Exploring Adsorption of Water and Ions on Carbon Surfaces using a Polarizable Force Field

A Fast, Convenient, Polarizable Electrostatic Model for Molecular Dynamics

We present an efficient polarizable electrostatic model, utilizing typed, atom-centered polarizabilities and the fast direct approximation, designed for efficient use in molecular dynamics (MD) simulations. The model provides two convenient approaches for assigning partial charges in the context of atomic polarizabilities. One is a generalization of RESP, called RESP-dPol, and the other, AM1-BCC-dPol, is an adaptation of the widely used AM1-BCC method. Both are designed to accurately replicate gas-phase quantum mechanical electrostatic potentials. Benchmarks of this polarizable electrostatic model against gas-phase dipole moments, molecular polarizabilities, bulk liquid densities, and static dielectric constants of organic liquids show good agreement with the reference values. Of note, the model yields markedly more accurate dielectric constants of organic liquids, relative to a matched nonpolarizable force field. MD simulations with this method, which is currently parametrized for molecules containing elements C, N, O, and H, run only about 3.6-fold slower than fixed charge force fields, while simulations with the self-consistent mutual polarization average 4.5-fold slower. Our results suggest that RESP-dPol and AM1-BCC-dPol afford improved accuracy relative to fixed charge force fields and are good starting points for developing general, affordable, and transferable polarizable force fields. The software implementing these approaches has been designed to utilize the force field fitting frameworks developed and maintained by the Open Force Field Initiative, setting the stage for further exploration of this approach to polarizable force field development.

Water Electric Field Induced Modulation of the Wetting of Hexagonal Boron Nitride: Insights from Multiscale Modeling of Many-Body Polarization

Understanding the behavior of water contacting two-dimensional materials, such as hexagonal boron nitride (hBN), is important in practical applications, including seawater desalination and energy harvesting. Water, being a polar solvent, can strongly polarize the hBN surface via the electric fields that it generates. However, there is a lack of molecular-level understanding about the role of polarization effects at the hBN/water interface, including its effect on the wetting properties of water. In this study, we develop a theoretical framework that introduces an all-atomistic polarizable force field to accurately model the interactions of water molecules with hBN surfaces. The force field is then utilized to self-consistently describe the water-induced polarization of hBN using the classical Drude oscillator model, including predicting the hBN-water binding energies which are found to be in excellent agreement with diffusion Monte Carlo (DMC) predictions. By carrying out molecular dynamics (MD) simulations, we demonstrate that the polarizable force field yields a water contact angle on multilayered hBN which is in close agreement with the recent experimentally reported values. Conversely, an implicit modeling of the hBN-water polarization energy utilizing a Lennard-Jones (LJ) potential, a commonly utilized approximation in previous MD simulation studies, leads to a considerably lower water contact angle. This difference in the predicted contact angles is attributed to the significant energy-entropy compensation resulting from the incorporation of polarization effects at the hBN-water interface. Our work highlights the importance of self-consistently modeling the hBN-water polarization energy and offers insights into the wetting-related interfacial phenomena of water on polarizable materials.

Application of a Fluctuating Charge Polarization Model to Large Polyaromatic Hydrocarbons and Graphene Nanoflakes

We present a polarization model incorporating coupled fluctuating charges and point inducible dipoles that is able to accurately describe the dipole polarizabilities of small hydrocarbons and, for sufficiently large graphene nanoflakes, reproduce the classical image potential of an infinite conducting sheet. When our fluctuating charge model is applied to the hexagonal carbon nanoflake C60000 we attain excellent agreement with the image potential and induced charge distribution of a conducting sheet. With the inclusion of inducible dipole terms, the model predicts an image plane of zim = 1.3334 a0, which falls in line with prior estimates for graphene. We consider the case of two charges placed on opposite sides of C60000 and find that the fluctuating charge model reproduces classical electrostatics once again. By testing opposing and similar signs of the external charges, we conclude that an atomically thin molecule or extended system does not fully screen their interaction.

