Atomic resolution electron microscopy has been used to obtain images of moving dislocation kinks on partial dislocations at 600 ± C in silicon. Video difference images are used to obtain direct estimates of kink velocity. Observations of kink delay at obstacles, thought to be oxygen atoms at the dislocation core, yield unpinning energies and parameters of the obstacle theory of kink motion. The kink formation energy is obtained from the distribution of kink pair separations in low-dose images and is compared to the kink migration energy. Unlike metals, kink migration rather than formation controls the velocity of unobstructed dislocations in silicon under these experimental conditions. [S0031-9007(96)01391-9]

Although the sub-angstrom resolution of the modern transmission electron microscope (TEM) has made major contributions to defect structure analysis in many fields (such as oxides, interfaces, nanoparticles and superconductors) it has yielded little direct information on the core structure of dislocations. We suggest that ''forbidden reflection'' lattice images recorded in an ultra-high vacuum TEM in projections normal to the dislocation line could provide interpretable images of cores at atomic resolution. These could answer crucial questions, such as the nature of kinks, core reconstruction and periodicity, the nature of obstacles, and help distinguish obstacle theories of kink motion from the secondary Peierls-valley Hirth-Lothe theory. We give experimental forbidden reflection images and a new image obtained from silicon under UHV conditions with atomically smooth surfaces, whose preparation did not anneal out all dislocations. We also show experimental coherent nanodiffraction patterns and scanning transmission electron microscope (STEM) images recorded with the beam parallel to the core, so that core reconstruction can be expected to introduce a ''half-order'' Laue zone ring. We discuss the contribution that energy-loss spectroscopy from dislocation cores can be expected to make if a nanoprobe beam is used.

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Multiparameter and multiscale real-time environmental monitoring of a river and estuary system will be realized through the River and Estuary Observatory Network (REON) for the Hudson River in New York. In this paper, we describe a system under development that provides a holistic view of this complex and dynamic natural environment for scientific research, education, management, and environmental policy-related applications. The system incorporates a complex array of sensor technologies encompassing the physical, chemical, and biological measurement domains. REON supports Lagrangian, Eulerian, and autonomous robot sensor deployments, as well as flexible telemetry options through an open and consistent middleware architecture with advanced device management capabilities. Multimodal data streams are ingested and analyzed by an intelligent distributed streaming data analysis system known as System S. The challenges of managing high volumes of complex heterogeneous data are addressed via a distributed network of intelligent computational nodes that incorporate both autonomic algorithms and active knowledge management including a temporal component. REON provides an adaptive computing environment that provides isotropy in terms of data access and collaborative computation in contrast to traditional hierarchical control systems for sensor environments. Also presented is the underlying information infrastructure that supports a robust and integrated data modeling, simulation, and visualization manifold.

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