<h3 id="isPasted">Background</h3>Global water pollution presents a formidable challenge, with traditional remediation methods often falling short due to their inefficacy, high costs, and environmental burden. This context <a href="https://pubs.rsc.org/en/content/articlelanding/2023/NR/D3NR03592A" target="_blank" rel="noopener noreferrer">underscores</a> the urgent need for innovative solutions that are both effective and sustainable. <h3>The Team and Their Inspiration</h3>"CoffeeBots" are a <a href="https://www.wusa9.com/article/news/local/virginia/rusty-coffee-cleaning-water-george-mason-university/65-0de9e05b-b8ed-4b5c-863d-de7323f75a09" target="_blank" rel="noopener noreferrer">collaborative invention</a> by Jeff Moran, an Assistant Professor of Mechanical Engineering at George Mason University, Amit Kumar Singh, a postdoctoral researcher at GMU, and Tarini Basireddy, an undergraduate student at Johns Hopkins University. Together, they engineered a low-cost and environmentally friendly solution to address severe water contamination issues using everyday materials. <iframe width="640" height="360" src="https://www.youtube.com/embed/cDSJA1JBTNk?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> <h3>Technical Details of CoffeeBots</h3>Composition and Manufacturing: CoffeeBots <a href="https://www.youtube.com/watch?v=cDSJA1JBTNk" target="_blank" rel="noopener noreferrer">consist</a> of spent coffee grounds coated with iron oxide nanoparticles. The synthesis of these nanoparticles employs green chemistry principles, ensuring an eco-friendly production process. The nanoparticles adhere to the coffee grounds, leveraging the grounds’ natural porous and hydrophobic surface, which is ideal for adsorbing oil and microplastics.Functionalization: Further enhancing their pollutant-binding capabilities, CoffeeBots are <a href="https://www.youtube.com/watch?v=cDSJA1JBTNk" target="_blank" rel="noopener noreferrer">functionalized</a> with ascorbic acid. This addition targets the removal of methylene blue dye, a common pollutant in industrial wastewater. The ascorbic acid acts both as a bioadsorbent and a reducing agent, facilitating the breakdown of the dye into less harmful compounds.Magnetic Navigation and Recovery: The integration of iron oxide nanoparticles allows for the magnetic manipulation of CoffeeBots. This feature enables the remote guidance of CoffeeBots through contaminated waters and their subsequent retrieval via magnetic forces once the cleanup task is completed. This magnetic property not only simplifies the operation but also allows for the reuse of CoffeeBots, significantly <a href="https://www.gmu.edu/news/2024-01/mason-engineers-develop-rusty-coffee-grounds-remove-pollutants-water" target="_blank" rel="noopener noreferrer">reducing</a> the cost and environmental impact of the cleanup process.Performance and Efficiency: In practical applications, CoffeeBots demonstrate a high efficacy in capturing and removing oil, microplastics, and dye pollutants from seawater. Their movement, driven by external magnetic fields, increases their contact with pollutants, enhancing the efficiency of pollutant uptake compared to static methods. Laboratory tests confirm that CoffeeBots can be recycled multiple times without significant loss of functionality, <a href="https://www.gmu.edu/news/2024-01/mason-engineers-develop-rusty-coffee-grounds-remove-pollutants-water" target="_blank" rel="noopener noreferrer">showcasing</a> their durability and long-term usability. <h3>Significance of the Solution</h3>CoffeeBots <a href="https://www.gmu.edu/news/2024-01/mason-engineers-develop-rusty-coffee-grounds-remove-pollutants-water" target="_blank" rel="noopener noreferrer">exemplify</a> a breakthrough in water purification technology by combining low-cost materials, innovative nano-engineering, and environmental sustainability. This technology not only addresses the immediate need for effective water purification but also aligns with global sustainability goals by repurposing waste products and minimizing chemical inputs. <iframe width="640" height="360" style="border:1px solid #e6e6e6;" src="https://www.wusa9.com/embeds/video/responsive/65-7e8fe0e0-65f0-4168-aee7-1a883a848df4/iframe" allowfullscreen="true" webkitallowfullscreen="true" mozallowfullscreen="true" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> <h3>Future Prospects and Applications</h3>Ongoing research <a href="https://www.wusa9.com/article/news/local/virginia/rusty-coffee-cleaning-water-george-mason-university/65-0de9e05b-b8ed-4b5c-863d-de7323f75a09" target="_blank" rel="noopener noreferrer">aims</a> to extend the capabilities of CoffeeBots, including the exploration of solar-activated propulsion mechanisms that would eliminate the need for external magnetic controls, thereby enhancing the autonomy of the CoffeeBots for more extensive and less supervised water treatment operations. <h3>Conclusion</h3>The creation of CoffeeBots by the team at George Mason University marks a meaningful advancement in nano- and environmental engineering. By harnessing simple yet innovative materials and methods, they have developed a promising solution to combat the pervasive issue of water pollution. As this technology evolves, it holds the <a href="https://pubs.rsc.org/en/content/articlelanding/2023/NR/D3NR03592A" target="_blank" rel="noopener noreferrer">potential</a> to revolutionize water purification practices globally, offering a potential beacon of hope for millions affected by polluted water sources.

How George Mason University's Nanotechnology Research Is Turning Waste From Your Daily Brew into a Powerful Pollution Solution

How to Turn Used Coffee Grounds into Water-Cleaning Superbots

All objects consist of atoms, which are made up of protons and neutrons in the atomic nucleus, surrounded by electrons. Once one enters this universe of the smallest things – the quantum world – it all gets very complicated very quickly. When researchers want to know exactly how atoms are connected and form solid objects, they come up against limits. No computer is powerful enough to calculate material properties precisely when many different atoms are involved. A researcher from the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt; DLR) has now investigated a way to do this via digital quantum simulation. This requires a quantum computer with initially only a few functioning computing and memory units, qubits, which could already answer questions about materials research – using quantum computing to ultimately even improve itself."In contrast to problems that can be solved with increased computing power alone, the complexity of quantum systems exceeds the capabilities of all supercomputers available today, combined. This means that we are currently unable to find explanations for phenomena from the quantum world, including conductivity, magnetism and superconductivity," says Benedikt Fauseweh from the <a href="https://www.dlr.de/en/sc" target="_blank">DLR Institute for Software Technology</a>. "Quantum physics is fundamental to understanding our world, especially solid-state physics." In solids, atoms or molecules are so close together that they hardly move at all. Metals, semiconductors, ceramics and many plastics are solids.<h2>A visionary idea – but quantum computers still make mistakes</h2>The concept of simulating quantum phenomena on a quantum computer is more than 40 years old. In 1982, the US-American physicist Richard Feynman (1918 to 1988) proposed using the principles of quantum mechanics itself to simulate the behaviour of quantum systems. “The development of modern quantum computers is bringing Feynman’s visionary idea closer to reality. Of course, it remains the dream of all physicists to describe all of nature in its full complexity,” says Fauseweh. But we are not there yet; quantum computers still make errors in complex calculations because their qubits (computing and storage units) are not stable or cannot be controlled, leading to incorrect results. Nevertheless, researchers are looking for ways to run sophisticated simulations on quantum computers.<h2>Large number of qubits not required</h2>Fauseweh has described this in the scientific journal <a href="https://www.nature.com/articles/s41467-024-46402-9" target="_blank" rel="noopener noreferrer">Nature Communications</a> and included worldwide research results. His analysis shows that a large number of qubits is not necessarily required for the simulation of complex quantum systems: "If we use too many qubits, the results are no longer useful due to errors in the quantum computer," explains Fauseweh. "We have to identify precisely those applications that still deliver a correct result even with errors in the quantum computer." So, with quality before quantity, digital quantum simulations could soon solve the mysteries of solid-state research: why do interactions between many particles prevent their movement in solids? Why, for example, do some materials not heat up as expected in a magnetic field? How do materials change their properties when they are irradiated with lasers? "It is also exciting that we can use quantum computers in materials research to make quantum computers themselves better."Different technologies for quantum computers certainly complement one another.<a href="https://www.dlr.de/en/latest/news/2022/03/computing-with-light" target="_blank">&nbsp;Photonic quantum computers</a> or quantum computers with <a href="https://www.dlr.de/en/latest/news/2023/02/atomic-shells-become-computational-building-blocks" target="_blank">neutral atoms</a>, for example, would be particularly suitable for some applications, while quantum computers with<a href="https://www.dlr.de/en/latest/news/2022/04/contract-awarded-as-part-of-the-dlr-quantum-computing-initiative" target="_blank">&nbsp;ion traps</a>, with <a href="https://www.dlr.de/en/latest/news/2022/04/how_diamonds_become_qubits" target="_blank">nitrogen vacancies in diamond</a> or other <a href="https://www.dlr.de/en/latest/news/2023/04/quantum-computers-out-of-the-lab-into-the-world" target="_blank">solid-state spins</a>, would suit others. These hardware technologies are being developed in the <a href="https://www.dlr.de/en/research-and-transfer/featured-topics/quantum-technologies/the-dlr-quantum-computing-initiative-qci" target="_blank">DLR Quantum Computing Initiative (DLR QCI)</a>.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1712996854792-image-1920-0e0e1372dc051ff5fc2e347f9452228c.jpeg" style="width: 100%px;" class="fr-fic fr-dib">Goal – improving materials. Quantum computers can simulate solid-state structures that even the best supercomputers cannot calculate. They can therefore help to improve materials for high-tech applications such as photovoltaic systems. Credit: © DLR. All rights reserved<h2 id="isPasted">Analogue simulations reach their limit</h2>In recent decades, researchers have used analogue quantum simulations to assist them – with a quantum platform that serves as a substitute for the actual system. The behaviour of the substitute quantum platform is adjusted so that it corresponds to that of the system under investigation. In this way, it is possible to simulate quantum systems that supercomputers had already failed to – and with this the advantages of quantum simulation become apparent. Analogue quantum simulation has been a common method until now. "However, it has the disadvantage that these machines are not flexible. They can only do one type of simulation," says Fauseweh. "What we want is the universality of a digital quantum computer. That is the most important advantage we expect from the different approaches."

