Efficient parametrization of complex molecule-surface force fields

We present an efficient scheme for parametrizing complex molecule-surface force fields from ab initio data. The cost of producing a sufficient fitting library is mitigated using a 2D periodic embedded slab model made possible by the quantum mechanics/molecular mechanics scheme in CP2K. These results were then used in conjunction with genetic algorithm (GA) methods to optimize the large parameter sets needed to describe such systems. The derived potentials are able to well reproduce adsorption geometries and adsorption energies calculated using density functional theory. Finally, we discuss the challenges in creating a sufficient fitting library, determining whether or not the GA optimization has completed, and the transferability of such force fields to similar molecules. © 2015 Wiley Periodicals, Inc

Atomic-scale dissipation processes in dynamic force spectroscopy

A systematic distance-dependent measurement of the quasistatic tip-sample interactions reveals a hidden stochastic dissipative interaction of the atomic-scale contact in dynamic force microscopy. By comparison of experiment with detailed molecular dynamics simulations, we demonstrate that the infrequently observed hysteresis loops are attributed to the formation of atomic chains during tip retraction. These lead to a large magnitude of energy dissipation in a single cycle and dominate the average measured dissipation, while also leading to differences in the forces measured in static and dynamic force microscopy. This paper provides quantitative force measurements and insights into atomic-scale dissipation processes.Peer reviewe

Using metallic noncontact atomic force microscope tips for imaging insulators and polar molecules: tip characterization and imaging mechanisms

We demonstrate that using metallic tips for noncontact atomic force microscopy (NC-AFM) imaging at relatively large (>0.5 nm) tip-surface separations provides a reliable method for studying molecules on insulating surfaces with chemical resolution and greatly reduces the complexity of interpreting experimental data. The experimental NC-AFM imaging and theoretical simulations were carried out for the NiO(001) surface as well as adsorbed CO and Co-Salen molecules using Cr-coated Si tips. The experimental results and density functional theory calculations confirm that metallic tips possess a permanent electric dipole moment with its positive end oriented toward the sample. By analyzing the experimental data, we could directly determine the dipole moment of the Cr-coated tip. A model representing the metallic tip as a point dipole is described and shown to produce NC-AFM images of individual CO molecules adsorbed onto NiO(001) in good quantitative agreement with experimental results. Finally, we discuss methods for characterizing the structure of metal-coated tips and the application of these tips to imaging dipoles of large adsorbed molecules. © 2014 American Chemical Society

Micrometre-long covalent organic fibres by photoinitiated chain-growth radical polymerization on an alkali-halide surface

On-surface polymerization is a promising technique to prepare organic functional nanomaterials that are challenging to synthesize in solution, but it is typically used on metal substrates, which play a catalytic role. Previous examples on insulating surfaces have involved intermediate self-assembled structures, which face high barriers to diffusion, or annealing to higher temperatures, which generally causes rapid dewetting and desorption of the monomers. Here we report the photoinitiated radical polymerization, initiated from a two-dimensional gas phase, of a dimaleimide monomer on an insulating KCl surface. Polymer fibres up to 1 μm long are formed through chain-like rather than step-like growth. Interactions between potassium cations and the dimaleimide’s oxygen atoms facilitate the propagation of the polymer fibres along a preferred axis of the substrate over long distances. Density functional theory calculations, non-contact atomic force microscopy imaging and manipulations at room temperature were used to explore the initiation and propagation processes, as well as the structure and stability of the resulting one-dimensional polymer fibres

Mixture of Clustered Bayesian Neural Networks for Modeling Friction Processes at the Nanoscale

Friction and wear are the source of every mechanical device failure, and lubricants are essential for the operation of the devices. These physical phenomena have a complex nature so that no model capable of accurately predicting the behavior of lubricants exists. Thus, lubricants cannot be designed from scratch but have to be screened through expensive trial-error tests. In this study we propose a machine learning (ML) method that infers the relationship between chemical composition of lubricants and their performance from a database. Because no such database of desirable size and completeness is publicly available, we compiled one from molecular dynamics (MD) simulations of toy-model fluids nanoconfined between shearing surfaces. The fluid-friction relation is modeled by a Bayesian neural network (BNN), trained to reproduce the results for a training set of fluids. Due to the inhomogeneous data distribution it was necessary to carefully pick fluids for training and validation from the database with advanced clustering algorithms, rather than using the standard random selection. Different BNNs were then trained on the data clusters and their predictions combined into a mixture of experts. The model provides a prediction of lubricants performance as well as an error bar, at a fraction of the cost of MD. Because most values agree with the actual MD simulations within the estimated error sigma, we conclude that the model is satisfactory. This method addresses the challenges brought by noisy, badly distributed, high-dimensional data that are likely to appear in reality as well, and it can be extended to real fluids, if a database could be provided.Peer reviewe

Simulating solid-liquid interfaces in atomic force microscopy

In this chapter, we will cover the main approaches taken to model AFM in liquids in a variety of different systems, discussing the advantages and problems of different methods, outlining the main issues to take into account in general, while also attempting to build a perspective for the future of the field. We hope this will provide a fundamental platform of understanding for future Atomic Force Microscopy studies of solid-liquid interfaces at the nanoscale. © Springer International Publishing Switzerland 201

Characteristics of Lithium Ions and Superoxide Anions in EMI-TFSI and Dimethyl Sulfoxide

To clarify the microscopic effects of solvents on the formation of the Li⁺-O₂^– process of a Li–O₂ battery, we studied the kinetics and thermodynamics of these ions in dimethyl sulfoxide (DMSO) and 1-ethyl-3-methylimidazolium bis­(trifluoromethylsulfonyl)­imide (EMI-TFSI) using classical molecular dynamics simulation. The force field for ions–solvents interactions was parametrized by force matching first-principles calculations. Despite the solvation energies of the ions are similar in both solvents, their mobility is much higher in DMSO. The free-energy profiles also confirm that the formation and decomposition rates of Li⁺-O₂^– pairs are greater in DMSO than in EMI-TFSI. Our atomistic simulations point out that the strong structuring of EMI-TFSI around the ions is responsible for these differences, and it explains why the LiO₂ clusters formed in DMSO during the battery discharge are larger than those in EMI-TFSI. Understanding the origin of such properties is crucial to aid the optimization of electrolytes for Li–O₂ batteries

Flexible Self-Assembled Molecular Templates on Graphene

| openaire: EC/FP7/278698/EU//PRECISE-NANOWe report on molecular self-assembly employing a host-guest architecture to pattern the growth of molecules on graphene model surface. Under suitable conditions, the 1,3,5-benzenetribenzoic acid (BTB) self-assembles into an extended honeycomb mesh on graphene on Ir(111), with the molecules in the network being stabilized by linear hydrogen bonds between the carboxylic groups. The nanopores of the mesh are used to host and govern the assembly of cobalt phthalocyanine (CoPC) guest molecules. We characterize the assembled structures structurally and electronically using low-temperature scanning tunneling microscopy (STM) and density functional theory (DFT) calculations. At a coverage higher than one CoPc per pore, the flexible hydrogen bonds of the host network undergo stretching to accommodate two CoPCs in a single pore. When the pores are uniformly doubly occupied, the guest molecules arrange into a herringbone pattern. This minimizes the energy cost associated with the stretching and twisting of the hydrogen bonds between the BTB molecules. The phenomenon observed here can be used to tailor molecular assemblies on graphene to controllably modify its properties. In addition, it allows the formation of guest monomers and dimers stabilized mechanically on the surface of graphene, an archetypical weakly interacting substrate.Peer reviewe