Physisorption of Water on Graphene: Subchemical Accuracy from Many-Body Electronic Structure Methods

Beyond Single-Reference Fixed-Node Approximation in Ab Initio Diffusion Monte Carlo Using Antisymmetrized Geminal Power Applied to Systems with Hundreds of Electrons

Diffusion Monte Carlo (DMC) is an exact technique to project out the ground state (GS) of a Hamiltonian. Since the GS is always bosonic, in Fermionic systems, the projection needs to be carried out while imposing antisymmetric constraints, which is a nondeterministic polynomial hard problem. In practice, therefore, the application of DMC on electronic structure problems is made by employing the fixed-node (FN) approximation, consisting of performing DMC with the constraint of having a fixed, predefined nodal surface. How do we get the nodal surface? The typical approach, applied in systems having up to hundreds or even thousands of electrons, is to obtain the nodal surface from a preliminary mean-field approach (typically, a density functional theory calculation) used to obtain a single Slater determinant. This is known as single reference. In this paper, we propose a new approach, applicable to systems as large as the C60 fullerene, which improves the nodes by going beyond the single reference. In practice, we employ an implicitly multireference ansatz (antisymmetrized geminal power wave function constraint with molecular orbitals), initialized on the preliminary mean-field approach, which is relaxed by optimizing a few parameters of the wave function determining the nodal surface by minimizing the FN-DMC energy. We highlight the improvements of the proposed approach over the standard single-reference method on several examples and, where feasible, the computational gain over the standard multireference ansatz, which makes the methods applicable to large systems. We also show that physical properties relying on relative energies, such as binding energies, are affordable and reliable within the proposed scheme.

Properties of aqueous electrolyte solutions at carbon electrodes: effects of concentration and surface charge on solution structure, ion clustering and thermodynamics in the electric double layer

Surfaces are able to control physical-chemical processes in multi-component solution systems and, as such, find application in a wide range of technological devices. Understanding the structure, dynamics and thermodynamics of non-ideal solutions at surfaces, however, is particularly challenging. Here, we use Constant Chemical Potential Molecular Dynamics (CμMD) simulations to gain insight into aqueous NaCl solutions in contact with graphite surfaces at high concentrations and under the effect of applied surface charges: conditions where mean-field theories describing interfaces cannot (typically) be reliably applied. We discover an asymmetric effect of surface charge on the electric double layer structure and resulting thermodynamic properties, which can be explained by considering the affinity of the surface for cations and anions and the cooperative adsorption of ions that occurs at higher concentrations. We characterise how the sign of the surface charge affects ion densities and water structure in the double layer and how the capacitance of the interface-a function of the electric potential drop across the double layer-is largely insensitive to the bulk solution concentration. Notably, we find that negatively charged graphite surfaces induce an increase in the size and concentration of extended liquid-like ion clusters confined to the double layer. Finally, we discuss how concentration and surface charge affect the activity coefficients of ions and water at the interface, demonstrating how electric fields in this region should be explicitly considered when characterising the thermodynamics of both solute and solvent at the solid/liquid interface.

Raman and IR spectra of water under graphene nanoconfinement at ambient and extreme pressure-temperature conditions: a first-principles study

The nanoconfinement of water can result in dramatic differences in its physical and chemical properties compared to bulk water. However, a detailed molecular-level understanding of these properties is still lacking. Vibrational spectroscopy, such as Raman and infrared, is a popular experimental tool for studying the structure and dynamics of water, and is often complemented by atomistic simulations to interpret experimental spectra, but there have been few theoretical spectroscopy studies of nanoconfined water using first-principles methods at ambient conditions, let alone under extreme pressure-temperature conditions. Here, we compute the Raman and IR spectra of water nanoconfined by graphene at ambient and extreme pressure-temperature conditions using ab initio simulations. Our results revealed alterations in the Raman stretching and low-frequency bands due to the graphene confinement. We also found spectroscopic evidence indicating that nanoconfinement considerably changes the tetrahedral hydrogen bond network, which is typically found in bulk water. Furthermore, we observed an unusual bending band in the Raman spectrum at ∼10 GPa and 1000 K, which is attributed to the unique molecular structure of confined ionic water. Additionally, we found that at ∼20 GPa and 1000 K, confined water transformed into a superionic fluid, making it challenging to identify the IR stretching band. Finally, we computed the ionic conductivity of confined water in the ionic and superionic phases. Our results highlight the efficacy of Raman and IR spectroscopy in studying the structure and dynamics of nanoconfined water in a large pressure-temperature range. Our predicted Raman and IR spectra can serve as a valuable guide for future experiments.

Origin of dielectric polarization suppression in confined water from first principles

It has long been known that the dielectric constant of confined water should be different from that in bulk. Recent experiments have shown that it is vanishingly small, however the origin of the phenomenon remains unclear. Here we used ab initio molecular dynamics simulations (AIMD) and AIMD-trained machine-learning potentials to understand water's structure and electronic properties underpinning this effect. For the graphene and hexagonal boron-nitride substrates considered, we find that it originates in the spontaneous anti-parallel alignment of the water dipoles in the first two water layers near the solid interface. The interfacial layers exhibit net ferroelectric ordering, resulting in an overall anti-ferroelectric arrangement of confined water. Together with constrained hydrogen-bonding orientations, this leads to much reduced out-of-plane polarization. Furthermore, we directly contrast AIMD and simple classical force-field simulations, revealing important differences. This work offers insight into a property of water that is critical in modulating surface forces, the electric-double-layer formation and molecular solvation, and shows a way to compute it.

Anisotropic Interfacial Force Field for Interfaces of Water with Hexagonal Boron Nitride

This study introduces an anisotropic interfacial potential that provides an accurate description of the van der Waals (vdW) interactions between water and hexagonal boron nitride (h-BN) at their interface. Benchmarked against the strongly constrained and appropriately normed functional, the developed force field demonstrates remarkable consistency with reference data sets, including binding energy curves and sliding potential energy surfaces for various configurations involving a water molecule adsorbed atop the h-BN surface. These findings highlight the significant improvement achieved by the developed force field in empirically describing the anisotropic vdW interactions of the water/h-BN heterointerfaces. Utilizing this anisotropic force field, molecular dynamics simulations demonstrate that atomically flat, pristine h-BN exhibits inherent hydrophobicity. However, when atomic-step surface roughness is introduced, the wettability of h-BN undergoes a significant change, leading to a hydrophilic nature. The calculated water contact angle (WCA) for the roughened h-BN surface is approximately 64°, which closely aligns with experimental WCA values ranging from 52° to 67°. These findings indicate the high probability of the presence of atomic steps on the surfaces of the experimental h-BN samples, emphasizing the need for further experimental verification. The development of the anisotropic interfacial force field for accurately describing interactions at the water/h-BN heterointerfaces is a significant advancement in accurately simulating the wettability of two-dimensional (2D) materials, offering a reliable tool for studying the dynamic and transport properties of water at these interfaces, with implications for materials science and nanotechnology.