Crystal lattice of a solid (symbolic image). When researchers want to know exactly how atoms are connected and form solid objects, they come up against limits. Digital quantum simulations could soon solve the mysteries of solid-state research. Credit: stock.adobe.com

Digital quantum simulations can be used to solve problems in solid-state research, for example conductivity, magnetism or superconductivity.

Quality matters - Advances in digital quantum simulation

In nanomaterials, shape is destiny. That is, the geometry of the particle in the material defines the physical characteristics of the resulting material.“A crystal made of nano-ball bearings will arrange themselves differently than a crystal made of nano-dice and these arrangements will produce very different physical properties,” said Wendy Gu, an assistant professor of mechanical engineering at Stanford University, introducing her latest <a href="https://www.nature.com/articles/s41467-024-46230-x" data-extlink="" target="_blank">paper</a> which appears in the journal Nature Communications. “We’ve used a 3D nanoprinting technique to produce one of the most promising shapes known – Archimedean truncated tetrahedrons. They are micron-scale tetrahedrons with the tips lopped off.”In the paper, Gu and her co-authors describe how they nanoprinted tens of thousands of these challenging nanoparticles, stirred them into a solution, and then watched as they self-assembled into various promising crystal structures. More critically, these materials can shift between states in minutes simply by rearranging the particles into new geometric patterns.This ability to change “phases,” as materials engineers refer to the shapeshifting quality, is similar to the atomic rearrangement that turns iron into tempered steel, or in materials that allow computers to store terabytes of valuable data in digital form.“If we can learn to control these phase shifts in materials made of these Archimedean truncated tetrahedrons it could lead in many promising engineering directions,” she said.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1712303729312-quasi-diamondphase_sb20um_0.png.png" style="width: 100%px;" class="fr-fic fr-dib">Confocal images of truncated tetrahedrons forming several quasi-diamond grains (left). Bond order analysis shows different quasi-diamond grains through alternating colors (right). Neighboring tetrahedrons that have alternating colors (i.e., blue and red/brown, or dark blue and yellow) indicate that they have the same grain orientation. Scale bars are 20 um. | Image courtesy of David Doan &amp; John Kulikowski<h2 id="isPasted">Elusive prey</h2>Archimedean truncated tetrahedrons (ATTs) have long been theorized to be among the most desirable of geometries for producing materials that can easily change phase, but until recently were challenging to fabricate – predicted in computer simulations yet difficult to reproduce in the real world.Gu is quick to point out that her team is not the first to produce nanoscale Archimedean truncated tetrahedrons in quantity, but they are among the first, if not the first, to use 3D nanoprinting to do it.“With 3D nanoprinting, we can make almost any shape we want. We can control the particle shape very carefully,” Gu explained. “This particular shape has been predicted by simulations to form very interesting structures. When you can pack them together in various ways they produce valuable physical properties.”ATTs form at least two highly desirable geometric structures. The first is a hexagonal pattern in which the tetrahedrons rest flat on the substrate with their truncated tips pointing upward like a nanoscale mountain range. The second is perhaps even more promising, Gu said. It is a crystalline quasi-diamond structure in which the tetrahedrons alternate in upward- and downward-facing orientations, like eggs resting in an egg carton. The diamond arrangement is considered a “Holy Grail” in the photonics community and could lead in many new and interesting scientific directions.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1712303758221-antiphaseboundary_sb25um_0.png.png" style="width: 100%px;" class="fr-fic fr-dib">Optical images of truncated tetrahedrons forming two large hexagonal grains at an anti-phase boundary (left), and transforming into a quasi-diamond phase that initiated at the anti-phase boundary (right). Scale bars are 25 um. | Image courtesy of David Doan &amp; John KulikowskiMost importantly, however, when properly engineered, future materials made of 3D printed particles can be rearranged rapidly, switching easily back and forth between phases with the application of a magnetic field, electric current, heat, or other engineering method.Gu said she can imagine coatings for solar panels that change throughout the day to maximize energy efficiency, new-age hydrophobic films for airplane wings and windows that mean they never fog or ice up, or new types of computer memory. The list goes on and on.“Right now, we’re working on making these particles magnetic to control how they behave,” Gu said of her latest research already underway using Archimedean truncated tetrahedron nanoparticles in new ways. “The possibilities are only beginning to be explored.”Additional co-authors of the work are PhD students David Doan and John Kulikowski. Gu is also a member of&nbsp;<a href="http://biox.stanford.edu/" data-extlink="" target="_blank">Stanford Bio-X</a>.

Optical images of truncated tetrahedrons forming multiple hexagonal grains (top). Bond order analysis shows different hexagonal grains through different colors (bottom). Neighboring tetrahedrons that have the same color indicate that they have the same grain orientation. Scale bar is 20 um. | Image courtesy of David Doan & John Kulikowski

Stanford materials engineers have 3D printed tens of thousands of hard-to-manufacture nanoparticles long predicted to yield promising new materials that change form in an instant.

