An Integrated Data-Driven Strategy for Safe-by-Design Nanoparticles: The FP7 MODERN Project.

The development and implementation of safe-by-design strategies is key for the safe development of future generations of nanotechnology enabled products. The safety testing of the huge variety of nanomaterials that can be synthetized is unfeasible due to time and cost constraints. Computational modeling facilitates the implementation of alternative testing strategies in a time and cost effective way. The development of predictive nanotoxicology models requires the use of high quality experimental data on the structure, physicochemical properties and bioactivity of nanomaterials. The FP7 Project MODERN has developed and evaluated the main components of a computational framework for the evaluation of the environmental and health impacts of nanoparticles. This chapter describes each of the elements of the framework including aspects related to data generation, management and integration; development of nanodescriptors; establishment of nanostructure-activity relationships; identification of nanoparticle categories; hazard ranking and risk assessment.

Temperature-dependent self-assembly of adenine derivative on HOPG.

Temperature-dependent self-assembly formed by the adsorption of the nucleobase adenine derivative on a graphite surface were investigated by in situ scanning tunneling microscopy (STM). The high-resolution STM images reveal two types of structures, α phase and ß phase, which are mainly driven by either hydrogen bonding or aromatic π-π interactions between adenine bases, respectively, as well as the interactions of alkyl chains. α-Phase structures can be transformed into ß-phase structures by increasing temperature. The reverse is true for decreasing temperature. This reflects structural stabilities resulting from the different interactions. Density functional theory (DFT) calculations were performed to characterize possible arrangements of adjacent adenine moieties systematically in terms of binding energies and structural properties. Via a systematic search algorithm, all possible network structures were determined on a microscopic level. In this way, it is possible to rationalize the structural parameters as found in the STM images.