{"slug": "this-researcher-is-using-ai-to-help-computers-catch-up-with-the-brain", "title": "This researcher is using AI to help computers catch up with the brain", "summary": "Northeastern University professor Hossein Mosallaei and his team received the U.S. Department of Energy's AI Genesis Award to advance research on brain-inspired computing devices called Self-Driving MXene Memristors, which process and store information simultaneously, mimicking the brain's synapses. The technology aims to overcome the energy-intensive divide between processing and memory in conventional computers.", "body_md": "# This researcher is using AI to help computers catch up with the brain\n\nNortheastern professor Hossein Mosallaei received the DoE Genesis Award for his brain-inspired computing research. His team is using AI to develop circuits that process information and remember it at the same time.\n\nFor decades, scientists held up the brain as the ultimate supercomputer. No device could come close to the squishy 3-pound bundle of folds and grooves. It was the information processing machine to beat — a model of what computers of the future could be.\n\nAccording to Northeastern University professor of electrical and computer engineering [Hossein Mosallaei](https://coe.northeastern.edu/people/mosallaei-hossein/), computers are finally closing the gap.\n\nEarlier this month, Mosallaei and his team received a U.S. Department of Energy grant, [the AI Genesis Award](https://www.energy.gov/articles/secretary-energy-chris-wright-announces-first-genesis-mission-projects-selected-accelerate), to continue research on the co-design of computing devices known as “Self-Driving MXene Memristors.” These tiny computer components built from ultra-thin materials called MXenes (pronounced “Maxines”) can process information and remember it at the same time.\n\nThe problem Mosallaei and his team took on is as old as computing itself. It’s the Achilles’ heel slowing down just about every device ever built: the divide between processing and memory.\n\nComputers are made from two basic parts. The central processing unit (CPU) performs calculations and carries out instructions. The random access memory (RAM), in turn, temporarily stores data that the CPU might need and keeps it on hand.\n\nBoth store data on circuits, and the electricity that flows through them represents information. The problem is that when processing and memory storage happen in two different places, it makes for one lengthy digital commute that uses up tons of energy.\n\nThe brain, on the other hand, uses the same physical machinery to process information and remember it. Billions of nerve cells, known as neurons, group into networks that communicate with each other via electrical and chemical signals. The repeated activation of the networks allows for thinking, learning, recognizing patterns and making decisions. It also creates a physical imprint that gets stronger with each round. The deepening imprint represents a memory of the activity — kind of like a path in the woods that becomes more prominent each time you walk along it.\n\nFor example, seeing a person’s face for the first time activates a set of networks associated with vision and face recognition. As you see them over and over again, those pathways get reinforced — they now encode a memory of your friend’s face and make it easier to recognize them.\n\nThe magic of the MXene Memristors Mosallaei and his team developed lies in their ability to mimic synapses by processing information and automatically storing a record of their past activity in their structure, much like the brain does.\n\nMXenes (pronounced like “Maxines”) come from the field of microelectronics and belong to a class of substances known as metamaterials, which rearrange familiar building blocks found in nature in new ways. While their origins go back to the 19th century, the field took off in the late nineties, with scientists developing materials that could bend light, manipulate electricity or steer radio waves in ways not found in the wild.\n\n## Editor’s Picks\n\nNathan Kundtz, chief executive officer [at the software company Rendered.ai](http://rendered.ai), talked to Northeastern Global News about the potential of metamaterials for computers, in particular when it comes to machines using light instead of electricity to perform calculations. Given the growing demands for computing power and the “tremendous amount of power saving you can get” with metamaterials, Kundtz said the application of this technology “can’t happen soon enough.”\n\nLikewise, Mosallaei has always been fascinated by the field. “I am a metamaterial person,” he said. “In the last 20 years, I have been interested in developing or creating new materials that you cannot find in nature.”\n\nMXenes are ultrathin, highly conductive metamaterials developed in 2011 by scientists Yury Gogotsi and Michel Barsoum. They’re highly customizable, and each individual layer is about one to two nanometers. To picture just how tiny that is, consider that a human hair is 50,000 to 100,000 nanometers wide!\n\nThe real magic happens when Memristor devices stack together into a 3D structure, Mossallaei said.\n\nA Memristor built from MXenes is constructed like a tiny sandwich: two sheets of metal atoms with a material in between them. Applying a voltage lets electricity flow through the layers, creating a bridge between them. Unlike in a conventional circuit, the bridge remains in place even after electricity stops flowing, allowing the circuit to keep a running log of its own activity.\n\n“The whole idea is to model the brain,” Mossallaei explained.\n\nThe trick lies in getting the details just right. “I can control the spacing between these layers,” Mossallaei said, “And then I can control the channel for the ions from one electrode to another one,” as well as the exact atomic composition of the layers.\n\nWith the right arrangement, the device can process information and store a record of it in the same physical structure, all the while dramatically reducing the energy requirements — much like the human brain.\n\nHowever, nailing down the right combo of features created a bottleneck, Mossallaei said.\n\nAI saved the day.\n\nMossallaei explained that large language models (LLMs) can sort through possible configurations and assess which ones work best through a process known as active learning. “If we see the output is not good, we throw away that design,” he explained. Ones that look promising get added to the keepers’ pile.\n\nMXenes alone can be used as sensors, water purification devices, desalination units or medical devices thanks to their electrical conductivity, mechanical strength and tunable surface chemistry.\n\nComputers equipped with MXene Memristor take the technology to a new level. Their brain-inspired design makes them faster and more energy efficient — a perfect fit for robotics, smart wearable devices, drones, satellites, microscopes and much more.\n\nMossallaei said receiving the award has been an honor that he owes in large part to his colleagues, whom he referred to as the “dream team” consisting of talented specialists including Qiangfei Xia, Ju Li, Jennifer Dy and Yury Gogotsi, among others.\n\nThe breakthrough was as much about assembling the right group of people as it was about pinning down the right mix of features of the device itself, he said.\n\nThe Department of Energy gave the award to 278 projects integrating AI with supercomputing to create “breakthroughs in energy, discovery science, and national security, ” according to a press release from the agency, which described the winning projects as representing “the very best” of U.S. scientific enterprise.", "url": "https://wpnews.pro/news/this-researcher-is-using-ai-to-help-computers-catch-up-with-the-brain", "canonical_source": "https://news.northeastern.edu/2026/08/03/memristors-supercomputer-research-ai/", "published_at": "2026-08-03 21:07:56+00:00", "updated_at": "2026-08-03 21:34:10.722663+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-research"], "entities": ["Hossein Mosallaei", "Northeastern University", "U.S. Department of Energy", "Self-Driving MXene Memristors", "MXenes", "Rendered.ai", "Nathan Kundtz"], "alternates": {"html": "https://wpnews.pro/news/this-researcher-is-using-ai-to-help-computers-catch-up-with-the-brain", "markdown": "https://wpnews.pro/news/this-researcher-is-using-ai-to-help-computers-catch-up-with-the-brain.md", "text": "https://wpnews.pro/news/this-researcher-is-using-ai-to-help-computers-catch-up-with-the-brain.txt", "jsonld": "https://wpnews.pro/news/this-researcher-is-using-ai-to-help-computers-catch-up-with-the-brain.jsonld"}}