Elusive 3D printed nanoparticles could lead to new shapeshifting materials

Memory, or the ability to store information in a readily accessible way, is an essential operation in computers and human brains. A key difference is that while brain information processing involves performing computations directly on stored data, computers shuttle data back and forth between a memory unit and a central processing unit (CPU). This inefficient separation (the von Neumann bottleneck) contributes to the rising energy cost of computers.Since the 1970s, researchers have been working on the concept of a memristor (memory resistor); an electronic component that can, like a synapse, both compute and store data. But Aleksandra Radenovic in the Laboratory of Nanoscale Biology (<a href="https://www.epfl.ch/labs/lben/" target="_blank">LBEN</a>) in EPFL’s School of Engineering set her sights on something even more ambitious: a functional nanofluidic memristive device that relies on ions, rather than electrons and their oppositely charged counterparts (holes). Such an approach would more closely mimic the brain’s own – much more energy efficient – way of processing information.“Memristors have already been used to build electronic neural networks, but our goal is to build a nanofluidic neural network that takes advantage of changes in ion concentrations, similar to living organisms,” Radenovic says.“We have fabricated a new nanofluidic device for memory applications that is significantly more scalable and much more performant than previous attempts,” says LBEN postdoctoral researcher Théo Emmerich. “This has enabled us, for the very first time, to connect two such ‘artificial synapses’, paving the way for the design of brain-inspired liquid hardware.”The research has <a href="https://www.nature.com/articles/s41928-024-01137-9" target="_blank" rel="noopener">recently been published in Nature Electronics.</a><h2>Just add water</h2>Memristors can switch between two conductance states – on and off – through manipulation of an applied voltage. While electronic memristors rely on electrons and holes to process digital information, LBEN’s memristor can take advantage of a range of different ions. For their study, the researchers immersed their device in an electrolyte water solution containing potassium ions, but others could be used, including sodium and calcium.“We can tune the memory of our device by changing the ions we use, which affects how it switches from on to off, or how much memory it stores,” Emmerich explains.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1712102720846-6b9cf0f3.jpg" style="width: 100%px;" class="fr-fic fr-dib">Illustration of a HAC circuit. 2023 EPFL/Andras Kis CC BY SA 4.0The device was fabricated on a chip at EPFL’s&nbsp;<a href="https://www.epfl.ch/research/facilities/cmi/" target="_blank">Center of MicroNanoTechnology</a> by creating a nanopore at the center of a silicon nitride membrane. The researchers added palladium and graphite layers to create nano-channels for ions. As a current flows through the chip, the ions percolate through the channels and converge at the pore, where their pressure creates a blister between the chip surface and the graphite. As the graphite layer is forced up by the blister, the device becomes more conductive, switching its memory state to ‘on’. Since the graphite layer stays lifted, even without a current, the device ‘remembers’ its previous state. A negative voltage puts the layers back into contact, resetting the memory to the ‘off’ state.“Ion channels in the brain undergo structural changes inside a synapse, so this also mimics biology,” says LBEN PhD student Yunfei Teng, who worked on fabricating the devices – dubbed highly asymmetric channels (HACs) in reference to the shape of the ion flow toward the central pores.LBEN PhD student Nathan Ronceray adds that the team’s observation of the HAC’s memory action in real time is also a novel achievement in the field. “Because we were dealing with a completely new memory phenomenon, we built a microscope to watch it in action.”By collaborating with Riccardo Chiesa and Edoardo Lopriore of the <a href="https://www.epfl.ch/labs/lanes/" target="_blank">Laboratory of Nanoscale Electronics and Structures</a>, led by Andras Kis, the researchers succeeded in connecting two HACs with an electrode to form a logic circuit based on ion flow. This achievement represents the first demonstration of digital logic operations based on synapse-like ionic devices. But the researchers aren’t stopping there: their next goal is to connect a network of HACs with water channels to create fully liquid circuits. In addition to providing an in-built cooling mechanism, the use of water would facilitate the development of bio-compatible devices with potential applications in brain-computer interfaces or neuromedicine.<hr>ReferencesEmmerich, T., Teng, Y., Ronceray, N. et al. Nanofluidic logic with mechano–ionic memristive switches. Nat Electron (2024). https://doi.org/10.1038/s41928-024-01137-9

Co-authors Nathan Ronceray and Théo Emmerich. 2023 EPFL/Titouan Veuillet CC BY SA 4.0

In a step toward nanofluidic-based neuromorphic – or brain-inspired – computing, EPFL engineers have succeeded in executing a logic operation by connecting two chips that use ions, rather than electrons, to process data.

Artificial nanofluidic synapses can store computational memory

Experimental computer memories and processors built from magnetic materials use far less energy than traditional silicon-based devices. Two-dimensional magnetic materials, composed of layers that are only a few atoms thick, have incredible properties that could allow magnetic-based devices to achieve unprecedented speed, efficiency, and scalability.While many hurdles must be overcome until these so-called van der Waals magnetic materials can be integrated into functioning computers, MIT researchers took an important step in this direction by demonstrating precise control of a van der Waals magnet at room temperature.This is key, since magnets composed of atomically thin van der Waals materials can typically only be controlled at extremely cold temperatures, making them difficult to deploy outside a laboratory.<iframe width="640" height="360" src="https://www.youtube.com/embed/XOWZ2ih0_5Q?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe>The researchers used pulses of electrical current to switch the direction of the device’s magnetization at room temperature. Magnetic switching can be used in computation, the same way a transistor switches between open and closed to represent 0s and 1s in binary code, or in computer memory, where switching enables data storage.The team fired bursts of electrons at a magnet made of a new material that can sustain its magnetism at higher temperatures. The experiment leveraged a fundamental property of electrons known as spin, which makes the electrons behave like tiny magnets. By manipulating the spin of electrons that strike the device, the researchers can switch its magnetization.“The heterostructure device we have developed requires an order of magnitude lower electrical current to switch the van der Waals magnet, compared to that required for bulk magnetic devices,” says Deblina Sarkar, the AT&amp;T Career Development Assistant Professor in the MIT Media Lab and Center for Neurobiological Engineering, head of the Nano-Cybernetic Biotrek Lab, and the senior author of a paper on this technique. “Our device is also more energy efficient than other van der Waals magnets that are unable to switch at room temperature.”In the future, such a magnet could be used to build faster computers that consume less electricity. It could also enable magnetic computer memories that are nonvolatile, which means they don’t leak information when powered off, or processors that make complex AI algorithms more energy-efficient.“There is a lot of inertia around trying to improve materials that worked well in the past. But we have shown that if you make radical changes, starting by rethinking the materials you are using, you can potentially get much better solutions,” says Shivam Kajale, a graduate student in Sarkar’s lab and co-lead author of the paper.Kajale and Sarkar are joined on the paper by co-lead author Thanh Nguyen, a graduate student in the Department of Nuclear Science and Engineering (NSE); Corson Chao, a graduate student in the Department of Materials Science and Engineering (DSME); David Bono, a DSME research scientist; Artittaya Boonkird, an NSE graduate student; and Mingda Li, associate professor of nuclear science and engineering. The research&nbsp;<a href="https://www.nature.com/articles/s41467-024-45586-4" target="_blank">appears this week</a> in&nbsp;Nature Communications.<h2>An atomically thin advantage</h2>Methods to fabricate tiny computer chips in a clean room from bulk materials like silicon can hamper devices. For instance, the layers of material may be barely 1 nanometer thick, so minuscule rough spots on the surface can be severe enough to degrade performance.By contrast, van der Waals magnetic materials are intrinsically layered and structured in such a way that the surface remains perfectly smooth, even as researchers peel off layers to make thinner devices. In addition, atoms in one layer won’t leak into other layers, enabling the materials to retain their unique properties when stacked in devices.“In terms of scaling and making these magnetic devices competitive for commercial applications, van der Waals materials are the way to go,” Kajale says.But there’s a catch. This new class of magnetic materials have typically only been operated at temperatures below 60 kelvins (-351 degrees Fahrenheit). To build a magnetic computer processor or memory, researchers need to use electrical current to operate the magnet at room temperature.To achieve this, the team focused on an emerging material called iron gallium telluride. This atomically thin material has all the properties needed for effective room temperature magnetism and doesn’t contain rare earth elements, which are undesirable because extracting them is especially destructive to the environment.Nguyen carefully grew bulk crystals of this 2D material using a special technique. Then, Kajale fabricated a two-layer magnetic device using nanoscale flakes of iron gallium telluride underneath a six-nanometer layer of platinum.Tiny device in hand, they used an intrinsic property of electrons known as spin to switch its magnetization at room temperature.<h2>Electron ping-pong</h2>While electrons don’t technically “spin” like a top, they do possess the same kind of angular momentum. That spin has a direction, either up or down. The researchers can leverage a property known as spin-orbit coupling to control the spins of electrons they fire at the magnet.The same way momentum is transferred when one ball hits another, electrons will transfer their “spin momentum” to the 2D magnetic material when they strike it. Depending on the direction of their spins, that momentum transfer can reverse the magnetization.In a sense, this transfer rotates the magnetization from up to down (or vice-versa), so it is called a “torque,” as in spin-orbit torque switching. Applying a negative electric pulse causes the magnetization to go downward, while a positive pulse causes it to go upward.The researchers can do this switching at room temperature for two reasons: the special properties of iron gallium telluride and the fact that their technique uses small amounts of electrical current. Pumping too much current into the device would cause it to overheat and demagnetize.The team faced many challenges over the two years it took to achieve this milestone, Kajale says. Finding the right magnetic material was only half the battle. Since iron gallium telluride oxidizes quickly, fabrication must be done inside a glovebox filled with nitrogen.“The device is only exposed to air for 10 or 15 seconds, but even after that I have to do a step where I polish it to remove any oxide,” he says.Now that they have demonstrated room-temperature switching and greater energy efficiency, the researchers plan to keep pushing the performance of magnetic van der Waals materials.“Our next milestone is to achieve switching without the need for any external magnetic fields. Our aim is to enhance our technology and scale up to bring the versatility of van der Waals magnet to commercial applications,” Sarkar says.This work was carried out, in part, using the facilities at MIT.Nano and the Harvard University Center for Nanoscale Systems.

