mtrl-sci↗

arXiv2017

Communication: Truncated non-bonded potentials can yield unphysical behavior in molecular dynamics simulations of interfaces

Non-bonded potentials are included in most force fields and therefore widely used in classical molecular dynamics simulations of materials and interfacial phenomena. It is commonplace to truncate these potentials for computational efficiency based on the assumption that errors are negligible for reasonable cutoffs or compensated for by adjusting other interaction parameters. Arising from a metadynamics study of the wetting transition of water on a solid substrate, we find that the influence of the cutoff is unexpectedly strong and can change the character of the wetting transition from continuous to first order by creating artificial metastable wetting states. Common cutoff corrections such as the use of a force switching function, a shifted potential, or a shifted force do not avoid this. Such a qualitative difference urges caution and suggests that using truncated non-bonded potentials can induce unphysical behavior that cannot be fully accounted for by adjusting other interaction parameters.

physics.comp-ph↗

arXiv2017

What Makes a Good Descriptor for Heterogeneous Ice Nucleation on OH-Patterned Surfaces

Freezing of water is arguably one of the most common phase transitions on Earth and almost always happens heterogeneously. Despite its importance, we lack a fundamental understanding of what makes substrates efficient ice nucleators. Here we address this by computing the ice nucleation (IN) ability of numerous model hydroxylated substrates with diverse surface hydroxyl (OH) group arrangements. Overall, for the substrates considered, we find that neither the symmetry of the OH patterns nor the similarity between a substrate and ice correlate well with the IN ability. Instead, we find that the OH density and the substrate-water interaction strength are useful descriptors of a material's IN ability. This insight allows the rationalization of ice nucleation ability across a wide range of materials, and can aid the search and design of novel potent ice nucleators in the future.

physics.chem-ph↗

arXiv2017

Hydrogenation Facilitates Proton Transfer Through Two-Dimensional Honeycomb Crystals

Recent experiments have triggered a debate about the ability of protons to transfer through individual layers of graphene and hexagonal boron nitride (h-BN). However, calculations have shown that the barriers to proton penetration can, at more than 3 eV, be excessively high. Here, on the basis of first principles calculations, we show that the barrier for proton penetration is significantly reduced, to less than 1 eV, upon hydrogenation even in the absence of pinholes in the lattice. Analysis reveals that the barrier is reduced because hydrogenation destabilises the initial state (a deep-lying chemisorption state) and expands the honeycomb lattice through which the protons penetrate. This study offers a rationalization of the fast proton transfer observed in experiments, and highlights the ability of proton transport through single-layer materials in hydrogen rich solutions.

cond-mat.mtrl-sci↗

arXiv2017

Properties of the water to boron nitride interaction: from zero to two dimensions with benchmark accuracy

Molecular adsorption on surfaces plays an important part in catalysis, corrosion, desalination, and various other processes that are relevant to industry and in nature. As a complement to experiments, accurate adsorption energies can be obtained using various sophisticated electronic structure methods that can now be applied to periodic systems. The adsorption energy of water on boron nitride substrates, going from zero to 2-dimensional periodicity, is particularly interesting as it calls for an accurate treatment of polarizable electrostatics and dispersion interactions, as well as posing a practical challenge to experiments and electronic structure methods. Here, we present reference adsorption energies, static polarizabilities, and dynamic polarizabilities, for water on BN substrates of varying size and dimension. Adsorption energies are computed with coupled cluster theory, fixed-node quantum Monte Carlo (FNQMC), the random phase approximation (RPA), and second order Møller-Plesset (MP2) theory. These explicitly correlated methods are found to agree in molecular as well as periodic systems. The best estimate of the water/h-BN adsorption energy is $-107\pm7$ meV from FNQMC. In addition, the water adsorption energy on the BN substrates could be expected to grow monotonically with the size of the substrate due to increased dispersion interactions but interestingly, this is not the case here. This peculiar finding is explained using the static polarizabilities and molecular dispersion coefficients of the systems, as computed from time-dependent density functional theory (DFT). Dynamic as well as static polarizabilities are found to be highly anisotropic in these systems. In addition, the many-body dispersion method in DFT emerges as a particularly useful estimation of finite size effects for other expensive, many-body wavefunction based methods.

