Antiferromagnetic multi-level memristor using linear magnetoelectricity.

2021 
The explosive growth of artificial intelligence and data-intensive computing has brought crucial challenge to modern information science and technology, i.e. conceptually new devices with superior properties are urgently desired. Memristor is recognized as a very promising circuit element to tackle the barriers, because of its fascinating advantages in imitating neural network of human brain, and thus realizing in-memory computing. However, there exist two core and fundamental issues: energy efficiency and accuracy, owing to the electric current operation of traditional memristors. In the present work, we demonstrate a new type of memristor, i.e. charge q and magnetic flux {\phi} space memristor, enabled by linear magnetoelectricity of Co4Nb2O9. The memory states show distinctly linear magnetoelectric coefficients with a large ratio of about 10, ensuing exceptional accuracy of related devices. The present q-{\phi} type memristor can be manipulated by magnetic and electric fields without involving electric current, paving the way to develop ultralow-energy-consuming devices. In the meanwhile, it is worth to mention that Co4Nb2O9 hosts an intrinsic compensated antiferromagnetic structure, which suggests interesting possibility of further integrating the unique merits of antiferromagnetic spintronics such as ultrahigh density and ultrafast switching. Linear magnetoelectricity is proposed to essential to the q-{\phi} type memristor, which would be accessible in a broad class of multiferroics and other magnetoelectric materials such as topological insulators. Our findings could therefore advance memristors towards new levels of functionality.
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