This illustration shows electric current being pumped into platinum (the bottom slab), which results in the creation of an electron spin current that switches the magnetic state of the 2D ferromagnet on top. The colored spheres represent the atoms in the 2D material. Image: Courtesy of the researchers

An MIT team precisely controlled an ultrathin magnet at room temperature, which could enable faster, more efficient processors and computer memories.

Researchers harness 2D magnetic materials for energy-efficient computing

<h2 id="isPasted">How Nanotechnology Is Inspiring the Next Generation of Batteries</h2>Rechargeable batteries are an important part of many modern-day technologies. Researchers, manufacturers and end-user companies are always looking to improve the efficiencies of batteries, making them safer, smaller, and more lightweight to fit in the requirements of new technologies—that is, the consumer desire to have higher-powered, smaller, and more lightweight electronic devices. Conventional fabrication methods, electrochemistries, and materials will take batteries technologies only so far, so a lot of interest in recent years has been around using nanomaterials within the electrodes.Nothing is wrong with current battery technologies—as showcased by the 2019 Nobel Prize in Chemistry, which honored the scientists behind the Li-ion battery—but change is inevitable. Without an ever-changing electronics industry, technological advances made in the past few decades would not have been possible.While lithium-ion (Li-ion) batteries are ubiquitous nowadays, their efficiencies aren’t overly impressive. They are much safer than other batteries while still having a good energy density, so there is room for improvement. Other types of batteries are gaining traction at both fundamental and commercial levels, but a drive to improve the already-established Li-ion batteries by incorporating nanomaterials into them has begun.<h2>Why Nanomaterials?</h2>The switch to trialing nanomaterials over bulkier materials is for many of the same reasons that other industries have made the switch (or have looked to make the switch). A number of properties can be harvested for a small amount of nanomaterials being included in a device (or within another material).Not all nanomaterials are suitable for batteries, as some nanomaterials are inherently insulating in nature. Rather, it is the conductive nanomaterials that are of use in battery systems, such as those of solid-state nature, or those which are incredibly thin (for example, some 2D materials). Luckily, the use of nanomaterials in electrodes is not a completely new invention. It is merely a natural progression to make systems more effective without altering the internal workings of the technology. While the inclusion of nanomaterials might slightly alter the specific mechanisms of how the ions move into the electrodes (because of different-sized/geometry atomic holes) via different architectures, the general operational mechanism of the batteries remains the same. This means that any safety or efficiency issues that arise can be pinpointed much easier than trying to develop a new type of battery from scratch. Sometimes, improving the status quo is better than trying to develop something completely novel.Many of the nanomaterials trialed have high electrical conductivity, and with this comes a high charge carrier mobility. These properties stem from nanomaterials having a very active surface–and a very high surface area–compared to bulkier materials. In some cases, the active surface is the whole nanomaterial (2D materials). Given that nanomaterials are inherently thin, they are a lot more flexible–even the inorganic materials–than bulk materials, meaning that they are more useful for the batteries used in flexible and wearable technologies (Figure 1).<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1709117096314-Flexible+Graphene+Image.webp" style="width: 100%px;" class="fr-fic fr-dib">Figure 1: The inherently thin nature of nanomaterials, as shown in this graphene sheet, means they are more flexible than bulk materials and thereby more suitable for batteries used in flexible and wearable technologies. (Source: BONNINSTUDIO/Shutterstock.com)Despite their small size, a lot of nanomaterials are very stable and are resistant to high temperatures, harsh chemicals, and high physical stresses. While this can’t be said for all nanomaterials, enough of them are stable and conductive enough for battery electrodes. One disadvantage of nanomaterials is their higher cost because of the more complex fabrication methods required to make them. However, because only a small amount is needed for the same (or better) properties than bulkier materials, the cost is a lot less than many people believe. The small addition of nanomaterials also means that less waste is often produced, and the batteries are more lightweight than when bulk materials are used.<h2>Graphene is the Front-Runner</h2>Of all the nanomaterials being trialed, graphene is the front-runner and is found in more prototypes than any other type of nanomaterial. A number of companies now commercially manufacture graphene batteries for different industrial sectors. Reportedly, some big cellphone manufacturers might use graphene batteries in some next-generation phones in the near future (graphene is already used in the cooling systems of some phones).Graphene exhibits some of the best recorded-values of almost all the properties that nanomaterials can exhibit, meaning that making compromises between the beneficial properties of different materials can often be negated by using graphene. Additionally, given that many batteries already use graphite—many graphene layers stacked on top of each other—it is a much more natural progression than other materials, and systems have been developed that use graphite-graphene electrodes.Graphene has one of the highest electrical conductivity and charge carrier mobilities known in the materials world. Moreover, it has an incredibly high tensile strength and flexibility (more than most nanomaterials and bulk materials), as well as being stable to high temperatures and harsh chemicals. The culmination of properties means that it can be used in a number of environments without its performance being affected, which is important when the batteries and the technologies they are in can get very hot internally, never mind the external heat they can be exposed to. Single-layer graphene is optically transparent, so it has the potential for being used to create transparent electrodes and transparent conductive films that could be used in batteries of the future that need to be invisible to the user.Aside from the properties being more suited to batteries than most other nanomaterials, the industry is in a much better place to cope with huge demands should it arrive. Because the properties and potential for graphene is well-understood, the industry has been preparing and growing in size around the world and graphene can now be produced at scale in a number of different forms. The raw material side is more scalable than other nanomaterials, making it a much more viable commercial option.<h2>Conclusion</h2>There is a drive in modern-day society for more efficient and smaller batteries, regardless of whether the application is consumer phones or remote monitoring equipment. Companies are starting to trial nanomaterials in battery systems because they bring about performance benefits and can make the batteries smaller, while not significantly increasing cost because only a small amount is required. A number of companies manufacture graphene batteries, but while graphene batteries are available for the industrial markets, it might take some time for the high-tech consumer markets (phones, tablets, etc.) to adopt graphene (or other nanomaterials) on a large-scale because the status quo is well-tested and any changes in these markets can take a long time to come to fruition.

Rechargeable batteries are an important part of many modern-day technologies. Researchers, manufacturers and end-user companies are always looking to improve the efficiencies of batteries, making them safer, smaller, and more lightweight to fit in the requirements of new technologies