cond-mat.mtrl-sci↗

arXiv2017

A comparison between quantum chemistry and quantum Monte Carlo techniques for the adsorption of water on the (001) LiH surface

We present a comprehensive benchmark study of the adsorption energy of a single water molecule on the (001) LiH surface using periodic coupled cluster and quantum Monte Carlo theories. We benchmark and compare different implementations of quantum chemical wave function based theories in order to verify the reliability of the predicted adsorption energies and the employed approximations. Furthermore we compare the predicted adsorption energies to those obtained employing widely-used van der Waals density-functionals. Our findings show that quantum chemical approaches are becoming a robust and reliable tool for condensed phase electronic structure calculations, providing an additional tool that can also help in potentially improving currently available van der Waals density-functionals.

physics.chem-ph↗

arXiv2017

Exploring water adsorption on isoelectronically doped graphene using alchemical derivatives

The design and production of novel 2-dimensional materials has seen great progress in the last decade, prompting further exploration of the chemistry of such materials. Doping and hydrogenating graphene is an experimentally realised method of changing its surface chemistry, but there is still a great deal to be understood on how doping impacts on the adsorption of molecules. Developing this understanding is key to unlocking the potential applications of these materials. High throughput screening methods can provide particularly effective ways to explore vast chemical compositions of materials. Here, alchemical derivatives are used as a method to screen the dissociative adsorption energy of water molecules on various BN doped topologies of hydrogenated graphene. The predictions from alchemical derivatives are assessed by comparison to density functional theory. This screening method is found to predict dissociative adsorption energies that span a range of more than 2 eV, with a mean absolute error $<0.1$ eV. In addition, we show that the quality of such predictions can be readily assessed by examination of the Kohn-Sham highest occupied molecular orbital in the initial states. In this way, the root mean square error in the dissociative adsorption energies of water is reduced by almost an order of magnitude (down to $\sim0.02$ eV) after filtering out poor predictions. The findings point the way towards a reliable use of first order alchemical derivatives for efficient screening procedures.

physics.chem-ph↗

arXiv2017

Double-layer ice from first principles

The formation of monolayer and multilayer ice with a square lattice structure has recently been reported on the basis of transmission electron microscopy experiments, renewing interest in confined two dimensional ice. Here we report a systematic density functional theory study of double-layer ice in nano-confinement. A phase diagram as a function of confinement width and lateral pressure is presented. Included in the phase diagram are honeycomb hexagonal, square-tube, hexagonal-close-packed and buckled-rhombic structures. However, contrary to experimental observations, square structures do not feature: our most stable double-layer square structure is predicted to be metastable. This study provides general insight into the phase transitions of double-layer confined ice and a fresh theoretical perspective on the stability of square ice in graphene nanocapillary experiments.

cond-mat.mtrl-sci↗

arXiv2017

How strongly do hydrogen and water molecules stick to carbon nanomaterials?

The interaction strength of molecular hydrogen and water to carbon nanomaterials is relevant to, among many applications, hydrogen storage, water treatment, and water flow. However, accurate interaction energies for hydrogen and water with carbon nanotubes(CNTs) remain scarce despite the importance of having reliable benchmark data to inform experiments and to validate computational models. Here, benchmark fixed-node diffusion Monte Carlo (DMC) interaction energies are provided for hydrogen and water monomers, inside and outside a typical zigzag CNT. The DMC interaction energies provide valuable insight into molecular interactions with CNTs in general, and are also expected to be particularly relevant to gas uptake studies on CNTs. In addition, a selection of density functional theory (DFT) exchangecorrelation(xc) functionals and force field potentials that ought to be suitable for these systems, is compared. An unexpected variation is found in the performance of DFT van der Waals (vdW) models in particular. An analysis of the peculiar discrepancy between different vdW models indicates that medium-range correlation (at circa 3 to 5 Å) plays a key role inside CNTs, and is poorly predicted by some vdW models. Using accurate reference information, this work reveals which xc functionals and force fields perform well for molecules interacting with CNTs. The findings will be valuable to future work on these and related systems, that involve molecules interacting with low-dimensional systems.