DFT study of water on graphene: Synergistic effect of multilayer p-doping

Recent experiments related to a study concerning the adsorption of water on graphene have demonstrated the p-doping of graphene, although most of the ab initio calculations predict nearly zero doping. To shed more light on this problem, we have carried out van der Waals density functional theory calculations of water on graphene for both individual water molecules and continuous water layers with coverage ranging from one to eight monolayers. Furthermore, we have paid attention to the influence of the water molecule orientation toward graphene on its doping properties. In this article, we present the results of the band structure and the Bader charge analysis, showing the p-doping of graphene can be synergistically enhanced by putting 4-8 layers of an ice-like water structure on graphene having the water molecules oriented with oxygen atoms toward graphene.

Many-Body Methods for Surface Chemistry Come of Age: Achieving Consensus with Experiments

The adsorption energy of a molecule onto the surface of a material underpins a wide array of applications, spanning heterogeneous catalysis, gas storage, and many more. It is the key quantity where experimental measurements and theoretical calculations meet, with agreement being necessary for reliable predictions of chemical reaction rates and mechanisms. The prototypical molecule-surface system is CO adsorbed on MgO, but despite intense scrutiny from theory and experiment, there is still no consensus on its adsorption energy. In particular, the large cost of accurate many-body methods makes reaching converged theoretical estimates difficult, generating a wide range of values. In this work, we address this challenge, leveraging the latest advances in diffusion Monte Carlo (DMC) and coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] to obtain accurate predictions for CO on MgO. These reliable theoretical estimates allow us to evaluate the inconsistencies in published temperature-programed desorption experiments, revealing that they arise from variations in employed pre-exponential factors. Utilizing this insight, we derive new experimental estimates of the (electronic) adsorption energy with a (more) precise pre-exponential factor. As a culmination of all of this effort, we are able to reach a consensus between multiple theoretical calculations and multiple experiments for the first time. In addition, we show that our recently developed cluster-based CCSD(T) approach provides a low-cost route toward achieving accurate adsorption energies. This sets the stage for affordable and reliable theoretical predictions of chemical reactions on surfaces to guide the realization of new catalysts and gas storage materials.

Highly Accurate Electronic Structure of Metallic Solids from Coupled-Cluster Theory with Nonperturbative Triple Excitations

Coupled-cluster theory with single, double, and perturbative triple excitations (CCSD(T))-often considered the "gold standard" of main-group quantum chemistry-is inapplicable to three-dimensional metals due to an infrared divergence, preventing its application to many important problems in materials science. We study the full, nonperturbative inclusion of triple excitations (CCSDT) and propose a new, iterative method, which we call ring-CCSDT, that resums the essential triple excitations with the same N^{7} run-time scaling as CCSD(T). CCSDT and ring-CCSDT are used to calculate the correlation energy of the uniform electron gas at metallic densities and the structural properties of solid lithium. Inclusion of connected triple excitations is shown to be essential to achieving high accuracy. We also investigate semiempirical CC methods based on spin-component scaling and the distinguishable cluster approximation and find that they enhance the accuracy of their parent ab initio methods.

Ab Initio Molecular Dynamics Investigation of the Solvation States of Hydrated Ions in Confined Water

Ionic transport in nanoscale channels with a critical size comparable to that of ions and solutes exhibits exceptional performance in water desalination, ion separation, electrocatalysts, and supercapacitors. However, the solvation states (SSs), i.e., the hydration structures and probability distribution, of hydrated ions in nanochannels differ from those in the bulk and the perspective of continuum theory. In this work, we conduct ab initio enhanced-sampling atomistic simulations to investigate the ion-specific SSs of monovalent ions (including Li+, Na+, K+, F-, Cl-, and I-) in the graphene channel with a width of 1 nm. Our findings highlight that the SSs of those ions are primarily determined by ion-water hydration, where ion-wall interactions play a minor role. The distribution of ions in layered confined water is a result of ion-specific hydration, which arises from the synergy of entropy and enthalpy. The free energy barriers for transitions between SSs are on the order of 1kBT, allowing for modulation through applying external fields or modifying surface properties. As the ion-wall interaction strengthens, as observed in vermiculite and carbides and nitrides of transition metal channels, the probability of near-wall SSs increases. These results help to improve the performance of nanofluidic devices and provide crucial insights for developing accurate force fields of molecular simulations or advanced theoretical approaches for ion dynamics in confined channels.

Machine Learning Density Functionals from the Random-Phase Approximation

Kohn-Sham density functional theory (DFT) is the standard method for first-principles calculations in computational chemistry and materials science. More accurate theories such as the random-phase approximation (RPA) are limited in application due to their large computational cost. Here, we use machine learning to map the RPA to a pure Kohn-Sham density functional. The machine learned RPA model (ML-RPA) is a nonlocal extension of the standard gradient approximation. The density descriptors used as ingredients for the enhancement factor are nonlocal counterparts of the local density and its gradient. Rather than fitting only RPA exchange-correlation energies, we also include derivative information in the form of RPA optimized effective potentials. We train a single ML-RPA functional for diamond, its surfaces, and liquid water. The accuracy of ML-RPA for the formation energies of 28 diamond surfaces reaches that of state-of-the-art van der Waals functionals. For liquid water, however, ML-RPA cannot yet improve upon the standard gradient approximation. Overall, our work demonstrates how machine learning can extend the applicability of the RPA to larger system sizes, time scales, and chemical spaces.

CO2 on Graphene: Benchmarking Computational Approaches to Noncovalent Interactions

Designing and optimizing graphene-based gas sensors in silico entail constructing appropriate atomistic representations for the physisorption complex of an analyte on an infinite graphene sheet, then selecting accurate yet affordable methods for geometry optimizations and energy computations. In this work, diverse density functionals (DFs), coupled cluster theory, and symmetry-adapted perturbation theory (SAPT) in conjunction with a range of finite and periodic surface models of bare and supported graphene were tested for their ability to reproduce the experimental adsorption energies of CO2 on graphene in a low-coverage regime. Periodic results are accurately reproduced by the interaction energies extrapolated from finite clusters to infinity. This simple yet powerful scheme effectively removes size dependence from the data obtained using finite models, and the latter can be treated at more sophisticated levels of theory relative to periodic systems. While for small models inexpensive DFs such as PBE-D3 afford surprisingly good agreement with the gold standard of quantum chemistry, CCSD(T), interaction energies closest to experiment are obtained by extrapolating the SAPT results and with nonlocal van der Waals functionals in the periodic setting. Finally, none of the methods and models reproduce the experimentally observed CO2 tilted adsorption geometry on the Pt(111) support, calling for either even more elaborate theoretical approaches or a revision of the experiment.

