Tag Archives: hexagonal boron nitride

Brainlike transistor and human intelligence

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This brainlike transistor (not a memristor) is important because it functions at room temperature as opposed to others, which require cryogenic temperatures.

A December 20, 2023 Northwestern University news release (received via email; also on EurekAlert) fills in the details,

  • Researchers develop transistor that simultaneously processes and stores information like the human brain
  • Transistor goes beyond categorization tasks to perform associative learning
  • Transistor identified similar patterns, even when given imperfect input
  • Previous similar devices could only operate at cryogenic temperatures; new transistor operates at room temperature, making it more practical

EVANSTON, Ill. — Taking inspiration from the human brain, researchers have developed a new synaptic transistor capable of higher-level thinking.

Designed by researchers at Northwestern University, Boston College and the Massachusetts Institute of Technology (MIT), the device simultaneously processes and stores information just like the human brain. In new experiments, the researchers demonstrated that the transistor goes beyond simple machine-learning tasks to categorize data and is capable of performing associative learning.

Although previous studies have leveraged similar strategies to develop brain-like computing devices, those transistors cannot function outside cryogenic temperatures. The new device, by contrast, is stable at room temperatures. It also operates at fast speeds, consumes very little energy and retains stored information even when power is removed, making it ideal for real-world applications.

The study was published today (Dec. 20 [2023]) in the journal Nature.

“The brain has a fundamentally different architecture than a digital computer,” said Northwestern’s Mark C. Hersam, who co-led the research. “In a digital computer, data move back and forth between a microprocessor and memory, which consumes a lot of energy and creates a bottleneck when attempting to perform multiple tasks at the same time. On the other hand, in the brain, memory and information processing are co-located and fully integrated, resulting in orders of magnitude higher energy efficiency. Our synaptic transistor similarly achieves concurrent memory and information processing functionality to more faithfully mimic the brain.”

Hersam is the Walter P. Murphy Professor of Materials Science and Engineering at Northwestern’s McCormick School of Engineering. He also is chair of the department of materials science and engineering, director of the Materials Research Science and Engineering Center and member of the International Institute for Nanotechnology. Hersam co-led the research with Qiong Ma of Boston College and Pablo Jarillo-Herrero of MIT.

Recent advances in artificial intelligence (AI) have motivated researchers to develop computers that operate more like the human brain. Conventional, digital computing systems have separate processing and storage units, causing data-intensive tasks to devour large amounts of energy. With smart devices continuously collecting vast quantities of data, researchers are scrambling to uncover new ways to process it all without consuming an increasing amount of power. Currently, the memory resistor, or “memristor,” is the most well-developed technology that can perform combined processing and memory function. But memristors still suffer from energy costly switching.

“For several decades, the paradigm in electronics has been to build everything out of transistors and use the same silicon architecture,” Hersam said. “Significant progress has been made by simply packing more and more transistors into integrated circuits. You cannot deny the success of that strategy, but it comes at the cost of high power consumption, especially in the current era of big data where digital computing is on track to overwhelm the grid. We have to rethink computing hardware, especially for AI and machine-learning tasks.”

To rethink this paradigm, Hersam and his team explored new advances in the physics of moiré patterns, a type of geometrical design that arises when two patterns are layered on top of one another. When two-dimensional materials are stacked, new properties emerge that do not exist in one layer alone. And when those layers are twisted to form a moiré pattern, unprecedented tunability of electronic properties becomes possible.

For the new device, the researchers combined two different types of atomically thin materials: bilayer graphene and hexagonal boron nitride. When stacked and purposefully twisted, the materials formed a moiré pattern. By rotating one layer relative to the other, the researchers could achieve different electronic properties in each graphene layer even though they are separated by only atomic-scale dimensions. With the right choice of twist, researchers harnessed moiré physics for neuromorphic functionality at room temperature.

“With twist as a new design parameter, the number of permutations is vast,” Hersam said. “Graphene and hexagonal boron nitride are very similar structurally but just different enough that you get exceptionally strong moiré effects.”