High-Performance Ionanofluids from Subzipped Carbon Nanotube Networks

Investments in the transfer and storage of thermal energy along with renewable energy sources strengthen health and economic infrastructure. These factors intensify energy diversification and the more rapid post-COVID recovery of economies. Ionanofluids (INFs) composed of long multiwalled carbon nanotubes (MWCNTs) rich in sp²-hybridized atoms and ionic liquids (ILs) display excellent thermal conductivity enhancement with respect to the pure IL, high thermal stability, and attractive rheology. However, the influence of the morphology, physicochemistry of nanoparticles and the IL-nanostructure interactions on the mechanism of heat transfer and rheological properties of INFs remain unidentified. Here, we show that intertube nanolayer coalescence, supported by 1D geometry assembly, leads to the subzipping of MWCNT bundles and formation of thermal bridges toward 3D networks in the whole INF volume. We identified stable networks of straight and bent MWCNTs separated by a layer of ions at the junctions. We found that the interactions between the ultrasonication-induced breaking nanotubes and the cations were covalent in nature. Furthermore, we found that the ionic layer imposed by close MWCNT surfaces favored enrichment of the cis conformer of the bis(trifluoromethylsulfonyl)imide anion. Our results demonstrate how the molecular perfection of the MWCNT structure with its supramolecular arrangement affects the extraordinary thermal conductivity enhancement of INFs. Thus, we gave the realistic description of the interactions at the IL-CNT interface with its (super)structure and chemistry as well as the molecular structure of the continuous phase. We anticipate our results to be a starting point for more complex studies on the supramolecular zipping mechanism. For example, ionically functionalized MWCNTs toward polyionic systems─of projected and controlled nanolayers─could enable the design of even more efficient heat-transfer fluids and miniaturization of flexible electronics.

Synergistic Effect of Bio-Inspired Nanochannels: Hydrophilic DNA Probes at Inner Wall and Hydrophobic Coating at Outer Surface for Highly Sensitive Detection

During the past few decades, bio-inspired nanochannels have been well developed and applied in biosensing, energy transfer, separation, and so on. Here, inspired by the synergistic effect of biological nanopores, biomimetic solid-state nanochannels with hydrophilic DNA probes at the inner wall (DNA@IW_Hydrophilic ) and hydrophobic coating at the outer surface (None@OS_Hydrophobic ) are designed. To demonstrate their prompted sensing properties, Hg²⁺ and its specific probe are selected as target and hydrophilic DNA probes, respectively. Compared with the traditional solid-state nanochannels with hydrophilic probes distributed on both the inner wall and outer surface, the nanochannels with DNA@IW_Hydrophilic +None@OS_Hydrophobic significantly decrease the limit of detection (LOD) by 10⁵ -fold. The obvious improvement of sensitivity (with LOD of 1 nM) is attributed to the synergistic effect: None@OS_Hydrophobic results in the nanochannel's effective diameter decrease and DNA@IW_Hydrophilic induces a specific sensing target. Meanwhile, nanomolar detection of Hg²⁺ in human serum and in vivo fish muscle are achieved. Through molecular dynamics simulation, the synergistic effect can be confirmed by ion fluxes increasement; the relative carbon nanotube increases from 135.64% to 135.84%. This work improves the understanding of nanochannels' synergistic effect and provides a significant insight for nanochannels with improved sensitivity.

Putting together the puzzle of ion transfer in single-digit carbon nanotubes: mean-field meets ab initio

Nature employs channel proteins to selectively pass water across cell membranes, which inspires the search for bio-mimetic analogues. Carbon nanotube porins (CNTPs) are intriguing mimics of water channels, yet ion transport in CNTPs still poses questions. As an alternative to continuum models, here we present a molecular mean-field model that transparently describes ion coupling, yet unlike continuum models, computes ab initio all required thermodynamic quantities for the KCl salt and H⁺ and OH^- ions present in water. Starting from water transfer, the model considers the transfer of free ions, along with ion-pair formation as a proxy of non-mean-field ion-ion interactions. High affinity to hydroxide, suggested by experiments, making it a dominant charge carrier in CNTPs, is revealed as an exceptionally favorable transfer of KOH pairs. Nevertheless, free ions, coexisting with less mobile ion-pairs, apparently control ion transport. The model well explains the observed effects of salt concentration and pH on conductivity, transport numbers, anion permeation and its activation energies, and current rectification. The proposed approach is extendable to other sub-nanochannels and helps design novel osmotic materials and devices.

DLPGEN: Preparing Molecular Dynamics Simulations with Support for Polarizable Force Fields

Preparing input files for molecular dynamics (MD) simulations can be a tedious task, particularly if different MD programs need to be used. Most simulation packages are accompanied by applications that handle this task, and, in some cases, software to perform interconversion between MD programs can be found. However, the conversion between different types of files is not always foolproof or the force field may not be fully supported, as quite often observed with polarization models. This work describes the program DLPGEN, which produces input files for the MD programs GROMACS, CHARMM, DL_POLY, and LAMMPS. The program can prepare polarizable force fields using a self-consistent field approach or with a dual thermostat-extended Lagrangian model. For GROMACS, a new polarization scheme suitable for the simulation of molecules containing more than one virtual particle is described. Results obtained for ethanol in the liquid state revealed that the system configurational energy, liquid density, and self-diffusion coefficient obtained with GROMACS are in good agreement with the data found with LAMMPS and CHARMM. In the case of DL_POLY, a problem with the Shells temperature control was found, suggesting that this program may not be suitable for the simulation of molecules containing multiple Drude particles.

