1. Virtual Laboratory for Nanotechnology Applications 1) ENEA, Ente per le Nuove Tecnologie, l’Energia e l’Ambiente, Casaccia Research Centre, Via Anguillarese 301, 00123 S. Maria di Galeria (Roma) 2) Ylichron srl, Casaccia Research Centre, Via Anguillarese 301, 00123 S. Maria di Galeria (Roma) 1) Massimo Celino, 2) Giulio Gianese, 1) Simone Giusepponi, 1) Michele Gusso, 1,2) Vittorio Rosato Abstract The availability of high performance computing platforms has opened the way to their use in Nanotechnology applications, also of interest for many industrial sectors. A virtual laboratory is a common environment where scientists and researchers from universities and industries can work together by sharing competences, software and specialized services. An example is the ENEA-GRID environment for Materials Science applications. Examples and main results are reported. Constant temperature and constant volume ab-initio molecular dynamics simulations (using the CPMD code) are performed from room temperature to 900 K for system. Atoms on the free surfaces in the system are kept fixed to mimic bulk behavior and to minimize interactions among the interface and the free surfaces. The final configurations reveal an increased mobility of hydrogen atoms near the interface. This mobility is much higher than for bulk hydrogen atoms. This difference increases at higher temperatures. No hydrogen atoms are observed to diffuse in the Mg bulk. T = 300 K T = 500 K T = 700 K T = 900 K Only recently numerical modelling has become a critical issue for industrial R&D. Thanks to the advent of high performance computing platforms (the so- called “supercomputers”), mathematical and physical models can be deployed for the study and the design of objects which have a strong interest even for industrial applications. An example, among others, is the solution of Schröedinger equations in quantum Physics that allows the accurate description of materials at the atomic scale. For many years, this equation has been numerically intractable. This has inhibited its deployment for practical purposes. Due to significant improvements on both software and hardware, the study and the visualization of complex physical, chemical and engineering processes has become possible with significant advantages for science and technology. Several technical fields have found, in the numerical approach, an effective methodology for the improvements of knowledge and the reduction of R&D costs. Current generation of supercomputers, due to their intrinsic complexity and fast evolution, needs large investments and can be managed only by specialized professionals. In this field ENEA has a long lasting experience coming from the field of nuclear research done in the sixties. Moreover recently ENEA has received a significant financial support (CRESCO Project) for the acquisition of a last generation supercomputer, now installed at the Portici ENEA Centre, nearby Naples (Italy). The CRESCO platform is not a standalone platform, but has been inserted into the ENEA-GRID environment which is integrated and opened to the most used european GRID infrastructures. The CRESCO platform is currently the 125th most powerful computational platform in the world, with respect to both peak and sustained performances. Materials science has received significant benefits by the availability of powerful supercomputers. These infrastructures allow the simulation of nanotechnology materials at the atomic scale with sufficient accuracy to impact on real applications. The main numerical technique used in this field is Molecular Dynamics (MD hereafter). In this approach, the equations of motion of an interacting N-particles system (ions, electrons) are iteratively solved. The behaviour of these particles can be simulated in different aggregation conditions (liquid, solid, amorphous etc.), at different thermodynamic conditions and under the effect of different external conditions and constraints. The evaluation of the dynamic behaviour of each particle of the system allows to evaluate its macroscopic properties and its global response to external conditions or perturbations. This is a key point because this opens the way to the evaluation of a large set of macroscopic quantities, often of interest for the industrial applications. Simulations can be seen as “thought experiments” which can be performed on a given system, under very well controlled conditions. IntroductionNanotechnology applications The increasing request for downsizing in microelectronics, implies the development of new materials able to mimic processes which spontaneously occur in organic or biological domains. New frontiers of research Atomic level characterization of the adhesion of a polypeptide molecule on a carbon nanotube. On the left scanning electron microscope image of the hydrogen desorption from magnesium hydride (MgH 2 ), thanks to dr. A.Montone, ENEA. On the right, the numerical model for the atomic simulation of the chemical and physical processes at the interface between MgH2 and Mg during hydrogen desorption. Hydrogen storage for automotive applications Organic-inorganic materials Highly ionic conductive materials Green spheres are carbons, blue nitrogens and red oxygens. The numerical experiment is performed in water (water molecules are not displayed). Spheres represent atoms and sticks are the bonds among the atoms. Multi-scale MD simulations enable an accurate description of the adhesion of a peptide on a carbon nanotube. From an experimental point of view, there is not a clear evidence on the peptide region which mainly affects its binding property with a given substrate and which are the energies involved. Simulations, as a powerful probe, can selectively test the adhesion of each part of the peptide and compute the electronic modifications. The concept of short range order is largely developed to describe disordered systems, since it is based on the idea that structural correlations do not extend beyond the first shell of neighbours. However, a more extended level of structural order involving atomic nanostructures can be found in disordered network forming systems, as those belonging to the AX 2 family (A= Si, Ge ; X=O, Se, S). Experimentally this long range order manifests itself through the appearance of a first sharp diffraction peak in the total structure factor. Disordered network forming systems have a high technological impact, since they can play the role of host glassy matrices whose structure can be changed by addition of fast ionic species, the so-called network modifiers. MD simulations is the method of choice to link the microscopic origins of the long correlations to macroscopic properties.