The pressing need for beyond-von-Neumann computing paradigms has triggered intensive efforts into understanding and controlling various resistive switching (RS) mechanisms. This switching, in which the two terminal resistance of a device is controlled by current is at the heart of emerging technologies such as resistive random access memory and neuromorphic computation. These technologies promise to revolutionize artificial neural networks and mimic the behavior of biological brains, triggering a race the for optimal RS materials.
In Mott insulators electrical currents can change resistance by orders-of-magnitude due to an insulator-metal phase transition. The volatility of switching in Mott insulators can be adjusted by several tuning parameters, enabling both memory devices and neuron-like functionalities. Moreover, in terms of fundamental switching timescales and energy efficiency, Mott insulators may have very significant advantages over other RS mechanisms. These unique properties have made Mott insulators prominent candidate materials for RS. However, the physical mechanisms behind RS in these materials are not well understood and often uncontrollable, hampering realization of their full potential.
We suggest two main routes towards Mott-insulator-based RS with ultrahigh energy efficiency. The first is by switching purely in the electronic sector while minimizing structural distortions. Thus, the low heat capacity of electrons may enable switching with a fraction of the energy required in an insulator-metal transition coupled to a structural transition. The second is absorption of latent heat and/or elastic energy from the surroundings of the switching volume, thus reducing the externally supplied power consumption. Our aim is to use defects, doping and strain engineering to understand and tune RS mechanisms, and develop novel functionalities with ultra-low energy consumption.
Fields of science
- HORIZON.1.1 - European Research Council (ERC) Main Programme