Carbon Dioxide Capture by Adsorption in a Model Hydroxy-Modified Graphene Pore

Concerns regarding the environmental impact of increasing levels of anthropogenic carbon dioxide have led to a variety of studies examining solid surfaces for their ability to trap this greenhouse gas (GHG). Atmospheric or post-combustion carbon capture requires an efficient separation of carbon dioxide and nitrogen gas. We used the molecular mechanics MM3 parameter set (previously shown to provide good estimates of molecule-surface binding energies) to calculate theoretical surface binding energies for carbon dioxide ∆E(CO₂) and nitrogen ∆E(N₂). For efficient separation, differentiation of these two gas-surface adsorption energies is required. Examined structures based on graphene, carbon slit width pore, and carbon nanotube gave ∆E(CO₂) to ∆E(N₂) ratios of 1.7, 1.8, and 1.9, respectively. To enhance the CO₂ adsorption, we developed a model graphene surface pore lined with four hydroxy groups whose orientation allowed them to form hydrogen bonds with the oxygens in CO₂. Both the single-layer and double-layer versions of this pore gave significant enhancement in the ability to trap CO₂ preferentially to N₂. The two-layer version of this pore gave ∆E(CO₂) = 73 and ∆E(N₂) = 6.8 kJ/mol. The one- and two-layer versions of this novel pore averaged a ∆E(CO₂) to ∆E(N₂) ratio of 12.

Quantifying the Impact of Halogenation on Intermolecular Interactions and Binding Modes of Aromatic Molecules

Halogenation of aromatic molecules is frequently used to modulate intermolecular interactions with ramifications for optoelectronic and mechanical properties. In this work, we accurately quantify and understand the nature of intermolecular interactions in perhalogenated benzene (PHB) clusters. Using benchmark binding energies from the fixed-node diffusion Monte Carlo (FN-DMC) method, we show that generalized Kohn-Sham semicanonical projected random phase approximation (GKS-spRPA) plus approximate exchange kernel (AKX) provides reliable interaction energies with mean absolute error (MAE) of 0.23 kcal/mol. Using the GKS-spRPA+AXK method, we quantify the interaction energies of several binding modes of PHB clusters ((C₆X₆)_n; X = F, Cl, Br, I; n = 2, 3). For a given binding mode, the interaction energies increase 3-4 times from X = F to X = I; the X-X binding modes have energies in the range of 2-4 kcal/mol, while the π-π binding mode has interaction energies in the range of 4-12 kcal/mol. SAPT-DFT-based energy decomposition analysis is then used to show that the equilibrium geometries are dictated primarily by the dispersion and exchange interactions. Finally, we test the accuracy of several dispersion-corrected density functional approximations and show that only the r2SCAN-D4 method has a low MAE and correct long-range behavior, which makes it suitable for large-scale simulations and for developing structure-function relationships of halogenated aromatic systems.

Ab initio study of water anchored in graphene pristine and vacancy-type defects

CONTEXT

In this paper, we have addressed two issues that are relevant to the interaction of water in pristine and vacant graphene through first-principles calculations based on the Density Functional Theory (DFT). The results showed that for the interaction of pristine graphene with water, the DOWN configuration (with the hydrogen atoms facing downwards) was the most stable, presenting binding energies in the order of -13.62 kJ/mol at a distance of 2.375 Å in the TOP position. We also evaluated the interaction of water with two vacancy models, removing one carbon atom (Vac-1C) and four atoms (Vac-4C). In the Vac-1C system, the most favourable system was the DOWN configuration, with binding energies ranging from -20.60 kJ/mol to -18.41 kJ/mol in the TOP and UP positions, respectively. A different behaviour was observed for the interaction of water with Vac-4C; regardless of the configuration of the water, it is always more favourable for the interaction to occur through the vacancy centre, with binding energies ​​between -13.28 kJ/mol and -20.49 kJ/mol. Thus, the results presented open perspectives for the technological development of nanomembranes as well as providing a better understanding of the wettability effects of graphene sheets, whether pristine or with defects.

METHOD

We evaluated the interaction of pristine and vacant graphene with the water molecule, through calculations based on Density Functional Theory (DFT); implemented by the SIESTA program. The electronic, energetic, and structural properties were analyzed by solving self-consistent Kohn-Sham equations. In all calculations, a double ζ plus a polarized function (DZP) was used for the numerical baise set. Local Density Approximation (LDA) with the Perdew and Zunger (PZ) parameterisation along with a basis set superposition error (BSSE) correction were used to describe the exchange and correlation potential (Vxc). The water and isolated graphene structures were relaxed until the residual forces were less than 0.05 eV/Å^-1 in all atomic coordinates.

Evaluating the evidence for exponential quantum advantage in ground-state quantum chemistry

Due to intense interest in the potential applications of quantum computing, it is critical to understand the basis for potential exponential quantum advantage in quantum chemistry. Here we gather the evidence for this case in the most common task in quantum chemistry, namely, ground-state energy estimation, for generic chemical problems where heuristic quantum state preparation might be assumed to be efficient. The availability of exponential quantum advantage then centers on whether features of the physical problem that enable efficient heuristic quantum state preparation also enable efficient solution by classical heuristics. Through numerical studies of quantum state preparation and empirical complexity analysis (including the error scaling) of classical heuristics, in both ab initio and model Hamiltonian settings, we conclude that evidence for such an exponential advantage across chemical space has yet to be found. While quantum computers may still prove useful for ground-state quantum chemistry through polynomial speedups, it may be prudent to assume exponential speedups are not generically available for this problem.

Coupled Interactions at the Ionic Graphene-Water Interface

We compute ionic free energy adsorption profiles at an aqueous graphene interface by developing a self-consistent approach. To do so, we design a microscopic model for water and put the liquid on an equal footing with the graphene described by its electronic band structure. By evaluating progressively the electronic and dipolar coupled electrostatic interactions, we show that the coupling level including mutual graphene and water screening permits one to recover remarkably the precision of extensive quantum simulations. We further derive the potential of mean force evolution of several alkali cations.

