January 30, 2006

DNA-nanotube combo spots toxins

Medical diagnostics and biomedical research are poised to benefit from nanosensors that combine DNA's sensitivity to specific substances and nanotubes' electrical and optical sensitivity to the environment.

Researchers from the University of Illinois at Urbana-Champaign have developed a DNA-nanotube sensor that detects metal ions in blood, tissue and even within cells. The presence of ions alters the DNA, which in turn alters the infrared emission of the nanotube.

The sensors consist of double-stranded DNA helixes wrapped around semiconducting, single-walled carbon nanotubes. When ions, or atoms with one or more extra or missing electrons, are present the DNA helixes separate, then reform with the spiral in the opposite direction. This change alters the electronic structure of the nanotubes, which can be detected as a dimming of their infrared fluorescence.

The researchers tested the sensor by causing living cells to absorb DNA-wrapped nanotubes, then mercury ions. The nanotubes' infrared emission dimmed in proportion to the amount of mercury ions the cells had absorbed, and returned to its normal level when the ions were removed.

The sensor could be used to detect contaminants and for research into why DNA helixes sometimes reverse.

(Optical Detection of DNA Confirmational Polymorphism on Single-Walled Carbon Nanotubes, Science, January 27, 2006)

Self-improving software

If people are expected to learn on the job, why isn't software? Although some kinds of software are capable of learning, it's more difficult to design software that learns as it works without requiring a separate training process.

Princeton University researchers have designed algorithms -- the logic underlying software -- that learn from data that they don't know anything about ahead of time and then tune themselves to better handle those types of data. The key is that the algorithms learn from how the pieces of data fit within the range of possibilities, rather than having to learn the data's details.

It turns out that even though any given piece of data is random, individual pieces fall into relatively narrow ranges that an algorithm can learn from. An algorithm can also improve after learning from a relatively small number of samples.

The researchers built two self-improving algorithms, a sorting algorithm and a clustering algorithm. Sorting algorithms put pieces of data into some type of order and clustering algorithms group like pieces of data.

The algorithms promise to be forerunners of software that alters its default configuration on its own as it learns how it is used.

(Self-Improving Algorithms, ACM-SIAM Symposium on Discrete Algorithms, January 22-24, 2006, Miami, Florida)

Bits and pieces

Detector boosts quantum crypto

A quantum cryptography system that includes high-efficiency superconducting photon detectors transmits secure messages over 50 kilometers of optical fiber at standard telecommunications wavelengths.

(Quantum Key Distribute Telecom Wavelengths with Noise-Free Detectors, Applied Physics Letters, January 9, 2006)

Self-assembly makes flexible LCD

A fabrication process causes liquid crystal to embed itself in a polymer to make flexible liquid crystal displays. The screens are potentially inexpensive because they use one surface instead of the usual sandwich of components.

(Single-Substrate Cholesteric Liquid Crystal Displays by Colloidal Self-Assembly, Applied Physics Letters, January 23, 2006)

Graphics chips speed holograms

A study shows that processing computer-generated holograms on a graphics processing unit (GPU) is much faster than using a central processing unit (CPU). Computer-generated holograms are require a lot of computer power; making them faster is a key step toward three-dimensional television.

(Computer-Generated Holography Using Any Graphics Processing Unit, Optics Express, January 23, 2006)

Nanorods focus microscope

A proposed imaging system uses hexagons made from 50- by 20-nanometer silver nanorods instead of lenses to make optical microscopic images that focus on objects as small as 40 nanometers. A nanometer is one millionth of a millimeter. This is far smaller than ordinary optical microscopes and comparable to near-field imaging systems, which use probes in extremely close proximity to a sample.

(Subwavelength Optical Imaging through a Metallic Nanorod Array, Physical Review Letters, December 31, 2005)