Molecular Basis of Artemisinin Derivatives Inhibition of Myeloid Differentiation Protein 2 by Combined in Silico and Experimental Study

Artemisinin (also known as Qinghaosu), an active component of the Qinghao extract, is widely used as antimalarial drug. Previous studies reveal that artemisinin and its derivatives also have effective anti-inflammatory and immunomodulatory properties, but the direct molecular target remains unknown. Recently, several reports mentioned that myeloid differentiation factor 2 (MD-2, also known as lymphocyte antigen 96) may be the endogenous target of artemisinin in the inhibition of lipopolysaccharide signaling. However, the exact interaction between artemisinin and MD-2 is still not fully understood. Here, experimental and computational methods were employed to elucidate the relationship between the artemisinin and its inhibition mechanism. Experimental results showed that artemether exhibit higher anti-inflammatory activity performance than artemisinin and artesunate. Molecular docking results showed that artemisinin, artesunate, and artemether had similar binding poses, and all complexes remained stable throughout the whole molecular dynamics simulations, whereas the binding of artemisinin and its derivatives to MD-2 decreased the TLR4(Toll-Like Receptor 4)/MD-2 stability. Moreover, artemether exhibited lower binding energy as compared to artemisinin and artesunate, which is in good agreement with the experimental results. Leu61, Leu78, and Ile117 are indeed key residues that contribute to the binding free energy. Binding free energy analysis further confirmed that hydrophobic interactions were critical to maintain the binding mode of artemisinin and its derivatives with MD-2.

Steered molecular dynamics and stability analysis on PAH dimerisation and condensation on fullerene and soot surfaces

The mechanism of how a soot nucleus is impacted by polycyclic aromatic hydrocarbons (PAHs) and then grows through PAH condensation remains unclear. Using steered molecular dynamics (SMD), the non-bonding interaction between PAHs and soot was quantitatively studied using the free energy distribution during the dimerisation and condensation. The results showed that only two dimers (A₇-A₁₀ and 2 A₁₀) remained stable at 1000 K. The simulations showed that PAH condensation on a fullerene should not be ignored in soot mass growth. For fullerenes with a diameter not less than 1.8 nm (C₅₄₀), even A₄ condenses at temperatures of 1500 K, and A10 condenses stably on the surface of fullerenes even at 2000 K. The effects of multilayers and hydrogenated fullerenes on the free energy of PAH condensation are different. The stability of PAH dimers and PAH condensation pairs was discussed through free energy and chemical equilibrium. The results show that larger dimers are more stable than small ones at flame temperatures. Condensation is far more important than nucleation in mass growth at flame temperatures. Furthermore, the larger the PAH is, the higher the transformation ratio of the PAH in condensation on soot and thus the more stable the condensation product is. Finally, both the stability analysis of an upper temperature limit for condensation and simulation results of ReaxFF-MD cross-confirm that pyrene stably condensates on a simplified nascent soot (C₅₄₀) and a simulated soot (C₆₅₈H₃₁₉O₉), respectively, at 1500 K, but not at higher temperatures over 1800 K.

Polarization influences the evolution of nucleobase-graphene interactions

In recent years, graphene has attracted attention from researchers as an atomistically thin solid state material for the study on the self-assembly of nucleobases. Non-covalent interactions between nucleobases and graphene sheets play a fundamental role in understanding the self-assembly of nucleobases on the graphene sheet. A fundamental understanding of the effect of molecular polarizability on these non-covalent interactions between the nucleobases and the underlying graphene sheet is absent in the literature. In this paper, we present the results from polarizable molecular dynamics simulation studies to understand the effect of polarization on the strength of non-covalent interactions. To this end, we report the development of Drude parameters for describing the polarizable graphene sheet. The developed parameters were used to study the self-aggregation phenomenon of nucleobases on a graphene support. We observe a significant change in the interaction patterns upon the inclusion of polarization into the system, with polarizable simulations yielding results that closely resemble the experimental studies. Two of the key observations were the probability of the formation of stacks in guanine-rich systems, and the spontaneous formation of H-bonded structures over the graphene sheet, which allude to the importance of the DNA sequence and composition. Both these effects were not observed in the additive simulations. The present study sheds light on the effect of polarization on the adsorption of DNA nucleobases on a graphene sheet, but the methodology can be extended to include a variety of small molecules and complete DNA strands.