Nanotechnology Is Inspiring Next-Gen Batteries

Medical technology has been a fascination of mine ever since I was introduced to engineering. I’ve been around medical equipment since I was three years old due to a heart condition, and I used to go into those huge MRI machines not knowing anything about what this technology did. Turns out that it’s a pretty important tool that doctors use to get images inside the body. Not even ten years after the first MRI was taken, the first robotic system was used for a biopsy, thus beginning the history of robotic technology used in medical applications.<h2 dir="ltr">Robotics&nbsp;</h2>The use of surgical robotics wasn’t approved in the US until 1997, when the Food and Drug Administration (FDA) allowed use of the technology for visualization and extraction purposes—only a fraction of its capabilities. Today, robotics help doctors perform minimally invasive surgeries, which allow patients to recover more quickly with less scarring and reduced risk of infection.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1706616150236-51973348978_5ea53c8bec_k.jpg" style="width: 766px;" class="fr-fic fr-dib">Nicolas DUPREY/ CD 78 on FlickrThe goal of using robots in surgical applications is complete autonomy. However, this quickly shifted to robotic systems that are controlled by the surgeon. The da Vinci system was the first FDA-approved controllable system used for medical robotics in North America. This system set the surgical robot standard and continues to grow to more than 6,000 units and 8.5 million operations worldwide1. For minimally invasive surgeries, the da Vinci system allows the surgeon to make precise incisions efficiently, effectively, and with fewer risks of error. The da Vinci system also eliminated the need for an assistant in the operating room, as engineers added a third arm equipped with the tools necessary to complete the procedure.Besides surgical robots, healthcare facilities have also implemented robotic systems such as exoskeletons and delivery robots to help both patients and doctors in their respective activities. Exoskeletons help rehabilitate patients with mobility issues primarily below the waist. Exoskeletons utilize sensors to detect small electrical signals and respond with movement2. At this time, mobile delivery robots have limited uses but currently assist in transporting medication to patients, reminding the patient to take their medicine, and delivering samples to and from the lab.<h2 dir="ltr">Nano-robots</h2>Nanorobotics is the next step in creating life-changing technology for the medical industry. These microscopic robots will be able to travel and think autonomously to find and fix health issues in the body. These tiny bots can be the size of a human hair and will be able to connect and form any shape necessary for treatment. In terms of the sensors used in these nanorobots, you might say that teamwork makes the dream work, as researchers continue to use biological reactions to target and determine what job needs to be accomplished.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA2NjE1OTQ0NDQ3LWxvdWlzLXJlZWQtcHdjS0Y3TDQtbm8tdW5zcGxhc2guanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 768px;" class="fr-fic fr-dib">Photo by Louis Reed on UnsplashWe aren’t quite at the level of Tony Stark’s nanotechnology, but we are closer than ever. Though the nanorobots won’t be able to generate a full body exoskeleton in seconds, nanorobots will have the ability to find and treat damaged cells anywhere in the body. Ideally, this technology will be used for cancer treatment, as there are very few treatment options currently available. However, these microscopic bots will have many more use cases than just medicine. They could be used as research vessels, allowing engineers and scientists to build or discover microscopic properties that were previously unknown to us. Hopefully, this leads us to a real-life nanotech Ironman suit. That would be awesome.We're not quite there yet, but the following product could be an essential step forward. This week’s New Tech Tuesday features the CUI Devices AMT13A Modular Incremental Encoder Kits.The AMT13A series is an industrial-grade encoder with endless industrial use-cases including robotics. Encoders are used to sense motion and determine the position of a shaft using an LED and recording the interruption of light while in use. Having accurate positioning of motors and avoiding unwanted movement of the robot itself is vital to the success of a robot, especially those used for surgical applications. Featuring a rugged design and compact package, the AMT13A series encoder offers high accuracy at 4096 pulses per revolution (PPR) and a low current draw. The modular incremental encoder kit contains various sizes of shaft adapters and a pre-installed alignment tool to get any project fitted with an encoder.<h2 dir="ltr">Conclusion</h2>Medtech is an important and developing industry and robots are increasingly playing a key role in lifesaving procedures. Robotics used in medical applications have been around for over 20 years and the benefits have been nothing short of amazing. Engineers are pioneering the new wave of medicine with the use of robotics in a way we have only seen in movies. Today’s surgical robots provide extreme accuracy and efficiency that has transformed the patient’s experience with smaller incisions, less recovery time, and lower risk of infection. Artificial nanorobots are the next step in the evolution of medical robotics. With the implementation of nanorobots, several medical treatments will become minimally invasive and hopefully be able to cure previously untreatable diseases.

Photo by National Cancer Institute on Unsplash

Nanorobotics is the next step in creating life-changing technology for the medical industry. These microscopic robots will be able to travel and think autonomously to find and fix health issues in the body.

From the da Vinci System to Nanorobots

Researchers at the Georgia Institute of Technology have developed a light-based means of printing nano-sized metal structures that is significantly faster and cheaper than any technology currently available. It is a scalable solution that could transform a scientific field long reliant on technologies that are prohibitively expensive and slow. The breakthrough has the potential to bring new technologies out of labs and into the world.Technological advances in many fields rely on the ability to print metallic structures that are nano-sized — a scale hundreds of times smaller than the width of a human hair. <a href="https://www.me.gatech.edu/faculty/saha" target="_blank">Sourabh Saha</a>, assistant professor in the <a href="https://www.me.gatech.edu/" target="_blank">George W. Woodruff School of Mechanical Engineering</a>, and Jungho Choi, a Ph.D. student in Saha’s lab, developed a technique for printing metal nanostructures that is 480 times faster and 35 times cheaper than the current conventional method.Their research was <a href="https://onlinelibrary.wiley.com/doi/10.1002/adma.202308112" target="_blank">published</a> in the journal Advanced Materials.Printing metal on the nanoscale — a technique known as nanopatterning — allows for the creation of unique structures with interesting functions. It is crucial for the development of many technologies, including electronic devices, solar energy conversion, sensors, and other systems.It is generally believed that high-intensity light sources are required for nanoscale printing. But this type of tool, known as a femtosecond laser, can cost up to half a million dollars and is too expensive for most research labs and small businesses.“As a scientific community, we don’t have the ability to make enough of these nanomaterials quickly and affordably, and that is why promising technologies often stay limited to the lab and don’t get translated into real-world applications,” Saha said.“The question we wanted to answer is, ‘Do we really need a high-intensity femtosecond laser to print on the nanoscale?’ Our hypothesis was that we don’t need that light source to get the type of printing we want.”They searched for a low-cost, low-intensity light that could be focused in a way similar to femtosecond lasers, and chose superluminescent light emitting diodes (SLEDs) for their commercial availability. SLEDs emit light that is a billion times less intense than that of femtosecond lasers.Saha and Choi set out to create an original projection-style printing technology, designing a system that converts digital images into optical images and displays them on a glass surface. The system operates like digital projectors but produces images that are more sharply focused. They leveraged the unique properties of the superluminescent light to generate sharply focused images with minimal defects.They then developed a clear ink solution made up of metal salt and added other chemicals to make sure the liquid could absorb light. When light from their projection system hit the solution, it caused a chemical reaction that converted the salt solution into metal. The metal nanoparticles stuck to the surface of the glass, and the agglomeration of the metal particles creates the nanostructures. Because it is a projection type of printing, it can print an entire structure in one go, rather than point by point — making it much faster.After testing the technique, they found that projection-style nanoscale printing is possible even with low-intensity light, but only if the images are sharply focused. Saha and Choi believe that researchers can readily replicate their work using commercially available hardware. Unlike a pricey femtosecond laser, the type of SLED that Saha and Choi used in their printer costs about $3,000.“At present, only top universities have access to these expensive technologies, and even then, they are located in shared facilities and are not always available,” Choi said. “We want to democratize the capability of nanoscale 3D printing, and we hope our research opens the door for greater access to this type of process at a low cost.”The researchers say their technique will be particularly useful for people working in the fields of electronics, optics, and plasmonics, which all require a variety of complex metallic nanostructures.“I think the metrics of cost and speed have been greatly undervalued in the scientific community that works on fabrication and manufacturing of tiny structures,” Saha said.“In the real world, these metrics are important when it comes to translating discoveries from the lab to industry. Only when we have manufacturing techniques that take these metrics into account will we be able to fully leverage nanotechnology for societal benefit.”<hr>Citation: J. Choi, S. K. Saha, Scalable Printing of Metal Nanostructures through Superluminescent Light Projection. Adv. Mater. 2024, 36, 2308112.DOI: https://doi.org/10.1002/adma.202308112

The researchers developed a light-based means of printing nano-sized metal structures that is 480 times faster and 35 times cheaper than the current conventional method.

