Investigation of the non-covalent interaction of biomolecules with aqueous graphene interfaces is a rapidly expanding area. However, reliable exploitation of these interfaces in many applications requires that the links between the sequence and binding of the adsorbed peptide structures be clearly established. Molecular dynamics (MD) simulations can play a key role in elucidating the conformational ensemble of peptides adsorbed at graphene interfaces, helping to elucidate these rules in partnership with experimental characterisation. We apply our recently-developed polarisable force-field for biomolecule–graphene interfaces, GRAPPA, in partnership with advanced simulation approaches, to probe the adsorption behaviour of peptides at aqueous graphene. First we determine the free energy of adsorption of all twenty naturally occurring amino acids (AAs) via metadynamics simulations, providing a benchmark for interpreting peptide–graphene adsorption studies. From these free energies, we find that strong-binding amino acids have flat and/or compact side chain groups, and we relate this behaviour to the interfacial solvent structuring. Second, we apply replica exchange with solute tempering simulations to efficiently and widely sample the conformational ensemble of two experimentally-characterised peptide sequences, P1 and its alanine mutant P1A3, in solution and adsorbed on graphene. For P1 we find a significant minority of the conformational ensemble possesses a helical structure, both in solution and when adsorbed, while P1A3 features mostly extended, random-coil conformations. In solution this helical P1 configuration is stabilised through favourable intra-peptide interactions, while the adsorbed structure is stabilised via interaction of four strongly-binding residues, identified from our metadynamics simulations, with the aqueous graphene interface. Our findings rationalise the performance of the P1 sequence as a known graphene binder.

Reverse osmosis (RO) is currently one of the most widely used methods of desalination in the world and rapidly increasing in usage. The membranes used in the RO process play a vital role in determining the effectiveness of the desalination process. In this work, fully atomistic molecular dynamics simulations of one of the most widely employed membranes, namely the FT30 polyamide material, have been carried out in order gain greater understanding of the structure of the system and its interaction with saline solution. The system studied consisted of a solvated membrane layer and a layer of bulk solution, thus allowing the membrane interface to be simulated. The behaviour of water and salt ions in both the bulk solution and membrane has been investigated. It was found that the diffusivities of water and the salt ions were reduced by an order of magnitude within the membrane. Furthermore, umbrella sampling methods have been used in order to determine the free energy surface associated with the salt ions passing through the membrane-solution interface. The present work demonstrates that there is a high degree of variability in the resistance to salt diffusion into the membrane associated with the structure of the water encountered as the ion permeates the membrane. Despite this variability in the free energy gradient, all cases ultimately exhibit a high resistance to ionic diffusion due to charge separation. However, migration of a sodium cation/chloride anion pair fails to substantially lower the barrier to salt diffusion, thus confirming the robust nature of the membrane selectivity for water.

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.