To test the transistor, Hersam and his team trained it to recognize similar — but not identical — patterns. Just earlier this month, Hersam introduced a new nanoelectronic device capable of analyzing and categorizing data in an energy-efficient manner, but his new synaptic transistor takes machine learning and AI one leap further.

“If AI is meant to mimic human thought, one of the lowest-level tasks would be to classify data, which is simply sorting into bins,” Hersam said. “Our goal is to advance AI technology in the direction of higher-level thinking. Real-world conditions are often more complicated than current AI algorithms can handle, so we tested our new devices under more complicated conditions to verify their advanced capabilities.”

First the researchers showed the device one pattern: 000 (three zeros in a row). Then, they asked the AI to identify similar patterns, such as 111 or 101. “If we trained it to detect 000 and then gave it 111 and 101, it knows 111 is more similar to 000 than 101,” Hersam explained. “000 and 111 are not exactly the same, but both are three digits in a row. Recognizing that similarity is a higher-level form of cognition known as associative learning.”

In experiments, the new synaptic transistor successfully recognized similar patterns, displaying its associative memory. Even when the researchers threw curveballs — like giving it incomplete patterns — it still successfully demonstrated associative learning.

“Current AI can be easy to confuse, which can cause major problems in certain contexts,” Hersam said. “Imagine if you are using a self-driving vehicle, and the weather conditions deteriorate. The vehicle might not be able to interpret the more complicated sensor data as well as a human driver could. But even when we gave our transistor imperfect input, it could still identify the correct response.”

The study, “Moiré synaptic transistor with room-temperature neuromorphic functionality,” was primarily supported by the National Science Foundation.

Here’s a link to and a citation for the paper,

Moiré synaptic transistor with room-temperature neuromorphic functionality by Xiaodong Yan, Zhiren Zheng, Vinod K. Sangwan, Justin H. Qian, Xueqiao Wang, Stephanie E. Liu, Kenji Watanabe, Takashi Taniguchi, Su-Yang Xu, Pablo Jarillo-Herrero, Qiong Ma & Mark C. Hersam. Nature volume 624, pages 551–556 (2023) DOI: https://doi.org/10.1038/s41586-023-06791-1 Published online: 20 December 2023 Issue Date: 21 December 2023

This paper is behind a paywall.

Psst: secret marriage … Buckyballs and Graphene get together!

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A March 1, 2018 news item on Nanowerk announces  a new coupling,

Scientists combined buckyballs, [also known as buckminsterfullerenes, fullerenes, or C60] which resemble tiny soccer balls made from 60 carbon atoms, with graphene, a single layer of carbon, on an underlying surface. Positive and negative charges can transfer between the balls and graphene depending on the nature of the surface as well as the structural order and local orientation of the carbon ball. Scientists can use this architecture to develop tunable junctions for lightweight electronic devices.

The researchers have made this illustration of their work available,

Researchers are developing new, lightweight electronics that rapidly conduct electricity by covering a sheet of carbon (graphene) with buckyballs. Electricity is the flow of electrons. On these lightweight structures, electrons as well as positive holes (missing electrons) transfer between the balls and graphene. The team showed that the crystallinity and orientation of the balls, as well as the underlying layer, affected this charge transfer. The top image shows a calculation of the charge density for a specific orientation of the balls on graphene. The blue represents positive charges, while the red is negative. The bottom image shows that the balls are in a close-packed structure. The bright dots correspond to the projected images of columns of buckyball molecules. Courtesy: US Department of Energy Office of Science

A February 28, 2018 US Department of Energy (DoE) Office of Science news release, which originated the news item, provides more detail,

The Impact

Fast-moving electrons and their counterpart, holes, were preserved in graphene with crystalline buckyball overlayers. Significantly, the carbon ball provides charge transfer to the graphene. Scientists expect the transfer to be highly tunable with external voltages. This marriage has ramifications for smart electronics that run longer and do not break as easily, bringing us closer to sensor-embedded smart clothing and robotic skin.