Researchers Create Faster and Cheaper Way to Print Tiny Metal Structures With Light

In a study published Nov. 24 in&nbsp;<a href="https://www.nature.com/articles/s41467-023-43501-x" rel="nofollow" target="_blank">Nature Communications</a>,&nbsp;<a href="https://www.engineering.columbia.edu/" rel="nofollow" target="_blank">Columbia Engineering</a> researchers and collaborators at the&nbsp;<a href="https://www.mpsd.mpg.de/en" rel="nofollow" target="_blank">Max Planck Institute for the Structure and Dynamics of Matter</a> find that pairing laser light to crystal lattice vibrations can enhance the nonlinear optical properties of a layered 2D material. The finding could lead to new ways of using light to modify materials.Cecilia Chen, a Columbia Engineering PhD student and co-author of the paper,&nbsp;and her colleagues from the&nbsp;<a href="https://gaeta.apam.columbia.edu/" rel="nofollow" target="_blank">Quantum and Nonlinear Photonics group</a>, led by&nbsp;<a href="https://www.apam.columbia.edu/faculty/alex-gaeta" rel="nofollow" target="_blank">Alexander Gaeta</a>, David M. Rickey Professor of&nbsp;<a href="https://www.apam.columbia.edu/" rel="nofollow" target="_blank">Applied Physics</a> and Materials Science, used hexagonal boron nitride (hBN). A 2D material similar to graphene, hBN’s atoms are arranged in a honey-combed-shaped repeating pattern and can be peeled into thin layers with unique quantum properties. Chen noted that hBN is stable at room temperature, and its constituent elements—boron and nitrogen—are very light. That means they vibrate very quickly.Atomic vibrations occur in all materials above absolute zero. That movement can be quantized into quasiparticles called phonons with particular resonances; in hBN's case, the team was interested in the optical phonon mode corresponding to a wavelength of 7.3 μm, in the mid-infrared regime of the electromagnetic spectrum. While mid-IR wavelengths are considered short, and thus, high energy, in the picture of crystal vibrations, they are considered very long and low energy in most optics research, where the overwhelming majority of experiments and studies are performed in the visible to near-IR range of approximately 400 nm to 2 um.When they tuned their laser system to hBN’s frequency, 7.3 μm, Chen, along with Jared Ginsberg PhD’21 (now a data scientist at Bank of America) and postdoc Mehdi Jadidi (now a team lead at PsiQuantum), were able to coherently drive the resonance of the hBN crystal and generate new optical frequencies from the medium—a goal of nonlinear optics. Theoretical work led by&nbsp;<a href="https://www.mpsd.mpg.de/person/39745/2736" rel="nofollow" target="_blank">Angel Rubio’s group</a> at Max Planck helped the experimental team understand their results.Using commercially available, table-top mid-infrared lasers, they explored the phonon-mediated four-wave mixing around even harmonic orders. The crystal could withstand up to 10% atomic displacement without damage. They also observed a 30-fold increase in third-harmonic generation.“We’re excited to show that amplifying the natural phonon motion with laser driving can enhance nonlinear optical effects and generate new frequencies,” said Chen. In future work, the team plans to explore how to modify hBN and materials like it using light.

The Gaeta lab used near-infrared light to drive particles in a crystal of hexagonal boron nitride, generating new optical frequencies. Credit: 420494 from Pixabay

Columbia Engineers pair vibrating particles, called phonons, with particles of light, called photons, to enhance the nonlinear optical properties of hexagonal boron nitride. The finding could lead to new ways of using light to modify materials. Learn more.

Laser-driving a 2D Material

MIT researchers and colleagues have demonstrated a way to precisely control the size, composition, and other properties of nanoparticles key to the reactions involved in a variety of clean energy and environmental technologies. They did so by leveraging ion irradiation, a technique in which beams of charged particles bombard a material.They went on to show that nanoparticles created this way have superior performance over their conventionally made counterparts.“The materials we have worked on could advance several technologies, from fuel cells to generate CO2-free electricity to the production of clean hydrogen feedstocks for the chemical industry [through electrolysis cells],” says Bilge Yildiz, leader of the work and a professor in MIT’s departments of Nuclear Science and Engineering and Materials Science and Engineering.<h2>Critical catalyst</h2>Fuel and electrolysis cells both involve electrochemical reactions through three principal parts: two electrodes (a cathode and anode) separated by an electrolyte. The difference between the two cells is that the reactions involved run in reverse.The electrodes are coated with catalysts, or materials that make the reactions involved go faster. But a critical catalyst made of metal-oxide materials has been limited by challenges including low durability. “The metal catalyst particles coarsen at high temperatures, and you lose surface area and activity as a result,” says Yildiz, who is also affiliated with the Materials Research Laboratory and is an author of&nbsp;<a href="https://pubs.rsc.org/en/content/articlelanding/2023/EE/D3EE02448B" target="_blank">an open-access paper on the work</a> published in the journal&nbsp;Energy &amp; Environmental Science.Enter metal exsolution, which involves precipitating metal nanoparticles out of a host oxide onto the surface of the electrode. The particles embed themselves into the electrode, “and that anchoring makes them more stable,” says Yildiz. As a result, exsolution has “led to remarkable progress in clean energy conversion and energy-efficient computing devices,” the researchers write in their paper.However, controlling the precise properties of the resulting nanoparticles has been difficult. “We know that exsolution can give us stable and active nanoparticles, but the challenging part is really to control it. The novelty of this work is that we’ve found a tool — ion irradiation — that can give us that control,” says Jiayue Wang PhD ’22, first author of the paper. Wang, who conducted the work while earning his PhD in the MIT Department of Nuclear Science and Engineering, is now a postdoc at Stanford University.Sossina Haile ’86, PhD ’92, the Walter P. Murphy Professor of Materials Science and Engineering at Northwestern University, who was not involved in the current work, says:“Metallic nanoparticles serve as catalysts in a whole host of reactions, including the important reaction of splitting water to generate hydrogen for energy storage. In this work, Yildiz and colleagues have created an ingenious method for controlling the way that nanoparticles form.”Haile continues, “the community has shown that exsolution results in structurally stable nanoparticles, but the process is not easy to control, so one doesn’t necessarily get the optimal number and size of particles. Using ion irradiation, this group was able to precisely control the features of the nanoparticles, resulting in excellent catalytic activity for water splitting.”<h2>What they did</h2>The researchers found that aiming a beam of ions at the electrode while simultaneously exsolving metal nanoparticles onto the electrode’s surface allowed them to control several properties of the resulting nanoparticles.“Through ion-matter interactions, we have successfully engineered the size, composition, density, and location of the exsolved nanoparticles,” the team writes in&nbsp;Energy &amp; Environmental Science.For example, they could make the particles much smaller — down to 2 billionths of a meter in diameter — than those made using conventional thermal exsolution methods alone. Further, they were able to change the composition of the nanoparticles by irradiating with specific elements. They demonstrated this with a beam of nickel ions that implanted nickel into the exsolved metal nanoparticle. As a result, they demonstrated a direct and convenient way to engineer the composition of exsolved nanoparticles.“We want to have multi-element nanoparticles, or alloys, because they usually have higher catalytic activity,” Yildiz says. “With our approach, the exsolution target does not have to be dependent on the substrate oxide itself.” Irradiation opens the door to many more compositions. “We can pretty much choose any oxide and any ion that we can irradiate with and exsolve that,” says Yildiz.The team also found that ion irradiation forms defects in the electrode itself. And these defects provide additional nucleation sites, or places for the exsolved nanoparticles to grow from, increasing the density of the resulting nanoparticles.Irradiation could also allow extreme spatial control over the nanoparticles. “Because you can focus the ion beam, you can imagine that you could ‘write’ with it to form specific nanostructures,” says Wang. “We did a preliminary demonstration [of that], but we believe it has potential to realize well-controlled micro- and nano-structures.”The team also showed that the nanoparticles they created with ion irradiation had superior catalytic activity over those created by conventional thermal exsolution alone.Additional MIT authors of the paper are Kevin B. Woller, a principal research scientist at the Plasma Science and Fusion Center (PSFC), home to the equipment used for ion irradiation; Abinash Kumar PhD ’22, who received his PhD from the Department of Materials Science and Engineering (DMSE) and is now at Oak Ridge National Laboratory; and James M. LeBeau, an associate professor in DMSE. Other authors are Zhan Zhang and Hua Zhou of Argonne National Laboratory, and Iradwikanari Waluyo and Adrian Hunt of Brookhaven National Laboratory.<hr>This work was funded by the OxEon Corp. and MIT’s PSFC. The research also used resources supported by the U.S. Department of Energy Office of Science, MIT’s Materials Research Laboratory, and MIT.nano. The work was performed, in part, at Harvard University through a network funded by the National Science Foundation.

