Research Bits: Aug. 23


Algae-powered microprocessor Engineers from the University of Cambridge, Arm Research, Scottish Association for Marine Science, and Norwegian University of Science and Technology used a widespread species of blue-green algae to power an Arm Cortex M0+ microprocessor continuously for over a year. The algae, Synechocystis, is non-toxic and harvests energy from photosynthesis. The tiny electri... » read more

Technical Paper Round-Up: June 8


  New technical papers added to Semiconductor Engineering’s library this week. [table id=32 /] Semiconductor Engineering is in the process of building this library of research papers. Please send suggestions (via comments section below) for what else you’d like us to incorporate. If you have research papers you are trying to promote, we will review them to see if they are a ... » read more

Hybrid Sensing Platform w/Silicon Nanowires on a Fully Functional CMOS Chip Containing the Readout Electronics & Signal amplification


New technical paper titled "Multisite Dopamine Sensing With Femtomolar Resolution Using a CMOS Enabled Aptasensor Chip" from TU Dresden, Riken Quantitative Biological Center, Imperial College London, NaMLab gGmbH, ETH Zürich, MaxWell Biosystems AG, TU Wien, and Institute of Radiopharmaceutical Cancer Research. Abstract "Many biomarkers including neurotransmitters are found in external bo... » read more

Research Bits: May 24


Printed flexible OLED display Researchers from the University of Minnesota Twin Cities and Korea Institute of Industrial Technology used a customized 3D printer to print a flexible OLED display. “OLED displays are usually produced in big, expensive, ultra-clean fabrication facilities,” said Michael McAlpine, a professor in the Department of Mechanical Engineering at University of Minnes... » read more

Power/Performance Bits: Dec. 14


Improved digital sensing Researchers from Imperial College London and Technical University of Munich propose a technique to improve the capability of many different types of sensors. The method addresses voltage limits in analog-to-digital converters and the saturation that results in poor quality when an incoming signal exceeds those limits. “Our new technique lets us capture a fuller ra... » read more

Absence of Barren Plateaus in Quantum Convolutional Neural Networks


Abstract:  Quantum neural networks (QNNs) have generated excitement around the possibility of efficiently analyzing quantum data. But this excitement has been tempered by the existence of exponentially vanishing gradients, known as barren plateau landscapes, for many QNN architectures. Recently, quantum convolutional neural networks (QCNNs) have been proposed, involving a sequence of convol... » read more

Power/Performance Bits: Oct. 12


More stable quantum states Researchers at the University of Chicago found a way to make quantum systems retain coherency 10,000 times longer. The fragile nature of quantum states remains a challenge for developing practical applications of quantum computing, as they can be easily disrupted by background noise coming from vibrations, temperature changes or stray electromagnetic fields. Ap... » read more

Power/Performance Bits: Oct. 6


Waste plastic supercapacitor Researchers from the University of California Riverside found a way to recycle waste plastic into energy storage devices. The work focused on polyethylene terephthalate plastic waste, or PET, which is found in soda bottles and many other consumer products. The researchers first dissolved pieces of PET plastic bottles in a solvent. Using electrospinning, they fab... » read more

Power/Performance Bits: Aug. 13


Smartphone virus scanner Scientists at the University of Tokyo built a new type of virus scanner for smartphones: to detect diseases, not malware. The handheld, portable device uses a smartphone to help scan biological samples for influenza virus. The virus scanner is about the size of a brick, with a slot to position a smartphone such that its camera looks through a lens. Inside the device... » read more

System Bits: April 8


Computers trained to design materials Researchers in the University of Missouri’s College of Engineering are applying deep learning technology to educate high-performance computers in the field of materials science, with the goal of having those computers design billions of potential materials. “You can train a computer to do what it would take many years for people to otherwise do,” ... » read more

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