cond-mat.mtrl-sci↗

arXiv2017

Is High-density Amorphous Ice Simply a 'Derailed' State along the Ice I to Ice IV Pathway?

The structural nature of high-density amorphous ice (HDA), which forms through low-temperature pressure-induced amorphization of the 'ordinary' ice I, is heavily debated. Clarifying this question is not only important for understanding the complex condensed states of H$_2$O but also in the wider context of pressure-induced amorphization processes, which are encountered across the entire materials spectrum. We first show that ammonium fluoride (NH$_4$F), which has a similar hydrogen-bonded network to ice I, also undergoes a pressure collapse upon compression at 77 K. However, the product material is not amorphous but NH$_4$F II, a high-pressure phase isostructural with ice IV. This collapse can be rationalized in terms of a highly effective mechanism. In the case of ice I, the orientational disorder of the water molecules leads to a deviation from this mechanism and we therefore classify HDA as a 'derailed' state along the ice I to ice IV pathway.

cond-mat.mtrl-sci↗

arXiv2016

The Many Faces of Heterogeneous Ice Nucleation: Interplay Between Surface Morphology and Hydrophobicity

What makes a material a good ice nucleating agent? Despite the importance of heterogeneous ice nucleation to a variety of fields, from cloud science to microbiology, major gaps in our understanding of this ubiquitous process still prevent us from answering this question. In this work, we have examined the ability of generic crystalline substrates to promote ice nucleation as a function of the hydrophobicity and the morphology of the surface. Nucleation rates have been obtained by brute-force molecular dynamics simulations of coarse-grained water on top of different surfaces of a model fcc crystal, varying the water-surface interaction and the surface lattice parameter. It turns out that the lattice mismatch of the surface with respect to ice, customarily regarded as the most important requirement for a good ice nucleating agent, is at most desirable but not a requirement. On the other hand, the balance between the morphology of the surface and its hydrophobicity can significantly alter the ice nucleation rate and can also lead to the formation of up to three different faces of ice on the same substrate. We have pinpointed three circumstances where heterogeneous ice nucleation can be promoted by the crystalline surface: (i) the formation of a water overlayer that acts as an in-plane template; (ii) the emergence of a contact layer buckled in an ice-like manner; and (iii) nucleation on compact surfaces with very high interaction strength. We hope that this extensive systematic study will foster future experimental work aimed at testing the physiochemical understanding presented herein.

physics.chem-ph↗

arXiv2016

Fast diffusion of water nanodroplets on graphene

Diffusion across surfaces generally involves motion on a vibrating but otherwise stationary substrate. Here, using molecular dynamics, we show that a layered material such as graphene opens up a new mechanism for surface diffusion whereby adsorbates are carried by propagating ripples via a motion similar to surfing. For water nanodroplets, we demonstrate that the mechanism leads to exceedingly fast diffusion that is 2-3 orders of magnitude faster than the self-diffusion of water molecules in liquid water. We also reveal the underlying principles that regulate this new mechanism for diffusion and show how it also applies to adsorbates other than water, thus opening up the prospect of achieving fast and controllable motion of adsorbates across material surfaces more generally.

physics.chem-ph↗

arXiv2016

Stability of Complex Biomolecular Structures: Vander Waals, Hydrogen Bond Cooperativity, and Nuclear Quantum Effects