Development of accurate potentials for the physisorption of water on graphene

From coupled-cluster singles and doubles model including connected triples corrections [CCSD(T)] calculations on the water dimer and B97D/CC on the water-circumcoronene complex at a large number of randomly generated conformations, interaction potentials for the physisorption of water on graphene are built, accomplishing almost sub-chemical accuracy. The force fields were constructed by decomposing the interaction into electrostatic and van der Waals contributions, the latter represented through improved Lennard-Jones potentials. Besides, a Chemistry at Harvard Macromolecular Mechanics (CHARMM)-like term was included in the water-water potential to improve the description of hydrogen bonds, and an induction term was added to model the polarization effects in the interaction between water and polyaromatic hydrocarbons (PAHs) or graphene. Two schemes with three and six point charges were considered for the interactions water-water and water-PAH, as Coulomb contributions are zero in the water-graphene system. The proposed fitted potentials reproduce the ab initio data used to build them in the whole range of distances and conformations and provide results for selected points very close to CCSD(T) benchmarks. When applied to the water-graphene system, the obtained results are in excellent agreement with p-CCSD(T), revised symmetry-adapted perturbation theory based on density functional theory monomer properties (DFT-SAPT), and diffusion Monte Carlo reference values. Furthermore, the stability of the various conformers water-PAH and water-graphene, as well as the different trends observed between these systems are rationalized in terms of the modifications of the electrostatic contribution.

Interfacial Liquid Water on Graphite, Graphene, and 2D Materials

The optical, electronic, and mechanical properties of graphite, few-layer, and two-dimensional (2D) materials have prompted a considerable number of applications. Biosensing, energy storage, and water desalination illustrate applications that require a molecular-scale understanding of the interfacial water structure on 2D materials. This review introduces the most recent experimental and theoretical advances on the structure of interfacial liquid water on graphite-like and 2D materials surfaces. On pristine conditions, atomic-scale resolution experiments revealed the existence of 1-3 hydration layers. Those layers were separated by ∼0.3 nm. The experimental data were supported by molecular dynamics simulations. However, under standard working conditions, atomic-scale resolution experiments revealed the presence of 2-3 hydrocarbon layers. Those layers were separated by ∼0.5 nm. Linear alkanes were the dominant molecular specie within the hydrocarbon layers. Paradoxically, the interface of an aged 2D material surface immersed in water does not have water molecules on its vicinity. Free-energy considerations favored the replacement of water by alkanes.

Water adsorption and dynamics on graphene and other 2D materials: Computational and experimental advances

The interaction of water and surfaces, at molecular level, is of critical importance for understanding processes such as corrosion, friction, catalysis and mass transport. The significant literature on interactions with single crystal metal surfaces should not obscure unknowns in the unique behaviour of ice and the complex relationships between adsorption, diffusion and long-range inter-molecular interactions. Even less is known about the atomic-scale behaviour of water on novel, non-metallic interfaces, in particular on graphene and other 2D materials. In this manuscript, we review recent progress in the characterisation of water adsorption on 2D materials, with a focus on the nano-material graphene and graphitic nanostructures; materials which are of paramount importance for separation technologies, electrochemistry and catalysis, to name a few. The adsorption of water on graphene has also become one of the benchmark systems for modern computational methods, in particular dispersion-corrected density functional theory (DFT). We then review recent experimental and theoretical advances in studying the single-molecular motion of water at surfaces, with a special emphasis on scattering approaches as they allow an unparalleled window of observation to water surface motion, including diffusion, vibration and self-assembly.

Nanoconfinement facilitates reactions of carbon dioxide in supercritical water

The reactions of CO₂ in water under extreme pressure-temperature conditions are of great importance to the carbon storage and transport below Earth’s surface, which substantially affect the carbon budget in the atmosphere. Previous studies focus on the CO₂(aq) solutions in the bulk phase, but underground aqueous solutions are often confined to the nanoscale, and nanoconfinement and solid-liquid interfaces may substantially affect chemical speciation and reaction mechanisms, which are poorly known on the molecular scale. Here, we apply extensive ab initio molecular dynamics simulations to study aqueous carbon solutions nanoconfined by graphene and stishovite (SiO₂) at 10 GPa and 1000 ~ 1400 K. We find that CO₂(aq) reacts more in nanoconfinement than in bulk. The stishovite-water interface makes the solutions more acidic, which shifts the chemical equilibria, and the interface chemistry also significantly affects the reaction mechanisms. Our findings suggest that CO₂(aq) in deep Earth is more active than previously thought, and confining CO₂ and water in nanopores may enhance the efficiency of mineral carbonation.

Aqueous CO₂under nanoconfinement is of great importance to the carbon storage and transport in Earth. Here, the authors apply ab initio molecular dynamics simulations to study the effects of confinement and interfaces, and show that that CO(aq) reacts more in nanoconfinement than in bulk.

The first-principles phase diagram of monolayer nanoconfined water

Water in nanoscale cavities is ubiquitous and of central importance to everyday phenomena in geology and biology. However, the properties of nanoscale water can be substantially different from those of bulk water, as shown, for example, by the anomalously low dielectric constant of water in nanochannels¹, near frictionless water flow² or the possible existence of a square ice phase³. Such properties suggest that nanoconfined water could be engineered for technological applications in nanofluidics⁴, electrolyte materials⁵ and water desalination⁶. Unfortunately, challenges in experimentally characterizing water at the nanoscale and the high cost of first-principles simulations have prevented the molecular-level understanding required to control the behaviour of water. Here we combine a range of computational approaches to enable a first-principles-level investigation of a single layer of water within a graphene-like channel. We find that monolayer water exhibits surprisingly rich and diverse phase behaviour that is highly sensitive to temperature and the van der Waals pressure acting within the nanochannel. In addition to multiple molecular phases with melting temperatures varying non-monotonically by more than 400 kelvins with pressure, we predict a hexatic phase, which is an intermediate between a solid and a liquid, and a superionic phase with a high electrical conductivity exceeding that of battery materials. Notably, this suggests that nanoconfinement could be a promising route towards superionic behaviour under easily accessible conditions.

