tag: Argonne National Laboratory

Power/Performance Bits: Aug. 24
By Jesse Allen - 24 Aug, 2021 - Comments: 0

Low power AI Engineers at the Swiss Center for Electronics and Microtechnology (CSEM) designed an SoC for edge AI applications that can run on solar power or a small battery. The SoC consists of an ASIC chip with RISC-V processor developed at CSEM along with two tightly coupled machine-learning accelerators: one for face detection, for example, and one for classification. The first is a bin... » read more

Intelligent Agents for the Optimization of Atomic Layer Deposition
By Technical Paper Link - 05 Aug, 2021 - Comments: 0

"Atomic layer deposition (ALD) is a highly controllable thin film synthesis approach with applications in computing, energy, and separations. The flexibility of ALD means that it can access a massive chemical catalogue; however, this chemical and process diversity results in significant challenges in determining processing parameters that result in stable and uniform film growth with minimal pr... » read more

Manufacturing Bits: June 29
By Mark LaPedus - 29 Jun, 2021 - Comments: 0

Speeding up ALD with AI The U.S. Department of Energy’s (DOE) Argonne National Laboratory has developed various ways to make atomic layer deposition (ALD) more efficient by using artificial intelligence (AI). ALD is a deposition technique that deposits materials one layer at a time on chips. For years, ALD has been used for the production of DRAMs, logic devices and other products. In ... » read more

Power/Performance Bits: June 15
By Jesse Allen - 15 Jun, 2021 - Comments: 0

Low-loss photonic IC Researchers at EPFL built a photonic integrated circuit with ultra-low loss. The team focused on silicon nitride (Si3N4), which has orders of magnitude lower optical loss compared to silicon. It is used in low-loss applications such as narrow-linewidth lasers, photonic delay lines, and nonlinear photonics. In applying the material to photonic ICs, they took advantage... » read more

Power/Performance Bits: Feb. 2
By Jesse Allen - 02 Feb, 2021 - Comments: 0

MXene antennas Researchers at Drexel University and Villanova University developed spray-on antennas made of the 2D materials MXene that is flexible and light while maintaining good signal. "This combination of communications performance with extreme thinness, flexibility and durability sets a new standard for antenna technology," said Yury Gogotsi, professor of Materials Science and Engine... » read more

Manufacturing Bits: Jan. 19
By Mark LaPedus - 19 Jan, 2021 - Comments: 0

X-ray imaging with AI The U.S. Department of Energy’s Argonne National Laboratory has demonstrated the use of artificial intelligence (AI) to accelerate the process of reconstructing images from coherent X-ray scattering data. Argonne’s technology, called PtychoNN, combines an X-ray imaging technique called ptychography with a neural network. This in turn enables researchers to decode X... » read more

The Battery Problem
By Ed Sperling - 14 Sep, 2020 - Comments: 2

The fires sweeping the West Coast of the United States point to the need for a whole different way of managing power on both a macro and a micro level. Since the millennium, the power demand from data centers and from mobile devices has been climbing steadily. There are roughly 7.8 billion people on the planet, up from 6.115 billion people in 2000, according to the World Bank. Many of them o... » read more

Manufacturing Bits: Aug. 18
By Mark LaPedus - 18 Aug, 2020 - Comments: 0

Quantum Internet The U.S. Department of Energy (DOE) recently unveiled a strategy to develop a quantum Internet in the United States. DOE’s 17 National Laboratories will serve as the backbone of the quantum Internet, which will rely on the laws of quantum mechanics to control and transmit information over a network. Currently in its initial stages of development, the quantum Internet coul... » read more

Power/Performance Bits: July 21
By Jesse Allen - 21 Jul, 2020 - Comments: 0

AI hardware Researchers at Purdue University, University of California San Diego, Argonne National Laboratory, University of Louisville, Brookhaven National Laboratory, and University of Iowa developed hardware that can learn skills, offloading some of the energy needed by AI software. "Software is taking on most of the challenges in AI. If you could incorporate intelligence into the circui... » read more

Making Chips At 3nm And Beyond
By Mark LaPedus and Ed Sperling - 16 Apr, 2020 - Comments: 4

Select foundries are beginning to ramp up their new 5nm processes with 3nm in R&D. The big question is what comes after that. Work is well underway for the 2nm node and beyond, but there are numerous challenges as well as some uncertainty on the horizon. There already are signs that the foundries have pushed out their 3nm production schedules by a few months due to various technical issu... » read more

← Older posts Newer posts →

  • Sponsors

About

Navigation

Connect With Us

Copyright ©2013-2024 SMG   |  Terms of Service  |  Privacy Policy