tag: Arizona State University

What’s the Right Path For Scaling?
By Mark LaPedus - 02 Jan, 2019 - Comments: 1

The growing challenges of traditional chip scaling at advanced nodes are prompting the industry to take a harder look at different options for future devices. Scaling is still on the list, with the industry laying plans for 5nm and beyond. But less conventional approaches are becoming more viable and gaining traction, as well, including advanced packaging and in-memory computing. Some option... » read more

Manufacturing Bits: Oct. 23
By Mark LaPedus - 23 Oct, 2018 - Comments: 0

3D stacked finFETs At the upcoming 2018 IEEE International Electron Devices Meeting (IEDM), Imec is expected to present a paper on a 3D stacked finFET architecture. IEDM is slated from Dec. 1-5 in San Francisco. Imec’s technology is based what on the R&D organization calls sequential integration. Another R&D organization, Leti, calls it 3D monolithic integration. Regardless, the idea... » read more

Week in Review: IoT, Security, Auto
By Jeff Dorsch - 19 Oct, 2018 - Comments: 0

Internet of Things At Arm TechCon, Arm unveiled its Neoverse brand identity, providing an infrastructure foundation for 5G, the Internet of Things, edge computing, and other applications. The Arm Neoverse IP will proliferate next year from Arm and its technology partners. With Arm’s “Ares” platform, to be introduced in 2019, the company promises to deliver 30% per-generation performance ... » read more

AI Accelerating Discovery
By Joanne Itow - 25 Apr, 2018 - Comments: 0

In early April 2018, the Materials Research Society held their spring meeting and exhibit at the Phoenix, Arizona convention center. With more than 110 symposium presentations, it was difficult to select which sessions to attend. But one forum caught my eye, “AI for Materials Development”. These days AI seems to be everywhere. As we all speculate about the impact of AI on autonomous driv... » read more

Manufacturing Bits: April 10
By Mark LaPedus - 10 Apr, 2018 - Comments: 1

Higher power GaN Imec and Qromis have announced the development of a new gallium nitride (GaN) substrate technology that enables power devices at 650 volts and above. GaN is an emerging technology for power semiconductor applications. Based on a GaN-on-silicon technology, GaN-based power semis operate at 650 volts and above. In simple terms, the buffer layers between the GaN device and the ... » read more

Power/Performance Bits: Mar. 20
By Jesse Allen - 20 Mar, 2018 - Comments: 0

Proton battery prototype A team at RMIT University built a prototype rechargeable proton battery combining hydrogen fuel cells and battery-based electrical power that has the potential, with further development, to store more energy than currently-available lithium ion batteries. The working prototype proton battery uses an activated carbon electrode for solid-state storage of hydrogen with... » read more

Non-Traditional Chips Gaining Steam
By Jeff Dorsch - 15 Mar, 2018 - Comments: 0

Flexible hybrid electronics are beginning to roll out in the form of medical devices, wearable electronics and even near-field communications tags in retail, setting the stage for a whole new wave of circuit design, manufacturing and packaging that reaches well beyond traditional chips. FHE devices begin with substrates made of ceramics, glass, plastic, polyimide, polymers, polysilicon, stai... » read more

What If We Had Bi-Directional RRAM?
By Katherine Derbyshire - 15 Feb, 2018 - Comments: 0

The ideal memristor device for neuromorphic computing would have linear and symmetric resistance behavior. Resistance would both increase and decrease gradually, allowing a direct correlation between the number of programming pulses and the resistance value. Real world RRAM devices, however, generally do not have these characteristics. In filamentary RRAM devices, the RESET operation can raise ... » read more

What’s Next In Neuromorphic Computing
By Katherine Derbyshire - 15 Feb, 2018 - Comments: 2

To integrate devices into functioning systems, it's necessary to consider what those systems are actually supposed to do. Regardless of the application, [getkc id="305" kc_name="machine learning"] tasks involve a training phase and an inference phase. In the training phase, the system is presented with a large dataset and learns how to "correctly" analyze it. In supervised learning, the data... » read more

System Bits: Jan. 23
By Ann Mutschler - 23 Jan, 2018 - Comments: 0

Artificial synapse for “brain-on-a-chip” portable AI devices In the emerging field of neuromorphic computing, researchers are attempting to design computer chips that work like the human brain, which, instead of carrying out computations based on binary, on/off signaling like digital chips do today, the elements of a brain-on-a-chip would work in an analog fashion, exchanging a gradient of... » read more

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