Phase-dependent friction of nanoconfined water meniscus

A water meniscus naturally forms under ambient conditions at the point of contact between a nanoscale tip and an atomically flat substrate. Here, we study the effect of the phase state of this nanoscale meniscus-consisting of coexisting monolayer, bilayer and trilayer phase domains-on the frictional behavior during tip sliding by means of molecular dynamics simulations. While the meniscus experiences a domain-by-domain liquid-to-solid phase transition induced by lateral compression, we observe an evident transition in measured friction curves from continuous sliding to stick-slip and meanwhile a gradual increase in friction forces. Moreover, the stick-slip friction can be modulated by varying lattice orientation of the monolayer ice domain in the meniscus, choosing the sliding direction or applying in-plane strains to the substrate. Our results shed light on the rational design of high-performance micro- and nano-electromechanical systems relying on hydration lubrication.

Solvent-Solvent Correlations across Graphene: The Effect of Image Charges

Wetting experiments show pure graphene to be weakly hydrophilic, but its contact angle (CA) also reflects the character of the supporting material. Measurements and molecular dynamics simulations on suspended and supported graphene often reveal a CA reduction due to the presence of the supporting substrate. A similar reduction is consistently observed when graphene is wetted from both sides. The effect has been attributed to transparency to molecular interactions across the graphene sheet; however, the possibility of substrate-induced graphene polarization has also been considered. Computer simulations of CA on graphene have so far been determined by ignoring the material's conducting properties. We improve the graphene model by incorporating its conductivity according to the constant applied potential molecular dynamics. Using this method, we compare the wettabilities of suspended graphene and graphene supported by water by measuring the CA of cylindrical water drops on the sheets. The inclusion of graphene conductivity and concomitant polarization effects leads to a lower CA on suspended graphene, but the CA reduction is significantly bigger when the sheets are also wetted from the opposite side. The stronger adhesion is accompanied by a profound change in the correlations among water molecules across the sheet. While partial charges on water molecules interacting across an insulator sheet attract charges of the opposite sign, apparent attraction among like charges is manifested across the conducting graphene. The change is associated with graphene polarization, as the image charges inside the conductor attract equally signed partial charges of water molecules on both sides of the sheet. Additionally, using a nonpolar liquid (diiodomethane), we affirm a detectable wetting translucency when liquid-liquid forces are dominated by dispersive interactions. Our findings are important for predictive modeling toward a variety of applications including sensors, fuel cell membranes, water filtration, and graphene-based electrode materials in high-performance supercapacitors.

A combined in silico and in vitro study on mouse Serpina1a antitrypsin-deficiency mutants

Certain point-mutations in the human SERPINA1-gene can cause severe α1-antitrypsin-deficiency (A1AT-D). Affected individuals can suffer from loss-of-function lung-disease and from gain-of-function liver-disease phenotypes. However, age of onset and severity of clinical appearance is heterogeneous amongst carriers, suggesting involvement of additional genetic and environmental factors. The generation of authentic A1AT-D mouse-models has been hampered by the complexity of the mouse Serpina1-gene locus and a model with concurrent lung and liver-disease is still missing. Here, we investigate point-mutations in the mouse Serpina1a antitrypsin-orthologue, which are homolog-equivalent to ones known to cause severe A1AT-D in human. We combine in silico and in vitro methods and we find that analyzed mutations do introduce potential disease-causing properties into Serpina1a. Finally, we show that introduction of the King’s-mutation causes inactivation of neutrophil elastase inhibitory-function in both, mouse and human antitrypsin, while the mouse Z-mutant retains activity. This work paves the path to generation of better A1AT-D mouse-models.

How does binding of agonist ligands control intrinsic molecular dynamics in human NMDA receptors?

NMDA-type glutamate receptors (NMDAR) are ligand-gated ion channels that contribute to excitatory neurotransmission in the central nervous system. NMDAR dysfunction has been found to be involved in various neurological disorders. Recent crystallographic and EM studies have shown the static structure of different states of the non-human NMDARs. Here we describe a model of a human NMDA receptor (hNMDAR) and its molecular dynamics (MD) before and after the binding of agonist ligands, glutamate and glycine. It is shown that the binding of ligands promotes a global reduction in molecular flexibility that produces a more tightly packed conformation than the unbound hNMDAR, and a higher cooperative regularity of moving. The ligand-induced synchronization of motion, identified on all structural levels of the modular hNMDA receptor is apparently a fundamental factor in channel gating. Although the time scale of the MD simulations (300 ns) was not sufficient to observe the complete gating event, the obtained data has shown the ligand-induced stabilization of hNMDAR that conforms the “going to be open state”. We propose a mechanistic dynamic model of the ligand-dependent gating mechanism in the hNMDA receptor. At the binding of the ligands, the differently twisted conformations of the highly flexible receptor are stabilized in unique conformation with a linear molecular axis, which is a condition that is optimal for pore development. By searching the receptor surface, we have identified three new pockets, which are different from the pockets described in the literature as the potential and known positive allosteric modulator binding sites. A successful docking of two NMDAR modulators to their binding sites validates the model of a human NMDA receptor as a biological relevant target.