Multilevel Computational Studies Reveal the Importance of Axial Ligand for Oxygen Reduction Reaction on Fe-N-C Materials

The systematic improvement of Fe-N-C materials for fuel cell applications has proven challenging, due in part to an incomplete atomistic understanding of the oxygen reduction reaction (ORR) under electrochemical conditions. Herein, a multilevel computational approach, which combines ab initio molecular dynamics simulations and constant potential density functional theory calculations, is used to assess proton-coupled electron transfer (PCET) processes and adsorption thermodynamics of key ORR intermediates. These calculations indicate that the potential-limiting step for ORR on Fe-N-C materials is the formation of the Fe^III-OOH intermediate. They also show that an active site model with a water molecule axially ligated to the iron center throughout the catalytic cycle produces results that are consistent with the experimental measurements. In particular, reliable prediction of the ORR onset potential and the Fe(III/II) redox potential associated with the conversion of Fe^III-OH to Fe^II and desorbed H₂O requires an axial H₂O co-adsorbed to the iron center. The observation of a five-coordinate rather than four-coordinate active site has significant implications for the thermodynamics and mechanism of ORR. These findings highlight the importance of solvent-substrate interactions and surface charge effects for understanding the PCET reaction mechanisms and transition-metal redox couples under realistic electrochemical conditions.

Water Flow in Single-Wall Nanotubes: Oxygen Makes It Slip, Hydrogen Makes It Stick

Experimental measurements have reported ultrafast and radius-dependent water transport in carbon nanotubes which are absent in boron nitride nanotubes. Despite considerable effort, the origin of this contrasting (and fascinating) behavior is not understood. Here, with the aid of machine learning-based molecular dynamics simulations that deliver first-principles accuracy, we investigate water transport in single-wall carbon and boron nitride nanotubes. Our simulations reveal a large, radius-dependent hydrodynamic slippage on both materials, with water experiencing indeed a ≈5 times lower friction on carbon surfaces compared to boron nitride. Analysis of the diffusion mechanisms across the two materials reveals that the fast water transport on carbon is governed by facile oxygen motion, whereas the higher friction on boron nitride arises from specific hydrogen-nitrogen interactions. This work not only delivers a clear reference of quantum mechanical accuracy for water flow in single-wall nanotubes but also provides detailed mechanistic insight into its radius and material dependence for future technological application.

Finite-Size Error Cancellation in Diffusion Monte Carlo Calculations of Surface Chemistry

The accurate prediction of reaction mechanisms in heterogeneous (surface) catalysis is one of the central challenges in computational chemistry. Quantum Monte Carlo methods─Diffusion Monte Carlo (DMC) in particular─are being recognized as higher-accuracy, albeit more computationally expensive, alternatives to Density Functional Theory (DFT) for energy predictions of catalytic systems. A major computational bottleneck in the broader adoption of DMC for catalysis is the need to perform finite-size extrapolations by simulating increasingly large periodic cells (supercells) to eliminate many-body finite-size effects and obtain energies in the thermodynamic limit. Here, we show that it is possible to significantly reduce this computational cost by leveraging the cancellation of many-body finite-size errors that accompanies the evaluation of energy differences when calculating quantities like adsorption (binding) energies and mapping potential energy surfaces. We analyze the cancellation and convergence of many-body finite-size errors in two well-known adsorbate/slab systems, H₂O/LiH(001) and CO/Pt(111). Based on this analysis, we identify strategies for obtaining binding energies in the thermodynamic limit that optimally utilize error cancellation to balance accuracy and computational efficiency. Using one such strategy, we then predict the correct order of adsorption site preference on CO/Pt(111), a challenging problem for a wide range of density functionals. Our accurate and inexpensive DMC calculations are found to unambiguously recover the top > bridge > hollow site order, in agreement with experimental observations. We proceed to use this DMC method to map the potential energy surface of CO hopping between Pt(111) adsorption sites. This reveals the existence of an L-shaped top-bridge-hollow diffusion trajectory characterized by energy barriers that provide an additional kinetic justification for experimental observations of CO/Pt(111) adsorption. Overall, this work demonstrates that it is routinely possible to achieve order-of-magnitude speedups and memory savings in DMC calculations by taking advantage of error cancellation in the calculation of energy differences that are ubiquitous in heterogeneous catalysis and surface chemistry more broadly.

The binding of atomic hydrogen on graphene from density functional theory and diffusion Monte Carlo calculations

In this work, density functional theory (DFT) and diffusion Monte Carlo (DMC) methods are used to calculate the binding energy of a H atom chemisorbed on the graphene surface. The DMC value of the binding energy is about 16% smaller in magnitude than the Perdew–Burke–Ernzerhof (PBE) result. The inclusion of exact exchange through the use of the Heyd–Scuseria–Ernzerhof functional brings the DFT value of the binding energy closer in line with the DMC result. It is also found that there are significant differences in the charge distributions determined using PBE and DMC approaches.

How do interfaces alter the dynamics of supercooled water?

The structure of liquid water in the proximity of an interface can deviate significantly from that of bulk water, with surface-induced structural perturbations typically converging to bulk values at about ∼1 nm from the interface. While these structural changes are well established it is, in contrast, less clear how an interface perturbs the dynamics of water molecules within the liquid. Here, through an extensive set of molecular dynamics simulations of supercooled bulk and interfacial water films and nano-droplets, we observe the formation of persistent, spatially extended dynamical domains in which the average mobility varies as a function of the distance from the interface. This is in stark contrast with the dynamical heterogeneity observed in bulk water, where these domains average out spatially over time. We also find that the dynamical response of water to an interface depends critically on the nature of the interface and on the choice of interface definition. Overall these results reveal a richness in the dynamics of interfacial water that opens up the prospect of tuning the dynamical response of water through specific modifications of the interface structure or confining material.

Regularized second-order correlation methods for extended systems

Second-order Møller-Plesset perturbation theory (MP2) constitutes the simplest form of many-body wavefunction theory and often provides a good compromise between efficiency and accuracy. There are, however, well-known limitations to this approach. In particular, MP2 is known to fail or diverge for some prototypical condensed matter systems like the homogeneous electron gas (HEG) and to overestimate dispersion-driven interactions in strongly polarizable systems. In this paper, we explore how the issues of MP2 for metallic, polarizable, and strongly correlated periodic systems can be ameliorated through regularization. To this end, two regularized second-order methods (including a new, size-extensive Brillouin-Wigner approach) are applied to the HEG, the one-dimensional Hubbard model, and the graphene-water interaction. We find that regularization consistently leads to improvements over the MP2 baseline and that different regularizers are appropriate for the various systems.

