MIT researchers have found new ways to cure headaches in manufacturing carbon nanotube processors, which are faster and less power hungry than silicon chips.
Category: computing – Page 673
Light and sound waves are at the basis of energy and signal transport and fundamental to some of our most basic technologies—from cell phones to engines. Scientists, however, have yet to devise a method that allows them to store a wave intact for an indefinite period of time and then direct it toward a desired location on demand. Such a development would greatly facilitate the ability to manipulate waves for a variety of desired uses, including energy harvesting, quantum computing, structural-integrity monitoring, information storage, and more.
In a newly published paper in Science Advances, a group of researchers led by Andrea Alù, founding director of the Photonics Initiative at the Advanced Science Research Center (ASRC) at The Graduate Center, CUNY, and by Massimo Ruzzene, professor of Aeronautics Engineering at Georgia Tech, have experimentally shown that it is possible to efficiently capture and store a wave intact then guide it towards a specific location.
“Our experiment proves that unconventional forms of excitation open new opportunities to gain control over wave propagation and scattering,” said Alù. “By carefully tailoring the time dependence of the excitation, it is possible to trick the wave to be efficiently stored in a cavity, and then release it on demand towards the desired direction.”
Credit: MIT Engineers from the MIT and Analog Devices have created the most complex chip design yet that uses transistors made of carbon nanotubes instead of silicon. The chip was manufactured using new technologies proven to work in a commercial chip-manufacturing facility.
The researchers seem to have chosen the RISC-V instruction set architecture (ISA) for the design of the chip, presumably due to the open source nature that didn’t require hassling with licensing restrictions and costs. The RISC-V processor handles 32-bit instructions and does 16-bit memory addressing. The chip is not meant to be used in mainstream devices quite yet, but it’s a strong proof of concept that can already run “hello world”-type applications.
One advantage transistors made out of carbon nanotubes have over silicon transistors is that they can be manufactured in multiple layers, allowing for very dense 3D chip designs. DARPA also believes that carbon nanotubes may allow for the manufacturing of future 3D chips that have performance similar or better than silicon chips, but they can also be manufactured for much lower costs.
It’s the most complex integration of carbon nanotube-based CMOS logic so far, with nearly 15,000 transistors, and it was done using technologies that have already been proven to work in a commercial chip-manufacturing facility. The processor, called RV16X-NANO, is a milestone in the development of beyond-silicon technologies, its inventors say.
Unlike silicon transistors, nanotube devices can easily be made in multiple layers with dense 3D interconnections. The Defense Advanced Research Projects Agency is hoping this 3D aspect will lead to commercial carbon nanotube (CNT) chips with the performance of today’s cutting-edge silicon but without the high design and manufacturing cost.
Some of the same researchers created a modest one-bit, 178-transistor processor back in 2013. In contrast, the new one, which is based on the open source RISC-V instruction set, is capable of working with 16-bit data and 32-bit instructions. Naturally, the team, led by MIT assistant professor Max Shulaker, tested the chip by running a version of the obligatory “Hello, World!” program. They reported the achievement this week in Nature.
In a study published in Scientific Reports, a group of researchers affiliated with São Paulo State University (UNESP) in Brazil describes an important theoretical finding that may contribute to the development of quantum computing and spintronics (spin electronics), an emerging technology that uses electron spin or angular momentum rather than electron charge to build faster, more efficient devices.
The study was supported by São Paulo Research Foundation—FAPESP. Its principal investigator was Antonio Carlos Seridonio, a professor in UNESP’s Department of Physics and Chemistry at Ilha Solteira, São Paulo State. His graduate students Yuri Marques, Willian Mizobata and Renan Oliveira also participated.
The researchers observed that molecules with the capacity to encode information are produced in systems called Weyl semimetals when time-reversal symmetry is broken.
Scientists at MIT built a 16-bit microprocessor out of carbon nanotubes and even ran a program on it, a new paper reports.
Silicon-based computer processors seem to be approaching a limit to how small they can be scaled, so researchers are looking for other materials that might make for useful processors. It appears that transistors made from tubes of rolled-up, single-atom-thick sheets of carbon, called carbon nanotubes, could one day have more computational power while requiring less energy than silicon.
“This work is particularly exciting because carbon nanotubes are one of the most promising supplements in the future of beyond-silicon computers,” Max Shulaker, the study’s corresponding author and assistant professor at MIT, told Gizmodo.
It’s official: Android 10, the next version of the Android operating system, ships 3 September 2019. Well, it’s semi-official, at least.
Mobile site PhoneArena reports that Google’s customer support staff let the date slip to a reader during a text conversation. Expect the operating system, also known as Android Q, to hit Google’s Pixel phones first before rolling out to other models. It will include a range of privacy and security improvements that should keep Android users a little safer.
Synthetic biological circuits are promising tools for developing sophisticated systems for medical, industrial, and environmental applications. So far, circuit implementations commonly rely on gene expression regulation for information processing using digital logic. Here, we present a different approach for biological computation through metabolic circuits designed by computer-aided tools, implemented in both whole-cell and cell-free systems. We first combine metabolic transducers to build an analog adder, a device that sums up the concentrations of multiple input metabolites. Next, we build a weighted adder where the contributions of the different metabolites to the sum can be adjusted. Using a computational model fitted on experimental data, we finally implement two four-input perceptrons for desired binary classification of metabolite combinations by applying model-predicted weights to the metabolic perceptron. The perceptron-mediated neural computing introduced here lays the groundwork for more advanced metabolic circuits for rapid and scalable multiplex sensing.
