A surface acoustic wave-based immunosensing device using a nanocrystalline ZnO film on Si

The novelty of this study resides in the fabrication of a bio-sensing device, based on the surface acoustic wave (SAW) on a nanocrystalline ZnO film. The ZnO film was deposited using an rf magnetron sputtering at room temperature on silicon. The deposited films showed the c-axisoriented crystallite with grain size of ∼40 nm. The immunosensing device was fabricated using photolithographic protocols on the film. As a model biomolecular recognition and immunosensing, biospecific interaction between a 6-(2,4-dinitrophenyl) aminohexanoic acid (DNP) antigen and its antibody was employed, demonstrating the shifts of resonant frequencies on SAW immunosensing device. The device exhibited a linearity as a function of the antibody concentration in the range of 20∼20,000 ng/ml. © 2009 American Scientific Publishers. All rights reserved.

Suspended multiwalled carbon nanotubes as self-aligned evaporation masks

We describe the nanofabrication study of self-aligned electrodes on suspended multiwalled carbon nanotube structures. When metal is deposited on a suspended multiwalled carbon nanotube structure, the nanotube acts as an evaporation mask, resulting in the formation of discontinuous electrodes. The metal deposits on the nanotubes are removed with lift-off. Using Al sacrificial layers, it was possible to fabricate self-aligned contact electrodes and control electrodes nanometers from the suspended carbon nanotubes with a single lithography step. It was also shown that the fabrication technique may also be used to form nano-gapped contact electrodes. The technique should prove useful for the fabrication of nano-electromechanical systems.

Gaussian processes for machine learning (GPML) toolbox

The GPML toolbox provides a wide range of functionality for Gaussian process (GP) inference and prediction. GPs are specified by mean and covariance functions; we offer a library of simple mean and covariance functions and mechanisms to compose more complex ones. Several likelihood functions are supported including Gaussian and heavy-tailed for regression as well as others suitable for classification. Finally, a range of inference methods is provided, including exact and variational inference, Expectation Propagation, and Laplace’s method dealing with non-Gaussian likelihoods and FITC for dealing with large regression tasks.