Molecular interactions and thermal transport in ionic liquids with carbon nanomaterials

We used molecular dynamics simulation to study the effect of suspended carbon nanomaterials, nanotubes and graphene sheets, on the thermal conductivity of ionic liquids, an issue related to understanding the properties of nanofluids. One important aspect that we developed is an atomistic model of the interactions between the organic ions and carbon nanomaterials, so we did not rely on existing force fields for small organic molecules or assume simple combining rules to describe the interactions at the liquid/material interface. Instead, we used quantum calculations with a density functional suitable for non-covalent interactions to parameterize an interaction model, including van der Waals terms and also atomic partial charges on the materials. We fitted a n-m interaction potential function with n values of 9 or 10 and m values between 5 and 8, so a 12-6 Lennard-Jones function would not fit the quantum calculations. For the atoms of ionic liquids and carbon nanomaterials interacting among themselves, we adopted existing models from the literature. We studied the imidazolium ionic liquids [C₄C₁im][SCN], [C₄C₁im][N(CN)₂], [C₄C₁im][C(CN)₃] and [C₄C₁im][(CF₃SO₂)₂N]. Attraction is stronger for cations (than for anions) above and below the π-system of the nanomaterials, whereas anions show stronger attraction for the hydrogenated edges. The ordering of ions around and inside (7,7) and (10,10) single-walled nanotubes, and near a stack of graphene sheets, was analysed in terms of density distribution functions. We verified that anions are found, as well as cations, in the first interfacial layer interacting with the materials, which is surprising given the interaction potential surfaces. The thermal conductivity of the ionic liquids and of composite systems containing one nanotube or one graphene stack in suspension was calculated using non-equilibrium molecular dynamics. Thermal conductivity was calculated along the axis of the nanotube and across the planes of graphene, in order to see the anisotropy. In the composite systems containing the nanotube, there is an enhancement of the overall thermal conductivity, with calculated values comparing well with experiments on nanotube suspensions, namely in terms of the order of the different ionic liquids. In the systems containing the graphene stack, the interfacial region of the ionic liquid near the surface of the material has an enhanced thermal conductivity with respect to the bulk liquid, but no significant discontinuity in the temperature profiles were observed. This is important information for models of thermal conduction in nanofluids.

Activity and Reactivity of Pyrogenic Carbonaceous Matter toward Organic Compounds

Pyrogenic carbonaceous matter (PCM) includes environmental black carbon (fossil fuel soot, biomass char), engineered carbons (biochar, activated carbon), and related materials like graphene and nanotubes. These materials contact organic pollutants due to their widespread presence in the environment or through their use in various engineering applications. This review covers recent advances in our understanding of adsorption and chemical reactions mediated by PCM and the links between these processes. It also covers adsorptive processes previously receiving little attention and ignored in models such as steric constraints, physicochemical effects of confinement in nanopores, π interactions of aromatic compounds with polyaromatic surfaces, and very strong hydrogen bonding of ionizable compounds with surface functional groups. Although previous research has regarded carbons merely as passive sorbents, recent studies show that PCM can promote chemical reactions of sorbed contaminants at ordinary temperature, including long-range electron conduction between molecules and between microbes and molecules, local redox reactions between molecules, and hydrolysis. PCM may itself contain redox-active functional groups that are capable of oxidizing or reducing organic compounds and of generating reactive oxygen species (ROS) from oxygen, peroxides, or ozone. Amorphous carbons contain persistent free radicals that may play a role in observed redox reactions and ROS generation. Reactions mediated by PCM can impact the biogeochemical fate of pollutants and lead to useful strategies for remediation.

Improved Description of Sulfur Charge Anisotropy in OPLS Force Fields: Model Development and Parameterization

The atomic point-charge model used in most molecular mechanics force fields does not represent well the electronic anisotropy that is featured in many directional noncovalent interactions. Sulfur participates in several types of such interactions with its lone pairs and σ-holes. The current study develops a new model, via the addition of off-atom charged sites, for a variety of sulfur compounds in the OPLS-AA and OPLS/CM5 force fields to address the lack of charge anisotropy. Parameter optimization is carried out to reproduce liquid-state properties, torsional and noncovalent energetics from reliable quantum mechanical calculations, and electrostatic potentials. Significant improvements are obtained for computed free energies of hydration, reducing the mean unsigned errors from ca. 1.4 to 0.4-0.7 kcal/mol. Enhanced accuracy in directionality and energetics is also obtained for molecular complexes with sulfur-containing hydrogen and halogen bonds. Moreover, the new model reproduces the unusual conformational preferences of sulfur-containing compounds with 1,4-intramolecular chalcogen bonds. Transferability of the new force field parameters to cysteine and methionine is verified via molecular dynamic simulations of blocked dipeptides. The study demonstrates the effectiveness of using off-atom charge sites to address electronic anisotropy, and provides a parametrization methodology that can be applied to other systems.