Surface science using coupled cluster theory via local Wannier functions and in-RPA-embedding: The case of water on graphitic carbon nitride

A first-principles study of the adsorption of a single water molecule on a layer of graphitic carbon nitride is reported employing an embedding approach for many-electron correlation methods. To this end, a plane-wave based implementation to obtain intrinsic atomic orbitals and Wannier functions for arbitrary localization potentials is presented. In our embedding scheme, the localized occupied orbitals allow for a separate treatment of short-range and long-range correlation contributions to the adsorption energy by a fragmentation of the simulation cell. In combination with unoccupied natural orbitals, the coupled cluster ansatz with single, double, and perturbative triple particle-hole excitation operators is used to capture the correlation in local fragments centered around the adsorption process. For the long-range correlation, a seamless embedding into the random phase approximation yields rapidly convergent adsorption energies with respect to the local fragment size. Convergence of computed binding energies with respect to the virtual orbital basis set is achieved employing a number of recently developed techniques. Moreover, we discuss fragment size convergence for a range of approximate many-electron perturbation theories. The obtained benchmark results are compared to a number of density functional calculations.

Enhancing the Accuracy of Ab Initio Molecular Dynamics by Fine Tuning of Effective Two-Body Interactions: Acetonitrile as a Test Case

Grimme's dispersion-corrected density functional theory (DFT-D) methods have emerged among the most practical approaches to perform accurate quantum mechanical calculations on molecular systems ranging from small clusters to microscopic and mesoscopic samples, i.e., including hundreds or thousands of molecules. Moreover, DFT-D functionals can be easily integrated into popular ab initio molecular dynamics (MD) software packages to carry out first-principles condensed-phase simulations at an affordable computational cost. Here, starting from the well-established D3 version of the dispersion-correction term, we present a simple protocol to improve the accurate description of the intermolecular interactions of molecular clusters of growing size, considering acetonitrile as a test case. Optimization of the interaction energy was performed with reference to diffusion quantum Monte Carlo calculations, successfully reaching the same inherent accuracy of the latter (statistical error of ∼0.1 kcal/mol per molecule). The refined DFT-D3 model was then used to perform ab initio MD simulations of liquid acetonitrile, again showing significant improvements toward available experimental data with respect to the default correction.

Osmotic Transport at the Aqueous Graphene and hBN Interfaces: Scaling Laws from a Unified, First-Principles Description

Osmotic transport in nanoconfined aqueous electrolytes provides alternative venues for water desalination and "blue energy" harvesting. The osmotic response of nanofluidic systems is controlled by the interfacial structure of water and electrolyte solutions in the so-called electrical double layer (EDL), but a molecular-level picture of the EDL is to a large extent still lacking. Particularly, the role of the electronic structure has not been considered in the description of electrolyte/surface interactions. Here, we report enhanced sampling simulations based on ab initio molecular dynamics, aiming at unravelling the free energy of prototypical ions adsorbed at the aqueous graphene and hBN interfaces, and its consequences on nanofluidic osmotic transport. Specifically, we predicted the zeta potential, the diffusio-osmotic mobility, and the diffusio-osmotic conductivity for a wide range of salt concentrations from the ab initio water and ion spatial distributions through an analytical framework based on Stokes equation and a modified Poisson-Boltzmann equation. We observed concentration-dependent scaling laws, together with dramatic differences in osmotic transport between the two interfaces, including diffusio-osmotic flow and current reversal on hBN but not on graphene. We could rationalize the results for the three osmotic responses with a simple model based on characteristic length scales for ion and water adsorption at the surface, which are quite different on graphene and on hBN. Our work provides fundamental insights into the structure and osmotic transport of aqueous electrolytes on 2D materials and explores alternative pathways for efficient water desalination and osmotic energy conversion.

Chemically Accurate Vibrational Free Energies of Adsorption from Density Functional Theory Molecular Dynamics: Alkanes in Zeolites

We present a methodology to compute, at reduced computational cost, Gibbs free energies, enthalpies, and entropies of adsorption from molecular dynamics. We calculate vibrational partition functions from vibrational energies, which we obtain from the vibrational density of states by projection on the normal modes. The use of a set of well-chosen reference structures along the trajectories accounts for the anharmonicities of the modes. For the adsorption of methane, ethane, and propane in the H-CHA zeolite, we limit our treatment to a set of vibrational modes localized at the adsorption site (zeolitic OH group) and the alkane molecule interacting with it. Only two short trajectories (1–20 ps) are required to reach convergence (<1 kJ/mol) for the thermodynamic functions. The mean absolute deviations from the experimentally measured values are 2.6, 2.8, and 4.7 kJ/mol for the Gibbs free energy, the enthalpy, and the entropy term (−TΔS), respectively. In particular, the entropy terms show a major improvement compared to the harmonic approximation and almost reach the accuracy of the previous use of anharmonic frequencies obtained with curvilinear distortions of individual modes. The thermodynamic functions so obtained follow the trend of the experimental values for methane, ethane, and propane, and the Gibbs free energy of adsorption at experimental conditions is correctly predicted to change from positive for methane (5.9 kJ/mol) to negative for ethane (−4.8 kJ/mol) and propane (−7.1 kJ/mol).

Molecular Origin of Wettability Alteration of Subsurface Porous Media upon Gas Pressure Variations

Upon extraction/injection of a large quantity of gas from/into a subsurface system in shale gas production or carbon sequestration, the gas pressure varies remarkably, which may significantly change the wettability of porous media involved. Mechanistic understanding of such changes is critical for designing and optimizing a related subsurface engineering process. Using molecular dynamics simulations, we have calculated the contact angle of a water droplet on various solid surfaces (kerogen, pyrophyllite, calcite, gibbsite, and montmorillonite) as a function of CO₂ or CH₄ gas pressure up to 200 atm at a temperature of 300 K. The calculation reveals a complex behavior of surface wettability alteration by gas pressure variation depending on surface chemistry and structure, and molecular interactions of fluid molecules with surfaces. As the CO₂ gas pressure increases, a partially hydrophilic kerogen surface becomes highly hydrophobic, while a calcite surface becomes more hydrophilic. Considering kerogen and calcite being the major components of a shale formation, we postulate that the wettability alteration of a solid surface induced by a gas pressure change may play an important role in fluid flows in shale gas production and geological carbon sequestration.

Interactions between large molecules pose a puzzle for reference quantum mechanical methods

Quantum-mechanical methods are used for understanding molecular interactions throughout the natural sciences. Quantum diffusion Monte Carlo (DMC) and coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] are state-of-the-art trusted wavefunction methods that have been shown to yield accurate interaction energies for small organic molecules. These methods provide valuable reference information for widely-used semi-empirical and machine learning potentials, especially where experimental information is scarce. However, agreement for systems beyond small molecules is a crucial remaining milestone for cementing the benchmark accuracy of these methods. We show that CCSD(T) and DMC interaction energies are not consistent for a set of polarizable supramolecules. Whilst there is agreement for some of the complexes, in a few key systems disagreements of up to 8 kcal mol^-1 remain. These findings thus indicate that more caution is required when aiming at reproducible non-covalent interactions between extended molecules.

