New hardware offers faster computation for artificial intelligence, with much less energy |
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This illustration shows an analog deep learning processor powered by ultra-fast protonics. Credit: Ella Maru Studio, Murat Onen |
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Engineers working on “analog deep learning” have found a way to propel protons through solids at unprecedented speeds. |
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As scientists push the boundaries of machine learning, the amount of time, energy, and money required to train increasingly complex neural network models is skyrocketing. A new area of artificial intelligence called analog deep learning promises faster computation with a fraction of the energy usage.
Programmable resistors are the key building blocks in analog deep learning, just like transistors are the core elements for digital processors. By repeating arrays of programmable resistors in complex layers, researchers can create a network of analog artificial “neurons” and “synapses” that execute computations just like a digital neural network. This network can then be trained to achieve complex AI tasks like image recognition and natural language processing.
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Explained: Why perovskites could take
solar cells to new heights
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Perovskites are widely seen as the likely platform for next-generation solar cells, replacing silicon because of its easier manufacturing process, lower cost, and greater flexibility. Just what is this unusual, complex crystal and why does it have such great potential?
Credit: Jose-Luis Olivares and Christine Daniloff, MIT
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This family of crystalline compounds is at the forefront of research seeking alternatives to silicon. |
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Perovskites hold promise for creating solar panels that could be easily deposited onto most surfaces, including flexible and textured ones. These materials would also be lightweight, cheap to produce, and as efficient as today’s leading photovoltaic materials, which are mainly silicon. They’re the subject of increasing research and investment, but companies looking to harness their potential do have to address some remaining hurdles before perovskite-based solar cells can be commercially competitive.
The term perovskite refers not to a specific material, like silicon or cadmium telluride, other leading contenders in the photovoltaic realm, but to a whole family of compounds. The perovskite family of solar materials is named for its structural similarity to a mineral called perovskite, which was discovered in 1839 and named after Russian mineralogist L.A. Perovski.
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Physicists discover a "family" of robust, superconducting graphene structures |
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When it comes to graphene, it appears that superconductivity runs in the family. Graphene is a single-atom-thin material that can be exfoliated from the same graphite that is found in pencil lead. The ultrathin material is made entirely from carbon atoms that are arranged in a simple hexagonal pattern, similar to that of chicken wire. Since its isolation in 2004, graphene has been found to embody numerous remarkable properties in its single-layer form.
In 2018, MIT researchers found that if two graphene layers are stacked at a very specific “magic” angle, the twisted bilayer structure could exhibit robust superconductivity, a widely sought material state in which an electrical current can flow through with zero energy loss. Recently, the same group found a similar superconductive state exists in twisted trilayer graphene — a structure made from three graphene layers stacked at a precise, new magic angle.
Now the team reports that — you guessed it — four and five graphene layers can be twisted and stacked at new magic angles to elicit robust superconductivity at low temperatures.
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Physicists see electron whirlpools for the first time |
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Long predicted but never observed, fluid-like electron whirlpools could be leveraged for next-gen low-power electronics. Credit: Christine Daniloff, MIT |
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Long predicted but never observed, this fluid-like electron behavior could be leveraged for low-power next-generation electronics. |
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Though they are discrete particles, water molecules flow collectively as liquids, producing streams, waves, whirlpools, and other classic fluid phenomena.
Not so with electricity. While an electric current is also a construct of distinct particles — in this case, electrons — the particles are so small that any collective behavior among them is drowned out by larger influences as electrons pass through ordinary metals. But, in certain materials and under specific conditions, such effects fade away, and electrons can directly influence each other. In these instances, electrons can flow collectively like a fluid.
Now, physicists at MIT and the Weizmann Institute of Science have observed electrons flowing in vortices, or whirlpools — a hallmark of fluid flow that theorists predicted electrons should exhibit, but that has never been seen until now.
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We invite your company to become a member of the MRL Industry Collegium. As a member, your company will receive:
- premium access to member only briefing materials and information via our website
- periodic publications and research activity highlights
- invitations to workshops, conferences and symposia
- support for research staff visits on-campus
- facilitation of corporate meetings and events
- customized interactions with MIT students
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To join the collegium contact:
Mark Beals
Associate Director, MRL
617-253-2129
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77 Massachusetts Avenue
Cambridge, MA 02139
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