Technical Paper Roundup: November 21


New technical papers recently added to Semiconductor Engineering’s library: [table id=167 /] More Reading Technical Paper Library home » read more

Using Atomic Vacancies In Silicon Carbide To Measure The Stability And Quality Of Acoustic Resonators


A technical paper titled “Spin-acoustic control of silicon vacancies in 4H silicon carbide” was published by researchers at Harvard University and Purdue University. Abstract: "Bulk acoustic resonators can be fabricated on the same substrate as other components and can operate at various frequencies with high quality factors. Mechanical dynamic metrology of these devices is challenging as... » read more

Week In Review: Auto, Security, Pervasive Computing


Google was hit with a class action suit in U.S. District Court in San Francisco, alleging data scraping from millions of users without consent and violation of copyright laws to train and develop its AI products. Last month, the same law firm filed a suit against OpenAI for ChatGPT. Despite calling for a pause on development of advanced AI in March, Elon Musk launched xAI, a new company focu... » read more

Research Bits: April 18


Simplified microwave photonic filter for 6G Researchers from Peking University developed a new chip-sized microwave photonic filter to separate communication signals from noise and suppress unwanted interference across the full radio frequency spectrum. “This new microwave filter chip has the potential to improve wireless communication, such as 6G, leading to faster internet connections, ... » read more

Week In Review: Design, Low Power


Worldwide semiconductor revenue increased 1.1% in 2022 to $601.7 billion, up from $595 billion in 2021, according to preliminary results from Gartner. The combined revenue of the top 25 semiconductor vendors increased 2.8% in 2022 and accounted for 77.5% of the market. The memory segment posted a 10% revenue decrease. Analog showed the strongest growth, up 19% from 2021, followed by discretes, ... » read more

Research Bits: Jan. 17


Ionic circuit for neural nets Researchers at Harvard University and DNA Script developed an ionic circuit comprising hundreds of ionic transistors for neural net computing. While ions in water move slower than electrons in semiconductors, the team noted that the diversity of ionic species with different physical and chemical properties could be harnessed for more diverse information process... » read more

Research Bits: Jan. 3


Printing electronics on curved surfaces Researchers from North Carolina State University have demonstrated a new technique for directly printing electronic circuits onto curved and corrugated surfaces. They have used the technique to create prototype “smart” contact lenses, pressure-sensitive latex gloves, and transparent electrodes. “There are many existing techniques for creating pr... » read more

Chip Industry’s Technical Paper Roundup: Dec. 20


New technical papers added to Semiconductor Engineering’s library this week. [table id=71 /] If you have research papers you are trying to promote, we will review them to see if they are a good fit for our global audience. At a minimum, papers need to be well researched and documented, relevant to the semiconductor ecosystem, and free of marketing bias. There is no cost involved for us po... » read more

Leveraging Multi-Agent RL for Microprocessor Design Space (Harvard, Google)


A new technical paper titled "Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration" was published by researchers at Harvard University and Google research groups. Abstract "Microprocessor architects are increasingly resorting to domain-specific customization in the quest for high-performance and energy-efficiency. As the systems grow in complexity, fine-tuning arch... » read more

Research Bits: Oct. 18


Modular AI chip Engineers at the Massachusetts Institute of Technology (MIT), Harvard University, Stanford University, Lawrence Berkeley National Laboratory, Korea Institute of Science and Technology, and Tsinghua University created a modular approach to building stackable, reconfigurable AI chips. The design comprises alternating layers of sensing and processing elements, along with LEDs t... » read more

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