Dynamical correlation energy of metals in large basis sets from downfolding and composite approaches

Coupled-cluster theory with single and double excitations (CCSD) is a promising ab initio method for the electronic structure of three-dimensional metals, for which second-order perturbation theory (MP2) diverges in the thermodynamic limit. However, due to the high cost and poor convergence of CCSD with respect to basis size, applying CCSD to periodic systems often leads to large basis set errors. In a common "composite" method, MP2 is used to recover the missing dynamical correlation energy through a focal-point correction, but the inadequacy of finite-order perturbation theory for metals raises questions about this approach. Here, we describe how high-energy excitations treated by MP2 can be "downfolded" into a low-energy active space to be treated by CCSD. Comparing how the composite and downfolding approaches perform for the uniform electron gas, we find that the latter converges more quickly with respect to the basis set size. Nonetheless, the composite approach is surprisingly accurate because it removes the problematic MP2 treatment of double excitations near the Fermi surface. Using this method to estimate the CCSD correlation energy in the combined complete basis set and thermodynamic limits, we find that CCSD recovers 85%-90% of the exact correlation energy at r_s = 4. We also test the composite approach with the direct random-phase approximation used in place of MP2, yielding a method that is typically (but not always) more cost effective due to the smaller number of orbitals that need to be included in the more expensive CCSD calculation.

How do the doping concentrations of N and B in graphene modify the water adsorption?

Understanding the interaction of water and graphene is crucial for various applications such as water purification, desalination, and electrocatalysis. Experimental and theoretical studies have already investigated water adsorption on N- and B-doped graphene. However, there are no reports available that elucidate the influences of the N and B doping content in graphene on the microscopic geometrical structure and the electronic properties of the adsorbed water. Thus, this work is devoted to solving this problem using self-consistent van der Waals density functional theory calculations. The N and B doping contents of 0.0, 3.1, 6.3, and 9.4% were considered. The results showed that the binding energy of water increases almost linearly as a function of doping content at all concentrations for N-doped graphene but below 6.3% for B-doped graphene. In the linear range, the binding energy increases by approximately 30 meV for each increment of the doping ratio. Analyses of the geometric and electronic structures explained the enhancement of the water-graphene interaction with the variation in doping percentage.

Water friction in nanofluidic channels made from two-dimensional crystals

Membrane-based applications such as osmotic power generation, desalination and molecular separation would benefit from decreasing water friction in nanoscale channels. However, mechanisms that allow fast water flows are not fully understood yet. Here we report angstrom-scale capillaries made from atomically flat crystals and study the effect of confining walls' material on water friction. A massive difference is observed between channels made from isostructural graphite and hexagonal boron nitride, which is attributed to different electrostatic and chemical interactions at the solid-liquid interface. Using precision microgravimetry and ion streaming measurements, we evaluate the slip length, a measure of water friction, and investigate its possible links with electrical conductivity, wettability, surface charge and polarity of the confining walls. We also show that water friction can be controlled using hybrid capillaries with different slip lengths at opposing walls. The reported advances extend nanofluidics' toolkit for designing smart membranes and mimicking manifold machinery of biological channels.

Reversible hydrogenation restores defected graphene to graphene

Graphene as a two-dimensional material is prone to hydrocarbon contaminations, which can significantly alter its intrinsic electrical properties. Herein, we implement a facile hydrogenation-dehydrogenation strategy to remove hydrocarbon contaminations and preserve the excellent transport properties of monolayer graphene. Using electron microscopy we quantitatively characterized the improved cleanness of hydrogenated graphene compared to untreated samples. In situ spectroscopic investigations revealed that the hydrogenation treatment promoted the adsorption ofytyt water at the graphene surface, resulting in a protective layer against the re-deposition of hydrocarbon molecules. Additionally, the further dehydrogenation of hydrogenated graphene rendered a more pristine-like basal plane with improved carrier mobility compared to untreated pristine graphene. Our findings provide a practical post-growth cleaning protocol for graphene with maintained surface cleanness and lattice integrity to systematically carry a range of surface chemistry in the form of a well-performing and reproducible transistor.

Associated molecular liquids at the graphene monolayer interface

We report molecular simulations of the interaction between a graphene sheet and different liquids such as water, ethanol, and ethylene glycol. We describe the structural arrangements at the graphene interface in terms of density profiles, number of hydrogen bonds (HBs), and local structuration in neighboring layers close to the surface. We establish the formation of a two-dimensional HB network in the layer closest to the graphene. We also calculate the interfacial tension of liquids with a graphene monolayer and its profile along the direction normal to the graphene to rationalize and quantify the strengthening of the intermolecular interactions in the liquid due to the presence of the surface.

New insights into the 1D carbon chain through the RPA

We investigated the electronic and structural properties of the infinite linear carbon chain (carbyne) using density functional theory (DFT) and the random phase approximation (RPA) to the correlation energy. The studies are performed in vacuo and for carbyne inside a carbon nano tube (CNT). In the vacuum, semi-local DFT and RPA predict bond length alternations of about 0.04 Å and 0.13 Å, respectively. The frequency of the highest optical mode at the Γ point is 1219 cm-1 and about 2000 cm-1 for DFT and the RPA. Agreement of the RPA to previous high level quantum chemistry and diffusion Monte-Carlo results is excellent. For the RPA we calculate the phonon-dispersion in the full Brillouine zone and find marked quantitative differences to DFT calculations not only at the Γ point but also throughout the entire Brillouine zone. To model carbyne inside a carbon nanotube, we considered a (10,0) CNT. Here the DFT calculations are even qualitatively sensitive to the k-points sampling. At the limes of a very dense k-points sampling, semi-local DFT predicts no bond length alternation (BLA), whereas in the RPA a sizeable BLA of 0.09 Å prevails. The reduced BLA leads to a significant red shift of the vibrational frequencies of about 350 cm-1, so that they are in good agreement with experimental estimates. Overall, the good agreement between the RPA and previously reported results from correlated wavefunction methods and experimental Raman data suggests that the RPA provides reliable results at moderate computational costs. It hence presents a useful addition to the repertoire of correlated wavefunction methods and its accuracy clearly prevails for low dimensional systems, where semi-local density functionals struggle to yield even qualitatively correct results.

