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Nanomaterials possess a wide range of potential applications due to their novel properties and exceptionally high activity as a result of their large surface to volume ratios compared to bulk matter. The active surface may present both advantage and risk when the nanomaterials interact with living organisms. As the overall biological impact of nanomaterials is triggered and mediated by interactions at the bio-nano interface, an ability to predict those from the atomistic descriptors, especially before the material is produced, can present enormous advantage for the development of nanotechnology. Fast screening of nanomaterials and their variations for specific biological effects can be enabled using computational materials modelling. The challenge lies in the range of scales that needs to be crossed from the material-specific atomistic representation to the relevant length scales covering typical biomolecules (proteins and lipids). In this work, we present a systematic multiscale approach that allows one to evaluate crucial interactions at the bionano interface from the first principles without any prior information about the material and thus establish links between the details of the nanomaterials structure to protein-nanoparticle interactions. As an example, an advanced computational characterization of titanium dioxide nanoparticles (6 different surfaces of rutile and anatase polymorphs) has been performed. We computed characteristics of the titanium dioxide interface with water using density functional theory for electronic density, used these parameters to derive an atomistic force field, and calculated adsorption energies for essential biomolecules on the surface of titania nanoparticles via direct atomistic simulations and coarse-grained molecular dynamics. Hydration energies, as well as adsorption energies for a set of 40 blood proteins are reported.

On a daily basis, people are exposed to a multitude of health-hazardous airborne particulate matter with notable deposition in the fragile alveolar region of the lungs. Hence, there is a great need for identification and prediction of material-associated diseases, currently hindered due to the lack of in-depth understanding of causal relationships, in particular between acute exposures and chronic symptoms. By applying advanced microscopies and omics to in vitro and in vivo systems, together with in silico molecular modeling, it is determined herein that the long-lasting response to a single exposure can originate from the interplay between the newly discovered nanomaterial quarantining and nanomaterial cycling between different lung cell types. This new insight finally allows prediction of the spectrum of lung inflammation associated with materials of interest using only in vitro measurements and in silico modeling, potentially relating outcomes to material properties for a large number of materials, and thus boosting safe-by-design-based material development. Because of its profound implications for animal-free predictive toxicology, this work paves the way to a more efficient and hazard-free introduction of numerous new advanced materials into our lives.

We report computer simulations of an excess electron in various structural motifs of polyethylene at room temperature, including lamellar and interfacial regions between amorphous and lamellae, as well as nanometre-sized voids. Electronic properties such as density of states, mobility edges, and mobilities are computed on the different phases using a block Lanczos algorithm. Our results suggest that the electronic density of states for a heterogeneous material can be approximated by summing the single phase density of states weighted by their corresponding volume fractions. Additionally, a quantitative connection between the localized states of the excess electron and the local atomic structure is presented.

Polyethylene is commonly used as an insulator for AC power cables. However it is known to undergo chemical and physical change which can lead to dielectric breakdown. Despite almost eighty years of experimental characterization of its electrical properties, very little is known about the details of the electrical behaviour of this material at the molecular level. An understanding of the mechanisms of charge trapping and transport could help in the development of materials with better insulating properties required for the next generation of high voltage AC and DC cables. Molecular simulation techniques provide a unique tool with which to study dielectric processes at the atomic and electronic level. Here we summarise simulation methodologies which have been used to study the properties of PE at the molecular level, elucidating the role of morphology in the trapping of excess electrons. We find that polyethylene has localised states due to conformational trapping extending below the mobility edge (above which the electrons are delocalised), at -0.1¿¿0.1eV with respect to the vacuum level. These trap states with localisation lengths between 0.3 and 1.2nm have energies as low as -0.4+0.1eV in the amorphous and interfacial regions of polyethylene with more positive values in lamella structures. Crystalline regions have a mobility edge at +0.46 +0.1eV, so we would expect transport by electrons excited above the mobility edge to delocalised states to be predominantly through amorphous regions if they percolate the sample.

We use a simple mean field scheme to compute the polarization energy of an excess electron in amorphous polyethylene that allows us to study dynamical properties. Nonadiabatic simulations of an excess electron in amorphous polyethylene at room temperature show the spontaneous formation of localized small polaron states in which the electron is confined in a spherically shaped region with a typical dimension of 5 Å. We compute the self-trapping energy to be −0.06±0.03 eV, with a lifetime on the time scale of a few tens of picoseconds.

We use a pseudopotential model to calculate the electronic states available to an excess electron in crystalline and amorphous regions of model polyethlyene as well as the molecular crystal of the linear alkane C27H56. It is shown that alkane crystals of whatever chain length are not representative of crystalline polyethylene (PE) although they are often considered to be so. We discuss the implications for electron transport in PE.