Development of non-bonded interaction parameters between graphene and water using particle swarm optimization

Modeling Water Interactions with Graphene and Graphite via Force Fields Consistent with Experimental Contact Angles

Accurate simulation models for water interactions with graphene and graphite are important for nanofluidic applications, but existing force fields produce widely varying contact angles. Our extensive review of the experimental literature reveals extreme variation among reported values of graphene-water contact angles and a clustering of graphite-water contact angles into groups of freshly exfoliated (60° ± 13°) and not-freshly exfoliated graphite surfaces. The carbon-oxygen dispersion energy for a classical force field is optimized with respect to this 60° graphite-water contact angle in the infinite-force-cutoff limit, which in turn yields a contact angle for unsupported graphene of 80°, in agreement with the mean of the experimental results. Interaction force fields for finite cutoffs are also derived. A method for calculating contact angles from pressure tensors of planar equilibrium simulations that is ideally suited to graphite and graphene surfaces is introduced. Our methodology is widely applicable to any liquid-surface combination.

Ab Initio Calculations of the Interaction Potential of the N2O-N2O Dimer: Strength of the Intermolecular Interactions and Physical Insights

N₂O, or nitrous oxide, is an important greenhouse gas with a significant impact on global warming and climate change. To accurately model the behavior of N₂O in the atmosphere, precise representations of its intermolecular force fields are required. First principles quantum mechanical calculations followed by appropriate fitting are commonly used to establish such force fields. However, fitting such force fields is challenging due to the complex mathematical functions that describe the molecular interactions of N₂O. As such, ongoing research is focused on improving our understanding of N₂O and developing more accurate models for use in climate modeling and other applications. In this study, we investigated the strength of the intermolecular interactions in the N₂O-N₂O dimer using the coupled-cluster theory with single, double, and perturbative triple excitation [CCSD(T)] method with the def2-QZVPP basis set. Our calculations provided a detailed understanding of the intermolecular forces that govern the stability and structure of the N₂O dimer. We found that the N₂O-N₂O dimer is stabilized by a combination of van der Waals forces and dipole-dipole interactions. The calculated interaction energy between the two N₂O molecules in the dimer was found to be -5.09 kcal/mol, which is in good agreement with previous theoretical and experimental results. Additionally, we analyzed the molecular properties of the N₂O-N₂O dimer, including its geometry and charge distribution. Our calculations provide a comprehensive understanding of the intermolecular interactions in the N₂O-N₂O dimer using the CCSD(T) method with the def2-QZVPP basis set by using the improved Lennard-Jones interaction potential method. These results can be used to improve our understanding of atmospheric chemistry and climate modeling, as well as to aid in the interpretation of experimental data.

Does Expanding or Contracting MgO Lattice Really Help with Corrosion Resistance of Mg Surface: Insights from Molecular Dynamics Simulations

In a humid environment, water droplets on the solid surface can act as a medium to accelerate corrosion. If the solid material has hydrophobic properties, the surface of the material will remain "clean" and corrosion may be retarded to a certain extent. In theory, MgO itself is a hydrophilic material, and we can apply additional stress or strain to change its lattice constant and adjust the wetting behavior of water on the MgO surface, resulting in changes of corrosion resistance. In order to study the effects of MgO lattice expansion or contraction on the wetting behavior of nano-water, molecular dynamics simulations have been performed in this work. It is found that the changes of the lattice constants on the MgO surface can significantly change the wetting tendency. It will alter the interaction forces between water molecules and MgO surfaces, which in turn changes the atomic density profiles, the orientation of OH bonds, and hydrogen bond networks. The contraction of MgO can actually result in the increase of wetting angles of nano-water droplets on the MgO surface and gradually exhibits hydrophobic properties.

Liquids relax and unify strain in graphene

Solid substrates often induce non-uniform strain and doping in graphene monolayer, therefore altering the intrinsic properties of graphene, reducing its charge carrier mobilities and, consequently, the overall electrical performance. Here, we exploit confocal Raman spectroscopy to study graphene directly free-floating on the surface of water, and show that liquid supports relief the preexisting strain, have negligible doping effect and restore the uniformity of the properties throughout the graphene sheet. Such an effect originates from the structural adaptability and flexibility, lesser contamination and weaker intermolecular bonding of liquids compared to solid supports, independently of the chemical nature of the liquid. Moreover, we demonstrate that water provides a platform to study and distinguish chemical defects from substrate-induced defects, in the particular case of hydrogenated graphene. Liquid supports, thus, are advantageous over solid supports for a range of applications, particularly for monitoring changes in the graphene structure upon chemical modification.

Here, the authors report water as a superior platform to suspend graphene compared to solid substrates that induce non-uniformity and do not provide structural flexibility. They utilize confocal Raman spectroscopy to study graphene floating freely on the surface of water to show that a liquid support relieves the pre-existing strain.

Characterizing surface wetting and interfacial properties using enhanced sampling (SWIPES)

We introduce an accurate and efficient method for characterizing surface wetting and interfacial properties, such as the contact angle made by a liquid droplet on a solid surface, and the vapor-liquid surface tension of a fluid. The method makes use of molecular simulations in conjunction with the indirect umbrella sampling technique to systematically wet the surface and estimate the corresponding free energy. To illustrate the method, we study the wetting of a family of Lennard-Jones surfaces by water. For surfaces with a wide range of attractions for water, we estimate contact angles using our method, and compare them with contact angles obtained using droplet shapes. Notably, our method is able to capture the transition from partial to complete wetting as surface-water attractions are increased. Moreover, the method is straightforward to implement and is computationally efficient, providing accurate contact angle estimates in roughly 5 nanoseconds of simulation time.

Machine-Learning Enabled New Insights into the Coil-to-Globule Transition of Thermosensitive Polymers Using a Coarse-Grained Model

We present a computational framework that integrates coarse-grained (CG) molecular dynamics (MD) simulations and a data-driven machine-learning (ML) method to gain insights into the conformations of polymers in solutions. We employ this framework to study conformational transition of a model thermosensitive polymer, poly( N-isopropylacrylamide) (PNIPAM). Here, we have developed the first of its kind, a temperature-independent CG model of PNIPAM that can accurately predict its experimental lower critical solution temperature (LCST) while retaining the tacticity in the presence of an explicit water model. The CG model was extensively validated by performing CG MD simulations with different initial conformations, varying the radius of gyration of chain, the chain length, and the angle between the adjacent monomers of the initial configuration of PNIPAM (total simulation time = 90 μs). Moreover, for the first time, we utilize the nonmetric multidimensional scaling (NMDS) method, a data-driven ML approach, to gain further insights into the mechanisms and pathways of this coil-to-globule transition by analyzing CG MD simulation trajectories. NMDS analysis provides entirely new insights and shows multiple metastable states of PNIPAM during its coil-to-globule transition above the LCST.