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An all-optical integrator, or lightwave capacitor, is a fundamental building block equivalent to those used in multi-functional electronic circuits. Associate Professor David Moss, a senior researcher within the Institute for Photonic and Optical Science (IPOS), leads an international team which has developed the optical integrator on a CMOS compatible silicon chip. The device, a photonic chip compatible with electronic technology (CMOS), will be a key enabler of next generation fully-integrated ultrafast optical data processing technologies for many applications including ultra-fast optical information-processing, optical memory, measurement, computing systems, and real-time differential equation computing units.

IBM's light-powered links overcome the greatest speed bump in supercomputing: interconnect bandwidth

The marriage of high performance optics with microfluidics could prove the perfect match for making lab-on-a-chip technologies more practical. Microfluidics, the ability to manipulate tiny volumes of liquid, is at the heart of many lab-on-a-chip devices. Such platforms can automatically mix and filter chemicals, making them ideal for disease detection and environmental sensing. The performance of these devices, however, is typically inferior to larger scale laboratory equipment. While lab-on-a-chip systems can deliver and manipulate millions of liquid drops, there is not an equally scalable and efficient way to detect the activity, such as biological reactions, within the drops.

A class of molecules whose size, structure and chemical composition have been optimized for photonic use could provide the demanding combination of properties needed to serve as the foundation for low-power, high-speed all-optical signal processing.

A new network design that avoids the need to convert optical signals into electrical ones could boost capacity while reducing power consumption.

South Korean researchers have recently made a flexible nonvolatile memory based on memristors—fundamental electronic circuit elements discovered in 2008—using thin graphene oxide films. Memristors promise a new type of dense, cheap, and low-power memory and have typically been made using metal oxide thin films. The new graphene oxide devices should be cheaper and simpler to fabricate—they could be printed on rolls of plastic sheets and used in plastic RFID tags or in the wearable electronics of the future. "We think graphene oxide can be a good candidate for next-generation memory," says Sung-Yool Choi, who leads flexible devices research at the Electronics and Telecommunications Research Institute in Daejeon, South Korea. Choi and his colleagues reported their device last week in Nano Letters.

Not so long ago, artists routinely made their own paints using all sorts of odd ingredients: clay, linseed oil, ground-up insects—whatever worked. It was a crude and rather ad hoc process, but the results were used to create some of the greatest paintings in the world. Today I and other scientists are developing our own special paints. We’re not trying to compete with Vermeer or Gauguin, though. We hope to create masterpieces of a more technical nature: optoelectronic components that will make for better photovoltaic cells, imaging sensors, and optical communications equipment. And we’re not mixing and matching ingredients quite so haphazardly. Instead, we’re using our blossoming understanding of the world of nanomaterials to design the constituents of our paints at the molecular level.

Model based Optical proximity correction is usually used to compensate for the pattern distortion during the microlithography process. Currently, almost all the lithography effects, such as the proximity effects from the limited NA, the 3D mask effects due to the shrinking critical dimension, the photo resist effects, and some other well known physical process, can all be well considered into modeling with the OPC algorithm. However, the micro-lithography is not the final step of the pattern transformation procedure from the mask to the wafer. The etch process is also a very important stage. It is well known that till now, the etch process still can't be well explained by physics theory. In this paper, we will demonstrate our study on the model based etch bias retarget for OPC.