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Showing posts with label information technology. Show all posts
Showing posts with label information technology. Show all posts

Light Trapping Nano-Antennas That Could Change The Application Of Technology

Travelling at a speed of 186,000 mi/s, light can be extremely fast. Even Superman, the fastest creature on Earth, cannot travel at the speed of light. Humans have shown several times that they can control the direction of light by passing it through a refractory medium. But is it possible to trap light in a medium and change its direction just as you can trap sound in an echo device? Before now that possibility was theoretical but new research has shown that this could be practical. Since light is useful for information exchange and so many applications, the ability to control light, trap it or even change its direction could have several applications in science and technology.

outline from light trapping device
 

In a recent paper published in “Nature Nanotechnology”, some Stanford scientists who were working at the lab of Jennifer Dionne, an associate professor of materials science and engineering at Stanford University, have demonstrated an approach to manipulating light which has been successful in its ability to significantly slow the speed of light and also change its direction at will. The researchers structured silicon chips into fine nanoscale bars and these bars were used to trap lights. Later, the trapped light was released or redirected.

One challenge the researchers faced was that the silicon chips were transparent boxes. Light can be trapped in boxes but it is not so easy to do if the light is free to enter and leave at will just as you find in transparent boxes.

Another challenge that was faced by the researchers was in manufacturing the resonators. The resonators consist of a silicone layer atop a wafer of transparent sapphire. The silicon layer is extremely thin and it has the ability to trap lights very effectively and efficiently. It was preferred because it has low absorption in the near-infrared spectrum which was the light spectrum that the scientists were interested in. This region is very difficult to visualize due to inherent noise but it has useful applications in the military and technology industry. Underneath the silicone layer is a bottom layer of sapphire which is transparent and the sapphire are arranged in wafers. Then a nano-antenna was constructed through this sapphire using an electron microscopic pen. The difficulty in etching the pattern for the microscopic pen lies in the fact that if there is an imperfection then it will be difficult for it to direct light as the sapphire layer is transparent.

The experiment would be a failure if the box of silicon allowed the leakage of light. There should be no possibility of that. Designing the structure on a computer was the easy part but the researchers discovered the difficulty lay in the manufacturing of the system because it has a nano-scale structure. Eventually they had to go for a trade-off with a design that gave good light trapping performance but could be possible with existing manufacturing methods.

The usefulness of the application

The researchers have over the years tinkered with the design of the device because they were trying to achieve significant quality factors. They believed that this application could have important ramifications in the technological industry if it was made practical. Quality factors are a measure of describing the resonance behavior involved in trapping light and in this case it is proportional to the lifetime of the light.

According to the researchers, the quality factors that were demonstrated by the device was close to 2,500 and if you compare this to similar devices, one could say that the experiment was very successful because it is two times order-of-magnitude or 100 times higher than previous devices.

According to Jennifer Dionne at Stanford University, by achieving a high quality factor in the design of the device, they have been able to place it at a great opportunity of making it practical in many technology applications. Some of these applications include those in quantum computing, virtual reality and augmented reality, light-based Wi-Fi, and also in the detection of viruses like SARS-CoV-2.

An example of how this technology could be applied is in biosensing. Biosensing is an analytical device used for the detection of biomolecules that combines a biological component with a physicochemical component. A single molecule is very small that essentially it is quite invisible but if light is used as a biosensor and passed over the molecule hundreds or even thousands of times, then the chances of creating a detectable scattering effect is increased, thereby making the molecule discernible.

According to Jennifer Dionne, her lab is working on applying the light device on the detection of Covid-19 antigens and antibodies produced by the body. Antigens are molecules produced by viruses that trigger an immune response while antibodies are proteins produced by the immune systems in response to the antigens. The ability to detect a single virus or very low concentration of multitudes of antibodies comes from the light – molecule interaction created by the device. The nanoresonators are designed to work independently so that each micro-antenna can detect different types of antibodies simultaneously.

The areas of application of this technology is immense. Only the future can predict the possibilities when other scientists start experimenting with what was discovered. I think this innovation is a game changer.

Materials for this post was taken from the Stanford University website.

When computer algorithms for artworks can match art historians, accuracy will match precision


Title picture
Biker and Son, Poster art. credit: Flickr.com, Moriza
When art historians evaluate an artwork, they ask and answer questions such as the time and place where the artwork was done, what school of art the artist represents as well as his influences, and the artists his work has influenced. Asking a computer using an algorithm to do this would be very difficult. This is a field where human intelligence is very much required. Yet, computers and computer algorithms can still help us novices evaluate a work of art.

Algorithms have been developed that demonstrates computer ability to perceive and understand art the same way expert art critics would. The algorithms work on the composition of colors and easily measurable artistic qualities of an artwork.

Computers as art historians: Good job done!

In a recently published experiment in the ACM Journal of Computing and Cultural Heritage, using approximately 1,000 paintings of 34 well-known artists,
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researchers showed that a computer was clearly able to identify different art styles and even little nuances between art schools using only visual content. The results obtained were largely in agreement with the perception of art historians and dwarfed what one can obtain from untrained humans in the analysis of artworks.

A similar algorithm that was designed to place artworks in particular artistic periods using artificial vision algorithms also gave outstanding results. The computers were able to “understand” images and also differentiate between artistic styles based on low-level pictorial information.

Low-level pictorial information encompasses aspects such as brush thickness, the type of material and the composition of the palette of color. Humans on the other hand perform art analysis more abstractly. They employ medium-level information which differentiates between objects and scenes in a picture and the type of painting, and high-level information that takes the historical context and artist’s knowledge along with artistic trends into consideration.

Computer algorithms for arts not yet fully explored.

The future is stillborn as to the scope and extent visual algorithms can be used in evaluating works of art. At least, when it involves broad artistic differentiation, usually amongst art schools and periods, computer algorithms can beat an untrained human in arts analysis but fall short in precisely dating art periods or styles. According to Miquel Feixas, one of the authors of the study that was published in the ACM journal, “it will never be possible to precisely determine mathematically an artistic period or to measure the human response to a work of art, but we can look for trends.”

This is not the only technique that has been expended towards paintings. Physicists sometimes use ion beams to determine paintings and painting authenticity. This is the first time though a machine has gone one step better than humans, whether trained or untrained, in evaluating and analyzing works of art. It is hoped that this work will also open the way for further work in developing image viewing and analysis tools, classifying and searching for collections in museums, creating public information and entertainment equipment and to better understand the interaction between humans, computers and works of art. Digital technology will not replace art historians at all, just as software has not replaced human mathematicians, but with digital technology, art historians have an arsenal that makes their work stand out with more precise accuracy.

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