Hierarchically structured bioinspired nanocomposites

Next-generation structural materials are expected to be lightweight, high-strength and tough composites with embedded functionalities to sense, adapt, self-repair, morph and restore. This Review highlights recent developments and concepts in bioinspired nanocomposites, emphasizing tailoring of the architecture, interphases and confinement to achieve dynamic and synergetic responses. We highlight cornerstone examples from natural materials with unique mechanical property combinations based on relatively simple building blocks produced in aqueous environments under ambient conditions. A particular focus is on structural hierarchies across multiple length scales to achieve multifunctionality and robustness. We further discuss recent advances, trends and emerging opportunities for combining biological and synthetic components, state-of-the-art characterization and modelling approaches to assess the physical principles underlying nature-inspired design and mechanical responses at multiple length scales. These multidisciplinary approaches promote the synergetic enhancement of individual materials properties and an improved predictive and prescriptive design of the next era of structural materials at multilength scales for a wide range of applications.

Mechanically Stable Ultrathin Layered Graphene Nanocomposites Alleviate Residual Interfacial Stresses: Implications for Nanoelectromechanical Systems

Advanced nanoelectromechanical systems made from polymer dielectrics deposited onto 2D-nanomaterials such as graphene are increasingly popular as pressure and touch sensors, resonant sensors, and capacitive micromachined ultrasound transducers (CMUTs). However, durability and accuracy of layered nanocomposites depend on the mechanical stability of the interface between polymer and graphene layers. Here we used molecular dynamics computer simulations to investigate the interface between a sheet of graphene and a layer of parylene-C thermoplastic polymer during large numbers of high-frequency (MHz) cycles of bending relevant to the operating regime. We find that important interfacial sliding occurs almost immediately in usage conditions, resulting in more than 2% expansion of the membrane, a detrimental mechanism which requires repeated calibration to maintain CMUTs accuracy. This irreversible mechanism is caused by relaxation of residual internal stresses in the nanocomposite bilayer, leading to the emergence of self-equilibrated tension in the polymer and compression in the graphene. It arises as a result of deposition-polymerization processing conditions. Our findings demonstrate the need for particular care to be exercised in overcoming initial expansion. The selection of appropriate materials chemistry including low electrostatic interactions will also be key to their successful application as durable and reliable devices.

Effects of Moisture and Synthesis-Derived Contaminants on the Mechanical Properties of Graphene Oxide: A Molecular Dynamics Investigation

This paper reports on the effects of the chemical composition of graphene oxide (GO) sheets on the mechanical properties of bulk GO. Three key factors were analyzed: (i) the oxygenated functional groups' concentration, (ii) the content of intersheet water (moisture), and (iii) the presence of residual contaminants observed from the synthesis of GO. Molecular dynamics simulations using the reactive force field ReaxFF were conducted to model tensile strength, indentation, and shear stress tests. The structural integrity of the carbon basal plane was the primary variable that determined mechanical behavior of GO slabs. Hydrogen-bond networks played an essential role in the tensile fracture mechanism, delaying the onset of fracture whenever strong hydrogen bonds existed in the intersheet space. The presence of interlayer sulfate ion contaminants negatively impacted the tensile strength, stiffness, and toughness of GO. Moreover, it was observed that intersheet sulfate ions improved the resistance to fracture of GO at low sulfur concentrations, while lower fracture strains were observed beyond a critical concentration. Alike the tensile stress findings, the indentation properties were determined by the integrity of the carbon basal plane. Our findings agree with experimental mechanical property measurements and reveal the importance of considering synthesis-derived contaminants in molecular models of GO.

Wettability of graphene oxide functionalized with N-alkylamines: a molecular dynamics study

The wettability of graphene oxide functionalized with N-alkylamines was studied by molecular dynamics simulations. Six different N-alkylamines and two functionalization degrees were reviewed. The nucleophilic ring-opening reaction mechanism between the N-alkylamines and epoxy functional groups of graphene oxide was considered to generate the atomistic models. Water contact angles increased with both the alkyl chain length and substitution degree. The Wenzel model was used to access the effect of both the surface roughness and alkyl chain length on wettability. The results indicated that functionalization introduces an important increase of surface roughness but its effect on wettability is countered by the alkyl chain length.

Uncertainty quantification in classical molecular dynamics

Molecular dynamics simulation is now a widespread approach for understanding complex systems on the atomistic scale. It finds applications from physics and chemistry to engineering, life and medical science. In the last decade, the approach has begun to advance from being a computer-based means of rationalizing experimental observations to producing apparently credible predictions for a number of real-world applications within industrial sectors such as advanced materials and drug discovery. However, key aspects concerning the reproducibility of the method have not kept pace with the speed of its uptake in the scientific community. Here, we present a discussion of uncertainty quantification for molecular dynamics simulation designed to endow the method with better error estimates that will enable it to be used to report actionable results. The approach adopted is a standard one in the field of uncertainty quantification, namely using ensemble methods, in which a sufficiently large number of replicas are run concurrently, from which reliable statistics can be extracted. Indeed, because molecular dynamics is intrinsically chaotic, the need to use ensemble methods is fundamental and holds regardless of the duration of the simulations performed. We discuss the approach and illustrate it in a range of applications from materials science to ligand-protein binding free energy estimation. This article is part of the theme issue 'Reliability and reproducibility in computational science: implementing verification, validation and uncertainty quantification in silico'.

From digital hype to analogue reality: Universal simulation beyond the quantum and exascale eras

Many believe that the future of innovation lies in simulation. However, as computers are becoming ever more powerful, so does the hyperbole used to discuss their potential in modelling across a vast range of domains, from subatomic physics to chemistry, climate science, epidemiology, economics and cosmology. As we are about to enter the era of quantum and exascale computing, machine learning and artificial intelligence have entered the field in a significant way. In this article we give a brief history of simulation, discuss how machine learning can be more powerful if underpinned by deeper mechanistic understanding, outline the potential of exascale and quantum computing, highlight the limits of digital computing - classical and quantum - and distinguish rhetoric from reality in assessing the future of modelling and simulation, when we believe analogue computing will play an increasingly important role.