Perovskite nanocrystals for better computing?
European team makes novel computer components inspired by brain cells
Human brains are superior to modern computers in many ways. While most people can't do maths as fast as computers, they can effortlessly process complex sensory information and learn from experiences. The brain does all this while consuming less than half the energy of a laptop.
One reason is that neurons and their connections (synapses) can both store and process information. In computers, however, the memory is separate from the processor, and data must be transported back and forth. The speed of transfer is limited, which can slow down the whole computer when working with large amounts of data.
One solution are novel computer architectures such as memristers that are modelled on the human brain . Now a team of researchers from the Swiss Federal Laboratories for Materials Science and Technology (Empa), ETH Zurich and the Politecnico di Milano has built memristers from halide perovskite nanocrystals. Their results are published in the journal Science Advances.
"Halide perovskites conduct both ions and electrons," explains Rohit John, former ETH Fellow and postdoctoral researcher at both ETH Zurich and Empa. "This dual conductivity enables more complex calculations that closely resemble processes in the brain."
The researchers conducted the experimental part of the study entirely at Empa: They manufactured the thin-film memristors at the Thin Films and Photovoltaics laboratory and investigated their physical properties at the Transport at Nanoscale Interfaces laboratory. Based on the measurement results, they then simulated a complex computational task that corresponds to a learning process in the visual cortex in the brain. The task involved determining the orientation of light based on signals from the retina.
"As far as we know, this is only the second time this kind of computation has been performed on memristors," says Maksym Kovalenko, professor at ETH Zurich and head of the Functional Inorganic Materials research group at Empa. "At the same time, our memristors are much easier to manufacture than before." This is because, in contrast to many other semiconductors, perovskites crystallize at low temperatures. In addition, the new memristors do not require the complex preconditioning through application of specific voltages that comparable devices need for such computing tasks. This makes them faster and more energy-efficient.
Complementing rather than replacing
The technology is not quite ready for deployment. The ease with which the new memristors can be manufactured also makes them difficult to integrate with existing computer chips. Perovskites cannot withstand temperatures of 400 to 500 degrees Celsius that are needed to process silicon – at least not yet.
But according to Daniele Ielmini, professor at the Politecnico di Milano, that integration is key to the success for new brain-like computer technologies. "Our goal is not to replace classical computer architecture," he explains. "Rather, we want to develop alternative architectures that can perform certain tasks faster and with greater energy efficiency. This includes, for example, the parallel processing of large amounts of data, which is generated everywhere today, from agriculture to space exploration."
Promisingly, there are other materials with similar properties that could be used to make high-performance memristors. "We can now test our memristor design with different materials," says Alessandro Milozzi, a doctoral student at the "Politecnico di Milano". "It is quite possible that some of them are better suited for integration with silicon."
Reference
Rohit Abraham John et al' 'Ionic-electronic halide perovskite memdiodes enabling neuromorphic computing with a second-order complexity'; Science Advances (2022).