Summary

Charge transfer at the interface between dissimilar materials is at the heart of almost all electronic technologies such as transistors and photovoltaic devices. In this study, scientists studied charge transfer at the interface region of buckyball molecules deposited on graphene, with and without a supporting substrate, such as hexagonal boron nitride. They employed ab initio density functional theory with van der Waals interactions to model the structure theoretically. Van der Waals interactions are weak connections between neutral molecules. The team used high-resolution transmission electron microscopy and electronic transport measurements to characterize experimentally the properties of the interface. The researchers observed that charge transfer between buckyballs and the graphene was sensitive to the nature of the underlying substrate, in addition, to the crystallinity and local orientation of the buckyballs. These studies open an avenue to devices where buckyball layers on top of graphene can serve as electron acceptors and other buckyball layers as electron donors. Even at room temperature, buckyball molecules were orientationally locked into position. This is in sharp contrast to buckyball molecules in un-doped bulk crystalline configurations, where locking occurs only at low temperature. High electron and hole mobilities are preserved in graphene with crystalline buckyball overlayers. This finding has ramifications for the development of organic high-mobility field-effect devices and other high mobility applications.

Here’s a link to and a citation for the paper,

Molecular Arrangement and Charge Transfer in C60 /Graphene Heterostructures by Claudia Ojeda-Aristizabal, Elton J. G. Santos, Seita Onishi, Aiming Yan, Haider I. Rasool, Salman Kahn, Yinchuan Lv, Drew W. Latzke, Jairo Velasco Jr., Michael F. Crommie, Matthew Sorensen, Kenneth Gotlieb, Chiu-Yun Lin, Kenji Watanabe, Takashi Taniguchi, Alessandra Lanzara, and Alex Zettl. ACS Nano, 2017, 11 (5), pp 4686–4693 DOI: 10.1021/acsnano.7b00551 Publication Date (Web): April 24, 2017

Copyright © 2017 American Chemical Society

This paper is behind a paywall.

Scaling graphene production up to industrial strength

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If graphene is going to be a ubiquitous material in the future, production methods need to change. An Aug. 7, 2015 news item on Nanowerk announces a new technique to achieve that goal,

Producing graphene in bulk is critical when it comes to the industrial exploitation of this exceptional two-dimensional material. To that end, [European Commission] Graphene Flagship researchers have developed a novel variant on the chemical vapour deposition process which yields high quality material in a scalable manner. This advance should significantly narrow the performance gap between synthetic and natural graphene.

An Aug. 7, 2015 European Commission Graphene Flagship press release by Francis Sedgemore, which originated the news item, describes the problem,

Media-friendly Nobel laureates peeling layers of graphene from bulk graphite with sticky tape may capture the public imagination, but as a manufacturing process the technique is somewhat lacking. Mechanical exfoliation may give us pristine graphene, but industry requires scalable and cost-effective production processes with much higher yields.

On to the new method (from the press release),

Flagship-affiliated physicists from RWTH Aachen University and Forschungszentrum Jülich have together with colleagues in Japan devised a method for peeling graphene flakes from a CVD substrate with the help of intermolecular forces. …

Key to the process is the strong van der Waals interaction that exists between graphene and hexagonal boron nitride, another 2d material within which it is encapsulated. The van der Waals force is the attractive sum of short-range electric dipole interactions between uncharged molecules.

Thanks to strong van der Waals interactions between graphene and boron nitride, CVD graphene can be separated from the copper and transferred to an arbitrary substrate. The process allows for re-use of the catalyst copper foil in further growth cycles, and minimises contamination of the graphene due to processing.

Raman spectroscopy and transport measurements on the graphene/boron nitride heterostructures reveals high electron mobilities comparable with those observed in similar assemblies based on exfoliated graphene. Furthermore – and this comes as something of a surprise to the researchers – no noticeable performance changes are detected between devices developed in the first and subsequent growth cycles. This confirms the copper as a recyclable resource in the graphene fabrication process.

