Power/Performance Bits: June 16


One-directional optical Researchers from University of Pennsylvania, Peking University and Massachusetts Institute of Technology developed a design for optical devices that radiate light in only one direction, which could reduce energy consumption in optical fiber networks and data centers. Light tends to flow in a single direction optical fibers, but while most of the light passing through... » read more

Power/Performance Bits: May 5


CMOS-compatible laser Researchers at Forschungszentrum Jülich, Center for Nanoscience and Nanotechnology (C2N), STMicroelectronics, and CEA-Leti Grenoble developed a CMOS-compatible laser for optical data transfer. Comprised of germanium and tin, the efficiency is comparable with conventional GaAs semiconductor lasers on Si. Optical communications provide much higher data rates, and are be... » read more

Power/Performance Bits: April 21


Focus-free lens Researchers from the University of Utah developed a new lens that doesn't require focusing. They present it as an alternative to the multiple lenses common in smartphone cameras. "Our flat lenses can drastically reduce the weight, complexity and cost of cameras and other imaging systems, while increasing their functionality," said research team leader Rajesh Menon from the U... » read more

Ansys SPEOS: Illuminating The Possibilities


Ansys SPEOS enables optical engineers to fine-tune critical factors such as propagation, reflection, visibility and legibility, while also identifying problems such as glare and hot spots. In a broad range of applications in the automotive, aerospace and general lighting segments, SPEOS cuts significant time and expense from the design cycle, while supporting the high degree of innovation neede... » read more

Making Light More Reliable


The buzz around photonics in packages and between packages is growing. Now the question is whether it will work as expected, and where it will be useful. Replacing electrical with optical signals has been on the technology horizon for some time. Light moves faster through fiber than electrons through copper. How much faster depends upon the diameter of the wires, the substrate and interconne... » read more

Die-To-Die Connectivity


Manmeet Walia, senior product marketing manager at Synopsys, talks with Semiconductor Engineering about how die-to-die communication is changing as Moore’s Law slows down, new use cases such as high-performance computing, AI SoCs, optical modules, and where the tradeoffs are for different applications.   Interested in more Semiconductor Engineering videos? Sign-up for our YouTu... » read more

Power/Performance Bits: Aug. 21


Physical neural network Engineers at UCLA built a physical artificial neural network capable of identifying objects as light passes through a series of 3D printed polymer layers. Called a "diffractive deep neural network," it uses the light bouncing from the object itself to identify that object, a process that consumes no energy and is faster than traditional computer-based methods of imag... » read more

Power/Performance Bits: Aug. 14


All-optical logic Researchers from Aalto University developed multifunction all-optical logic gates using a network of nanowires. To build the nanostructure, the team assembled two different semiconductor nanowires, indium phosphide and aluminum gallium arsenide. The nanowires have a unique one-dimensional structure, which allows them to function like nanosized antennas for light. Using ... » read more

Power/Performance Bits: Aug. 7


Optical neural network Researchers at the National Institute of Standards and Technology (NIST) have made a silicon chip that distributes optical signals precisely across a miniature brain-like grid, showcasing a potential new design for neural networks. Using light would eliminate interference due to electrical charge and the signals would travel faster and farther, said the researchers. "... » read more

Power/Performance Bits: July 31


Training optical neural networks Researchers from Stanford University used an optical chip to train an artificial neural network, a step that could lead to faster, more efficient AI tasks. Although optical neural networks have been recently demonstrated, the training step was performed using a model on a traditional digital computer and the final settings were then imported into the optical... » read more

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