Hydrogen bonding and collective proton modes in clusters and periodic layers of squaric acid: A density functional study

Hydrogen bonding in clusters and extended layers of squaric acid molecules has been investigated by density functional computations. Equilibrium geometries, harmonic vibrational frequencies, and energy barriers for proton transfer along hydrogen bonds have been determined using the Car-Parrinello method. The results provide crucial parameters for a first principles modeling of the potential energy surface, and highlight the role of collective modes in the low-energy proton dynamics. The importance of quantum effects in condensed squaric acid systems has been investigated, and shown to be negligible for the lowest-energy collective proton modes. This information provides a quantitative basis for improved atomistic models of the order-disorder and displacive transitions undergone by squaric acid crystals as a function of temperature and pressure. (C) 2001 American Institute of Physics.

Epipolar geometry estimation based on evolutionary agents

This paper presents a novel approach based on the use of evolutionary agents for epipolar geometry estimation. In contrast to conventional nonlinear optimization methods, the proposed technique employs each agent to denote a minimal subset to compute the fundamental matrix, and considers the data set of correspondences as a 1D cellular environment, in which the agents inhabit and evolve. The agents execute some evolutionary behavior, and evolve autonomously in a vast solution space to reach the optimal (or near optima) result. Then three different techniques are proposed in order to improve the searching ability and computational efficiency of the original agents. Subset template enables agents to collaborate more efficiently with each other, and inherit accurate information from the whole agent set. Competitive evolutionary agent (CEA) and finite multiple evolutionary agent (FMEA) apply a better evolutionary strategy or decision rule, and focus on different aspects of the evolutionary process. Experimental results with both synthetic data and real images show that the proposed agent-based approaches perform better than other typical methods in terms of accuracy and speed, and are more robust to noise and outliers.

Laser annealing of sputtered silicon for wafer-bonding applications

Sputtered silicon is investigated as a bonding layer for transfer of pre-processed silicon layers to various insulating substrates. Although the material appears suitable for low temperature processing, previous work has shown that gas trapped in the pores of the sputtered material is released at temperatures above 350 degrees C and further increases of temperature lead to destruction of any bonded interface. Pre-annealing at 1000 degrees C before bonding drives out gas and/or seals the surface, but for device applications where processing temperatures must be kept below about 300 degrees C, this technique cannot be used. In the current work, we have investigated the effect of excimer laser-annealing to heat the sputtered silicon surface to high temperature whilst minimising heating of the underlying substrate. Temperature profile simulations are presented and the results of RBS, TEM and AFM used to characterise the annealed layers. The results verify that gases are present in the sub-surface layers and suggest that while sealing of the surface is important for suppression of the out-diffusion of gases, immediate surface gas removal may also play a role. The laser-annealing technique appears to be an effective method of treating sputtered silicon, yielding a low roughness surface suitable for wafer bonding, thermal splitting and layer transfer.