“Chemical vapour deposition is a highly scalable and cost-efficient technology,” says Christoph Stampfer, head of the 2nd Institute of Physics A in Aachen, and co-author of the technical article. “Until now, graphene synthesised this way has been significantly lower in quality than that obtained with the scotch-tape method, especially when it comes to the material’s electronic properties. But no longer. We demonstrate a novel fabrication process based on CVD that yields ultra-high quality synthetic graphene samples. The process is in principle suitable for industrial-scale production, and narrows the gap between graphene research and its technological applications.”

With their dry-transfer process, Banszerus and his colleagues have shown that the electronic properties of CVD-grown graphene can in principle match those of ultrahigh-mobility exfoliated graphene. The key is to transfer CVD graphene from its growth substrate in such a way that chemical contamination is avoided. The high mobility of pristine graphene is thus preserved, and the approach allows for the substrate material to be recycled without degradation.

Here’s a link to and citation for the paper,

Ultrahigh-mobility graphene devices from chemical vapor deposition on reusable copper by Luca Banszerus, Michael Schmitz, Stephan Engels, Jan Dauber, Martin Oellers, Federica Haupt, Kenji Watanabe, Takashi Taniguchi, Bernd Beschoten, and Christoph Stampfer. Science Advances  31 Jul 2015: Vol. 1, no. 6, e1500222 DOI: 10.1126/sciadv.1500222

This article appears to be open access.

For those interested in finding out more about chemical vapour deposition (CVD), David Chandler has written a June 19, 2015 article for the Massachusetts Institute of Technology (MIT) titled:  Explained: chemical vapor deposition (Technique enables production of pure, uniform coatings of metals or polymers, even on contoured surfaces.)

Good heat, bad heat, and cooling oils

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The good heat is what keeps you warm in the cold; the bad heat is what melts your computer’s motherboard. All equipment generates heat and engineers, industrial designers, and others spend a fair chunk of time trying to minimize or remove the amount of ‘bad’ heat that is generated. Researchers at Rice University have developed an oil sprinkled with nanoparticles that could help with dissipating ‘bad’ heat  in at least one industry sector. From the Feb. 1, 2012 news item on Nanowerk,

Rice University scientists have created a nano-infused oil that could greatly enhance the ability of devices as large as electrical transformers and as small as microelectronic components to shed excess heat.

Research in the lab of Rice materials scientist Pulickel Ajayan, which appears in the American Chemical Society journal ACS Nano (“Electrically Insulating Thermal Nano-Oils Using 2D Fillers”), could raise the efficiency of such transformer oils by as much as 80 percent in a way that is both cost-effective and environmentally friendly.

The Rice team headed by lead authors Jaime Taha-Tijerina, a graduate student, and postdoctoral researcher Tharangattu Narayanan focused their efforts on transformers for energy systems. Transformers are filled with mineral oils that cool and insulate the windings inside, which must remain separated from each other to keep voltage from leaking or shorting.

I was a little puzzled by that reference to “nano-infused oil”, thankfully an explanation follows,

The researchers discovered that a very tiny amount of hexagonal boron nitride (h-BN) particles, two-dimensional cousins to carbon-based graphene, suspended in standard transformer oils are highly efficient at removing heat from a system.

“We don’t need a large amount of h-BN,” Narayanan said. “We found that 0.1 weight percentage of h-BN in transformer oil enhances it by nearly 80 percent.” ”

And at 0.01 weight percentage, the enhancement was around 9 percent,” Taha-Tijerina said. “Even with a very low amount of material, we can enhance the fluids without compromising the electrically insulating properties.”

…

Narayanan said the h-BN particles, about 600 nanometers wide and up to five atomic layers thick, disperse well in oil and, unlike highly conductive graphene, are highly resistant to electricity. With help from co-author Matteo Pasquali, a Rice professor of chemical and biomolecular engineering and of chemistry, the team determined that the oil’s viscosity – another important quality – is minimally affected by the presence of the nanoparticle fillers.

I have previously mentioned hexagonal boron nitride in a Mar. 2, 2010 posting (scroll down) about Rice University researchers, h-BN combined with graphene, and a challenge to Moore’s law.