Peptide interactions with zigzag edges in graphene

Recognition and manipulation of graphene edges enable the control of physical properties of graphene-based devices. Recently, the authors have identified a peptide that preferentially binds to graphene edges from a combinatorial peptide library. In this study, the authors examine the functional basis for the edge binding peptide using experimental and computational methods. The effect of amino acid substitution, sequence context, and solution pH value on the binding of the peptide to graphene has been investigated. The N-terminus glutamic acid residue plays a key role in recognizing and binding to graphene edges. The protonation, substitution, and positional context of the glutamic acid residue impact graphene edge-binding. Our findings provide insights into the binding mechanisms and the design of peptides for recognizing and functionalizing graphene edges.

Modeling and simulation of protein-surface interactions: achievements and challenges

Understanding protein-inorganic surface interactions is central to the rational design of new tools in biomaterial sciences, nanobiotechnology and nanomedicine. Although a significant amount of experimental research on protein adsorption onto solid substrates has been reported, many aspects of the recognition and interaction mechanisms of biomolecules and inorganic surfaces are still unclear. Theoretical modeling and simulations provide complementary approaches for experimental studies, and they have been applied for exploring protein-surface binding mechanisms, the determinants of binding specificity towards different surfaces, as well as the thermodynamics and kinetics of adsorption. Although the general computational approaches employed to study the dynamics of proteins and materials are similar, the models and force-fields (FFs) used for describing the physical properties and interactions of material surfaces and biological molecules differ. In particular, FF and water models designed for use in biomolecular simulations are often not directly transferable to surface simulations and vice versa. The adsorption events span a wide range of time- and length-scales that vary from nanoseconds to days, and from nanometers to micrometers, respectively, rendering the use of multi-scale approaches unavoidable. Further, changes in the atomic structure of material surfaces that can lead to surface reconstruction, and in the structure of proteins that can result in complete denaturation of the adsorbed molecules, can create many intermediate structural and energetic states that complicate sampling. In this review, we address the challenges posed to theoretical and computational methods in achieving accurate descriptions of the physical, chemical and mechanical properties of protein-surface systems. In this context, we discuss the applicability of different modeling and simulation techniques ranging from quantum mechanics through all-atom molecular mechanics to coarse-grained approaches. We examine uses of different sampling methods, as well as free energy calculations. Furthermore, we review computational studies of protein-surface interactions and discuss the successes and limitations of current approaches.

Evaluation of Representations and Response Models for Polarizable Force Fields

For classical simulations of condensed-phase systems, such as organic liquids and biomolecules, to achieve high accuracy, they will probably need to incorporate an accurate, efficient model of conformation-dependent electronic polarization. Thus, it is of interest to understand what determines the accuracy of a polarizable electrostatics model. This study approaches this problem by breaking polarization models down into two main components: the representation of electronic polarization and the response model used for mapping from an inducing field to the polarization within the chosen representation. Among the most common polarization representations are redistribution of atom-centered charges, such as those used in the fluctuating charge model, and atom-centered point dipoles, such as those used in a number of different polarization models. Each of these representations has been combined with one or more response models. The response model of fluctuating charge, for example, is based on the idea of electronegativity equalization in the context of changing electrostatic potentials (ESPs), whereas point-dipole representations typically use a response model based on point polarizabilities whose induced dipoles are computed based on interaction with other charges and dipoles. Here, we decouple polarization representations from their typical response models to analyze the strengths and weaknesses of various polarization approximations. First, we compare the maximal possible accuracies achievable by the charge redistribution and point-dipole model representations, by testing their ability to replicate quantum mechanical (QM) ESPs around small molecules polarized by external inducing charges. Perhaps not surprisingly, the atom-centered dipole model can yield higher accuracy. Next, we test two of the most commonly used response functions used for the point-dipole representations, self-consistent and direct (or first-order) inducible point polarizabilities, where the polarizabilities are optimized to best fit the full set of polarized QM potentials for each molecule studied. Strikingly, the induced-dipole response model markedly degrades accuracy relative to that obtainable with optimal point dipoles. In fact, the maximal accuracy achievable with this response model is even lower than that afforded by an optimal charge-redistribution representation. This means that, if coupled with a sufficiently accurate response function, the point-charge representation could outperform the standard induced-dipole model. Furthermore, although a key advantage of the point-dipole representation, relative to charge redistribution, is its ability to capture out-of-plane polarization, the inducible dipole response model causes it to be less accurate than optimal charge redistribution for out-of-plane induction of the planar nitrobenzene molecule. Thus, the widely used inducible dipole response function falls short of the full potential accuracy achievable with the point-dipole representation it employs. Additional results reported here bear on the relative accuracy of self-consistent inducible dipoles versus that of the first-order, or direct, approximation and on methods for assigning partial atomic charges for use in conjunction with inducible dipole models. In sum, these results point to the improvement of polarization response models as an important direction for future research aimed at improving the accuracy of molecular simulations.