Artist’s representation of nanoparticles with different compositions created by combining two techniques: metal exsolution and ion irradiation. The different colors represent different elements, such as nickel, that can be implanted into an exsolved metal particle to tailor the particle’s compositions and reactivity. Image: Jiayue Wang

The work demonstrates control over key properties leading to better performance.

Team engineers nanoparticles using ion irradiation to advance clean energy and fuel conversion

In this episode, we talk all about connectomics - the study of animal brains - and how researchers at MIT have started leveraging AI to break through the primary bottleneck: brain image acquisition.

Podcast: Reverse Engineering The Brain With AI

As information and communication technologies (ICT) process data, they convert electricity into heat. Already today, the global ICT ecosystem’s CO2 footprint rivals that of aviation. It turns out, however, that a big part of the energy consumed by computer processors doesn’t go into performing calculations. Instead, the bulk of the energy used to process data is spent shuttling bytes between the memory to the processor.In a <a href="https://dx.doi.org/10.1038/s41928-023-01064-1" target="_blank" rel="noopener">paper published</a> in the journal Nature Electronics, researchers from EPFL’s School of Engineering in the <a href="https://www.epfl.ch/labs/lanes/" target="_blank">Laboratory of Nanoscale Electronics and Structures (LANES)</a> present a new processor that tackles this inefficiency by integrating data processing and storage onto a single device, a so-called in-memory processor. They broke new ground by creating the first in-memory processor based on a two-dimensional semiconductor material to comprise more than 1000 transistors, a key milestone on the path to industrial production.<h2>Von Neuman’s legacy</h2>According to Andras Kis, who led the study, the main culprit behind the inefficiency of today’s CPUs is the universally adopted von Neumann architecture. Specifically, the physical separation of the components used to perform calculations and to store data. Because of this separation, processors need to retrieve data from the memory to perform calculations, which involves moving electrical charges, charging and discharging capacitors, and transmitting currents along lines – all of which dissipate energy.Until around 20 years ago, this architecture made sense, as different types of devices were required for data storage and processing. But the von Neumann architecture is increasingly being challenged by more efficient alternatives. “Today, there are ongoing efforts to merge storage and processing into a more universal in-memory processors that contain elements which work both as a memory and as a transistor,” Kis explains. His lab has been exploring ways to achieve this goal using molybdenum disulfide (MoS2), a semiconductor material.<h2>A new two-dimensional processor architecture</h2>In their Nature Electronics paper, Guilherme Migliato Marega, doctoral assistant at LANES, and his co-authors present an MoS2-based in-memory processor dedicated to one of the fundamental operations in data processing: vector-matrix multiplication. This operation is ubiquitous in digital signal processing and the implementation of artificial intelligence models. Improvements in its efficiency could yield substantial energy savings throughout the entire ICT sector.Their processor combines 1024 elements onto a one-by-one-centimeter chip. Each element comprises a 2D MoS2transistor as well as a floating gate, used to store a charge in its memory that controls the conductivity of each transistor. Coupling processing and memory in this way fundamentally changes how the processor carries out the calculation. “By setting the conductivity of each transistor, we can perform analog vector-matrix multiplication in a single step by applying voltages to our processor and measuring the output,” explains Kis.<h2>A big step closer to practical applications</h2>The choice of material – MoS2 – played a vital role in the development of their in-memory processor. For one, MoS2 is a semiconductor – a requirement for the development of transistors. Unlike silicon, the most widely used semiconductor in today’s computer processors, MoS2 forms a stable monolayer, just three atoms thick, that only interacts weakly with its surroundings. Its thinness offers the potential to produce extremely compact devices. Finally, it’s a material that Kis’s lab knows well. In 2010, they created their first single MoS2 transistor using a monolayer of the material peeled off a crystal using Scotch tape.Over the past 13 years, their processes have matured substantially, with Migliato Marega’s contributions playing a key role. “The key advance in going from a single transistor to over 1000 was the quality of the material that we can deposit. After a lot of process optimization, we can now produce entire wafers covered with a homogenous layer of uniform MoS2. This lets us adopt industry standard tools to design integrated circuits on a computer and translate these designs into physical circuits, opening the door to mass production,” says Kis.<h2>Revitalizing European chip manufacturing</h2>Aside from its purely scientific value, Kis sees this result as a testament to the importance of close scientific collaboration between Switzerland and the EU, in particular in the context of the European Chips Act, which aims to bolster Europe’s competitiveness and resilience in semiconductor technologies and applications. “EU funding was crucial for both this project and those that preceded it, including the one that financed the work on the first MoS2 transistor, showing just how important it is for Switzerland,” says Kis.“At the same time, it shows how work carried out in Switzerland can benefit the EU as it seeks to reinvigorate electronics fabrication. Rather than running the same race as everyone else, the EU could, for example, focus on developing non-von Neumann processing architectures for AI accelerators and other emerging applications. By defining its own race, the continent could get a head start to secure a strong position in the future,” he concludes.<hr>ReferencesMarega, G. M., Ji, H. G., Wang, Z., Pasquale, G., Tripathi, M., Radenovic, A., &amp; Kis, A. (2023). Large-Scale Integrated Vector-Matrix Multiplication Processor Based on Monolayer MoS2. Nature Electronics. DOI: <a href="https://dx.doi.org/10.1038/s41928-023-01064-1" target="_blank" rel="noopener">http://dx.doi.org/10.1038/s41928-023-01064-1</a>

Developed by EPFL researchers, the first large-scale in-memory processor using 2D semiconductor materials could substantially cut the ICT sector’s energy footprint.

Redefining energy efficiency in data processing

This article was discussed in our <a href="https://www.wevolver.com/profile/the.next.byte" rel="noopener noreferrer" target="_blank">Next Byte podcast</a>.&nbsp;<iframe height="200px" width="100%" frameborder="no" scrolling="no" seamless="" src="https://player.simplecast.com/2dca102f-80d1-4182-8d29-b2f6cf6ed323?dark=false" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> The full article will continue below.<hr>Now that ChatGPT has revealed connections in meaning that can emerge from the simple premise of predicting the next word, a team of researchers led by the University of Michigan aims to do the same for atoms strung together to build molecules.The research is supported with a one-year grant from the Department of Energy providing 200,000 node hours on <a href="https://www.alcf.anl.gov/polaris" target="_blank" rel="noreferrer noopener">Polaris, a 34-petaflop supercomputer</a> at Argonne National Laboratory. The team will build a foundational model for molecules, similar to the GPT models that support applications like ChatGPT. The new model will focus on small organic molecules with relevance to energy storage and conversion applications—mainly composed of carbon, hydrogen, oxygen and nitrogen.“What we’ve learned from language models is that size matters. The interesting behavior happens when you make it very big,” said <a href="https://aero.engin.umich.edu/people/viswanathan-venkat/" target="_blank" rel="noreferrer noopener">Venkat Viswanathan</a>, U-M associate professor of aerospace engineering and principal investigator of the award. “If you train on a small amount of data and ask it to write Shakespeare, it’s not good. But a larger data set is better, and when it’s big enough, text that sounds like Shakespeare emerges.”The team is planning to use their model to predict better battery electrolytes—the medium through which ions shuttle from one electrode to the other during charge and discharge cycles. Many electrode pairs offer the potential for higher energy densities than our current lithium-based batteries, but the electrolyte needs to work with both electrodes. That’s often a tall order, and the team is betting AI can help.As with GPT’s steady diet of text with no annotation, the chemical model will be fed text-based representations of atomic structures with no additional information like chemical properties.“There are several billions of molecules that are possible to make, and we have the text-based representation for them,” Viswanathan said. “Our slice of that will be synthesizable small molecules similar to those used in pharmaceuticals and electrolytes.”When the model is able to predict missing atoms in small organic compounds, the team will move on to fine-tuning—feeding it the properties of some compounds and asking it to predict the properties of others. Through iterative feedback, they intend to build an AI that can master small organic molecule chemistry.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzAwMTA1MjE3NTA5LW1vZGVsLWRpYWdyYW0uanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib">The diagram shows 2D representations of molecular structures on the left, simplified to text representations in the arrows and then mapped by the foundational model in a way that enables it to predict molecular properties and design molecules with the right properties. Credit: Viswanathan Group, University of Michigan“Deep Forest Sciences has built considerable expertise in applying molecular foundation models to drug discovery, and we are excited to apply that knowledge to batteries,” said Bharath Ramsundar, founder and CEO of Deep Forest Sciences, and a key collaborator in building the model.&nbsp;Once the model is up and running, the team will ask it to predict electrolytes suited to a particular pair of electrodes. It will then experimentally test each prescription in the lab with a robotic setup, Clio, that was developed by Viswanathan and collaborator <a href="https://www.cmu.edu/epp/people/faculty/jay-f-whitacre.html" target="_blank" rel="noreferrer noopener">Jay Whitacre</a>, professor of materials science, engineering and public policy at Carnegie Mellon University.They are also looking for new design rules that may emerge from the model—rules that humans haven’t been able to consider.“When we learn chemistry, we learn each rule, and then we learn about a dozen exceptions,” Viswanathan said. “Can this now help us learn better rules or be able to design with more sophisticated combined rules?”As an example, he said that it was easy for humans to add one atom to a structure and see whether it works or not. Adding pairs of atoms to the structure at different locations results in too many possibilities for humans to easily parse. But AI might be able to do it.The DOE’s <a href="https://science.osti.gov/ascr/Facilities/Accessing-ASCR-Facilities/INCITE/About-incite" target="_blank" rel="noreferrer noopener">INCITE program</a>, which provides the funding for this study, was conceived to seek out computationally intensive, large-scale research projects with the potential to significantly advance key areas in science and engineering.

