Interface design and processes of self-organization in nanosystems

摘要

The role of structural design of nanosystems, i.e. systems with high density of surfaces, boundaries and interfaces greatly increases as material science rapidly develops in the direction of molecular and atomic assembly technology of materials and constructions. The processes occurring in interface layers determine the unique properties of nanosystems. The evolution of a substance in a boundary layer tends to a stationary state corresponding to external conditions. For micro(nano)-systems interfaces corresponding to a symmetry dictated energy extremum can be selected as states -attractors. To optimize structural design, forecasting and achievement of desirable characteristics, the processes of internal structural self-organization of a system should be in resonance with processes of controlling external influences (synergy resonance principle). This approach, together with earlier developed crystallochemical methods of searching for symmetry preferred interfaces of heteroepitaxy, allows one to carry out modeling generation and experimental selection of nanosystems with desirable properties and purposeful nanodesigning to create new materials, structures and devices. In view these tasks the discussion concentrates on: (1) Processes of special boundary texture formation in order to obtain high stable magnetic properties of permanent magnets on the basis of Sm-Co powders; (2) Processes of structural self-organization and boundary design upon Bi, Bi-Sb nanofilm formation with a big length of electron mean free path; (3) Creation of coherent solid-state heterojunctions of superionic conductor- an electronic conductor in order to conserve fast ionic transport and low activation energy of ion-movement in the crystal layer interface. Formation of such hererojunctions is of the key role in the creation of new types of devices with high frequency capacitance characteristics and a necessary element for the future information technologies, namely, wireless networks of autonomous microsensors and microrobots.