Perspektiven der Chemie - Stufen zur komplexen Materie

Complex networks describe a wide range of systems in nature and society, much quoted examples including the cell, a network of chemicals linked by chemical reactions, or the Internet, a network of routers and computers connected by physical links. While traditionally these systems were modeled as random graphs, it is increasingly recognized that the topology and evolution of real networks is governed by robust organizing principles. Here we review the recent advances in the field of complex networks, focusing on the statistical mechanics of network topology and dynamics. After reviewing the empirical data that motivated the recent interest in networks, we discuss the main models and analytical tools, covering random graphs, small-world and scale-free networks, as well as the interplay between topology and the network's robustness against failures and attacks. Show more

Computational properties of use of biological organisms or to the construction of computers can emerge as collective properties of systems having a large number of simple equivalent components (or neurons). The physical meaning of content-addressable memory is described by an appropriate phase space flow of the state of a system. A model of such a system is given, based on aspects of neurobiology but readily adapted to integrated circuits. The collective properties of this model produce a content-addressable memory which correctly yields an entire memory from any subpart of sufficient size. The algorithm for the time evolution of the state of the system is based on asynchronous parallel processing. Additional emergent collective properties include some capacity for generalization, familiarity recognition, categorization, error correction, and time sequence retention. The collective properties are only weakly sensitive to details of the modeling or the failure of individual devices. Show more

The widespread use of controlled molecular-level motion in key natural processes suggests that great rewards could come from bridging the gap between the present generation of synthetic molecular systems, which by and large rely upon electronic and chemical effects to carry out their functions, and the machines of the macroscopic world, which utilize the synchronized movements of smaller parts to perform specific tasks. This is a scientific area of great contemporary interest and extraordinary recent growth, yet the notion of molecular-level machines dates back to a time when the ideas surrounding the statistical nature of matter and the laws of thermodynamics were first being formulated. Here we outline the exciting successes in taming molecular-level movement thus far, the underlying principles that all experimental designs must follow, and the early progress made towards utilizing synthetic molecular structures to perform tasks using mechanical motion. We also highlight some of the issues and challenges that still need to be overcome. Show more