Controlled self‐assembly of biomolecules on graphene offers a pathway for realizing its full potential in biological applications. Microscopy has revealed the self‐assembly of amino acid adlayers into dimer rows on nonreactive substrates. However, neither the spontaneous formation of these patterns, nor the influence of amino acid termination state on the formation of patterns has been directly resolved to date. Molecular dynamics simulations, with the ability to reveal atomic level details and exert full control over the termination state, are used here to model initially disordered adlayers of neutral, zwitterionic, and neutral–zwitterionic mixtures for two types of amino acids, tryptophan and methionine, adsorbed on graphene in vacuo. The simulations of the zwitterion‐containing adlayers exhibit the spontaneous emergence of dimer row ordering, mediated by charge‐driven intermolecular interactions. In contrast, adlayers containing only neutral species do not assemble into ordered patterns. It is also found that the presence of trace amounts of water reduces the interamino acid interactions in the adlayers, but does not induce or disrupt pattern formation. Overall, the findings reveal the balance between the lateral interamino acid interactions and amino acid–graphene interactions, providing foundational insights for ultimately realizing the predictable pattern formation of biomolecules adsorbed on unreactive surfaces.

Graphene oxide (GO) sheet structures are highly variable and depend on preparation conditions. The use of molecular simulation is a complementary strategy to explore how this complexity influences the ion transport properties of GO membranes. However, despite recent advances, computational models of GO typically lack the required complexity as suggested by experiment. The labor required to create such an ensemble of such structural models with the required complexity is impractical without recourse to automated approaches, but no such code currently can meet this challenge. Here, a modular tiling concept is introduced, along with the HierGO suite of code; an automated approach to producing highly complex hierarchically-structured models of GO with a high degree of control in terms of holes and topological defects, and oxygen-group placement, that can produce simulation-ready input files. The benefits of the code are exemplified by modeling and contrasting the properties of three types of GO membrane stack; the widely-modeled Lerf-Klinowski structure, and two types of highly heterogeneous GO sheet reflecting differing processing conditions. The outcomes of this work clearly demonstrate how the introduction of the complexity modeled here leads to new insights into the structure/property relationships of GO with respect to permeation pathways of water, ions and molecular agents that are inaccessible using previously-considered models.

We present density functional theory calculations of the adsorption of arsenic acid (AsO(OH)3) and arsenous acid (As(OH)3) on the Al(III)-modified natural zeolite clinoptilolite under anhydrous and hydrated conditions. From our calculated adsorption energies, we show that adsorption of both arsenic species is favorable (associative and exothermic) under anhydrous conditions. When the zeolite is hydrated, adsorption is less favourable, with the water molecules causing dissociation of the arsenic complexes, although exothermic adsorption is still observed for some sites. The strength of interaction of the arsenic complexes is shown to depend sensitively on the Si/Al ratio in the Al(III)-modified clinoptilolite, which decreases as the Si/Al ratio increases. The calculated large adsorption energies indicate the potential of Al(iii)-modified clinoptilolite for arsenic immobilization.

The spontaneous emergence of several co-existing ordered nano-motifs in initially spatially randomised amino acid adlayers adsorbed on graphene in vacuo is influenced by side-chain characteristics.

No abstract