Taking inspiration from the word-predicting large language models, a U-M team is kickstarting an atom-predicting model with 200,000 node hours on Argonne’s Polaris.

Building a chemical 'GPT' to help design a key battery component

This article was discussed in our <a href="https://www.wevolver.com/profile/the.next.byte" rel="noopener noreferrer" target="_blank">Next Byte podcast</a>.&nbsp;<iframe height="200px" width="100%" frameborder="no" scrolling="no" seamless="" src="https://player.simplecast.com/94de5079-b574-4a3f-8251-3be6800d1ac5?dark=false" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true"></iframe> The full article will continue below.<hr>Connectomics, the ambitious field of study that seeks to map the intricate network of animal brains, is undergoing a growth spurt. Within the span of a decade, it has journeyed from its nascent stages to a discipline that is poised to (hopefully) unlock the enigmas of cognition and the physical underpinning of neuropathologies such as in Alzheimer’s disease.&nbsp;At its forefront is the use of powerful electron microscopes, which researchers from the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Samuel and Lichtman Labs of Harvard University bestowed with the analytical prowess of machine learning. Unlike traditional electron microscopy, the integrated AI serves as a “brain” that learns a specimen while acquiring the images, and intelligently focuses on the relevant pixels at nanoscale resolution similar to how animals inspect their worlds.&nbsp;“<a href="https://www.biorxiv.org/content/10.1101/2023.10.05.561103v1.abstract" target="_blank">SmartEM</a>” assists connectomics in quickly examining and reconstructing the brain’s complex network of synapses and neurons with nanometer precision. Unlike traditional electron microscopy, its integrated AI opens new doors to understand the brain's intricate architecture.The integration of hardware and software in the process is crucial. The team embedded a GPU into the support computer connected to their microscope. This enabled running machine-learning models on the images, helping the microscope beam be directed to areas deemed interesting by the AI. “This lets the microscope dwell longer in areas that are harder to understand until it captures what it needs,” says MIT professor and CSAIL principal investigator Nir Shavit. “This step helps in mirroring human eye control, enabling rapid understanding of the images.”&nbsp;“When we look at a human face, our eyes swiftly navigate to the focal points that deliver vital cues for effective communication and comprehension,” says the lead architect of SmartEM, Yaron Meirovitch, a visiting scientist at MIT CSAIL who is also a former postdoc and current research associate neuroscientist at Harvard. “When we immerse ourselves in a book, we don't scan all of the empty space; rather, we direct our gaze towards the words and characters with ambiguity relative to our sentence expectations. This phenomenon within the human visual system has paved the way for the birth of the novel microscope concept.”&nbsp;For the task of reconstructing a human brain segment of about 100,000 neurons, achieving this with a conventional microscope would necessitate a decade of continuous imaging and a prohibitive budget. However, with SmartEM, by investing in four of these innovative microscopes at less than $1 million each, the task could be completed in a mere three months.<h2>Nobel Prizes and little worms &nbsp;</h2>Over a century ago, Spanish neuroscientist Santiago Ramón y Cajal was heralded as being the first to characterize the structure of the nervous system. Employing the rudimentary light microscopes of his time, he embarked on leading explorations into neuroscience, laying the foundational understanding of neurons and sketching the initial outlines of this expansive and uncharted realm&nbsp;— a feat that earned him a Nobel Prize. He noted, on the topics of inspiration and discovery, that “As long as our brain is a mystery, the universe, the reflection of the structure of the brain will also be a mystery.”Progressing from these early stages, the field has advanced dramatically, evidenced by efforts in the 1980s, mapping the relatively simpler connectome of <a href="https://www.nature.com/articles/s41586-021-03778-8" target="_blank">C. elegans</a>, small worms, to today’s endeavors probing into more intricate brains of organisms like zebrafish and mice. This evolution reflects not only enormous strides, but also escalating complexities and demands: mapping the mouse brain alone means managing a staggering thousand petabytes of <a href="https://www.cell.com/cell/pdf/S0092-8674(20)31001-1.pdf" target="_blank" data-lf-fd-inspected-kn9eq4roawkarlvp="true">data</a>, a task that vastly eclipses the storage capabilities of any university, the team says.&nbsp;<h2>Testing the waters</h2>For their own work, Meirovitch and others from the research team studied 30-nanometer thick slices of octopus tissue that were mounted on tapes, put on wafers, and finally inserted into the electron microscopes. Each section of an octopus brain, comprising billions of pixels, was imaged, letting the scientists reconstruct the slices into a three-dimensional cube at nanometer resolution. This provided an ultra-detailed view of synapses. The chief aim? To colorize these images, identify each neuron, and understand their interrelationships, thereby creating a detailed map or “connectome” of the brain's circuitry.“SmartEM will cut the imaging time of such projects from two weeks to 1.5 days,” says Meirovitch. “Neuroscience labs that currently can't be engaged with expensive and long EM imaging will be able to do it now,” The method should also allow synapse-level circuit analysis in samples from patients with psychiatric and neurologic disorders.&nbsp;Down the line, the team envisions a future where connectomics is both affordable and accessible. They hope that with tools like SmartEM, a wider spectrum of research institutions could contribute to neuroscience without relying on large partnerships, and that the method will soon be a standard pipeline in cases where biopsies from living patients are available. Additionally, they’re eager to apply the tech to understand pathologies, extending utility beyond just connectomics. “We are now endeavoring to introduce this to hospitals for large biopsies, utilizing electron microscopes, aiming to make pathology studies more efficient,” says Shavit.&nbsp;Two other authors on the paper have MIT CSAIL ties: lead author Lu Mi MCS ’19, PhD ’22, who is now a postdoc at the Allen Institute for Brain Science, and Shashata Sawmya, an MIT graduate student in the lab. The other lead authors are Core Francisco Park and Pavel Potocek, while Harvard professors Jeff Lichtman and Aravi Samuel are additional senior authors. Their research was supported by the NIH BRAIN Initiative and was presented at the 2023 International Conference on Machine Learning (ICML) Workshop on Computational Biology. The work was done in collaboration with scientists from Thermo Fisher Scientific.

MIT researchers invented a technology and software to take electron microscopy to the next level by seamlessly integrating real-time machine learning into the imaging process — “smart microscopy.” Left image: Yaron Meirovitch via the Stable Diffusion XL AI image generator and Alex Shipps via the Midjourney AI image generator. Right image: Daniel Berger and Meirovitch, edited by Alex Shipps/MIT CSAIL

MIT CSAIL researchers combine AI and electron microscopy to expedite detailed brain network mapping, aiming to enhance connectomics research and clinical pathology.

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