Modelling of graphene functionalization

This perspective describes the available theoretical methods and models for simulating graphene functionalization based on quantum and classical mechanics.

Direct computation of parameters for accurate polarizable force fields

We present an improved electronic linear response model to incorporate polarization and charge-transfer effects in polarizable force fields. This model is a generalization of the Atom-Condensed Kohn-Sham Density Functional Theory (DFT), approximated to second order (ACKS2): it can now be defined with any underlying variational theory (next to KS-DFT) and it can include atomic multipoles and off-center basis functions. Parameters in this model are computed efficiently as expectation values of an electronic wavefunction, obviating the need for their calibration, regularization, and manual tuning. In the limit of a complete density and potential basis set in the ACKS2 model, the linear response properties of the underlying theory for a given molecular geometry are reproduced exactly. A numerical validation with a test set of 110 molecules shows that very accurate models can already be obtained with fluctuating charges and dipoles. These features greatly facilitate the development of polarizable force fields.

Computational chemistry for graphene-based energy applications: progress and challenges

Research in graphene-based energy materials is a rapidly growing area. Many graphene-based energy applications involve interfacial processes. To enable advances in the design of these energy materials, such that their operation, economy, efficiency and durability is at least comparable with fossil-fuel based alternatives, connections between the molecular-scale structure and function of these interfaces are needed. While it is experimentally challenging to resolve this interfacial structure, molecular simulation and computational chemistry can help bridge these gaps. In this Review, we summarise recent progress in the application of computational chemistry to graphene-based materials for fuel cells, batteries, photovoltaics and supercapacitors. We also outline both the bright prospects and emerging challenges these techniques face for application to graphene-based energy materials in future.

The Band Gap of Graphene Is Efficiently Tuned by Monovalent Ions

Small monovalent ions are able to polarize carbonaceous nanostructures significantly. We report a systematic investigation of how monovalent and divalent ions influence valence electronic structure of graphene. Pure density functional theory is employed to compute electronic energy levels. We show that the lowest unoccupied molecular orbital (LUMO) of an alkali ion (Li(+), Na(+)) fits between the highest occupied molecular orbital (HOMO) and LUMO of graphene, in such a way as to tune the bottom of the conduction band (i.e., band gap). In turn, Mg(2+) shares its orbitals with graphene. The corresponding binding energy is ca. 4 times higher than that in the case of alkali ions. The reported insights provide inspiration for engineering electrical properties of the graphene-containing systems.

Are metal-free pristine carbon nanotubes electrocatalytically active?

Metal-free carbon nanotubes (CNTs) do show electrocatalytic activity for H₂ evolution, O₂ evolution and O₂ reduction reactions in alkaline solutions, but their activities strongly depend on the number of walls or inner tubes with a maximum for CNTs with 2–3 walls.

Structure, dynamics and thermodynamics of single-file water under confinement: effects of polarizability of water molecules

Various structural, dynamic and thermodynamic properties of water molecules confined in single-wall carbon nanotubes are investigated using both polarizable and non-polarizable water models.

Efficient simulations of the aqueous bio-interface of graphitic nanostructures with a polarisable model

To fully harness the enormous potential offered by interfaces between graphitic nanostructures and biomolecules, detailed connections between adsorbed conformations and adsorption behaviour are needed. To elucidate these links, a key approach, in partnership with experimental techniques, is molecular simulation. For this, a force-field (FF) that can appropriately capture the relevant physics and chemistry of these complex bio-interfaces, while allowing extensive conformational sampling, and also supporting inter-operability with known biological FFs, is a pivotal requirement. Here, we present and apply such a force-field, GRAPPA, designed to work with the CHARMM FF. GRAPPA is an efficiently implemented polarisable force-field, informed by extensive plane-wave DFT calculations using the revPBE-vdW-DF functional. GRAPPA adequately recovers the spatial and orientational structuring of the aqueous interface of graphene and carbon nanotubes, compared with more sophisticated approaches. We apply GRAPPA to determine the free energy of adsorption for a range of amino acids, identifying Trp, Tyr and Arg to have the strongest binding affinity and Asp to be a weak binder. The GRAPPA FF can be readily incorporated into mainstream simulation packages, and will enable large-scale polarisable biointerfacial simulations at graphitic interfaces, that will aid the development of biomolecule-mediated, solution-based graphene processing and self-assembly strategies.