Regional Embedding Enables High-Level Quantum Chemistry for Surface Science

Compared to common density functionals, ab initio wave function methods can provide greater reliability and accuracy, which could prove useful when modeling adsorbates or defects of otherwise periodic systems. However, the breaking of translational symmetry necessitates large supercells that are often prohibitive for correlated wave function methods. As an alternative, this paper introduces the regional embedding approach, which enables correlated wave function treatments of only a target fragment of interest through small, fragment-localized orbital spaces constructed using a simple overlap criterion. Applications to the adsorption of water on lithium hydride, hexagonal boron nitride, and graphene substrates show that regional embedding combined with focal-point corrections can provide converged CCSD(T) (coupled-cluster) adsorption energies with very small fragment sizes.

Polycrystalline Few-Layer Graphene as a Durable Anticorrosion Film for Copper

Corrosion of metals in atmospheric environments is a worldwide problem in industry and daily life. Traditional anticorrosion methods including sacrificial anodes or protective coatings have performance limitations. Here, we report atomically thin, polycrystalline few-layer graphene (FLG) grown by chemical vapor deposition as a long-term protective coating film for copper (Cu). A six-year old, FLG-protected Cu is visually shiny and detailed material characterizations capture no sign of oxidation. The success of the durable anticorrosion film depends on the misalignment of grain boundaries between adjacent graphene layers. Theoretical calculations further found that corrosive molecules always encounter extremely high energy barrier when diffusing through the FLG layers. Therefore, the FLG is able to prevent the corrosive molecules from reaching the underlying Cu surface. This work highlights the interesting structures of polycrystalline FLG and sheds insight into the atomically thin coatings for various applications.

Effects of the Interfacial Modeling Approach on Equilibrium Calculations of Slip Length for Nanoconfined Water in Carbon Slits

In this investigation, equilibrium molecular dynamics simulations were conducted to assess the influence of the interface modeling approach on the calculation of hydrodynamic slip in carbon nanochannels. A Green-Kubo formalism was implemented for the calculation of the slip length in water confined by graphite layers. The nonbonded interactions between solid and liquid atoms (interface models) were modeled using parameters optimized to represent the wetting behavior and adsorption energy curves from electronic structure calculations. Conventional carbon-oxygen-only interaction models were compared against comprehensive models able to represent the molecular-orientation-dependent energy of interaction. Quasi-universal relationships built under the premise of the slip length dependence on the water-graphite affinity and characterized by macroscopic wettability were critically assessed. It was found that the wetting behavior cannot fully characterize the hydrodynamic slip because interface models that produced the same surface wettability yielded different values of the friction coefficient. Alternatively, the density depletion length, used to characterize the interfacial liquid structuring and the availability of momentum carriers (interfacial water molecules), was able to accurately represent the slip length trends independently of the interface model. These findings reassert the importance of physically sound interface models to study interfacial transport properties and the need of reliable parameters and characterization procedures to support theoretical models that seek to unveil the inconsistencies in hydrodynamic slip calculations.

Computational Investigations of Dispersion Interactions between Small Molecules and Graphene-like Flakes

We investigate dispersion interactions in a selection of atomic, molecular, and molecule-surface systems, comparing high-level correlated methods with empirically corrected density functional theory (DFT). We assess the efficacy of functionals commonly used for surface-based calculations, with and without the D3 correction of Grimme. We find that the inclusion of the correction is essential to get meaningful results, but there is otherwise little to distinguish between the functionals. We also present coupled-cluster quality interaction curves for H₂, NO₂, H₂O, and Ar interacting with large carbon flakes, acting as models for graphene surfaces, using novel absolutely localized molecular orbital based methods. These calculations demonstrate that the problems with empirically corrected DFT when investigating dispersion appear to compound as the system size increases, with important implications for future computational studies of molecule-surface interactions.

Hydration of NH_{4}^{+} in Water: Bifurcated Hydrogen Bonding Structures and Fast Rotational Dynamics

Understanding the hydration and diffusion of ions in water at the molecular level is a topic of widespread importance. The ammonium ion (NH_{4}^{+}) is an exemplar system that has received attention for decades because of its complex hydration structure and relevance in industry. Here we report a study of the hydration and the rotational diffusion of NH_{4}^{+} in water using ab initio molecular dynamics simulations and quantum Monte Carlo calculations. We find that the hydration structure of NH_{4}^{+} features bifurcated hydrogen bonds, which leads to a rotational mechanism involving the simultaneous switching of a pair of bifurcated hydrogen bonds. The proposed hydration structure and rotational mechanism are supported by existing experimental measurements, and they also help to rationalize the measured fast rotation of NH_{4}^{+} in water. This study highlights how subtle changes in the electronic structure of hydrogen bonds impacts the hydration structure, which consequently affects the dynamics of ions and molecules in hydrogen bonded systems.

A QM/MD Coupling Method to Model the Ion-Induced Polarization of Graphene

We report a new Quantum Mechanical/Molecular Dynamics (QM/MD) simulation loop to model the coupling between the electron and atom dynamics in solid/liquid interfacial systems. The method can describe simultaneously both the quantum mechanical surface polarizability emerging from the proximity to the electrolyte and the electrolyte structure and dynamics. In the current setup, Density Functional Tight Binding calculations for the electronic structure calculations of the surface are coupled with classical molecular dynamics to simulate the electrolyte solution. The reduced computational cost of the QM part makes the coupling with a classical simulation engine computationally feasible and allows simulation of large systems for hundreds of nanoseconds. We tested the method by simulating both a noncharged graphene flake and a noncharged and charged infinite graphene sheet immersed in an NaCl electrolyte solution. We found that, when no bias is applied, ions preferentially remained in solution, and only cations are mildly attracted to the surface of the graphene. This preferential adsorption of cations vs anions seems to persist also when the surface is moderately charged and rules out any substantial ions/surface charge transfer.

Ab initio nanofluidics: disentangling the role of the energy landscape and of density correlations on liquid/solid friction

Despite relevance to water purification and renewable energy conversion membranes, the molecular mechanisms underlying water slip are poorly understood. We disentangle the static and dynamical origin of water slippage on graphene, hBN and MoS2 by means of large-scale ab initio molecular dynamics. Accounting for the role of the electronic structure of the interface is essential to determine that water slips five and eleven times faster on graphene compared to hBN and to MoS2, respectively. Intricate changes in the water energy landscape as well as in the density correlations of the fluid provide, respectively, the main static and dynamical origin of water slippage. Surprisingly, the timescales of the density correlations are the same on graphene and hBN, whereas they are longer on MoS2 and yield a 100% slowdown in the flow of water on this material. Our results pave the way for an in silico first principles design of materials with enhanced water slip, through the modification of properties connected not only to the structure, but also to the dynamics of the interface.