Biomolecules are complex systems stabilized by a delicate balance of weak interactions, making it important to assess all energetic contributions in an accurate manner. However, it is a priori unclear which contributions make more of an impact. Here, we examine stacked polyglutamine (polyQ) strands, a peptide repeat often found in amyloid aggregates. We investigate the role of hydrogen bond (HB) cooperativity, van der Waals (vdW) dispersion interactions, and quantum contributions to free energies, including anharmonicities through density functional theory and ab initio path integral simulations. Of these various factors, we find that the largest impact on structural stabilization comes from vdW interactions. HB cooperativity is the second largest contribution as the size of the stacked chain grows. Competing nuclear quantum effects make the net quantum contribution small but very sensitive to anharmonicities, vdW, and the number of HBs. Our results suggest that a reliable treatment of these systems can only be attained by considering all of these components.

physics.chem-ph↗

arXiv2016

Evidence for Stable Square Ice from Quantum Monte Carlo

Recent experiments on ice formed by water under nanoconfinement provide evidence for a two-dimensional (2D) `square ice' phase. However, the interpretation of the experiments has been questioned and the stability of square ice has become a matter of debate. Partially this is because the simulation approaches employed so far (force fields and density functional theory) struggle to accurately describe the very small energy differences between the relevant phases. Here we report a study of 2D ice using an accurate wave-function based electronic structure approach, namely Diffusion Monte Carlo (DMC). We find that at relatively high pressure square ice is indeed the lowest enthalpy phase examined, supporting the initial experimental claim. Moreover, at lower pressures a `pentagonal ice' phase (not yet observed experimentally) has the lowest enthalpy, and at ambient pressure the `pentagonal ice' phase is degenerate with a `hexagonal ice' phase. Our DMC results also allow us to evaluate the accuracy of various density functional theory exchange correlation functionals and force field models, and in doing so we extend the understanding of how such methodologies perform to challenging 2D structures presenting dangling hydrogen bonds.

physics.chem-ph↗

arXiv2016

Crystal Nucleation in Liquids: Open Questions and Future Challenges in Molecular Dynamics Simulations

The nucleation of crystals in liquids is one of nature's most ubiquitous phenomena, playing an important role in areas such as climate change and the production of drugs. As the early stages of nucleation involve exceedingly small time and length scales, atomistic computer simulations can provide unique insight into the microscopic aspects of crystallization. In this review, we take stock of the numerous molecular dynamics simulations that in the last few decades have unraveled crucial aspects of crystal nucleation in liquids. We put into context the theoretical framework of classical nucleation theory and the state of the art computational methods, by reviewing simulations of e.g. ice nucleation or crystallization of molecules in solutions. We shall see that molecular dynamics simulations have provided key insight into diverse nucleation scenarios, ranging from colloidal particles to natural gas hydrates, and that in doing so the general applicability of classical nucleation theory has been repeatedly called into question. We have attempted to identify the most pressing open questions in the field. We believe that by improving (i.) existing interatomic potentials; and (ii.) currently available enhanced sampling methods, the community can move towards accurate investigations of realistic systems of practical interest, thus bringing simulations a step closer to experiments.

cond-mat.mtrl-sci↗

arXiv2016

Inverse Temperature Dependence of Nuclear Quantum Effects in DNA Base Pairs

Despite the inherently quantum mechanical nature of hydrogen bonding, it is unclear how nuclear quantum effects (NQEs) alter the strengths of hydrogen bonds. With this in mind, we use ab initio path integral molecular dynamics to determine the absolute contribution of NQEs to the binding in DNA base pair complexes, arguably the most important hydrogen-bonded systems of all. We find that depending on the temperature, NQEs can either strengthen or weaken the binding within the hydrogen-bonded complexes. As a somewhat counterintuitive consequence, NQEs can have a smaller impact on hydrogen bond strengths at cryogenic temperatures than at room temperature. We rationalize this in terms of a competition of NQEs between low-frequency and high-frequency vibrational modes. Extending this idea, we also propose a simple model to predict the temperature dependence of NQEs on hydrogen bond strengths in general.

physics.chem-ph↗