Cooperative effects and optimal halogen bonding motifs for self-assembling systems

Halogen bonding, due to its directionality and tunable strength, is being increasingly utilized in self-assembling materials and crystal engineering. Using density functional theory (DFT) and molecular mechanics (OPLS/CM1Ax) calculations, multiply halogen bonded complexes of brominated imidazole and pyridine are investigated along with their potential in construction of self-assembling architectures. Dimers with 1–10 halogen bonds are considered and reveal maximal binding energies of 3–36 kcal/mol. Cooperative (nonadditive) effects are found in complexes that extend both along and perpendicular to the halogen bonding axes, with interaction energies depending on polarization, secondary interactions, and ring spacers. Four structural motifs were identified to yield optimal halogen bonding. For the largest systems, the excellent agreement found between the DFT and OPLS/CM1Ax results supports the utility of the latter approach for analysis and design of self-assembling supramolecular structures.

Ordered phases of ethylene adsorbed on charged fullerenes and their aggregates

In spite of extensive investigations of ethylene adsorbed on graphite, bundles of nanotubes, and crystals of fullerenes, little is known about the existence of commensurate phases; they have escaped detection in almost all previous work. Here we present a combined experimental and theoretical study of ethylene adsorbed on free C₆₀ and its aggregates. The ion yield of [Formula: see text] measured by mass spectrometry reveals a propensity to form a structurally ordered phase on monomers, dimers and trimers of C₆₀ in which all sterically accessible hollow sites over carbon rings are occupied. Presumably the enhancement of the corrugation by the curvature of the fullerene surface favors this phase which is akin to a hypothetical 1 × 1 phase on graphite. Experimental data also reveal the number of molecules in groove sites of the C₆₀ dimer through tetramer. The identity of the sites, adsorption energies and orientations of the adsorbed molecules are determined by molecular dynamics calculations based on quantum chemical potentials, as well as density functional theory. The decrease in orientational order with increasing temperature is also explored in the simulations whereas in the experiment it is impossible to vary the temperature.

Ion enrichment on the hydrophobic carbon-based surface in aqueous salt solutions due to cation-π interactions

By incorporating cation-π interactions to classic all-atoms force fields, we show that there is a clear enrichment of Na⁺ on a carbon-based π electron-rich surface in NaCl solutions using molecular dynamics simulations. Interestingly, Cl⁻ is also enriched to some extend on the surface due to the electrostatic interaction between Na⁺ and Cl⁻, although the hydrated Cl⁻-π interaction is weak. The difference of the numbers of Na⁺ and Cl⁻ accumulated at the interface leads to a significant negatively charged behavior in the solution, especially in nanoscale systems. Moreover, we find that the accumulation of the cations at the interfaces is universal since other cations (Li⁺, K⁺, Mg²⁺, Ca²⁺, Fe²⁺, Co²⁺, Cu²⁺, Cd²⁺, Cr²⁺, and Pb²⁺) have similar adsorption behaviors. For comparison, as in usual force field without the proper consideration of cation-π interactions, the ions near the surfaces have a similar density of ions in the solution.

Graphitic carbon-water nonbonded interaction parameters

In this study, we develop graphitic carbon-water nonbonded interaction parameters entirely from ab initio calculation data of interaction energies between graphene and a single water molecule. First, we employ the Møller-Plesset perturbation theory of the second order (MP2) method to compute the polycyclic aromatic hydrocarbon (PAH)-water interaction energies, with proper size of basis sets and energy component analysis to extrapolate to infinite-sized graphene limit. Then, we develop graphitic carbon-water interaction parameters based on the MP2 data from this work and the ab initio data available in the literature from other methods such as random-phase approximation (RPA), density functional theory-symmetry-adapted perturbation theory (DFT-SAPT), and coupled cluster treatment with single and double excitations and perturbative triples (CCSD(T)). The accuracy of the interaction parameters is evaluated by predicting water contact angle on graphite and carbon nanotube (CNT) radial breathing mode (RBM) frequency shift and comparing them with experimental data. The interaction parameters obtained from MP2 data predict the CNT RBM frequency shift that is in good agreement with experiments. The interaction parameters obtained from RPA and DFT-SAPT data predict the contact angles and the CNT RBM frequency shift that agree well with experiments. The interaction parameters obtained from CCSD(T) data underestimate the contact angles and overestimate the CNT RBM frequency shift probably due to the use of small basis sets in CCSD(T) calculations.